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Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window

机译:使用优化的Slepian窗口的电流传感器对瞬态情况下的感应电机进行故障诊断

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摘要

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current’s spectrogram with a significant reduction of the required computational resources.
机译:本文的目的是介绍一种使用时频分析工具对瞬态工作的感应电机进行故障诊断的新方法。所提出的方法依靠优化的Slepian窗口的使用来执行定子电流信号的短时傅立叶变换(STFT)。结果表明,对于给定的有限持续时间序列长度,Slepian窗口具有最大的能量集中度,大于通常用作分析窗口的门控高斯窗口所能达到的最大能量集中度。本文从理论上介绍了Slepian窗口在感应电机故障诊断中的使用和优化,并通过在启动瞬态过程中对带有断条的3.15-MW感应电机的测试进行了实验验证。理论分析和实验结果表明,使用Slepian窗口可以突出显示当前频谱图中的故障分量,从而显着减少了所需的计算资源。

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