Telemetry Vibration Signal Analysis and Fault Detection based on Multi-scale Permutation Entropy

Hongzhou Xu, Xue Liu, Suting Qiu
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Abstract

Aiming at the characteristics of strong noise and non-stationarity of telemetry vibration signals, a multi-scale entropy-based telemetry vibration signal analysis and fault detection method was proposed. Firstly, the collected signals were modified with zero-drift and tendency eliminating. Secondly, the mutual information and Cao’s algorithm were used to select the delay time and embedding dimension, we could have more excellent performance to distinguish the abnormities of telemetry vibration signal through this step. Finally, the partial mean of multi-scale permutation entropy of all signals was calculated, which were used to distinguish the abnormities of telemetry vibration signal. The measured data demonstrated the effectiveness of this method.
基于多尺度排列熵的遥测振动信号分析与故障检测
针对遥测振动信号具有强噪声和非平稳性的特点,提出了一种基于多尺度熵的遥测振动信号分析与故障检测方法。首先对采集到的信号进行零漂移和趋势消除处理;其次,利用互信息和Cao算法选择延迟时间和嵌入维数,通过这一步可以更好地识别遥测振动信号的异常。最后,计算各信号的多尺度排列熵的偏均值,用于遥测振动信号的异常识别。实测数据证明了该方法的有效性。
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