感应电动机气隙混合偏心严重程度检测

B.L. Rajalakshmi Samaga, K. Vittal
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引用次数: 7

摘要

异步电动机的非侵入式故障检测装置已成为工业传动的重要组成部分。由于电流是受非均匀气隙磁通影响的主要量,在异步电动机混合偏心故障检测中,电机电流特征分析优于振动分析。本文对异步电动机建模仿真得到的定子电流数据样本进行功率谱密度分析。定义了偏心严重系数,并表明该系数随机内气隙偏心的增大而增大。因此,它可以作为评估机器偏心程度的一种措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Air gap mixed eccentricity severity detection in an induction motor
Non invasive fault detection unit for an induction motor has become an integral part of industrial drives. As the current is the primary quantity to get affected by the non uniform air gap flux, Motor Current Signature Analysis is preferred as compared to vibration analysis for mixed eccentricity fault detection in an induction motor. In this paper, Power Spectral Density analysis is performed on the stator current data samples obtained from modeling and simulation of the induction motor. An Eccentricity Severity Factor is defined and is shown that this factor increases with increase of air gap eccentricity in the machine. Hence it can be used as a measure to assess the degree of eccentricity in the machine.
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