Time domain averaging across all scales: A novel method for detection of gearbox faults
Time domain averaging across all scales: A novel method for detection of gearbox faults
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DOI：
10.1016/j.ymssp.2007.08.006
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发表时间：
2008-02-01
影响因子：
8.4
通讯作者：
Zuo, Ming J.
中科院分区：
文献类型：
--
作者：
Halim, Enayet B.;Choudhury, M. A. A. Shoukat;Zuo, Ming J.
齿轮箱的振动信号带有齿轮故障的特征。因此，通过使用不同的信号处理技术分析振动信号，可以对齿轮箱进行早期故障检测。时间同步平均可以提取噪声振动信号的周期波形，而小波变换能够表征信号在不同尺度上的局部特征。本文提出了一种新技术——全尺度时域平均，将时间同步平均和小波变换结合起来，从噪声振动信号中提取不同尺度的周期波形。该技术可以有效地消除噪声并同时检测局部和分布式故障。提出了一个中试工厂案例研究来证明所提出技术的有效性。 (c) 2007 年，爱思唯尔有限公司出版。
The vibration signal of a gearbox carries the signature of the fault in the gears. As such early fault detection of the gearbox is possible by analyzing the vibration signal using different signal processing techniques. Time synchronous averaging can extract the periodic waveforms of a noisy vibration signal, whereas Wavelet transformation is able to characterize the local features of the signal at different scales. This paper proposes a new technique, time domain averaging across all scales, which combines the time synchronous average and wavelet transformation together to extract the periodic waveforms at different scales from noisy vibration signals. The technique efficiently cleans up noise and detects both local and distributed faults simultaneously. A pilot plant case study is presented to demonstrate the efficacy of the proposed technique. (c) 2007 Published by Elsevier Ltd.