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文章基本信息

  • 标题:Analysis of Progressively Unbalanced Induction Motor Current Signals Based on Information Entropy
  • 本地全文:下载
  • 作者:Andrijauskas ; Ignas ; Adaskevicius
  • 期刊名称:Studies About Languages
  • 印刷版ISSN:2029-7203
  • 出版年度:2018
  • 卷号:24
  • 期号:4
  • 页码:15-19
  • DOI:10.5755/j01.eie.24.4.21472
  • 语种:English
  • 出版社:Faculty of Humanities, Kaunas University of Technology
  • 其他摘要:The article presents the capabilities of a new fault identification method used for different fault levels. The method allows identifying unbalanced induction motor by only using stator current signals. The signal analysis was done by using wavelet packet decomposition and reconstruction (WPDR) and information entropy methods. The validation of proposed method was carried out by comparing unbalanced fault progressive simulation and experimentally obtained results. The experimental results were also analysed to identify the most band of frequencies (node) for the proposed method. Signals were divided into five overlapped time intervals in order to investigate which interval is the most informative for fault diagnosis. DOI: http://dx.doi.org/10.5755/j01.eie.24.4.21472
  • 关键词:Induction motors;Information entropy;Unbalance;Wavelet packets
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