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  • 标题:A friction estimation approach to fault detection in electromechanical systems
  • 本地全文:下载
  • 作者:Fabio Angeloni ; Michele Ermidoro ; Fabio Previdi
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:21
  • 页码:720-725
  • DOI:10.1016/j.ifacol.2015.09.612
  • 语种:English
  • 出版社:Elsevier
  • 摘要:This paper presents a sensor fusion approach, using an Extended Kalman filter, in order to estimate the friction coefficient inside an electromechanical system. This method has the main advantage of merging the information arising from acceleration and motor current into a single variable. This new signal permits to improve the performance of a fault detection algorithm. An application showing the advantages of the proposed approach is shown; the electromechanical system chosen for the tests is an automatic access gate.
  • 关键词:Sensor data fusionfault detectionfriction estimationExtended Kalman filter
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