liu.seSearch for publications in DiVA
Change search
Refine search result
12 1 - 50 of 55
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Armengol Llobet, J.
    et al.
    n/a.
    Bregon, A.
    n/a.
    Escobet, E
    n/a.
    Gelso, R.
    n/a.
    Krysander, Mattias
    n/a.
    Nyberg, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Olive, X.
    n/a.
    Pulido, B.
    n/a.
    Trave-Massuyes, L.
    n/a.
    Minimal Structurally Overdetermined Sets for Residual Generation: A Comparison of Alternative Approaches2009In: Proceedings of IFAC Safeprocess'09, Barcelona, Spain, 2009, p. 1480-1485Conference paper (Refereed)
    Abstract [en]

    The issue of residual generation using structural analysis has been studied by several authors. Structural analysis does not permit to generate the analytical expressions of residuals since the model of the system is abstracted by its structure. However, it determines the set of constraints from which residuals can be generated and it provides the computation sequence to be used. This paper presents and compares four recently proposed algorithms that solve this problem.

  • 2.
    Biteus, Jonas
    et al.
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Cedersund, Gunnar
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Improving Airplane Safety by Incorporating Diagnosis into Existing Safety Practice2004Report (Other academic)
    Abstract [en]

    Safety has always been at premium in airfare. There is a long history of systematic work in the field, and current practice has established a high degree of safety that has resulted in so low failure numbers that the public finds confidence in the process of air worthiness certification. However, the design and development process of airplanes to achieve this is costly and may be even more so since modern airplanes become more and more complex. Furthermore, recent trends towards Unmanned Aerial Vehicles (UAV) are likely to require even more efforts and costs, to fulfill the increased safety requirements. Therefore it is interesting to investigate modern techniques that promises to improve safety at reduced costs. One such technique is diagnosis. Diagnosis in general is a term that includes several research and application fields. Examples of such fields, that are technology drivers, are the fields of supervision both on-line (on-board) and off-line (on ground), operator support that evolved from the Harrisburg accident, and law based emission diagnostics regulation e.g. as stipulated by California Air Resource Board (CARB).

    The current work is an investigation in the cross field between safety assessment and diagnosis techniques. The first step was to root the work in existing safety practice. This means that the Swedish defense procedure has been adopted as described in H SystSäk E. It is a safety framework that uses fault tree analysis and failure mode effect analysis as important tools. Thereafter some flight applications were investigated together with Saab specialists to capture and formulate some aspects that are non-trivial to cast in the existing safety framework. Examples of such aspects found are for instance related to performance requirements in different operational model. A principle case study was then formulated using laboratory equipment, with the aim to capture some of the identified aspects in the problem formulation. A complete process for safety analysis was then completed along the lines of H SystSäk E including all meetings and documents required therein. Several observations were done during this work, but the overall conclusion so far is that the effect of introducing diagnosis algorithms can be handled in the safety analysis, and, yes, that there is a promise that diagnosis algorithms can improve safety in a structured quantitative way by lowering the contribution to the total failure risk from the subsystem being diagnosed.

  • 3. Düstegör, Dilek
    et al.
    Frisk, Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Coquempot, Vincent
    Krysander, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Staroswiecki, Marcel
    Structural Analysis of Fault Isolability in the DAMADICS benchmark2006In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 14, no 6, p. 597-608Article in journal (Refereed)
    Abstract [en]

    Structural analysis is a powerful tool for early determination of fault detectability/fault isolability possibilities. It is shown how different levels of knowledge about faults can be incorporated in a structural fault isolability analysis and how they result in different isolability properties. The results are evaluated on the DAMADICS valve benchmark model. It is also shown how to determine which faults in the benchmark that need further modelling to get desired isolability properties of the diagnosis system.

  • 4.
    Eriksson, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Analysis and optimization with the Kullback-Leibler divergence for misfire detection using estimated torque2013Report (Other academic)
    Abstract [en]

    Engine misfire detection is an important part of the On-Board Diagnostics (OBDII) legislations to reduce exhaust emissions and avoid damage to the catalytic converters. The flywheel angular velocity signal is analyzed, investigating how to use the signal in order to best detect misfires. An algorithm for engine misfire detection is proposed based on the flywheel angular velocity signal. The flywheel signal is used to estimate the torque at the flywheel and a test quantity is designed by weighting and thresholding the samples of estimated torque related to one combustion. During the development process, the Kullback-Leibler divergence is used to analyze the ability to detect a misfire given a test quantity and how the misfire detectability performance varies depending on, e.g., load and speed. The Kullback-Leibler divergence is also used for parameter optimization to maximize the difference between misfire data and fault-free data. Evaluation shows that the proposed misfire detection algorithm is able to have a low probability of false alarms while having a low probability of missed detections.

  • 5.
    Eriksson, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Flywheel angular velocity model for misfire and driveline disturbance simulation2013In: Proceedings of the 7th IFAC Symposium on Advances in Automotive Control, The International Federation of Automatic Control, Elsevier, 2013, Vol. 46, no 21, p. 570-575Conference paper (Refereed)
    Abstract [en]

    A flywheel angular velocity model for misfire and disturbance simulation is presented. Applications of the model are, for example, initial parameter calibration and robustness analysis of misfire detection algorithms. An analytical cylinder pressure model is used to model cylinder torque and a multi-body model with torsional flexibilities is used to model crankshaft and driveline oscillations. Misfires, cylinder variations, changes in auxiliary load, and flywheel manufacturing errors can be injected in the model and the resulting speed variations can be simulated. A qualitative validation of the model shows that simulated angular velocity captures the amplitude and oscillatory behavior of measurement data and the effects of different phenomena, such as misfire and flywheel manufacturing errors.

  • 6.
    Eriksson, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Flywheel angular velocity model for misfire simulation2013Manuscript (preprint) (Other academic)
    Abstract [en]

    A flywheel angular velocity model for misfire and disturbance simulation is presented. Applications of the model are, for example, initial parameter calibration or robustness analysis of misfire detection algorithms. An analytical model of cylinder pressure is used to model cylinder torque and a multi-body model is used to model crankshaft and driveline oscillations. Different types of disturbances, such as cylinder variations, changes in auxiliary load, and flywheel manufacturing errors can be injected in the model. A qualitative validation of the model shows that simulated angular velocity captures the amplitude and oscillatory behavior of real measurements and the effects of different types of disturbances, e.g. misfire and flywheel manufacturing errors.

