Signal de-noising algorithm of vehicle hub unit vibration based on mathematical morphology

MENG Qing-hua， HOU Zhou-bo， SUN Xiao-hong
（School of Mechanical Engineering， Hangzhou Dianzi University， Hangzhou 310018， China）

Abstract： Aiming at improving the efficiency of signal de-noising，the mathematical morphology was investigated and it was combined with 3σ rule. An algorithm of hub unit vibration signal de-noising based on morphological operations and soft threshold was put forward. Firstly，morphology filtering was used in hub unit vibration signal with noise and extract peak-valley signal. Secondly，for threshold processing，3σ rule was applied to the peak-valley signal，then the processed peak-valley signals were combined with the results of the operation of morphology filtering，as the results of the de-noising. Finally，features were extracted from the results through anglicizing the spectrum. This algorithm was verified by using the simulation data and real signal from the hub unit test. The experimental results indicate that the algorithm is not simple but it can reserve most of the useful signals while de-noising to the maximum extent，and the rate of fault signal recognition increases by 20%.
Key words： mathematical morphology； hub unit； de-noising algorithm； 3σ rule； feature extraction