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Journal ArticleDOI

Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results

Paul M. Frank
- 01 May 1990 - 
- Vol. 26, Iss: 3, pp 459-474
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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.
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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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Citations
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Journal ArticleDOI

Fault detection for discrete-time linear systems based on descriptor observer approach

TL;DR: This paper investigates the problem of actuator fault detection filter design for discrete-time linear systems with output disturbance by using the descriptor observer method and utilizing Lyapunov function approach to guarantee the residual system is admissible and satisfies the H∞ performance.
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H∞ Detection Filter Design for State Delayed Linear Systems

TL;DR: In this paper, the authors studied the problem of H ∞ detection filter design for state delayed linear continuous-time systems, in which the effects of faults and unknown inputs, including model uncertainties and external plant disturbances, cannot be decoupled from each other.
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Probabilistic Monitoring of Sensors in State-Space With Variational Bayesian Inference

TL;DR: It is shown that the proposed algorithm provides not only a complete picture of the working status of each sensor, but also satisfied estimates of the hidden states in the presence of faulty signals.
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Component reliability in fault-diagnosis decision making based on dynamic Bayesian networks

TL;DR: In this paper, a new approach of decision making for the signature vectors for various identical or similar faults is presented, which consists in the fusion between the reliability and the evaluation of the residuals in order to increase the fault isolation efficiency.
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Experimental interval models for the robust Fault Detection of Aircraft Air Data Sensors

TL;DR: Data-based approaches for a robust Fault Detection of the Air Data Sensors including airspeed angles of attack and sideslip are proposed and the proposed FD scheme has shown to be remarkably robust in all phases of the flight in terms of low false alarm rates while maintaining desirable detectability to faults.
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.
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Process fault detection based on modeling and estimation methods-A survey

Rolf Isermann
- 01 Jul 1984 - 
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.
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Analytical redundancy and the design of robust failure detection systems

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.