  • 7.
    Eriksson, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    A method for quantitative fault diagnosability analysis of stochastic linear descriptor models2013In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 49, no 6, p. 1591-1600Article in journal (Refereed)
    Abstract [en]

    Analyzing fault diagnosability performance for a given model, before developing a diagnosis algorithm, can be used to answer questions like “How difficult is it to detect a fault fi?” or “How difficult is it to isolate a fault fi from a fault fj?”. The main contributions are the derivation of a measure, distinguishability, and a method for analyzing fault diagnosability performance of discrete-time descriptor models. The method, based on the Kullback–Leibler divergence, utilizes a stochastic characterization of the different fault modes to quantify diagnosability performance. Another contribution is the relation between distinguishability and the fault to noise ratio of residual generators. It is also shown how to design residual generators with maximum fault to noise ratio if the noise is assumed to be i.i.d. Gaussian signals. Finally, the method is applied to a heavy duty diesel engine model to exemplify how to analyze diagnosability performance of non-linear dynamic models.

  • 8.
    Eriksson, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    A sequential test selection algorithm for fault isolation2012In: Proceedings of the 10th European Workshop on Advanced Control and Diagnosis, ACD 2012, Copenhagen, Denmark, 2012Conference paper (Refereed)
    Abstract [en]

    A sequential test selection algorithm is proposed which updates the set of active test quantities depending on the present minimal candidates. By sequentially updating the set of active test quantities, computational time and memory usage can be reduced. If test quantities are generated on-line, a sequential test selection algorithm gives information about which test quantities that should be created. The test selection problem is defined as an optimization problem where a set of active test quantities is chosen such that the cost is minimized while the set fulfills a required minimum detectability and isolability performance. A quantitative diagnosability measure, distinguishability, is used to quantify diagnosability performance of test quantities. The proposed test selection algorithm is applied to a DC-circuit where the diagnosis algorithm generates residuals on-line. Experiments show that the sequential test selection algorithm can significantly reduce the number of active test quantities during a scenario and still be able to identify the true faults.

  • 9.
    Eriksson, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Quantitative Fault Diagnosability Performance of Linear Dynamic Descriptor Models2011Conference paper (Refereed)
    Abstract [en]

    A theory is developed for quantifying fault detectability and fault isolability properties of time discrete linear dynamic models. Based on the model, a stochastic characterization of system behavior in different fault modes is defined and a general measure, called distinguishability, based on the Kullback-Leibler information, is used to quantify the difference between the modes. An analysis of distinguishability as a function of the number of observations is discussed. This measure is also shown to be closely related to the fault to noise ratios in residual generators. Further, the distinguishability of the model is shown to give upper limits of the fault to noise ratios of residual generators.

  • 10.
    Eriksson, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Quantitative Stochastic Fault Diagnosability Analysis2011In: 2011 50th IEEE Conference on Decision and Control andEuropean Control Conference (CDC-ECC)Orlando, FL, USA, December 12-15, 2011, Institute of Electrical and Electronics Engineers (IEEE), 2011, p. 1563-1569Conference paper (Refereed)
    Abstract [en]

    A theory is developed for quantifying fault detectability and fault isolability properties of static linear stochastic models. Based on the model, a stochastic characterization of system behavior in different fault modes is defined and a general measure, based on the Kullback-Leibler information, is proposed to quantify the difference between the modes. This measure, called distinguishability, of the model is shown to give sharp upper limits of the fault to noise ratios of residual generators. Finally, a case-study of a diesel engine model shows how the general framework can be applied to a dynamic and nonlinear model.

  • 11.
    Eriksson, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Using quantitative diagnosability analysis for optimal sensor placement2012In: Proceedings of the 8th IFAC Safe Process, Mexico City, Mexico / [ed] Carlos Manuel Astorga-Zaragoza, Arturo Molina Gutierrez and Adriana Aguilera-Gonzalez, Curran Associates, Inc., 2012, p. 940-945Conference paper (Refereed)
    Abstract [en]

    A good placement of sensors is crucial to get good performance in detecting and isolating faults. Here, the sensor placement problem is cast as a minimal cost optimization problem. Previous works have considered this problem with qualitative detectability and isolability specifications. A key contribution here is that quantified detectability and isolability performance is considered in the optimization formulation. The search space for the posed optimization problem is exponential in size, and to handle complexity a greedy optimization algorithm that compute optimal sensor positions is proposed. Two examples illustrate how the optimal solution depends on the required quantified diagnosability performance and the results are compared to the solutions using a deterministic method.

  • 12.
    Frisk, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Bregon, Anibal
    University of Valladolid, Spain .
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Pulido, Belarmino
    University of Valladolid, Spain .
    Biswas, Gautam
    Vanderbilt University, TN 37235 USA Vanderbilt University, TN 37235 USA .
    Diagnosability Analysis Considering Causal Interpretations for Differential Constraints2012In: IEEE transactions on systems, man and cybernetics. Part A. Systems and humans, ISSN 1083-4427, E-ISSN 1558-2426, Vol. 42, no 5, p. 1216-1229Article in journal (Refereed)
    Abstract [en]

    This paper is focused on structural approaches to study diagnosability properties given a system model taking into account, both simultaneously or separately, integral and differential causal interpretations for differential constraints. We develop a model characterization and corresponding algorithms, for studying system diagnosability using a structural decomposition that avoids generating the full set of system analytical redundancy relations. Simultaneous application of integral and differential causal interpretations for differential constraints results in a mixed causality interpretation for the system. The added power of mixed causality is demonstrated using a Reverse Osmosis Subsystem from the Advanced Water Recovery System developed at the NASA Johnson Space Center. Finally, we summarize our work and provide a discussion of the advantages of mixed causality over just derivative or just integral causality.

  • 13.
    Frisk, Erik
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Dustegör, Dilek
    LAIL Universite des Sciences et Technologies de Lille.
    Krysander, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Cocquempot, Vincent
    LAIL Universite des Sciences et Technologies de Lille.
    Improving fault isolability properties by structural analysis of faulty behavior models: application to the DAMADICS benchmark problem2003In: IFAC Safeprocess03,2003, Washington D.C., USA, 2003Conference paper (Refereed)
    Abstract [en]

    Structural analysis is a powerful tool for early determination of detectability/isolability possibilities. It is shown how different levels of knowledge about faults can be incorporated in a structural fault-isolability analysis and how they result in different isolability properties. The results are evaluated on the DAMADICS valve benchmark model. It is also shown how to determine which faults in the benchmark that need further modeling to get desired isolability properties of the diagnosis system.

