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A new method of accurate broken rotor bar diagnosis based on modulation signal bispectrum analysis of motor current signals

机译:基于电机电流信号调制信号双谱分析的转子断条准确诊断新方法

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摘要

Motor current signature analysis (MCSA) has been an effective way of monitoring electrical machines for many years. However, inadequate accuracy in diagnosing incipient broken rotor bars (BRB) has motivated many studies into improving this method. In this paper a modulation signal bispectrum (MSB) analysis is applied to motor currents from different broken bar cases and a new MSB based sideband estimator (MSB-SE) and sideband amplitude estimator are introduced for obtaining the amplitude at (1±2s)fs(1±2s)fs (s is the rotor slip and fsfs is the fundamental supply frequency) with high accuracy. As the MSB-SE has a good performance of noise suppression, the new estimator produces more accurate results in predicting the number of BRB, compared with conventional power spectrum analysis. Moreover, the paper has also developed an improved model for motor current signals under rotor fault conditions and an effective method to decouple the BRB current which interferes with that of speed oscillations associated with BRB. These provide theoretical supports for the new estimators and clarify the issues in using conventional bispectrum analysis.
机译:电机电流特征分析(MCSA)多年来一直是监视电机的有效方法。但是,诊断初期转子转子断线(BRB)的准确性不足,促使许多研究人员对该方法进行了改进。本文将调制信号双频谱(MSB)分析应用于来自不同断条情况的电动机电流,并引入了一种新的基于MSB的边带估计器(MSB-SE)和边带幅度估计器,以获取(1±2s)fs的幅度(1±2s)fs(s是转子打滑,fsfs是基本供电频率)具有高精度。由于MSB-SE具有良好的噪声抑制性能,因此与传统的功率谱分析相比,新的估算器在预测BRB数量方面产生了更准确的结果。此外,本文还针对转子故障条件下的电动机电流信号开发了一种改进的模型,并建立了一种有效的方法来使BRB电流解耦,该电流会干扰与BRB相关的速度振荡。这些为新的估计器提供了理论支持,并阐明了使用常规双谱分析时的问题。

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