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  • 标题:Incipient Fault Detection Based on Robust Threshold Generators: A Sliding Mode Interval Estimation Approach
  • 本地全文:下载
  • 作者:Kangkang Zhang ; Bin Jiang ; Xing-Gang Yan
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2017
  • 卷号:50
  • 期号:1
  • 页码:5067-5072
  • DOI:10.1016/j.ifacol.2017.08.953
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper presents an incipient fault detection framework for systems with process disturbances and sensor disturbances based on a novel proposed threshold generator. Firstly, the definition of incipient faults is given using the H-from the quantitative point of view. Then, from the generated residuals and RMS evaluation function, the threshold generator is proposed based on sliding mode interval estimation module to ensure that the RMS evaluation of residuals is less than the generated threshold. By using recent results of the bounded real lemma for internally positive systems, a set of sufficient conditions to detect incipient faults via linear matrix inequality (LMI) is presented. Case study on an electrical traction device is presented to verify the effectiveness of the proposed method.
  • 关键词:KeywordsIncipient fault detectionthreshold generatorsliding modeinterval estimator
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