  • 14.
    Frisk, Erik
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Krysander, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Leakage Detection In a Fuel Evaporative System2008In: IFAC World Congress,2008, Seoul, Korea: IFAC , 2008Conference paper (Refereed)
    Abstract [en]

    On-Board Diagnostics (OBD) regulations require that the fuel system in personal vehicles must be supervised for leakages. Legislative requirement on the smallest leakage size that has to be detected is decreasing and at the same time the requirement on number of leakage checks are increasing. A consequence is that detection must be performed under more and more diverse operating conditions. This paper describes a vacuum-decay based approach for evaporative leak detection. The approach requires no additional hardware such as pumps or pressure regulators, it only utilizes the pressure sensor that is mounted in the fuel tank. A detection algorithm is proposed that detects small leakages under different operating conditions. The method is based on a first principles physical model of the pressure in the fuel tank. Careful statistical analysis of the model and measurement data together with statistical maximum-likelihood estimation methods, results in a systematic design procedure that is easily tuned with few and intuitive parameters. The approach has been successfully evaluated on real data measured in a research laboratory.

  • 15.
    Frisk, Erik
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Krysander, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Sensor placement for maximum fault isolability2007In: 18th International Workshop on Principles of Diagnosis,2007, Nashville, USA, 2007, p. 106-113Conference paper (Refereed)
    Abstract [en]

    An algorithm is developed for computing which sensors to add to obtain maximum fault detectability and fault isolability. The method is based on only the structural information in a model which means that large and non-linear differential-algebraic models can be handled in an efficient manner. The approach is exemplified on a model of an industrial valve where the benefits and properties of the method is clearly shown.

  • 16.
    Frisk, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Larsson, Emil
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Data-driven Lead-Acide Battery Prognostics Using Random Survival Forests2014In: PMH 2014. Proceedings of the Annual Conference of The Prognostics and Health Management Society. Fort Worth, Texas, USA / [ed] Mathew J. Daigle and Anibal Bregon, PMH Society , 2014, p. 92-101Conference paper (Refereed)
    Abstract [en]

    Problems with starter batteries in heavy-duty trucks can cause costly unplanned stops along the road. Frequent battery changes can increase availability but is expensive and sometimes not necessary since battery degradation is highly dependent on the particular vehicle usage and ambient conditions. The main contribution of this work is a case-study where prognostic information on remaining useful life of lead-acid batteries in individual Scania heavy-duty trucks is computed. A data-driven approach using random survival forests is proposed where the prognostic algorithm has access to fleet management data including 291 variables from 33 603 vehicles from 5 different European markets. The data is a mix of numerical values such as temperatures and pressures, together with histograms and categorical data such as battery mount point. Implementation aspects are discussed such as how to include histogram data and how to reduce the computational complexity by reducing the number of variables. Finally, battery lifetime predictions are computed and evaluated on recorded data from Scania's fleet-management system.

  • 17.
    Frisk, Erik
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Krysander, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Nyberg, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    A toolbox for design of diagnosis systems2006In: IFAC Safeprocess06,2006, Beijing, China: IFAC , 2006, p. 703-Conference paper (Refereed)
    Abstract [en]

    Design of diagnosis systems is a complex task that involves many different steps. Full understanding of all different parts of the design procedure requires deep knowledge on theory from a wide variety of subjects. Thus, to encourage the use of results from diagnosis research it is highly desirable to have software support in the design process. This paper describes ongoing work for determining an architecture for such a toolbox. The paper also describes software solutions in the toolbox. In industry as well as in universities, Matlab is probably the most widespread tool used by control engineers. Therefore the toolbox is primarily based upon Matlab but also some computer algebraic tools such as Mathematica and Maple are used.

  • 18.
    Frisk, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Sensor placement for fault isolation in linear differential-algebraic systems2009In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 45, no 2, p. 364-371Article in journal (Refereed)
    Abstract [en]

    An algorithm is proposed for computing which sensor additions make a diagnosis requirement specification regarding fault detectability and isolability attainable for a given linear differential-algebraic model. Restrictions on possible sensor locations can be given, and if the diagnosis specification is not attainable with any available sensor addition, the algorithm provides the solutions that maximize specification fulfillment. Previous approaches with similar objectives have been based on the model structure only. Since the proposed algorithm utilizes the analytical expressions, it can handle models where structural approaches fail.

  • 19.
    Gustafsson, Fredrik
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Frisk, Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Krysander, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Nielsen, Lars
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    On Threshold Optimization in Fault Tolerant Systems2008In: Proceedings of the 17th IFAC World Congress, 2008, p. 7883-7888Conference paper (Refereed)
    Abstract [en]

    Fault tolerant systems are considered, where a nominal system is monitored by a fault detection algorithm, and the nominal system is switched to a backup system in case of a detected fault. Conventional fault detection is in the classical setting a trade-off between detection probability and false alarm probability. For the considered fault tolerant system, a system failure occurs either when the nominal system gets a fault that is not detected, or when the fault detector signals an alarm and the backup system breaks down. This means that the trade-off for threshold setting is different and depends on the overall conditions, and the characterization and understanding of this trade-off is important. It is shown that the probability of system failure can be expressed in a general form based on the probability of false alarm and detection power, and based on this form the influence ratio is introduced. This ratio includes all information about the supervised system and the backup system that is needed for the threshold optimization problem. It is shown that the influence ratio has a geometrical interpretation as the gradient of the receiver operating characteristics (ROC) curve at the optimal point, and furthermore, it is the threshold for the optimal test quantity in important cases.

  • 20.
    Heintz, Fredrik
    et al.
    Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Roll, Jacob
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    FlexDx: A Reconfigurable Diagnosis Framework2008In: Proceedings of the 19th International Workshop on Principles of Diagnosis (DX), 2008Conference paper (Refereed)
    Abstract [en]

    Detecting and isolating multiple faults is a computationally intense task which typically consists of computing a set of tests, and then computing the diagnoses based on the test results. This paper describes FlexDx, a reconfigurable diagnosis framework which reduces the computational burden by only running the tests that are currently needed. The method selects tests such that the isolation performance of the diagnostic system is maintained. Special attention is given to the practical issues introduced by a reconfigurable diagnosis framework such as FlexDx. For example, tests are added and removed dynamically, tests are partially performed on historic data, and synchronous and asynchronous processing are combined. To handle these issues FlexDx uses DyKnow, a stream-based knowledge processing middleware framework. The approach is exemplified on a relatively small dynamical system, which still illustrates the computational gain with the proposed approach.

