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  • 1.
    Biteus, Jonas
    et al.
    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.
    Frisk, Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    An algorithm for computing the diagnoses with minimal cardinality in a distributed system2008In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 21, no 2, p. 269-276Article in journal (Refereed)
    Abstract [en]

    In fault diagnosis, the set of minimal diagnoses is commonly calculated. However, due to for example limited computation resources, the search for the set of minimal diagnoses is in some applications focused on to the smaller set of diagnoses with minimal cardinality. The key contribution in this paper is an algorithm that calculates the diagnoses with minimal cardinality in a distributed system. The algorithm is constructed such that the computationally intensive tasks are distributed to the different units in the distributed system, and thereby reduces the need for a powerful central diagnostic unit. © 2007 Elsevier Ltd. All rights reserved.

  • 2.
    Biteus, Jonas
    et al.
    Power-Train Division, Scania.
    Nyberg, Mattias
    Power-Train Division, Scania.
    Frisk, Erik
    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.
    Determining the Fault Status of a Component and its Readiness, with a Distributed Automotive Application2009In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 22, no 3, p. 363-373Article in journal (Refereed)
    Abstract [en]

    In systems using only single-component tests, the fault status of a component is ready if a test only supervising the component has been evaluated. However, if plausibility tests that supervise multiple components are used, then a component can be ready before all tests supervising the component have been evaluated. Based on test results, this paper contributes with conditions on when a component is ready. The conditions on readiness are given for both centralized and distributed systems and are here applied to the distributed diagnostic system in an automotive vehicle.

  • 3.
    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.

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  • 4.
    Norrlöf, Mikael
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Disturbance Aspects of Iterative Learning Control2001In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 14, no 1, p. 87-94Article in journal (Refereed)
    Abstract [en]

    Disturbance aspects of iterative learning control (ILC) are considered. By using a linear framework it is possible to investigate the influence of the disturbances in the frequency domain. The effects of the design filters in the ILC algorithm on the disturbance properties can then be analyzed. The analysis is supported by simulations and experiments.

  • 5.
    Pernestål, Anna
    et al.
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Nyberg, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Warnquist, Håkan
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Modeling and inference for troubleshooting with interventions applied to a heavy truck auxiliary braking system2012In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 25, no 4, p. 705-719Article in journal (Refereed)
    Abstract [en]

    Computer assisted troubleshooting with external interventions is considered. The work is motivated by the task of repairing an automotive vehicle at lowest possible expected cost. The main contribution is a decision theoretic troubleshooting system that is developed to handle external interventions. In particular, practical issues in modeling for troubleshooting are discussed, the troubleshooting system is described, and a method for the efficient probability computations is developed. The troubleshooting systems consists of two parts; a planner that relies on AO* search and a diagnoser that utilizes Bayesian networks (BN). The work is based on a case study of an auxiliary braking system of a modern truck. Two main challenges in troubleshooting automotive vehicles are the need for disassembling the vehicle during troubleshooting to access parts to repair, and the difficulty to verify that the vehicle is fault free. These facts lead to that probabilities for faults and for future observations must be computed for a system that has been subject to external interventions that cause changes in the dependency structure. The probability computations are further complicated due to the mixture of instantaneous and non-instantaneous dependencies. To compute the probabilities, we develop a method based on an algorithm, updateBN, that updates a static BN to account for the external interventions.

  • 6.
    Ribeiro, Luis
    et al.
    Uninova - CTS, Departamento de Engenharia Electrote ́ cnica, Faculdade de Ci ˆ encias e Tecnologia, FCT, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal.
    Barata, Jose
    Uninova - CTS, Departamento de Engenharia Electrote ́ cnica, Faculdade de Ci ˆ encias e Tecnologia, FCT, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal.
    IMS 10 €”Validation of a co-evolving diagnostic algorithm for evolvable production systems2012In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 25, no 6, p. 1142-1160Article in journal (Refereed)
    Abstract [en]

    With the systematic implantation and acceptance of IT in the shop-floor a wide range of production paradigms, relying in open interoperable architectures, have been developed. Exploring these technological novelties, they promise to revolutionize the way current plant floors operate and react to emerging opportunities and disturbances. There is a high interest of module providers in the adoption of these open mechatronic architectures as they may provide a new business model where the automation solution can be easily tailored for each customer in due time and ships with a significant part of the control solution (high added value). Final customers on their side can contract operating hours rather than buying modules. Moreover, the automation solution can be swiftly modified to meet changing requirements.

    The necessary increase in the number of distributed and autonomous components that interact in the execution of processes implies that new diagnostic approaches should be developed to tackle the network layer of these highly dynamic systems. In fact fault propagation events can be harder to understand and can affect the system in unpredictable and pervasive ways.

