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  • 标题:Fault Diagnosis in Braking System of Mine Hoist Based on the Moment Characteristics
  • 本地全文:下载
  • 作者:Li Juanjuan ; Wang Aiming ; Meng Guoying
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2017
  • 卷号:7
  • 期号:12
  • 页码:01-11
  • DOI:10.5121/csit.2017.71201
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:Fault diagnosis method based on the moment characteristic of system pressure data is presentedin this paper. Using AMESim simulation technology, three typical faults of the brake system arestudied. After the moment and the percentile characteristics of the pressure curve of thehydraulic system are extracted and used as characteristic parameter, fault information isdiagnosed effectively using the BP neural network. The problem that the signal is notsynchronized and the characteristic parameters can not be obtained accurately are overcome. Itprovides some theoretical basis for the intelligent diagnosis and predictive maintenance of thehigh speed deep well hoist.
  • 关键词:Moment characteristics; Fault diagnosis; Braking system; Performance degradation; Deep;mine hoist
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