  • 21.
    Jakobsson, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering. Atlas Copco Rock Drills AB, Örebro, Sweden.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Pettersson, Robert
    Atlas Copco Rock Drills AB, Örebro, Sweden.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Data driven modeling and estimation of accumulated damage in mining vehicles using on-board sensors2017In: PHM 2017. Proceedings of the Annual Conference of the Prognostics and Health Management Society 2017, St. Petersburg, Florida, USA, October 2–5, 2017 / [ed] Anibal Bregon and Matthew J. Daigle, phmSociety , 2017, p. 98-107Conference paper (Refereed)
    Abstract [en]

    The life and condition of a MT65 mine truck frame is to a large extent related to how the machine is used. Damage from different stress cycles in the frame are accumulated over time, and measurements throughout the life of the machine are needed to monitor the condition. This results in high demands on the durability of sensors used. To make a monitoring system cheap and robust enough for a mining application, a small number of robust sensors are preferred rather than a multitude of local sensors such as strain gauges. The main question to be answered is whether a low number of robust on-board sensors can give the required information to recreate stress signals at various locations of the frame. Also the choice of sensors among many different locations and kinds are considered. A final question is whether the data could also be used to estimate road condition. By using accelerometer, gyroscope and strain gauge data from field tests of an Atlas Copco MT65 mine truck, coherence and Lasso-regression were evaluated as means to select which signals to use. ARX-models for stress estimation were created using the same data. By simulating stress signals using the models, rain flow counting and damage accumulation calculations were performed. The results showed that a low number of on-board sensors like accelerometers and gyroscopes could give enough information to recreate some of the stress signals measured. Together with a linear model, the estimated stress was accurate enough to evaluate the accumulated fatigue damage in a mining truck. The accumulated damage was also used to estimate the condition of the road on which the truck was traveling. To make a useful road monitoring system some more work is required, in particular regarding how vehicle speed influences damage accumulation.

  • 22.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Dong, Yi
    Institute for Software Integrated Systems, Vanderbilt University, Nashville, USA.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    Biswas, Gautam
    Institute for Software Integrated Systems, Vanderbilt University, Nashville, USA.
    Sensor selection for fault diagnosis in uncertain systems2018In: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, p. 1-11Article in journal (Refereed)
    Abstract [en]

    Finding the cheapest, or smallest, set of sensors such that a specified level of diagnosis performance is maintained is important to decrease cost while controlling performance. Algorithms have been developed to find sets of sensors that make faults detectable and isolable under ideal circumstances. However, due to model uncertainties and measurement noise, different sets of sensors result in different achievable diagnosability performance in practice. In this paper, the sensor selection problem is formulated to ensure that the set of sensors fulfils required performance specifications when model uncertainties and measurement noise are taken into consideration. However, the algorithms for finding the guaranteed global optimal solution are intractable without exhaustive search. To overcome this problem, a greedy stochastic search algorithm is proposed to solve the sensor selection problem. A case study demonstrates the effectiveness of the greedy stochastic search in finding sets close to the global optimum in short computational time.

  • 23.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    Development of misfire detection algorithm using quantitative FDI performance analysis2015In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 34, p. 49-60Article in journal (Refereed)
    Abstract [en]

    A model-based misfire detection algorithm is proposed. The algorithm is able to detect misfires and identify the failing cylinder during different conditions, such as cylinder-to-cylinder variations, cold starts, and different engine behavior in different operating points. Also, a method is proposed for automatic tuning of the algorithm based on training data. The misfire detection algorithm is evaluated using data from several vehicles on the road and the results show that a low misclassification rate is achieved even during difficult conditions. (C) 2014 Elsevier Ltd. All rights reserved.

  • 24.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    A flywheel error compensation algorithm for engine misfire detection2016In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 47, p. 37-47Article in journal (Refereed)
    Abstract [en]

    A commonly used signal for engine misfire detection is the crankshaft angular velocity measured at the flywheel. However, flywheel manufacturing errors result in vehicle-to-vehicle variations in the measurements and have a negative impact on the misfire detection performance, where the negative impact is quantified for a number of vehicles. A misfire detection algorithm is proposed with flywheel error adaptation in order to increase robustness and reduce the number of mis-classifications. Since the available computational power is limited in a vehicle, a filter with low computational load, a Constant Gain Extended Kalman Filter, is proposed to estimate the flywheel errors. Evaluations using measurements from vehicles on the road show that the number of mis-classifications is significantly reduced when taking the estimated flywheel errors into consideration.

  • 25.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    Quantitative isolability analysis of different fault modes2015In: 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015 – Paris, 2–4 September 2015: Proceedings / [ed] Didier Maquin, Elsevier, 2015, Vol. 48(21), p. 1275-1282Conference paper (Refereed)
    Abstract [en]

    To be able to evaluate quantitative fault diagnosability performance in model-based diagnosis is useful during the design of a diagnosis system. Different fault realizations are more or less likely to occur and the fault diagnosis problem is complicated by model uncertainties and noise. Thus, it is not obvious how to evaluate performance when all of this information is taken into consideration. Four candidates for quantifying fault diagnosability performance between fault modes are discussed. The proposed measure is called expected distinguishability and is based of the previous distinguishability measure and two methods to compute expected distinguishability are presented.

  • 26.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Khorasgani, Hamed
    Inst. of Software-integrated Systems, Vanderbilt Univ., USA.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Biswas, Gautam
    Inst. of Software-integrated Systems, Vanderbilt Univ., USA.
    Analysis of fault isolation assumptions when comparing model-based design approaches of diagnosis systems2015In: Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes Safeprocess'15, Elsevier, 2015, Vol. 48, no 21, p. 1289-1296Conference paper (Refereed)
    Abstract [en]

    Most model-based diagnosis approaches reported in the literature adopt a generic architecture and approach. However, the fault hypotheses generated by these methods may differ. This is not only due to the methods, but also on the basic assumptions made by different diagnostic algorithms on fault manifestation and evolution. While comparing different diagnosis approaches, the assumptions made in each case will have a significant effect on fault diagnosability performance and must therefore also be taken into consideration. Thus, to make a fair comparison, the different approaches should be designed based on the same assumptions. This paper studies the relation between a set of commonly made assumptions and fault isolability performance in order to compare different diagnosis approaches. As a case study, five developed diagnosis systems for a wind turbine benchmark problem are evaluated to analyze the type of assumptions that are applied in the different designs.

