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Updated: Jan 13, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Published on: October 28, 2022

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基于声学特征的电机轴承传动系统故障诊断

Long Ma1, Yan Zhang1, Zhongqiu Wang2

  • 1China Coal Technology & Engineering Group (CCTEG) Shenyang Research Institute, Shenyang 113122, China.

Sensors (Basel, Switzerland)
|January 10, 2026
PubMed
概括

本研究介绍了一种非接触式声学方法,用于使用CNN-注意力-LSTM模型进行轴承故障诊断. 该方法达到99.90%的准确性,为传统的振动分析提供了有效的替代方案.

关键词:
这是LSTM的LSTM.梅尔的频率是塞普斯特拉尔系数.声学特征 声学特征 声学特征注意力机制注意力机制深度学习是一种深度学习.错误诊断 错误诊断 错误诊断 是一个问题.

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