Envelope Spectral Kurtosis and SVD Analysis of Stray Flux Signals for the Diagnosis of Field Winding Faults in Synchronous Motors

M. E. I. Martínez, J. Antonino-Daviu, C. Platero, L. Dunai, J. Conejero, P. F. Córdoba
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Abstract

In this work, the application of an unsupervised algorithm based on Singular Values Decomposition (SVD) and on the Envelope Spectral Kurtosis of stray flux signals is proposed as a way to detect field winding faults in synchronous motors. These signals are analyzed both under starting and under steady-state regimes for two different types of flux sensors. Furthermore, a new fault indicator based on the SVD of the envelope of the spectral kurtosis is proposed, yielding satisfactory results for fault classification, observing a common trend in both cases at starting and in steady-state independent of the flux sensor type and position. A comparative analysis between the two motor operating regimes is carried out, obtaining several conclusions about the suitability of each regime for the application of the methodology in real applications.
杂散磁通信号的包络谱峭度和奇异值分解分析在同步电机绕组故障诊断中的应用
本文提出了一种基于奇异值分解(SVD)和杂散磁通信号包络谱峰度的无监督算法,用于同步电机励磁绕组故障检测。对两种不同类型的磁通传感器在起动和稳态状态下的信号进行了分析。在此基础上,提出了一种基于谱峰度包络的奇异值分解(SVD)的故障指示器,该故障指示器与磁通传感器的类型和位置无关,在启动和稳态状态下都具有共同的故障趋势,得到了令人满意的故障分类结果。进行了两种电机运行状态之间的比较分析,得出了关于每种状态在实际应用中应用该方法的适用性的几个结论。
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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