Journal ArticleDOI
Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results
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TLDR
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).read more
Citations
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Journal ArticleDOI
Assessment of structural interventions using Bayesian updating and subspace-based fault detection methods: the case study of S. Maria di Collemaggio basilica, L’Aquila, Italy
TL;DR: A permanent monitoring system installed in a monumental masonry structure, the basilica of Santa Maria di Collemaggio in L’Aquila Italy, continuously acquires vibration data, which leads to the assessment of a structural intervention using a simple Bayesian approach driven by subspace-based indicators.
Proceedings ArticleDOI
Design of sliding mode observers for TS fuzzy systems with application to disturbance and actuator fault estimation
TL;DR: A sliding mode fuzzy observer that deals with unmeasurable premise variables, bounded uncertainties in the plant and allows fault estimation based on an equivalent output error injection approach is proposed.
Journal ArticleDOI
Robust Fault Detection for Uncertain Discrete-Time Systems
Haibo Wang,James Lam +1 more
TL;DR: In this paper, an unconstrained optimization approach is taken to design a robust fault detection observer, which aims at enhancing the fault detection robustness to uncertainties without sacrie cing the faultdetectionsensitivity.
Journal ArticleDOI
Machine learning technique for data-driven fault detection of nonlinear processes
TL;DR: This paper proposes a new machine learning method for fault detection using a reduced kernel partial least squares (RKPLS), in static and online forms, for handling nonlinear dynamic systems.
Proceedings ArticleDOI
A sequential Monte Carlo filtering approach to fault detection and isolation in nonlinear systems
TL;DR: In this paper, the authors use the sequential Monte Carlo filtering approach where the complete posterior distribution of the estimates are represented through samples or particles as opposed to the mean and covariance of an approximated Gaussian distribution.
References
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Journal ArticleDOI
Paper: A survey of design methods for failure detection in dynamic systems
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.
Journal ArticleDOI
Process fault detection based on modeling and estimation methods-A survey
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.
Journal ArticleDOI
Analytical redundancy and the design of robust failure detection systems
E. Chow,Alan S. Willsky +1 more
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.
A survey of design methods for failure detection in dynamic systems
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.