柴油机传动机构振动信号具有强耦合、强冲击及强干扰特征,准确的信号特征提取是振动源识别及抑制的关键.针对变分模态提取(variational mode extraction,VME)方法在处理柴油机振动信号存在自适应性及准确性不足的问题,本研究以振动信号的峰值频率为中心频率的初始值,考虑分解信号与原始信号的相关性,以分解分量的峰峰值、均方根值及峰值因子为判定指标,提出一种参数自适应变分模态提取(parameter adaptive variational mode extraction,PAVME)算法,并通过构建强干扰环境下柴油机振动特征的模拟信号验证了该方法的准确性和鲁棒性.基于PAVME和功率谱密度函数(power spectral density function,PSD)识别出齿轮箱异常振动源为齿轮啮合激励.综合激励源和传递路径两个维度考虑,最后提出了通过轴系扭振控制进行传动机构振动抑制的方案.
Abnormal vibration diagnosis of diesel engine transmission mechanism based on PAVME
Vibration signals of diesel engine transmission mechanism have strong coupling,strong impact and strong interference features.Correct signal feature extraction is the key to identifying and suppressing vibration sources.Here,aiming at problems of insufficient adaptability and correctness of variational mode extraction(VME)method in processing diesel engine vibration signals,taking peak frequency of a vibration signal as the initial value of center frequency,considering the correlation between the decomposed signal and the original signal,and taking peak-peak value,RMS value and peak factor of the decomposed components as judgment indexes,a parameter adaptive variational mode extraction(PAVME)algorithm was proposed.The correctness and robustness of this method were verified by constructing simulated signals with diesel engine vibration features under strong interference environment.Based on PAVME and power spectral density(PSD)function,the abnormal vibration source of a gearbox was identified as gear meshing excitation.Comprehensively considering two dimensions of excitation source and transmission path,a scheme for suppressing transmission mechanism vibration with shafting torsional vibration control was finally proposed.