基于稀疏表示的IM半断转子棒检测

C. Morales-Perez, J. Rangel-Magdaleno, H. Peregrina-Barreto, J. Ramírez-Cortés
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引用次数: 4

摘要

目前,感应电动机因其易于安装和操作,在工业上得到了广泛的应用。感应电动机需要更可靠的监测,因为持续运行增加了故障的可能性,例如,转子断条故障。早期,断条不容易被发现,其演变缓慢而安静。大多数情况下,是在严重故障和其他故障已经出现的情况下检测到的。文献中提出了许多技术,但大多数技术在频域进行分析,应用额外的变换或预处理方法。本文提出了一种检测半断棒故障的新方法,该方法利用了感应电动机在健康和半断棒两种故障状态下的振动信号;还有三种装载情况:空载、半载和四分之三载。由于原始信号的稀疏表示,然后通过最小分解误差准则进行评估,因此可以进行检测。这样就不需要预处理方法,可以更早、更直接地发现故障。这些测试是在Matlab软件中开发的,感应电动机的振动信号处于稳态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Half-broken rotor bar detection on IM by using sparse representation under different load conditions
Currently, the Induction Motor is widely used in industry, due to its easy installation and operation. Induction motors require a more reliable monitoring due to constant operation increases the possibility of faults, for example, a broken rotor bar fault. Early stage, broken bar is not easy to detect, and its evolves is slow and quiet. In the most of cases, it is detected when the fault is critical and other faults have appeared. Many techniques have been proposed in the literature, but majority of these performs analysis in frequency domain, applying additional transformation or preprocessing methods. In this paper, a novel methodology to detect a half-broken bar fault is proposed, making use of the vibration signal from induction motor under two fault conditions: healthy and half-broken bar; and three load conditions: unloaded, half-loaded and three-fourths loaded. The detection is possible due to the sparse representation of the raw signal which is obtained and then evaluated by minimal decomposition error criterion. In this way, preprocessing methods are not needed, and the fault is detected early and directly. These tests were developed in Matlab software, with vibration signals from induction motors in steady state.
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