基于改进自适应EEMD的柴油机气缸磨损诊断

Wear Diagnosis of Diesel Cylinder Liner via Improved Adaptive EEMD Method

为有效地从实测的柴油机机体表面振动信号中提取缸套磨损故障特征,提出了一种改进的自适应集合经验模态分解(EEMD)方法.针对目前集合经验模式分解方法中两个参数(加入白噪声的幅值系数、集合平均次数)依靠人工选择难以准确获取的问题,通过引入相关系数、相对均方根误差准则以及信噪比分析,给出一种可自适应确定这两个参数取值的方法,提高了信号的分解质量,通过仿真分析验证了改进自适应EEMD方法的良好性能.最后,将该方法应用于柴油机缸套磨损故障特征的提取,以各状态下的实测振动信号的瞬时能量谱和特征分量的能量作为故障特征,实现对缸套磨损诊断和磨损程度的识别.

To extract the cylinder liner wear characteristics from the surface vibration signals measured from the diesel engine, an improved adaptive ensemble empirical mode decomposition （EEMD）method is proposed. To solve the tough problem of the determination of the two critical parameters （the amplitude coefficient of the added white noise and the number of ensemble trials）, obtaining difficultly by artificial selection EEMD, the effective performance indices of correlation coefficient, relative root-mean-square error （RRMSE） and signal-to-noise ratio （SNR） are intro- duced to guide the selection of the proper noise amplitude and the number of ensemble trials. The analysis results indi- cate that the improved adaptive EEMD method represents a sound improvement over the original EEMD method, and has strong practicability. Finally, the vibration signals of diesel cylinder liner wear are analyzed and the results show that the proposed method is feasible and effective in feature extraction and condition evaluation of the cylinder liner wear fault.