  • 27.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Ng, Kok Yew
    School of Engineering, Ulster University, Newtownabbey, UK; Electrical and Computer Systems Engineering, School of Engineering, Monash University Malaysia, Malaysia.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Combining model-based diagnosis and data-driven anomaly classifiers for fault isolation2018In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 80, p. 146-156Article in journal (Refereed)
    Abstract [en]

    Machine learning can be used to automatically process sensor data and create data-driven models for prediction and classification. However, in applications such as fault diagnosis, faults are rare events and learning models for fault classification is complicated because of lack of relevant training data. This paper proposes a hybrid diagnosis system design which combines model-based residuals with incremental anomaly classifiers. The proposed method is able to identify unknown faults and also classify multiple-faults using only single-fault training data. The proposed method is verified using a physical model and data collected from an internal combustion engine.

    The full text will be freely available from 2020-09-09 11:37
  • 28. Khorasgani, Hamed
    et al.
    Jung, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Biswas, Gautam
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Off-line robust residual selection using sensitivity analysis2014Conference paper (Refereed)
    Abstract [en]

    Model-based approaches to fault detection and isolation (FDI) rely on accurate models of the plant and a sufficient number of reliable measurements for residual generation and analysis. However, in realistic situations, there can be uncertainties in the plant models and measurements, which have a negative impact on the diagnosability performance that depends on the system state. In other words, the impact of the uncertainties can be larger in some operating regions as compared to others. To achieve acceptable performance in practice, it is necessary to find a set of residuals that are sufficiently sensitive to faults but robust to uncertainties across all operating conditions. In this paper, a quantitative measure, called detectability ratio, is used to evaluate and quantify detectability performance of different residuals in different operating regions. This measure is used to find a minimal residual set that fulfills a set of desired diagnosability performance requirements. The proposed method is demonstrated and validated through a case study.

  • 29.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Design and Analysis of Diagnosis Systems Using Structural Methods2006Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In complex and automated technological processes the effects of a fault can quickly propagate and lead to degradation of process performance or even worse to a catastrophic failure. This means that faults have to be found as quickly as possible and decisions have to be made to stop the propagation of their effects and to minimize process performance degradation. The behavior of the process is affected in different ways by different faults and the fault can be found by ruling out faults for which the expected behavior of the process is not consistent with the observed behavior. In model-based diagnosis, a model describes the expected behavior of the process for the different faults.

    A device for finding faults is called a diagnosis system. In the diagnosis systems considered here, a number of tests check the consistency of different parts of the model, by using observations of the process. To be able to identify which fault that has occurred, the set of tests that is used must be carefully selected. Furthermore, to reduce the on-line computational cost of running the diagnosis system and to minimize the in general difficult and time-consuming work of tests construction, it is also desirable to use few tests.

    A two step design procedure for construction of a diagnosis systems is proposed and it provides the means for selecting which tests to use implicitly by selecting which parts of the model that should be tested with each test. Then, the test design for each part can be done with any existing technique for model-based diagnosis.

    Two different types of design goals concerning the capability of distinguishing faults is proposed. The first goal is to design a sound and complete diagnosis system, i.e., a diagnosis system with the following property. For any observation, the diagnosis system computes

    exactly the faults that together with the observation are consistent with the model. The second goal is specified by which faults that should be distinguished from other faults, and this is called the desired isolability.

    Given any of these two design goals, theory and algorithms for selecting a minimum cardinality set of parts of the model are presented. Only parts with redundancy can be used for test construction and a key result is that there exists a sound and complete diagnosis system based on the set of all minimal parts with redundancy in the model. In differentialalgebraic models, it is in general difficult to analytically identify parts with redundancy, because it corresponds to variable elimination or projection. It is formally shown that redundant parts can be found by using a structural approach, i.e., to use only which variables that are included in each equation. In the structural approach, parts with more equations than unknowns are identified with efficient graph-theoretical tools. A key contribution is a new algorithm for finding all minimal parts with redundancy of the model. The efficiency of the algorithm is demonstrated on a truck engine model and compared to the computational complexity of previous algorithms.

    In conclusion, tools for test selection have been developed. The selection is based on intuitive requirements such as soundness or isolability requirements specified by the diagnosis system designer. This leads to a more straightforward design of diagnosis systems, valuable engineering time can be saved, and the resulting diagnosis systems use minimum number of tests, i.e., the on-line computational complexity of the resulting diagnosis systems become low.

  • 30.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Design and analysis of diagnostic systems utilizing structural methods2003Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Today many technical processes are complex and highly integrated. When a process has failed, the complexity of the process makes it hard for humans to troubleshoot it. To facilitate troubleshooting a diagnostic system can supervise and alarm an operator when a fault is detected and also identify one, or several faults, that may have caused the alarm.

    It is a demanding and time-consuming task to design a diagnostic system. Therefore this thesis presents algorithms and analysis methods that help and automate the design of diagnostic systems. In model-based diagnosis a model, in this thesis called a diagnostic model, of the process is used to design a diagnostic system. A diagnostic model describes the different behaviors of the behavioral modes of the process, which are chosen for the diagnosis task. Typical behavioral modes are the normally working mode and specified faulty working modes.

    In a diagnostic system a number of diagnostic tests validate different models, by using observations of the process. Each test decides if the present behavioral mode of the process belongs to a subset of considered behavioral modes. If a test gives the same possible behavioral modes as the behavioral modes that together with the observations are consistent with a model, and this is true for any observation, then the test is a strong test for this model.

    If the diagnostic model exactly describes the behaviors of the process, a goal is to design a diagnostic system such that for any observations exactly the same possible behavioral modes are given from the diagnostic system as the behavioral modes that together with the observations are consistent with the diagnostic model. A system with a set of tests so designed is called a sound and complete diagnostic system.

    A key result of the thesis is, if the goal is to design a strong test for each model in a set of models, a necessary and sufficient condition for which set of models that results in a sound and complete diagnostic system. An algorithm that computes a set of models that fulfills this condition is presented. Further, an algorithm that generates a sound and complete diagnostic system for any linear static model is given.

    In the two proposed algorithms for designing diagnostic systems, there is a common step that analyzes the structure of the diagnostic model, i.e. which variables that are included in each equation. The structure is used to find all minimal models of a certain type, named minimal structurally singular (MSS) sets of equations. A structural algorithm that finds all MSS sets in a model described by differential­ algebraic equations is given. It uses a new way of handling derivatives in structural models.

    Finally, the structural algorithm is applied to a large non-linear example, a part of a paper mill. In spite of the complexity of this process, a small set of tests with high isolability is successfully derived.

