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Wavelet Transform in Vibroacoustic Diagnostics of Combustion Engines

机译:小波变换在内燃机振动声学诊断中的应用

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This article discusses the use of wavelet decomposition in the diagnostics of vibrometric signals of an engine. Apart from presenting the possibility of using wavelets in diagnostics, the authors take up the subject of the applicability range of processing for stationary signals, which until now has been reserved for non-stationary signals. A unified definition of signal stationarity has been proposed, which is not based on statistics. The authors presented methods of wavelet decomposition of a vibrometric signal of combustion engine vibrations, measured with the use of LDV (Laser Doppler Vibrometry). Laser measurements allow for studying an object without “touching” its housing. Basing on the relative velocity of engine vibrations, the authors indicate how reliable vibrations are in diagnostics. Despite higher costs, this measurement method gives better results (for specific cases) than acoustic studies. Transform-wavelet decomposition is a solution hardly ever used in machine diagnostics; it is more often applied in medicine and image recognition. The authors presented the differences that can be obtained for different levels of decomposition, and also presented the impact on the engine condition assessment through the use of filtering (windowing) the signal before decomposition.
机译:本文讨论了小波分解在发动机振动测量信号诊断中的应用。除了提出在诊断中使用小波的可能性外,作者还讨论了固定信号处理的适用范围,到目前为止,该范围一直被保留用于非固定信号。已经提出了信号平稳性的统一定义,该定义不基于统计数据。作者介绍了使用LDV(激光多普勒振动法)测量的内燃机振动振动信号的小波分解方法。激光测量允许研究对象而无需“触摸”其外壳。基于发动机振动的相对速度,作者指出了振动在诊断中的可靠性。尽管成本较高,但这种测量方法(针对特定情况)仍比声学研究提供更好的结果。变换小波分解是一种几乎没有用于机器诊断的解决方案。它更常用于医学和图像识别。作者介绍了不同分解级别可获得的差异,还介绍了通过使用分解前对信号进行滤波(加窗)对发动机状态评估的影响。

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