Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results
TL;DR: In this article, the authors review the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and present some new results with emphasis on the latest attempts to achieve robustness with respect to modelling errors.
About: This article is published in Automatica.The article was published on 1990-05-01. It has received 3313 citations till now. The article focuses on the topics: Fault detection and isolation & Robustness (computer science).
Citations
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TL;DR: The state of the art of model-based fault diagnosis in plants of automatic control systems is reviewed, the basic idea of a novel type of diagnostic observer, the so-called knowledge observer, is introduced and some new results of the author's research group are outlined.
548 citations
14 Dec 1994
TL;DR: A discrete event systems (DES) approach to the failure diagnosis problem is proposed and the notion of diagnosability is discussed, and the construction procedure of the diagnoser is presented.
Abstract: We propose a discrete event systems (DES) approach to the failure diagnosis problem. We present a methodology for modeling physical systems in a DES framework. We discuss the notion of diagnosability and present the construction procedure of the diagnoser. Finally, we illustrate our approach using a heating, ventilation and air conditioning (HVAC) system. >
505 citations
TL;DR: A unified methodology for detecting, isolating and accommodating faults in a class of nonlinear dynamic systems is presented and it is shown that the system signals remain bounded and the output tracking error converges to a neighborhood of zero.
Abstract: This paper presents a unified methodology for detecting, isolating and accommodating faults in a class of nonlinear dynamic systems. A fault diagnosis component is used for fault detection and isolation. On the basis of the fault information obtained by the fault-diagnosis procedure, a fault-tolerant control component is designed to compensate for the effects of faults. In the presence of a fault, a nominal controller guarantees the boundedness of all the system signals until the fault is detected. Then the controller is reconfigured after fault detection and also after fault isolation, to improve the control performance by using the fault information generated by the diagnosis module. Under certain assumptions, the stability of the closed-loop system is rigorously investigated. It is shown that the system signals remain bounded and the output tracking error converges to a neighborhood of zero.
505 citations
TL;DR: In this article, the best known residual generation methods in model-based fault detection and isolation, including parity equations, diagnostic observers and Kalman filtering, are presented in a consistent framework.
498 citations
TL;DR: Some schemes extending the well-known diagnosis methods for linear systems to the nonlinear case are considered and the robustness of these schemes in presence of unknown inputs is discussed.
486 citations
References
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TL;DR: This paper surveys a number of methods for the detection of abrupt changes in stochastic dynamical systems, focusing on the class of linear systems, but the basic concepts carry over to other classes of systems.
2,416 citations
TL;DR: This contribution presents a brief summary of some basic fault detection methods, followed by a description of suitable parameter estimation methods for continuous-time models.
2,367 citations
TL;DR: In this article, a robust failure detection and identification (FDI) process is viewed as consisting of two stages: residual generation and decision making, and it is argued that a robust FDI system can be achieved by designing a robust residual generation process.
Abstract: The failure detection and identification (FDI) process is viewed as consisting of two stages: residual generation and decision making. It is argued that a robust FDI system can be achieved by designing a robust residual generation process. Analytical redundancy, the basis for residual generation, is characterized in terms of a parity space. Using the concept of parity relations, residuals can be generated in a number of ways and the design of a robust residual generation process can be formulated as a minimax optimization problem. An example is included to illustrate this design methodology.
1,480 citations
01 Jan 1975
TL;DR: A number of methods for detecting abrupt changes (such as failures) in stochastic dynamical systems are surveyed in this paper, where tradeoffs in complexity versus performance are discussed, ranging from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, and the development of jump process formulations.
Abstract: A number of methods for detecting abrupt changes (such as failures) in stochastic dynamical systems are surveyed. The class of linear systems is concentrated on but the basic concepts, if not the detailed analyses, carry over to other classes of systems. The methods surveyed range from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, to the development of jump process formulations. Tradeoffs in complexity versus performance are discussed.
1,451 citations
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01 Nov 19891,169 citations