  • 31.
    Krysander, Mattias
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Frisk , Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Sensor Placement for Fault Diagnosis2008In: IEEE transactions on systems, man and cybernetics. Part A. Systems and humans, ISSN 1083-4427, E-ISSN 1558-2426, Vol. 38, no 6, p. 1398-1410Article in journal (Refereed)
    Abstract [en]

    An algorithm is developed for computing which sensors to add to meet a diagnosis requirement specification concerning fault detectability and fault isolability. The method is based only on the structural information in a model, which means that possibly large and nonlinear differential-algebraic models can be handled in an efficient manner. The approach is exemplified on a model of an industrial valve where the benefits and properties of the method are clearly shown.

  • 32.
    Krysander, Mattias
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Leakage Detection In a Fuel Evaporative System2009In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 17, no 11, p. 1273-1279Article in journal (Refereed)
    Abstract [en]

    On-board diagnostic (OBD) regulations require that the fuel system in personal vehicles must be supervised for leakages. Legislative requirement on the smallest leakage size that has to be detected is decreasing and at the same time the requirement on the number of leakage checks is increasing. A consequence is that detection must be performed under more and more diverse operating conditions. This paper describes a vacuum-decay based approach for evaporative leak detection. The approach requires no additional hardware such as pumps or pressure regulators, it only utilizes the pressure sensor that is mounted in the fuel tank. A detection algorithm is proposed that detects small leakages under different operating conditions. The method is based on a first principles physical model of the pressure in the fuel tank. Careful statistical analysis of the model and measurement data together with statistical maximum-likelihood estimation methods, results in a systematic design procedure that is easily tuned with few and intuitive parameters. The approach has been successfully evaluated on a production engine and fuel system setup in a laboratory environment.

  • 33.
    Krysander, Mattias
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Some theoretical results on sensor placement for diagnosis based on fault isolability specifications2007Report (Other academic)
    Abstract [en]

    This report presents the theoretical results of the work in. The report is not self-contained and should be considered to be complementary to the paper.

  • 34.
    Krysander, Mattias
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Frisk, Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Sensor Placement for Fault Isolation in Linear Differential-Algebraic Systems2008In: IFAC World Congress,2008, Seoul, Korea: IFAC , 2008Conference paper (Refereed)
    Abstract [en]

    An algorithm is proposed for computing which sensor additions that make a diagnosis requirement specification regarding fault detectability and isolability attainable for a given linear differential-algebraic model. Restrictions on possible sensor locations can be given and if the diagnosis specification is not attainable with any available sensor addition, the algorithm provides the solutions that maximize specification fulfillment. Previous approaches with similar objectives have been structural, but since this algorithm is analytical, it can handle models where structural approaches fail. A Mathematica implementation of the algorithm can be downloaded from http://www.fs.isy.liu.se/Software/LinSensPlaceTool/.

  • 35.
    Krysander, Mattias
    et al.
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Roll, Jacob
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Dynamic Test Selection for Reconfigurable Diagnosis2008In: Proceedings of the 47th IEEE Conference on Decision and Control, IEEE , 2008, p. 1066-1072Conference paper (Refereed)
    Abstract [en]

    Detecting and isolating multiple faults is a computationally intense task which typically consists of computing a set of tests, and then computing the diagnoses based on the test results. This paper proposes a method to reduce the computational burden by only running the tests that are currently needed, and dynamically starting new tests when the need changes. A main contribution is a method to select tests such that the computational burden is reduced while maintaining the isolation performance of the diagnostic system. Key components in the approach are the test selection algorithm, the test initialization procedures, and a knowledge processing framework that supports the functionality needed. The approach is exemplified on a relatively small dynamical system, which still illustrates the complexity and possible computational gain with the proposed approach.

  • 36.
    Krysander, Mattias
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Roll, Jacob
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    FlexDx: A Reconfigurable Diagnosis Framework2010In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 23, no 8, p. 1303-1313Article in journal (Refereed)
    Abstract [en]

    Detecting and isolating multiple faults is a computationally expensive task. It typically consists of computing a set of tests and then computing the diagnoses based on the test results. This paper describes FlexDx, a reconfigurable diagnosis framework which reduces the computational burden while retaining the isolation performance by only running a subset of all tests that is sufficient to find new conflicts. Tests in FlexDx are thresholded residuals used to indicate conflicts in the monitored system. Special attention is given to the issues introduced by a reconfigurable diagnosis framework. For example, tests are added and removed dynamically, tests are partially performed on historic data, and synchronous and asynchronous processing are combined. To handle these issues FlexDx has been implemented using DyKnow, a stream-based knowledge processing middleware framework. Concrete methods for each component in the FlexDx framework are presented. The complete approach is exemplified on a dynamic system which clearly illustrates the complexity of the problem and the computational gain of the proposed approach.

  • 37.
    Krysander, Mattias
    et al.
    Linköping University, Department of Electrical Engineering.
    Nyberg, Mattias
    Linköping University, Department of Electrical Engineering.
    Fault Isolability Prediction of Diagnostic Models2005In: 16th International Workshop on Principles of Diagnosis DX-05,2005, Pacific Grove, California, USA, 2005, p. 163-168Conference paper (Refereed)
    Abstract [en]

    Fault isolability plays a significant role and could be critical with respect to many aspects such as safety and maintenance for a process to be diagnosed. In the development of processes including diagnosis, design decisions are taken, e.g. sensor configuration selection, which affects the fault isolability possibilities. In this paper an algorithm for predicting fault isolability possibilities using a structural model describing the process is proposed. Since only a structural model is needed as input, the algorithm can easily predict fault isolability possibilities of different design concepts. In contrast to previous algorithms using structural models no assumption is imposed on the model. The algorithm computes faults that cannot be distinguished from other faults, which can be used to exclude design alternatives with insufficient isolability possibility.

  • 38.
    Krysander, Mattias
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Nyberg, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Statistical Properties and Design Criterions for Fault Isolation in Noisy Systems2008In: 19th International Workshop on Principles of Diagnosis, DX,2008, Sydney, Australia: DX , 2008Conference paper (Refereed)
    Abstract [en]

    Fault diagnosis in the presence of noise and model errors is of fundamental importance. In the paper, the meaning of fault isolation performance is formalized by using the established notion of coverage and false coverage from the field of statistics. Then formal relations describing the relationship between fault isolation performance and the residual related design parameters are derived. For small faults, the measures coverage and false coverage are not applicable so therefore, a different performance criteria, called sub-coverage, is proposed. The performance of different AI-based fault isolation schemes is evaluated and it is notably shown that the well known principle of minimal cardinality diagnosis gives a bad performance. Finally, some general design guidelines that guarantee and maximize the fault isolation performance are proposed.

