Based on the research of crank bearing wear fault mechanics, the fault feature extraction and fault diagnosis method are further studied.

在曲柄轴承磨损故障机理的研究基础上，论文对其故障特征信息提取及故障识别方法开展了进一步的研究。

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The combination of curvilinear component analysis (CCA) and self-organizing feature map (SOFM) were applied to a diagnosis for fault feature extraction of bearing.

提出曲元分析(CCA)和自组织特征映射(SOFM)相结合的方法用于轴承的故障诊断特征提取。

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During the gear fault detection and diagnosis, the fault feature extraction is the key of diagnosis, but it is multifarious for the method of fault feature extraction.

在齿轮故障监测与诊断中，故障特征提取是诊断的关键，而特征提取的方法也是多种多样的。

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