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  • 标题:Modulating Function Based Fault Diagnosis Using the Parity Space Method
  • 本地全文:下载
  • 作者:Luis Enciso ; Matti Noack ; Johann Reger
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:7
  • 页码:268-273
  • DOI:10.1016/j.ifacol.2021.08.370
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractA model-based method for the detection and estimation of faults in dynamic systems is proposed. The method is based on the combination of the parity space approach and the modulating function framework for estimation. The parity space method is employed as an efficient geometric procedure determining null subspaces for annihilating unknown terms and formulating residuals. With the modulating functions technique the dynamic relation from output differentiation is reformulated as an algebraic expression. This substantially reduces the noise sensitivity of the output derivatives required. The design allows for the robust fault detection and isolation also for some nonlinear systems. The robustness of the approach is demonstrated on a nonlinear model of a four-tank process.
  • 关键词:KeywordsModulating Functions ApproachFault DetectionParity Space Method
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