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Diagnosis of Broken-Bar Fault in Induction Machines Using Discrete Wavelet Transform Without Slip Estimation

机译:无离散滑差估计的离散小波变换在异步电机断条故障诊断中的应用

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摘要

The aim of this paper is to present a wavelet-based method for broken-bar detection in squirrel-cage induction machines. The frequency-domain methods, which are commonly used, need speed information or accurate slip estimation for frequency-component localization in any spectrum. Nevertheless, the fault frequency bandwidth can be well defined for any squirrel-cage induction machine due to numerous previous investigations. The proposed approach consists in the energy evaluation of a known bandwidth with time-scale analysis using the discrete wavelet transform. This new technique has been applied to the stator-current space-vector magnitude and the instantaneous magnitude of the stator-current signal for different broken-bar fault severities and load levels.
机译:本文的目的是提出一种基于小波的鼠笼感应电机断条检测方法。常用的频域方法需要速度信息或准确的滑移估计,才能在任何频谱中定位频率分量。然而,由于先前的大量研究,故障频率带宽对于任何鼠笼式感应电机都可以很好地定义。所提出的方法包括使用离散小波变换的时标分析对已知带宽进行能量评估。对于不同的断条故障严重程度和负载水平,该新技术已应用于定子电流空间矢量幅度和定子电流信号的瞬时幅度。

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