Optimal measurement points evaluation for friction plate via a comprehensive analysis of correlation and clustering
编号:20 访问权限:公开 更新:2022-12-19 15:18:33 浏览:364次 张贴报告

报告开始:暂无开始时间(Asia/Shanghai)

报告时间:暂无持续时间

所在会场:[暂无会议] [暂无会议段]

摘要
As an important component of the transmission chain, it is of great significance to monitor the running status of the friction plate in real time. Aiming at the problems of  high cost of friction plate fault diagnosis, difficult fault signal acquisition, mutual coupling of vibration signals and the ambiguous selection and evaluation rules of the measuring points, an optimal measurement points evaluation for friction plate based on a comprehensive analysis of correlation and clustering is proposed. Firstly, wavelet packet decomposition (WPT) is processed on the vibration signals to construct a WPE flow image feature for an energy flow distribution, where the unusual characteristics would be described in a clear way. Secondly, considering the ability of correlation and clustering, a comprehensive index, named as the redundant and clustering index (RC-index), is calculated for each measuring point, then the measuring points are sorted according to RC-index. The final optimal measurement points sets are evaluated and built via the identification accuracy based on k-nearest neighbor (KNN) classifier. Experiments on the actual friction plate test bench are analyzed to indicate that the optimal measurement points set can maintain relatively high fault type identification accuracy with fewer measuring points.
关键词
Friction plate, Optimal measurement points, correlation, clustering, KNN
报告人
Huaping Tan
College of Mechanical and Vehicle Engineering Chongqing University

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重要日期
  • 会议日期

    11月30日

    2022

    12月02日

    2022

  • 11月30日 2022

    初稿截稿日期

  • 12月24日 2022

    报告提交截止日期

  • 04月13日 2023

    注册截止日期

主办单位
Harbin Insititute of Technology
China Instrument and Control Society
Heilongjiang Instrument and Control Society
Chinese Institute of Electronics
IEEE I&M Society Harbin Chapter
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