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基于小波包频带能量分解和欧氏贴近度的柴油机气阀机构故障诊断

Fault Diagnosis for Diesel Valve Drain Based on Euclidean Closeness Degree and Frequency Band Energy Decomposition Using Wavelet Packets

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【作者】 姚良成曙张振仁

【Author】 YAO Liang,CHENG Shu,ZHANG Zhen-ren(No.502 Sector,the Second Artillery Engineering College,Xi’an710025,China)

【机构】 第二炮兵工程学院第二炮兵工程学院 陕西西安710025陕西西安710025

【摘要】 通过调整柴油机气阀机构的不同气门间隙,采集柴油机缸盖表面的振动信号。利用小波包改进算法对所采集的信号进行频带分解,研究了不同气阀间隙情况下的缸盖振动频带能量分布规律。以频带能量为特征向量,以同一工况下多次采样均值作为标准模式,通过计算欧几里得贴近度实现了对柴油机气阀机构间隙异常的故障诊断。

【Abstract】 Based on the improved algorithm of wavelet packets,the signals are decomposed into the individual frequency bands and the wavelet packet energy distribution law in the case of different valve clearance is studied in this paper.Taking the frequency band energy as the feature vector and the mean data of enormous samples sampled in the same work condition as the standard mode,the fault diagnosis for the abnormal diesel valve clearance is realized by computing the Euclidean closeness degree between the feature vector and the standard mode.

  • 【文献出处】 机电工程技术 ,Mechanical & Electrical Engineering Technology , 编辑部邮箱 ,2006年01期
  • 【分类号】TK428
  • 【被引频次】9
  • 【下载频次】166
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