  • 39.
    Krysander, Mattias
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nyberg, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Structural Analysis for Fault Diagnosis of DAE Systems Utilizing Graph Theory and MSS Sets2002Report (Other academic)
    Abstract [en]

    When designing model-based fault-diagnostic systems, the use of consistency relations (also called e.g. parity relations) is a common choice. Different consistency relations are sensitive to different subsets of faults, and thereby isolation can be achieved. This report presents an algorithm for finding a small set of submodels that can be used to derive consistency relations with highest possible diagnosis capability. The algorithm handles differential-algebraic models and is based on graph theoretical reasoning about the structure of the model. An important step towards finding these submodels, and therefore also towards finding consistency relations, is to find all minimal structurally singular (MSS) sets of equations. These sets characterize the fault diagnosability. The algorithm is applied to a large nonlinear industrial example, a part of a paper plant. In spite of the complexity of this process, a small set of consistency relations with high diagnosis capability is successfully derived.

  • 40.
    Krysander, Mattias
    et al.
    Linköping University, Department of Electrical Engineering.
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Graph Theoretical Methods for Finding Analytical Redundancy Relations in Overdetermined Differential Algebraic Systems2005In: 17th IMACS World Congress, Scientific Computation, Applied Mathematics and Simulation,2005, Paris, France, 2005Conference paper (Refereed)
    Abstract [en]

    One approach for design of diagnosis systems is to use residuals based on analytical redundancy. Overdetermined systems of equations provide analytical redundancy and by using minimal overdetermined subsystems, sensitivity to few faults is obtained. In this paper, overdetermined differential algebraic systems are considered and their structure is represented by bipartite graphs with equations and unknowns as node sets. By differentiating equations, a new set is formed, that is an overdetermined static algebraic system if derivatives of unknown signals are considered as separate independent variables. The task to derive analytical redundancy relations is thereby reduced to an algebraic problem. It is desirable to differentiate the equations as few times as possible and it is shown that there exists a unique minimally differentiated overdetermined system.

  • 41.
    Krysander, Mattias
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Nyberg, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    An Efficient Algorithm for Finding Minimal Overconstrained Subsystems for Model-Based Diagnosis2008In: IEEE transactions on systems, man and cybernetics. Part A. Systems and humans, ISSN 1083-4427, E-ISSN 1558-2426, Vol. 38, no 1, p. 197-206Article in journal (Refereed)
    Abstract [en]

    In model based diagnosis, the diagnostic system construction is based on a model of the technical system to be diagnosed. To handle large differential algebraic models and to achieve fault isolation, a common strategy is to pick out small over-constrained parts of the model and to test these separately against measured signals. A new algorithm for computing all minimal over-constrained sub-systems in a model is proposed. For complexity comparison, previous algorithms are recalled. It is shown that the time complexity under certain conditions is much better for the new algorithm. This is illustrated using a truck engine model.

  • 42.
    Krysander, Mattias
    et al.
    Linköping University, Department of Electrical Engineering.
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Nyberg, Mattias
    Linköping University, Department of Electrical Engineering.
    An Efficient Algorithm for Finding Over-constrained Sub-systems for Construction of Diagnostic Tests2005In: 16th International Workshop on Principles of Diagnosis DX-05,2005, Pacific Grove, California, USA, 2005, p. 55-60Conference paper (Refereed)
    Abstract [en]

    In this paper, a new algorithm for computing all minimal over-constrained sub-systems in a structural model is proposed. To handle large differential algebraic models in diagnosis, systematic structural approaches to find testable sub-systems have been suggested. It is shown how the algorithm can be incorporated and improve some of them. Previous algorithms are recalled and it is shown that the new algorithm is 14000 times faster when applied to a Scania truck engine model.

  • 43.
    Lee, Chih Feng
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Khong, Sei Zhen
    Department of Automatic Control, Lund University.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    An extremum seeking approach to parameterised loop-shaping control design2014In: Proceedings of The 19th World Congress of the International Federation of Automatic Control (IFAC 2014), Elsevier, 2014, Vol. 47, no 3, p. 10251-10256Conference paper (Refereed)
    Abstract [en]

    An approach to loop-shaping feedback control design in the frequency domain via extremum seeking is proposed. Both plants and controllers are linear time-invariant systems of possibly infinite dimension. The controller is assumed to be dependent on a finite number of parameters. Discrete-time global extremum seeking algorithms are employed to minimise the difference between the desired loop shape and the estimate of the present loop shape by fine-tuning the controller parameters within a sampled-data framework. The sampling period plays an important role in guaranteeing global practical convergence to the optimum. A case study on PID control tuning is presented to demonstrate the applicability of the proposed method.

  • 44.
    Nilsson, Tomas
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nyberg, Peter
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Sundström, Christofer
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    Robust Driving Pattern Detection and Identification with a Wheel Loader Application2014In: International journal of vehicle systems modelling and testing, ISSN 1745-6436, Vol. 9, no 1, p. 56-76Article in journal (Refereed)
    Abstract [en]

    Information about wheel loader usage can be used in several ways to optimize customer adaption. First, optimizing the configuration and component sizing of a wheel loader to customer needs can lead to a significant improvement in e.g. fuel efficiency and cost. Second, relevant driving cycles to be used in the development of wheel loaders can be extracted from usage data. Third, on-line usage identification opens up for the possibility of implementing advanced look-ahead control strategies for wheel loader operation. The main objective here is to develop an on-line algorithm that automatically, using production sensors only, can extract information about the usage of a machine. Two main challenges are that sensors are not located with respect to this task and that significant usage disturbances typically occur during operation. The proposed method is based on a combination of several individually simple techniques using signal processing, state automaton techniques, and parameter estimation algorithms. The approach is found to berobust when evaluated on measured data of wheel loaders loading gravel and shot rock.

  • 45.
    Nyberg, Mattias
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Krysander, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Statistical Properties and Design Criterions for AI-Based Fault Isolation2008In: IFAC World Congress,2008, Seoul, Korea: IFAC , 2008Conference paper (Refereed)
    Abstract [en]

    Fault diagnosis in the presence of noise and model errors is of fundamental importance. In the paper, the meaning of fault isolation performance is formalized by using the established notion of coverage and false coverage from the field of statistics. Then formal relations describing the relationship between fault isolation performance and the residual related design parameters are derived. For small faults, the measures coverage and false coverage are not applicable so therefore, a different performance criteria, called sub-coverage, is proposed. The performance of different AI-based fault isolation schemes is evaluated and it is shown that the well known principle of minimal cardinality diagnosis gives a very bad performance. Finally, some general design guidelines that guarantee and maximize the fault isolation performance are proposed.

