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Two Stage Helical Gearbox Fault Detection and Diagnosis based on Continuous Wavelet Transformation of Time Synchronous Averaged Vibration Signals

机译:基于连续小波变换的时间同步平均振动信号的两级斜齿轮箱故障检测与诊断

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摘要

Vibration signals from a gearbox are usually very noisy which makes it difficult to find reliable symptoms of a fault in a multistage gearbox. This paper explores the use of time synchronous average (TSA) to suppress the noise and Continue Wavelet Transformation (CWT) to enhance the non-stationary nature of fault signal for more accurate fault diagnosis. The results obtained in diagnosis an incipient gear breakage show that fault diagnosis results can be improved by using an appropriate wavelet. Moreover, a new scheme based on the level of wavelet coefficient amplitudes of baseline data alone, without faulty data samples, is suggested to select an optimal wavelet.
机译:来自齿轮箱的振动信号通常非常嘈杂,这使得很难在多级齿轮箱中找到可靠的故障症状。本文探索了使用时间同步平均(TSA)来抑制噪声,并使用连续小波变换(CWT)来增强故障信号的非平稳性,从而更准确地进行故障诊断。诊断初期齿轮损坏得到的结果表明,通过使用适当的小波可以改善故障诊断结果。此外,提出了一种仅基于基线数据的小波系数幅度水平而没有错误数据样本的新方案来选择最佳小波。

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