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
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Proceedings ArticleDOI
A frequency domain approach to fault detection of uncertain dynamic systems
X. Ding,L. Guo,Paul M. Frank +2 more
TL;DR: In this paper, the authors formulated the residual generation and evaluation problems as optimization problems that are solvable using frequency domain optimization techniques and derived an expression for achievable minimum size of detectable faults by using linear residual generators.
Journal ArticleDOI
A hybrid framework for large scale process fault diagnosis
TL;DR: A hybrid framework in which different diagnostic methods perform collective problem solving shows a lot of promise, and combines causal model-based diagnosis with statistical classifiers and syntactic pattem recognition, called DKit is proposed.
Journal ArticleDOI
A review of data-driven fault detection and diagnosis methods: applications in chemical process systems
TL;DR: The aim of this review is to provide the state-of-the-art reference for chemical engineers and to promote the application of data-driven FDD methods in chemical process systems by providing a guideline for selecting the best possible data- driven method for FDD systems based on their faults.
Journal ArticleDOI
A Model-Based Fault-Detection and Prediction Scheme for Nonlinear Multivariable Discrete-Time Systems With Asymptotic Stability Guarantees
TL;DR: A novel, unified model-based fault-detection and prediction (FDP) scheme is developed for nonlinear multiple-input-multiple-output (MIMO) discrete-time systems and the asymptotic stability of the FDP scheme enhances the detection and TTF accuracy.
Journal ArticleDOI
Optimal statistical fault detection with nuisance parameters
Mitra Fouladirad,Igor Nikiforov +1 more
TL;DR: The goal of this paper is to propose an optimal statistical tool to detect a fault in a linear stochastic system with uncertainties (nuisance parameters or nuisance faults) that is supposed that the nuisance parameters are unknown but non-random.
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.