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Residual Generation Methods for Fault Diagnosis with Automotive Applications
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
2009 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The problem of fault diagnosis consists of detecting and isolating faults present in a system. As technical systems become more and more complex and the demands for safety, reliability and environmental friendliness are rising, fault diagnosis is becoming increasingly important. One example is automotive systems, where fault diagnosis is a necessity for low emissions, high safety, high vehicle uptime, and efficient repair and maintenance.

One approach to fault diagnosis, providing potentially good performance and in which the need for additional hardware is minimal, is model-based fault diagnosis with residuals. A residual is a signal that is zero when the system under diagnosis is fault-free, and non-zero when particular faults are present in the system. Residuals are typically generated by using a mathematical model of the system and measurements from sensors and actuators. This process is referred to as residual generation.

The main contributions in this thesis are two novel methods for residual generation. In both methods, systems described by Differential-Algebraic Equation (DAE) models are considered. Such models appear in a large class of technical systems, for example automotive systems. The first method consider observer-based residual generation for linear DAE-models. This method places no restrictions on the model, such as e.g. observability or regularity, in comparison with other previous methods. If the faults of interest can be detected in the system, the output from the design method is a residual generator, in state-space form, that is sensitive to the faults of interest. The method is iterative and relies on constant matrix operations, such as e.g. null-space calculations and equivalence transformations.

In the second method, non-linear DAE-models are considered. The proposed method belongs to a class of methods, in this thesis referred to as sequential residual generation, which has shown to be successful for real applications. This method enables simultaneous use of integral and derivative causality, and is able to handle equation sets corresponding to algebraic and differential loops in a systematic manner. It relies on a formal framework for computing unknown variables in the model according to a computation sequence, in which the analytical properties of the equations in the model as well as the available tools for equation solving are taken into account. The method is successfully applied to complex models of an automotive diesel engine and a hydraulic braking system.

Place, publisher, year, edition, pages
Linkö: Linköping University Electronic Press , 2009. , 28 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1406
Keyword [en]
Diagnosis, fault diagnosis, FDI, fault detection, residual, residual generation, residual generator, DAE
National Category
Information Science
Identifiers
URN: urn:nbn:se:liu:diva-19104Local ID: LIU-TEK-LIC-2009:14ISBN: 978-91-7393-608-8 (print)OAI: oai:DiVA.org:liu-19104DiVA: diva2:223267
Presentation
2009-06-04, Visionen, B-huset, ingång 27, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2009-06-15 Created: 2009-06-11 Last updated: 2012-05-08Bibliographically approved
List of papers
1. An Observer-Based Residual Generation Method for Linear Differential-Algebraic Equation Systems
Open this publication in new window or tab >>An Observer-Based Residual Generation Method for Linear Differential-Algebraic Equation Systems
2009 (English)In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671Article in journal (Other academic) Submitted
Abstract [en]

Residual generation for linear differential-algebraic systems is considered. A new systematic method for observer-based residual generation is presented. The proposed design method places no restrictions on the system to be diagnosed. If the fault of interest can be detected in the system, the output from the design method is a residual generator in state-space form that is sensitive to the fault of interest. The method is iterative and relies only on constant matrix operations such as multiplications, null-space calculations and equivalence transformations, and thereby straightforward to implement. An illustrative numerical example is included, where the design method is applied to a nonobservable model of a robot manipulator.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-19252 (URN)
Available from: 2009-06-15 Created: 2009-06-15 Last updated: 2017-12-13Bibliographically approved
2. Residual Generators for Fault Diagnosis Using Computation Sequences With Mixed Causality Applied to Automotive Systems
Open this publication in new window or tab >>Residual Generators for Fault Diagnosis Using Computation Sequences With Mixed Causality Applied to Automotive Systems
2010 (English)In: IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, ISSN 1083-4427, Vol. 40, no 6, 1310-1328 p.Article in journal (Refereed) Published
Abstract [en]

An essential step in the design of a model-based diagnosis system is to find a set of residual generators fulfilling stated fault detection and isolation requirements. To be able to find a good set, it is desirable that the method used for residual generation gives as many candidate residual generators as possible, given a model. This paper presents a novel residual generation method that enables simultaneous use of integral and derivative causality, i.e., mixed causality, and also handles equation sets corresponding to algebraic and differential loops in a systematic manner. The method relies on a formal framework for computing unknown variables according to a computation sequence. In this framework, mixed causality is utilized, and the analytical properties of the equations in the model, as well as the available tools for algebraic equation solving, are taken into account. The proposed method is applied to two models of automotive systems, a Scania diesel engine, and a hydraulic braking system. Significantly more residual generators are found with the proposed method in comparison with methods using solely integral or derivative causality.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA, 2010
Keyword
Fault diagnosis, model-based diagnosis, nonlinear systems, residual generation
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-61313 (URN)10.1109/TSMCA.2010.2049993 (DOI)000283447200015 ()
Note
©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Carl Svärd and Mattias Nyberg, Residual Generators for Fault Diagnosis Using Computation Sequences With Mixed Causality Applied to Automotive Systems, 2010, IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, (40), 6, 1310-1328. http://dx.doi.org/10.1109/TSMCA.2010.2049993 Available from: 2010-11-12 Created: 2010-11-12 Last updated: 2012-05-08

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