Fault Classification of Induction Motor Using Discrete Wavelet Transform and Fuzzy Inference System

Kuspijani Kuspijani, Richa Watiasih, Prihastono Prihastono
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引用次数: 2

Abstract

This paper develops a real-time condition-monitoring algorithm for induction motor. The condition monitoring mechanism is based on the discrete wavelet transform (DWT) and the fuzzy inference system (FIS). In this method, the stator currents are used as an input to the system. No direct access to the induction motor is required. The developed system has been rigorously assessed theoretically and experimentally, and it has been shown that the system is robust and reliable.
基于离散小波变换和模糊推理系统的异步电动机故障分类
本文提出了一种异步电动机实时状态监测算法。该状态监测机制基于离散小波变换和模糊推理系统。在这种方法中,定子电流被用作系统的输入。不需要直接进入感应电动机。所开发的系统经过了严格的理论和实验评估,证明了系统的鲁棒性和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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