A New Method of Machine Fault Detection Based on Machine Learning on Line

Jiang Yi, Lei Lin
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Abstract

The article first analyzes many existing machine running fault diagnosis methods, which may not be good for on-line detection in view of the complexity of the algorithm. At the same time, studies the characteristics of random noise modulation. Then, designs a new on-line self-learning evolutionary fault detection method based on the FFT algorithm. The simulation shows that the method has good detection performance for a weak fault signal.
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基于在线机器学习的机器故障检测新方法
本文首先分析了现有的许多机器运行故障诊断方法,考虑到算法的复杂性,这些方法可能不利于在线检测。同时,研究了随机噪声调制的特性。然后,设计了一种基于FFT算法的在线自学习进化故障检测方法。仿真结果表明,该方法对微弱的故障信号具有良好的检测性能。
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