Motor current signature analysis and fuzzy logic applied to the diagnosis of short-circuit faults in induction motors
Motor current signature analysis and fuzzy logic applied to the diagnosis of short-circuit faults in induction motors
复制标题
电机电流特征分析和模糊逻辑应用于感应电机短路故障诊断
DOI：
10.1109/iecon.2005.1568916
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
L. A. Pereira
中科院分区：
文献类型：
--
作者：
L. A. Pereira;Daniel da Silva Gazzana;L. A. Pereira
本文介绍了感应电机定子绕组匝间短路检测和诊断系统的开发和实际实施。利用电机电流特征分析 (MCSA) 和模糊逻辑技术来实现这一目标。在简要描述 MCSA 后，讨论了短路的原因并用频率关系和频谱来表征。随后，提出了基于模糊逻辑的故障诊断技术。随后，对故障检测与诊断系统的实际实施结果进行了展示和评论。 MATLAB 6.0 和内置工具箱（DSP 模块集、模糊逻辑和实时工作坊）用作开发工具。实施和测试的方法显示出效率，因为实际结果与开发系统的预测相符。获得的结果具有很高的可靠性，这使得它们可以用作类似电机的监测工具。
The paper presents the development and the practical implementation of a system for detection and diagnosis of interturn short-circuits in the stator windings of induction motors. Motor current signature analysis (MCSA) and fuzzy logic techniques are utilized in order to achieve that. After a brief description of the MCSA, the causes of short circuits are discussed and characterized with frequency relationships and frequency spectra. Subsequently, failure diagnosis techniques based on fuzzy logic are presented. Afterwards, the results of the practical implementation of fault detection and diagnosis system are shown and commented. MATLAB 6.0 and built-in toolboxes (DSP blockset, fuzzy logic and real-time workshop) are used as a development tool. The implemented and tested method showed efficiency as the practical results corresponded to the predicted with the developed system. The results obtained present a great degree of reliability, which enables them to be used as a monitoring tool for similar motors.