人工蚂蚁在感应电机状态监测中的专用应用

A. Soualhi, H. Razik, G. Clerc
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引用次数: 1

摘要

在过去的十年中,诊断领域引起了许多研究者的关注,特别是感应电动机的故障检测。感应电动机的状态监测一般是基于对来自一个或多个传感器的信号的分析。这种分析是通过电机电流特征分析(MCSA)来完成的,这是目前最流行的故障检测技术。该方法认为故障部件在电机电流谱中产生一个频率,测量该频率的幅值可以帮助我们识别和量化故障的严重程度。因此,故障分量的频率幅值必须是已知的。本文建议使用一种启发式技术,这种技术受到蚁群行为的启发来跟踪这些频率。这种技术非常容易实现,并且可以快速收敛为解决方案。本文介绍了该方法,并对实验结果进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A dedicated Application of artificial ants for the condition monitoring of induction motors
In the last decade, the field of diagnosis has attracted the attention of many researchers, especially for the detection of faults in induction motors. The condition monitoring of induction motors is generally based on the analysis of signals coming from one or several sensors. This analysis is performed by the motor current signature analysis (MCSA) which is considered as the most popular fault detection technique. This approach considers that a failed component generates a frequency in the motor current spectrum and measuring the amplitude of this frequency can help us to identify and quantify the fault severity. So, the frequency amplitude of the faulty component has to be known. This paper suggests the use of a heuristic technique inspired by the behavior of a colony of ants to track these frequencies. This technique is very easy to implement and converge quickly to a solution. The proposed technique is described and the experimental results illustrate this novel technique.
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