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).
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TL;DR: A bibliographical review on reconfigurable fault-tolerant control systems (FTCS) is presented, with emphasis on the reconfiguring/restructurable controller design techniques.
2,455 citations
TL;DR: This three part series of papers is to provide a systematic and comparative study of various diagnostic methods from different perspectives and broadly classify fault diagnosis methods into three general categories and review them in three parts.
2,263 citations
TL;DR: The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade.
Abstract: With the continuous increase in complexity and expense of industrial systems, there is less tolerance for performance degradation, productivity decrease, and safety hazards, which greatly necessitates to detect and identify any kinds of potential abnormalities and faults as early as possible and implement real-time fault-tolerant operation for minimizing performance degradation and avoiding dangerous situations. During the last four decades, fruitful results have been reported about fault diagnosis and fault-tolerant control methods and their applications in a variety of engineering systems. The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade. In this paper, fault diagnosis approaches and their applications are comprehensively reviewed from model- and signal-based perspectives, respectively.
2,026 citations
TL;DR: This final part discusses fault diagnosis methods that are based on historic process knowledge that need to be addressed for the successful design and implementation of practical intelligent supervisory control systems for the process industries.
1,902 citations
TL;DR: The approach to failure diagnosis presented in this paper is applicable to systems that fall naturally in the class of DES's; moreover, for the purpose of diagnosis, most continuous variable dynamic systems can be viewed as DES's at a higher level of abstraction.
Abstract: Fault detection and isolation is a crucial and challenging task in the automatic control of large complex systems We propose a discrete-event system (DES) approach to the problem of failure diagnosis We introduce two related notions of diagnosability of DES's in the framework of formal languages and compare diagnosability with the related notions of observability and invertibility We present a systematic procedure for detection and isolation of failure events using diagnosers and provide necessary and sufficient conditions for a language to be diagnosable The diagnoser performs diagnostics using online observations of the system behavior; it is also used to state and verify off-line the necessary and sufficient conditions for diagnosability These conditions are stated on the diagnoser or variations thereof The approach to failure diagnosis presented in this paper is applicable to systems that fall naturally in the class of DES's; moreover, for the purpose of diagnosis, most continuous variable dynamic systems can be viewed as DES's at a higher level of abstraction >
1,599 citations
References
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Dissertation•
01 Feb 1986TL;DR: In this article, it is shown that it is possible to design a causal linear-time-invariant processor that can be used to detect and uniquely identify a component failure in a linear time-inariant system, assuming: (1) the components can fail simultaneously, and (2) the component can fail only one at a time.
Abstract: Using concepts of (C,A)-invariant and unobservability (complementary observability) subspaces, a geometric formulation of the failure detection and identification filter problem is stated. Using these geometric concepts, it is shown that it is possible to design a causal linear time-invariant processor that can be used to detect and uniquely identify a component failure in a linear time-invariant system, assuming: (1) The components can fail simultaneously, and (2) The components can fail only one at a time. In addition, a geometric formulation of Beard's failure detection filter problem is stated. This new formulation completely clarifies of output separability and mutual detectability introduced by Beard and also exploits the dual relationship between a restricted version of the failure detection and identification problem and the control decoupling problem. Moreover, the frequency domain interpretation of the results is used to relate the concepts of failure sensitive observers with the generalized parity relations introduced by Chow. This interpretation unifies the various failure detection and identification concepts and design procedures.
114 citations
TL;DR: In this paper, a procedure for the design of a pair of sensitivity discriminating Luenberger observers for instrument failure detection (IFD) is presented, which permits detection of instrument malfunctions with reduced sensitivity to process parameter variations.
Abstract: A procedure is presented for the design of a pair of sensitivity discriminating Luenberger observers for instrument failure detection (IFD). The proposed IFD scheme permits detection of instrument malfunctions with reduced sensitivity to process parameter variations. The efficiency of detecting instrument malfunctions and the influence of parameter variations are illustrated with an example.
