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首页> 外文期刊>日本機械学会論文集. C編 >Failure Diagnosis for Machinery in an Unsteady Operating Condition (1st Report, Failure Diagnosis Method for Rtating Machinery by Genetic Programming and Wavelet Analysis)
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Failure Diagnosis for Machinery in an Unsteady Operating Condition (1st Report, Failure Diagnosis Method for Rtating Machinery by Genetic Programming and Wavelet Analysis)

机译：不稳定工况下的机械故障诊断（第一篇报告，通过遗传编程和小波分析的旋转机械故障诊断方法）

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摘要

In the field of condition diagnosis of machinery, one of popular and practical methods is vibration analysis. Recently, dimensional and undimensional symptom parameters have been used for the condition diagnosis. However, these parameters can not be used to precisely detect failures of machinery in unsteady operating conditions, namely, in this case, the rotating speed and operating load of the machine are always changing. In order to overcome this difficulty, this paper proposes a new methods. by which the optimum symptom parameters can be automatically generated by Genetic Programming and the optimum frequency band can be decided to extract failure signal by Wavelet analysis for the precise diagnosis. The efficiency of the new methods is verified by applying them to the condition diagnosis of rolling bearing.
机译：在机械状态诊断领域，振动分析是一种流行且实用的方法。最近，已将维度和无维度症状参数用于状况诊断。但是，这些参数不能用于精确地检测不稳定工况下的机械故障，也就是说，在这种情况下，机械的转速和工作负荷始终在变化。为了克服这个困难，本文提出了一种新的方法。通过遗传编程可以自动生成最佳症状参数，并可以通过小波分析确定最佳频带以提取故障信号，从而进行精确诊断。通过将新方法应用于滚动轴承的状态诊断，验证了新方法的有效性。

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