    Following this rationale the paper presents a potential diagnostic solution that targets multiagent-based mechatronic systems where their components are highly decoupled from a control point of view. The diagnostic architecture presented tackles the problem of fault propagation while preserving the decoupled nature of the Mechatronic Agent concept. In this context the diagnostic system explores self-organization to enact an emergent response that denotes macro-level coherence. The system's response is the result of an individual probabilistic diagnostic inference based on Hidden Markov Models that capture the propagating nature of a failure.

    The validation results of the proposed diagnostic approach are detailed for the system's response in simulation (highlighting the main variables that affect the performance of the system) and compared to the system applied to a pilot assembly cell. The simulation model and the performance metrics considered are detailed and discussed along with the main implementation details.

  • 7.
    Ribeiro, Luis
    et al.
    Electrical Engineering Department, Faculty of Sciences and Technology, New University of Lisbon, 2829-516 Monte de Caparica, Portugal.
    Barata, Jose
    Electrical Engineering Department, Faculty of Sciences and Technology, New University of Lisbon, 2829-516 Monte de Caparica, Portugal.
    Colombo, Armando
    Schneider Electric, Seligenstadt, Germany.
    Supporting agile supply chains using a service-oriented shop floor2009In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 22, no 6, p. 950-960Article in journal (Refereed)
    Abstract [en]

    The globalized nature of current business environments led to the emergence of new networked enterprise organizational paradigms (supply chains, extended enterprises, virtual enterprises, collaborative networks, etc.) to meet changing requirements and tackle profitable but volatile opportunities overall agility is required.

    Eventually the shop floor will have to react and accommodate (re)adjustments in the supply chain making it an important piece in the competitiveness puzzle. So far, the research focus has been in high level aspects of supply chain management and the integration of shop floor activities in the process has been left relatively unattended.

    However, shop floor data is increasingly required in business tools that support decision making. In this context, failing to support agility at shop floor level can compromise the agility of the supply chain.

    Recent developments in networked information technologies and embedded devices allow enabling intelligence in shop floor rendering it an active and live entity that further enhances the dynamics of the supply chain.

    The goal of the present work, supported by an implemented test case in the assembly domain, is to demonstrate how one is able to seamless integrate the shop floor with external tools and achieve a highly reconfigurable environment that adapts to changing production requirements and disturbances using service-oriented technology.

  • 8.
    Saar de Moraes, Rodrigo
    et al.
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Nadjm-Tehrani, Simin
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    NetGAP: A graph grammar approach for concept design of networked platforms with extra-functional requirements2024In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 133, article id 108089Article in journal (Refereed)
    Abstract [en]

    During the concept design of complex networked systems, concept developers have to ensure that the choice of hardware modules and the topology of the target platform will provide adequate resources to support the needs of the application. For example, future -generation aerospace systems need to consider multiple requirements, with many trade-offs, foreseeing rapid technological change and a long period for realization and service. For that purpose, we introduce NetGAP, an automated 3 -phase approach to synthesize network topologies and support the exploration and concept design of networked systems with multiple requirements including dependability, security, and performance. NetGAP represents the possible interconnections between hardware modules using a graph grammar and uses a Monte Carlo Tree Search optimization to generate candidate topologies from the grammar while aiming to satisfy the requirements. We apply the proposed approach to a synthetic version of a realistic avionics application use case. It includes 99 processes and 660 messages. The experiment shows the merits of the solution to support the early -stage exploration of alternative candidate topologies. The method vividly characterizes the topology -related trade-offs between requirements stemming from security, fault tolerance, timeliness, and the "cost'' of adding new modules or links. We also create a scaled -up version of the problem (267 processes, 1887 messages) to illustrate scalability. Finally, we discuss the flexibility of using the approach when changes in the application and its requirements occur.

  • 9.
    Voronov, Sergii
    et al.
    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.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    A forest-based algorithm for selecting informative variables using Variable Depth Distribution2021In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 97, article id 104073Article in journal (Refereed)
    Abstract [en]

    Predictive maintenance of systems and their components in technical systems is a promising approach to optimize system usage and reduce system downtime. Various sensor data are logged during system operation for different purposes, but sometimes not directly related to the degradation of a specific component. Variable selection algorithms are necessary to reduce model complexity and improve interpretability of diagnostic and prognostic algorithms. This paper presents a forest-based variable selection algorithm that analyzes the distribution of a variable in the decision tree structure, called Variable Depth Distribution, to measure its importance. The proposed variable selection algorithm is developed for datasets with correlated variables that pose problems for existing forest-based variable selection methods. The proposed variable selection method is evaluated and analyzed using three case studies: survival analysis of lead-acid batteries in heavy-duty vehicles, engine misfire detection, and a simulated prognostics dataset. The results show the usefulness of the proposed algorithm, with respect to existing forest-based methods, and its ability to identify important variables in different applications. As an example, the battery prognostics case study shows that similar predictive performance is achieved when only 17% percent of the variables are used compared to all measured signals.

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