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Updated: Sep 16, 2025

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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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

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滚动轴承故障诊断通过时间图卷积融合

Fan Li1,2, Yunfeng Li1,2, Dongfeng Wang3

  • 1School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang 471003, China.

Sensors (Basel, Switzerland)
|July 12, 2025
PubMed
概括

一个新的时间图卷积融合网络 (T-GCFN) 改善了滚动轴承故障诊断. 这种方法通过融合时间和频率域特征来提高小样本条件的准确性.

关键词:
道注意力聚合层的注意力聚合层图表 卷积网络 卷积网络滚动轴承 的 滚动轴承 .时间卷积网络变化模式分解的变化模式分解

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