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Monitoring gear vibrations through motor current signature analysis and wavelet transform

机译:通过电机电流信号分析和小波变换监测齿轮振动

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In gearboxes, load fluctuations on the gearbox and gear defects are two major sources of vibration. Further, at times, measurement of vibration in the gearbox is not easy because of the inaccessibility in mounting the vibration transducers. An efficient and new but non-intrusive method to detect the fluctuation in gear load may be the motor current signature analysis (MCSA). In this paper, a multi-stage transmission gearbox (with and without defects) has been studied in order to replace the conventional vibration monitoring by MCSA. It has been observed through FFT analysis that low frequencies of the vibration signatures have sidebands across line frequency of the motor current whereas high frequencies of vibration signature are difficult to be detected. Hence, discrete wavelet transform (DWT) is suggested to decompose the current signal, and FFT analysis is carried out with the decomposed current signal to trace the sidebands of the high frequencies of vibration. The advantage of DWT technique to study the transients in MCSA has also been cited. The inability of CWT in detecting either defects or load fluctuation has been shown. The results indicate that MCSA along with DWT can be a good replacement for conventional vibration monitoring.
机译:在变速箱中,变速箱上的负载波动和齿轮缺陷是振动的两个主要来源。此外,有时由于难以安装振动传感器而难以测量齿轮箱中的振动。检测齿轮负载波动的有效且新颖但非侵入性的方法可能是电动机电流信号分析(MCSA)。本文研究了一种多级变速箱(有缺陷和无缺陷),以代替MCSA的常规振动监测。通过FFT分析已经观察到,振动信号的低频具有跨电动机电流的线频率的边带,而很难检测到振动信号的高频。因此,建议采用离散小波变换(DWT)分解电流信号,并对分解后的电流信号进行FFT分析,以追踪高频振动的边带。还提到了DWT技术在MCSA中研究瞬态的优势。已经显示出CWT无法检测缺陷或负载波动。结果表明,MCSA和DWT可以很好地替代传统的振动监测。

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