Variable-scale Modal Sparse Filtering for Gearbox Weak Fault Feature Diagnosis
编号:31 访问权限:公开 更新:2022-12-24 09:23:34 浏览:368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
The gear fault features are drowned by strong noise, which makes difficult to detect early faults. Additionally, gear fault features are often adjusted into several frequency bands, which weakens the effect of fault identification. Aiming these problems, this paper proposes a variable-scale filtering method, named as variable-scale modal sparse filtering, to enhance the early weak fault features. First, the collected vibration signals are adaptively decomposed into a series of component signals with limited bandwidth, where the timing modes can be conduct according to the learned center frequency and bandwidth of the component signals. Then, a series of learned modes are further processed by shift-invariant sparse representation to realize the modal filtering for the original signals. Finally, a series of filtered signal is obtained by the proposed variable scale mode filtering, and those periodic impacts would be more obvious in the time domain, and the characteristics are also significantly enhanced in the envelope spectrum. Simulation and experimental results show that the method is effective. And diagnosis results and comparison further expose the ability of the method in gearbox early weak fault feature enhancement.
关键词
Variable-scale filtering, shift-invariant sparse representation, variational mode decomposition, Gearbox, weak fault feature
报告人
Hao Xiang
College of Mechanical 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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