Nonlinear Model Decomposition for Fault Detection and Isolation System Design

Berdjag, Denis; Christophe, C.; Cocquempot, Vincent

doi:10.1109/cdc.2006.377518

Cited by 14 publications

(18 citation statements)

References 7 publications

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“…An algebraic formulation of the problem and of the solution was presented, based on previous work on continuous-time model decoupling (Berdjag et al, 2006c). This general formulation permits addressing all types of deterministic models.…”

Section: Resultsmentioning

confidence: 99%

“…The decomposition algorithm is then applied to a particular problem: the constrained decomposition of FSMs. It is important to notice that the algebraic formalism used to implement the decomposition (Algorithm 1) remains the same in the case of continuous-time models (Berdjag et al, 2006b).…”

Section: Resultsmentioning

confidence: 99%

“…The algebraic structure used is known under the name of the algebra of functions. Recently, the algebra of functions was used in several topics of model-based monitoring for deterministic systems (Berdjag, 2006b;2006c), uncertain systems (Shumsky, 2007) and canonical decomposition (Zhirabok, 2006). An analysis of the algebra of functions was presented by Zhirabok and Shumsky (1993) and Berdjag et al (2006b).…”

Section: Decomposition Algorithmmentioning

confidence: 99%

“…In this paper we use a particular algebraic formalism, inspired by the algebra of functions (Shumsky, 1991;Zhirabok and Shumsky, 1993;Shumsky and Zhirabok, 2006). Decomposition based on the algebra of functions was the topic of our previous publications (Berdjag et al, 2006a;2006c), where an iterative decomposition algorithm using output injection was presented for nonlinear continuous-time models. This paper emphasizes the extension of the decomposition algorithm to major types of deterministic behavioural models, using set-theory notions (Vereshchagin and Shen, 2002).…”

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confidence: 99%

See 3 more Smart Citations

Algebraic approach for model decomposition: Application to fault detection and isolation in discrete-event systems

Berdjag¹,

Cocquempot²,

Christophe³

et al. 2011

International Journal of Applied Mathematics and Computer Science

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This paper presents a constrained decomposition methodology with output injection to obtain decoupled partial models. Measured process outputs and decoupled partial model outputs are used to generate structured residuals for Fault Detection and Isolation (FDI). An algebraic framework is chosen to describe the decomposition method. The constraints of the decomposition ensure that the resulting partial model is decoupled from a given subset of inputs. Set theoretical notions are used to describe the decomposition methodology in the general case. The methodology is then detailed for discrete-event model decomposition using pair algebra concepts, and an extension of the output injection technique is used to relax the conservatism of the decomposition.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Decomposition Algorithmmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Algebraic approach for model decomposition: Application to fault detection and isolation in discrete-event systems

Berdjag¹,

Cocquempot²,

Christophe³

et al. 2011

International Journal of Applied Mathematics and Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…Model-based FDI have been mostly studied for linear time invariant (LTI) systems (Gertler, 1998;Chen and Patton, 1999;Isermann, 2005;Ding, 2008), whereas nonlinear systems have been studied to a lesser extent and limited to some particular classes of systems (De Persis and Isidori, 2001;Xu and Zhang, 2004;Berdjag et al, 2006). This paper is focused on actuator fault diagnosis for linear time-varying (LTV) systems, including the particular case of linear parameter varying (LPV) systems.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Kalman filter for actuator fault diagnosis

Zhang

2018

Automatica

131

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An adaptive Kalman filter is proposed in this paper for actuator fault diagnosis in discrete time stochastic time varying systems. By modeling actuator faults as parameter changes, fault diagnosis is performed through joint state-parameter estimation in the considered stochastic framework. Under the classical uniform complete observability-controllability conditions and a persistent excitation condition, the exponential stability of the proposed adaptive Kalman filter is rigorously analyzed. The minimum variance property of the combined state and parameter estimation errors is also demonstrated. Numerical examples are presented to illustrate the performance of the proposed algorithm.

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Sensor fault detection and isolation for wind turbines based on subspace identification and Kalman filter techniques

Wei

Verhaegen

Engelen

2010

Adaptive Control & Signal

114

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This paper aims at the blade root moment sensor fault detection and isolation issue for three-bladed wind turbines with horizontal axis. The underlying problem is crucial to the successful application of the individual pitch control system, which plays a key role for reducing the blade loads of large offshore wind turbines. In this paper, a wind turbine model is built based on the closed loop identification technique, where the wind dynamics is included. The fault detection issue is investigated based on the residuals generated by dual Kalman filters. Both additive faults and multiplicative faults are considered in this paper. For the additive fault case, the mean value change detection of the residuals and the generalized likelihood ratio test are utilized respectively. For multiplicative faults, they are handled via the variance change detection of the residuals. The fault isolation issue is proceeded with the help of dual sensor redundancy. Simulation results show that the proposed approach can be successfully applied to the underlying issue.

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Nonlinear Model Decomposition for Fault Detection and Isolation System Design

Cited by 14 publications

References 7 publications

Algebraic approach for model decomposition: Application to fault detection and isolation in discrete-event systems

Algebraic approach for model decomposition: Application to fault detection and isolation in discrete-event systems

Adaptive Kalman filter for actuator fault diagnosis

Sensor fault detection and isolation for wind turbines based on subspace identification and Kalman filter techniques

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