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Vibration signal analysis using wavelet transform for isolation and identification of electrical faults in induction machine

机译:基于小波变换的振动信号分析用于感应电机电气故障的隔离与识别

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摘要

Condition monitoring is used for increasing machinery availability and machinery performance, reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient condition monitoring scheme is capable of providing warning and predicting the faults at early stages. The monitoring system obtains information about the machine in the form of primary data and through the use of modern signal processing techniques; it is possible to give vital information to equipment operator before it catastrophically fails. The suitability of a signal processing technique to be used depends upon the nature of the signal and the required accuracy of the obtained information. Therefore, in this paper, signals obtained from monitoring system have been processed using wavelet transform (WT) with suitably modified algorithms to extract detailed information for induction machine fault diagnosis. The results of this investigation depict that the application of WT for processing and analysis of the vibration signal to different frequency regions in time domain improves the extraction of the information that can enhance the ability of the system for diagnosis.
机译:状态监视用于增加机器的可用性和机器性能,减少间接损失,延长机器寿命,减少备件库存并减少故障维护。有效的状态监视方案能够在早期阶段提供警告并预测故障。监视系统以原始数据的形式并通过使用现代信号处理技术来获取有关机器的信息;可以在灾难性故障之前向设备操作员提供重要信息。所使用的信号处理技术的适用性取决于信号的性质和所获得信息的所需精度。因此,在本文中,使用小波变换(WT)以及经过适当修改的算法对从监控系统获得的信号进行了处理,以提取详细信息以进行感应电机故障诊断。这项研究的结果表明,WT在时域中对不同频率区域的振动信号进行处理和分析的应用,可以改善信息的提取,从而增强系统的诊断能力。

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