Detector design for active fault diagnosis in closed‐loop systems

Summary Fault diagnosis of closed‐loop systems is extremely relevant for high‐precision equipment and safety critical systems. Fault diagnosis is usually divided into 2 schemes: active and passive fault diagnosis. Recent studies have highlighted some advantages of active fault diagnosis based on dua...

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Bibliographic Details
Published inInternational journal of adaptive control and signal processing Vol. 32; no. 5; pp. 647 - 664
Main Authors Sekunda, A. K., Niemann, H. H., Poulsen, N. K.
Format Journal Article
LanguageEnglish
Published Bognor Regis Wiley Subscription Services, Inc 01.05.2018
Subjects
active fault diagnosis
closed‐loop systems
Computer simulation
Fault detection
Fault diagnosis
Parameters
Safety critical
statistical test
White noise
YJBK parameters
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Summary:Summary Fault diagnosis of closed‐loop systems is extremely relevant for high‐precision equipment and safety critical systems. Fault diagnosis is usually divided into 2 schemes: active and passive fault diagnosis. Recent studies have highlighted some advantages of active fault diagnosis based on dual Youla‐Jabr‐Bongiorno‐Kucera parameters. In this paper, a method for closed‐loop active fault diagnosis based on statistical detectors is given using dual Youla‐Jabr‐Bongiorno‐Kucera parameters. The goal of this paper is 2‐fold. First, the authors introduce a method for measuring a residual signal subject to white noise. Second, an optimal detector design is presented for single and multiple faults using the amplitude and phase shift of the residual signal to conduct diagnosis. Here, both the optimal case of a perfect model and the suboptimal case of a model with uncertainties are discussed. The method is successfully tested on a simulated system with parametric faults.
ISSN:0890-6327
1099-1115
DOI:10.1002/acs.2858