92 citations
01 Jan 1987
TL;DR: The resulting observer is described by equations that allow the estimation of a linear combination of the state with a delay of a finite number of samplings and this robust state estimation though hardly usable for control purposes can successfully be considered for failure detection.
Abstract: This paper describes the design and the application of so called “Unknown Input Observers” or “Robust Observers” for failure detection. The fist part of the paper shows a design procedure for a discrete time observer which considers the concept of the “invariant subspace” and of the “almost invariant subspace”. Design tool is the Kronecker canonical form which also gives a complete answer to the question of state estimation of discrete time systems acting under unknown inputs. The resulting observer is described by equations that allow the estimation of a linear combination of the state with a delay of a finite number of samplings. This robust state estimation though hardly usable for control purposes can successfully be considered for failure detection.
81 citations
TL;DR: In this article, an extension of the idea of using analytical redundancy to design a match between m components of the observation error space instead of using state estimates has been presented, which eliminates the need for state-space computations, thus producing an effective real-time fault monitor for fly-by-wire aircraft.
Abstract: A new method of analyzing faults in the m measurements of an nth-order system is presented. The proposed approach uses the estimation error space of each observer in a bank of observers to detect and isolate sensor faults. The designs are applied to a nonlinear model of an unmanned aircraft that has been described in previous publications. The reconfigurability of the aircraft sensor system is demonstrated, and the results show rapid recovery from a faulty sensor. The use of the observation error eliminates the need for state-space computations, thus producing an effective real-time fault monitor for fly-by-wire aircraft. N an earlier paper,1 a comparison of two techniques of instrument fault diagnosis (IFD) was made. This work is an extension of Patton and Willcox's idea of using analytical redundancy to design a match between m components of the observation error space instead of using state estimates di- rectly as discussed by Clark,3'4 Clark and Setzer,5 Frank and Keller,6 and Watanabe and Himmelblau.7 IFD in dynamic systems has received a significant amount of attention recently.2"11 Most methods described in the liter- ature discuss the analytical redundancy approach in prefer- ence to the use of redundant hardware. Analytical redundancy provides redundant (estimate) information from different measurements of a process, usually with observer or Kalman filter schemes. The commonly discussed state estimate solu- tion to IFD is based on the principle of generating estimates of part or all of the system state vector from subsets of the measurements, which when compared with similar estimates from other observers can be used to monitor the health of an instrument. The problem with the state estimate solution to IFD arises as the observer requires a good linear model of the process, and it must also be assumed that the disturbances on the system are well modeled or else have an insignificant effect on plant parameter variations. These limitations cause the state estimate approach to be inadequate for many real en- gineering applications. Sensitivity to input-induced parameter variations causes uncertain errors between redundant state estimate vectors, and in an IFD scheme these errors could cause false signaling of an instrument fault. It becomes clear that the bandwidth of uncertain signals should be estimated prior to the IFD system design. The use of frequency domain sensitivity information in this way enables a robust approach to the observer design to be made. The conjecture used is that the "innovations" or prediction error signals contain all the information concerning the parameter variations of the pro- cess being identified and controlled. Attention is thus turned toward the use of an innovations-based approach to system fault diagnosis that has wide potential applications. By using a weighting of the measurement estimation error as a parity
76 citations
01 Dec 1981
TL;DR: In this article, a fault detection and isolation methodology for validation of sensors and plant components is developed for real-time applications, and validated by on-line demonstration in an operating nuclear reactor.
Abstract: A fault detection and isolation methodology has been developed for validation of sensors and plant components. Significantly, the isolation of most consistent and inconsistent subsets of measurements for the purposes of estimation and failure detection is performed on the basis of a multi-level, as opposed to the usual bi-level, fail/no fail, characterization of the inconsistencies among measurements. This is achieved by the concurrent checking of the relative consistency of smaller size subsets of measurements. The algorithm has been computer-coded for real time applications, and validated by on-line demonstration in an operating nuclear reactor.
68 citations