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  • 标题:Kalman predictor subspace residual for mechanical system damage detection
  • 本地全文:下载
  • 作者:Michael Döhler ; Qinghua Zhang ; Laurent Mevel
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:6
  • 页码:37-42
  • DOI:10.1016/j.ifacol.2022.07.102
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractFor mechanical system structural health monitoring, a new residual generation method is proposed in this paper, inspired by a recent result on subspace system identification. It improves statistical properties of the existing subspace residual, which has been naturally derived from the standard subspace system identification method. Replacing the monitored system state-space model by the Kalman filter one-step ahead predictor is the key element of the improvement in statistical properties, as originally proposed by Verhaegen and Hansson in the design of a new subspace system identification method.
  • 关键词:KeywordsStructural health monitoringdamage detectionfault diagnosisresidual designsubspace system identificationvibration analysis
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