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  • 标题:From structural analysis to observer-based residual generation for fault detection
  • 本地全文:下载
  • 作者:Sebastian Pröll ; Jan Lunze ; Fabian Jarmolowitz
  • 期刊名称:International Journal of Applied Mathematics and Computer Science
  • 电子版ISSN:2083-8492
  • 出版年度:2018
  • 卷号:28
  • 期号:2
  • 页码:1-13
  • DOI:10.2478/amcs-2018-0017
  • 出版社:De Gruyter Open
  • 摘要:This paper combines methods for the structural analysis of bipartite graphs with observer-based residual generation. The analysis of bipartite structure graphs leads to over-determined subsets of equations within a system model, which make it possible to compute residuals for fault detection. In observer-based diagnosis, by contrast, an observability analysis finds observable subsystems, for which residuals can be generated by state observers. This paper reveals a fundamental relationship between these two graph-theoretic approaches to diagnosability analysis and shows that for linear systems the structurally over-determined set of model equations equals the output connected part of the system. Moreover, a condition is proved which allows us to verify structural observability of a system by means of the corresponding bipartite graph. An important consequence of this result is a comprehensive approach to fault detection systems, which starts with finding the over-determined part of a given system by means of a bipartite structure graph and continues with designing an observerbased residual generator for the fault-detectable subsystem found in the first step.
  • 关键词:fault diagnosis; structural analysis; observer;based diagnosis; diagnosability analysis
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