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滚动轴承故障诊断的关键问题之一是如何有效准确地提取故障特征信息,为了更好地刻画各频带能量,提出了改进小波包能量算法,提取分解频带的能量在时间域上的分布,更好地刻画了能量随时间变化的分布。同时引入包络分析,更好地体现信号的间断点,从而提高故障信号分析的准确度。诊断实例验证了利用改进小波包能量法进行故障诊断的有效性。
One of the key problems of rolling bearing fault diagnosis is how to extract the fault characteristic information effectively and accurately. In order to characterize the energy of each band better, an improved wavelet packet energy algorithm is proposed to extract the energy distribution of the decomposed band in the time domain, Characterize the distribution of energy over time. At the same time, the envelope analysis is introduced to better reflect the discontinuity of the signal, so as to improve the accuracy of fault signal analysis. The diagnostic examples verify the effectiveness of fault diagnosis using improved wavelet packet energy method.