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基于小波包分析的气门间隙异常故障诊断 被引量:12

Valve clearance fault detection based on wavelet packet analysis
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摘要 以DA462型发动机为研究对象,人为地将气门间隙调整到不同状态来模拟发动机气门间隙异常故障,测取正常和异常情况下的缸盖振动信号,对其进行时域分析,并对振动信号中的燃烧激励响应信号和排气门落座冲击信号进行小波包分解,通过计算各个重构子频带振动能量均方根值(特征值)来判断各激励响应信号的频率带,经特征值比较确定气门间隙异常与否,取得满意的诊断结果。 Taking a DA462 engine as an object to be studied, its valve clearance was adjusted artificially to different values to simulate faults of abnormal engine valve clearance, and cylinder head vibration signals in normal and abnormal states were measured, respectively. In order to do analysis in time domain, the combustion excitation signals and the exhaust valve shut excitation signals were decomposed with wavelet packet. The frequency bands of the excitation signals were determined by calculating the root mean square ( RMS ) values of vibrational energy of reconstruction sub- frequency bands. In order to achieve satisfactory results, whether the valve clearance is normal or not was determined, by comparing the RMS values.
出处 《振动与冲击》 EI CSCD 北大核心 2011年第12期64-68,共5页 Journal of Vibration and Shock
基金 内蒙古自然基金资助项目(20080404MS0709) 内蒙古高校科研基金重点项目(NJZZ11070)
关键词 气门间隙 小波包 故障诊断 信号处理 valve clearance wavelet packet fault diagnosis signal processing
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