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Updated: May 30, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

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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使用机器学习预测感应电机故障.

Ademola Abdulkareem1, Tochukwu Anyim1, Olawale Popoola2

  • 1Electrical and Information Engineering Department, Covenant University, P.M.B 1023, Ota, 112212, Ogun State, Nigeria.

Heliyon
|January 27, 2025
PubMed
概括

这项研究开发了机器学习模型来预测感应电机故障,减少工业无计划停机时间. 随机森林模型实现了91%的准确性,实现了主动维护和提高运营效率.

关键词:
人工神经网络分类器决策树分类器决定树分类器感应电机的感应电机是什么预测性维护是一种预测性维护.随机森林分类器 随机森林分类器k-NN 分类器

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Conducting a three-phase short circuit test on an unloaded synchronous machine helps understand its impact on the system. The AC fault current's oscillogram, with the DC offset removed, reveals that the waveform amplitude decreases from an initially high value to a steady-state level for one phase of the machine.
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