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Brush wear detection by continuous wavelet transform

机译：通过连续小波变换检测电刷磨损

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摘要

This paper is concerned with the singularity detection of a motor current signal. These singularities are related to the brushes condition, which are one of the sensible parts of the motor to wear out. As the mechanical contact between brushes and commutation segments increases, the rising parts of the current commutation waves become wider and this is a signal of brush wear. We successfully implement an algorithm to localise the singular points of the commutation waves based on the wavelet maxima lines. The width of the rising part of the commutation waves is then calculated from these maxima lines.
机译：本文涉及电机电流信号的奇异性检测。这些奇异性与电刷状况有关，电刷状况是电动机磨损的敏感部分之一。随着电刷和换向片之间的机械接触增加，电流换向波的上升部分变得更宽，这是电刷磨损的信号。我们成功地实现了一种基于小波极大值线的换向波奇异点定位算法。然后根据这些最大值线计算出换向波上升部分的宽度。

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