基于EMD-LS-MFDFA法的离心泵异常振动识别

Identification of abnormal vibration of centrifugal pump based on EMD-LS-MFDFA

为探究离心泵地脚螺栓松动引起的非线性非平稳故障特征,利用经验模态分解(Empirical Mode Decomposition,EMD)提取信号趋势项,采用最小二乘(Least Squares,LS)对趋势项进行优化拟合的思路,对多重分形去趋势波动分析法(Multi-Fractal Detrended Fluctuation Analysis,MFDFA)进行优化,提出一种新的离心泵信号分析法。该分析法通过提取离心泵在正常和地脚螺栓松动状态下实测的泵壳振动信号、电机壳振动信号、扭矩信号,进行特征分析。实验结果表明,离心泵故障信号多重分形特征更为明显,提取的特征参数能够有效区分离心泵正常信号和地脚螺栓松动引起的各类故障信号。此外,通过分析特征参数的均值及均方差值,说明松动状态下会对离心泵造成较大的影响,对电机等部分产生相对较小的影响。

In order to explore the characteristics of nonlinear and non-stationary faults caused by the loosening of anchor bolts of centrifugal pumps,Empirical Mode Decomposition(EMD)is used to extract the signal trend term,and then the least squares(Least Squares,LS)is used to optimize the trend term.The idea of fitting is to optimize the multi-fractal de-trend fluctuation analysis(MFDFA),and propose a new centrifugal pump signal analysis method.Then we extract the pump casing vibration signal,the motor casing vibration signal,the torque signal,etc.,which are measured in the normal state and the anchor bolt loose state of the centrifugal pump for feature extraction and analysis.The experimental results show that the multi-fractal characteristics of the fault signal of the centrifugal pump are more obvious,and the extracted characteristic parameters can effectively distinguish the normal signal of the centrifugal pump from the various fault signals caused by the loosening of the anchor bolts.In addition,by analyzing the mean value and mean square deviation of the characteristic parameters,it is shown that the loose state will have a greater impact on the centrifugal pump,and will have a relatively small impact on the motor and other parts.