  • 46. Polverino, Pierpaolo
    et al.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Jung, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Pianese, Cesare
    Model-based diagnosis through Structural Analysis and Causal Computation for automotive Polymer Electrolyte Membrane Fuel Cell systems2017In: Journal of Power Sources, ISSN 0378-7753, E-ISSN 1873-2755, Vol. 357, p. 26-40Article in journal (Refereed)
    Abstract [en]

    The present paper proposes an advanced approach for Polymer Electrolyte Membrane Fuel Cell (PEMFC) systems fault detection and isolation through a model-based diagnostic algorithm. The considered algorithm is developed upon a lumped parameter model simulating a whole PEMFC system oriented towards automotive applications. This model is inspired by other models available in the literature, with further attention to stack thermal dynamics and water management. The developed model is analysed by means of Structural Analysis, to identify the correlations among involved physical variables, defined equations and a set of faults which may occur in the system (related to both auxiliary components malfunctions and stack degradation phenomena). Residual generators are designed by means of Causal Computation analysis and the maximum theoretical fault isolability, achievable with a minimal number of installed sensors, is investigated. The achieved results proved the capability of the algorithm to theoretically detect and isolate almost all faults with the only use of stack voltage and temperature sensors, with significant advantages from an industrial point of view. The effective fault isolability is proved through fault simulations at a specific fault magnitude with an advanced residual evaluation technique, to consider quantitative residual deviations from normal conditions and achieve univocal fault isolation.

  • 47.
    Sundström, Christofer
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Smart Energy Usage for Vehicle Charging and House Heating2015Conference paper (Refereed)
    Abstract [en]

    In northern Europe the electricity price is set by hourly rates one day in advance. The price fluctuates due to supply and demand, and these fluctuations are expected to increase when solar and wind power are increased in the energy system. The potential in cost reduction for heating a house and charging of an electrified vehicle by using a smart energy management system in a household is investigated. Dynamic programming is used and a simulation study of a household in Sweden comparing this optimal control scheme with a heuristic controller is carried out. The time frame in the study is one year and a novel way of handling the fact that the vehicle is disconnected from the grid at some times is developed. A plug-in hybrid electric vehicle is considered, but the methodology is the same also for pure electric vehicles. It is found that the potential in energy cost reduction for house heating and vehicle charging is significant and that using a smart energy management system is a promising path of cost reduction, especially with the introduction of electrified vehicles. 

  • 48.
    Sundström, Timmy
    et al.
    Linköping University, Department of Electrical Engineering, Electronic Devices. Linköping University, The Institute of Technology.
    Mesgarzadeh, Behzad
    Linköping University, Department of Electrical Engineering, Electronic Devices. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Klein, Markus
    SAAB AB, Linköping, Sweden.
    Söderquist, Ingemar
    SAAB AB, Linköping, Sweden.
    Crona, Anneli
    SAAB AB, Linköping, Sweden.
    Fransson, Torbjörn
    SAAB AB, Linköping, Sweden.
    Alvandpour, Atila
    Linköping University, Department of Electrical Engineering, Electronic Devices. Linköping University, The Institute of Technology.
    Prognostics of Electronic Systems through Power Supply Current Trends2008Conference paper (Refereed)
    Abstract [en]

    As today’s avionic systems highly rely on electronic components, the prognostic of electronic systems in the context of avionics has become crucial. This paper presents a prognostic method applicable to electronic components and systems based on the analysis of the power supply current. In this method, the focus is on trends in the measured power supply current of the device under prognostic process. The discussion in this paper reveals that there is a measurable relationship between the supply current and the remaining lifetime of the electronic devices. The presented methodology is supported by circuit simulations performed on a system consisting of reference circuitry. The prognostic method shows great promise due to the ability of being applicable at any prognostic level.

  • 49.
    Sundström, Timmy
    et al.
    Linköping University, Department of Electrical Engineering, Electronic Devices. Linköping University, The Institute of Technology.
    Mesgarzadeh, Behzad
    Linköping University, Department of Electrical Engineering, Electronic Devices. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Klein, Markus
    Saab AB.
    Söderquist, Ingemar
    Saab AB.
    Krona, Anneli
    Saab AB.
    Fransson, Torbjörn
    Saab AB.
    Alvandpour, Atila
    Linköping University, Department of Electrical Engineering, Electronic Devices. Linköping University, The Institute of Technology.
    Prognostics of electronic systems through power supply current trends2008In: IEEE Internatioanl Conference on Prognostics and Health Management, Denver, USA, 2008Conference paper (Other academic)
    Abstract [en]

    As today's avionic systems highly rely on electronic components, the prognostic of electronic systems in the context of avionics has become crucial. This paper presents a prognostic method applicable to electronic components and systems based on the analysis of the power supply current. In this method, the focus is on trends in the measured power supply current of the device under prognostic process. The discussion in this paper reveals that there is a measurable relationship between the supply current and the remaining lifetime of the electronic devices. The presented methodology is supported by circuit simulations performed on a system consisting of reference circuitry. The prognostic method shows great promise due to the ability of being applicable at any prognostic level.

  • 50.
    Svärd, Carl
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nyberg, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    A Data-Driven and Probabilistic Approach to Residual Evaluation for Fault Diagnosis2011In: 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), 2011, Institute of Electrical and Electronics Engineers (IEEE), 2011, p. 95-102Conference paper (Refereed)
    Abstract [en]

    An important step in fault detection and isolation is residual evaluation where residuals, signals ideally zero in the no-fault case, are evaluated with the aim to detect changes in their behavior caused by faults. Generally, residuals deviate from zero even in the no-fault case and their probability distributions exhibit non-stationary features due to, e.g., modeling errors, measurement noise, and different operating conditions. To handle these issues, this paper proposes a data-driven approach to residual evaluation based on an explicit comparison of the residual distribution estimated on-line and a no-fault distribution, estimated off-line using training data. The comparison is done within the framework of statistical hypothesis testing. With the Generalized Likelihood Ratio test statistic as starting point, a more powerful and computational efficient test statistic is derived by a properly chosen approximation to one of the emerging likelihood maximization problems. The proposed approach is evaluated with measurement data on a residual for diagnosis of the gas-flow system of a Scania truck diesel engine. The proposed test statistic performs well, small faults can for example be reliable detected in cases where regular methods based on constant thresholding fail.

12 1 - 50 of 55
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf