基于高频电感变化的电气化铁路牵引电动机轴承故障预测方法

C. Attaianese, P. De Falco, A. D. Pizzo, L. D. di Noia
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引用次数: 1

摘要

本文对牵引电机轴承健康状况的预测技术进行了分析。文献中通常采用的方法使用振动和加速度信号,而本文提出的方法是基于传感器的,完全基于电磁方法。通过放置在轴承附近的高频电感线圈的值的变化来监测轴承状况。磨损、腐蚀和缺陷影响轴承金属部件的磁性行为,从而影响线圈电感的总价值。测量数据在回归模型中进行处理。实验结果表明了该预测技术的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bearing Failure Prognostic Method Based on High Frequency Inductance Variation in Electric Railway Traction Motors
This paper deals with the analysis of a prognostic technique able to analyze the health condition of traction motor bearings. While the methods commonly adopted in literature use vibration and acceleration signals, the proposed method is sensor-based and entirely based on an electromagnetic approach. The bearing conditions are monitored through the variation of the value of a high frequency inductance coil positioned near the bearing. The wear, the corrosion and the defects influence the magnetic behavior of metal parts of the bearing and therefore the total value of the coil inductance. The measurement data are processed in a regression model. The experimental results show the feasibility of the proposed prognostic technique.
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