Diagnosis of gear tooth fault in a bevel gearbox using discrete wavelet transform and autoregressive modeling

Snehsheel Sharma; S. K. Tiwari; Sukhjeet Singh

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Diagnosis of gear tooth fault in a bevel gearbox using discrete wavelet transform and autoregressive modeling

机译：斜齿轮箱齿故障的诊断使用离散小波变换自回归建模

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Vibration signals from any dynamic system are measured with respect to time. Different options are available to analyze these measured signals due to the advancement in computing and signal processing techniques. In the present work, a methodology comprising of discrete wavelet transform and autoregressive model has been proposed for detection of single tooth fault in single stage reduction bevel gearbox. An autoregressive model is constructed using detailed coefficients of discrete wavelet transform to highlight the presence of the fault in gearbox. The results show that variance of autoregressive coefficients obtained for faulty signal is more than the variance of autoregressive coefficients extracted from healthy signal. Based on the results, it is concluded that the proposed methodology can be used as health condition indicator of the gearbox system.

机译：振动信号的动态系统测量时间。可用来分析这些测量信号由于计算和进步的信号处理技术。离散小波的方法组成变换和自回归模型提出了单齿故障的检测单级减速斜齿轮箱。使用自回归模型详细的离散小波系数变换来突出的存在过错在齿轮箱。自回归系数获得错误的信号的方差自回归系数提取健康的信号。得出结论,该方法可以作为健康状况指示器的变速箱系统。

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来源
《Life Cycle Reliability and Safety Engineering》 |2019年第1期|21-32|共12页
作者
Snehsheel Sharma; S. K. Tiwari; Sukhjeet Singh;
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作者单位

National Institute of Technology;

Department of Mechanical Engineering, Guru Nanak Dev University Regional Campus Sathiala;

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原文格式 PDF
正文语种英语
中图分类安全科学;
关键词
discrete wavelet transform; autoregressive processes; Vibration analysisFault diagnosisGear teethwavelet transforms;

机译：离散小波变换,自回归流程;振动analysisFault diagnosisGearteethwavelet转换;

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Diagnosis of gear tooth fault in a bevel gearbox using discrete wavelet transform and autoregressive modeling

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