基于小波阈值去噪与二次经验模态分解的发动机点火波形分析方法

摘要

An engine waveform analysis method is proposed by combing wavelet threshold denoising with secondary empirical mode decomposition ( SEMD) . By analyzing the characteristics of eliminated noise, it is found that wavelet threshold denoising works better than SEMD denoising. SEMD-based time-frequency analysis can effec-tively analyze the abnormal components of ignition waveforms according to the features of intrinsic mode function ( IMF) . The method proposed takes full advantage of both wavelet threshold denoising and SEMD-based time-fre-quency analysis, and once the database of waveform is set up based on the method, the non-disassembling fault di-agnosis of engine can be realized.%提出了一种结合小波阈值去噪和二次经验模态分解( SEMD)时频分析的发动机点火波形时频分析方法,通过分析去除的噪声特征发现小波阈值去噪比SEMD去噪的效果更好,SEMD时频分析能有效地根据固有模态函数特征来分析点火波形的异常成分. 该方法充分利用小波阈值去噪和SEMD时频分析的优点,建立波形库后可实现发动机的不解体故障诊断.