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Analytic-Wavelet-Ridge-Based Detection of Dynamic Eccentricity in Brushless Direct Current (BLDC) Motors Functioning Under Dynamic Operating Conditions

机译:在动态工作条件下运行的基于分析小波脊基的无刷直流(BLDC)电动机动态偏心率检测

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摘要

A new method using the analytic wavelet transform of the stator-current signal is proposed for detecting dynamic eccentricity in brushless direct current (BLDC) motors operating under rapidly varying speed and load conditions. As wavelets are inherently suited for nonstationary signal analysis, this method does not require the use of any windows, nor is it dependent on any assumption of local stationarity as in the case of the short-time Fourier transform. The proposed technique uses analytic wavelets, which are smooth wavelets that possess both magnitude and phase information. This makes them particularly suitable for motor-fault diagnostics. Experimental results are provided to show that the proposed method works over a wide speed range of motor operation and provides an effective and robust way of detecting rotor faults such as dynamic eccentricity in BLDC motors
机译:提出了一种使用定子电流信号的解析小波变换的新方法,用于检测在快速变化的速度和负载条件下运行的无刷直流(BLDC)电动机的动态偏心率。由于小波固有地适合于非平稳信号分析,因此该方法不需要使用任何窗口,也不像短时傅立叶变换的情况那样依赖于任何局部平稳性的假设。所提出的技术使用解析小波,解析小波是同时具有幅度和相位信息的平滑小波。这使得它们特别适合于电动机故障诊断。实验结果表明,该方法可在较宽的电动机运行速度范围内工作,并且为检测转子故障(如BLDC电动机的动态偏心率)提供了有效而可靠的方法

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