Rotor Fault Diagnostic of Inverter Fed Induction Motor Using Frequency Analysis

B. Asad, T. Vaimann, A. Belahcen, A. Kallaste, A. Rassõlkin
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引用次数: 7

Abstract

Condition monitoring of electrical machines is essential in industrial operations for improving workplace safety and ensuring reliable and economical exploitation of the machines. Motor current signature analysis (MCSA) monitoring technique is gaining heightened popularity due to the simplicity of its algorithms and the least number of sensors required. In this paper, the harmonic spectrum of industrial inverter fed induction motor is investigated for the detection of broken rotor bars. To improve the legibility of the spectrum, the fundamental component is attenuated using infinite impulse response (IIR) filter because of its good transition band, less passband ripples and low order. The results are first taken from finite element method (FEM) based simulation, where the motor is fed with pure sinusoidal current and only faulty and spatial frequencies are investigated and used as a benchmark. The practical results are based on the measurements taken from the laboratory setup, where the motor under investigation is fed through an industrial inverter working under scalar control mode. The data acquisition is done with a good sampling rate of 100 kHz for better resolution.
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基于频率分析的变频异步电动机转子故障诊断
在工业操作中,电机的状态监测对于提高工作场所的安全性和确保机器的可靠和经济利用是必不可少的。电机电流特征分析(MCSA)监测技术由于其算法简单和所需传感器数量最少而越来越受欢迎。本文研究了工业变频异步电动机的谐波谱,用于转子断条的检测。为了提高光谱的易读性,利用基波信号良好的过渡带、较少的通带波纹和低阶特征,利用无限脉冲响应滤波器对基波信号进行衰减。结果首先来自基于有限元法(FEM)的仿真,其中电机以纯正弦电流供电,仅研究故障频率和空间频率并将其作为基准。实际结果基于实验室设置的测量,其中所研究的电机通过在标量控制模式下工作的工业逆变器馈电。数据采集以100khz的采样率完成,以获得更好的分辨率。
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