Optimization of fault feature extraction method for bearings of reusable rocket turbopumps
Turbo pump bearings are the key to reusable rockets.Therefore,it is very important to extract the bearing fault characteristic frequency effectively to carry out fault diagnosis.Singular value decompo-sition(SVD)and envelope spectrum demodulation are combined to extract the fault features of rocket turbopump bearings.By processing and analyzing the fault data of the bearing's inner ring,outer ring and rolling element,the results show that compared with the traditional envelope spectrum demodulation method,the improved method has significantly improved the fault feature extraction effect for the data with a lot of noise in the signal.Compared with traditional envelope spectrum demodulation,the relative amplitudes of three kinds of fault low frequency characteristic frequencies extracted by this method are im-proved.At the same time,it can effectively reduce the interference of high frequency noise.Especially in the high frequency region,characteristic frequency can still be seen more obviously,while the high frequency region of the traditional envelope spectrum demodulation method is basically covered by noise.Through calculation,the signal-to-noise ratio of the signal is improved by more than 60 dB.
turbopumprolling bearingenvelope spectrumsingular value decompositionfault diagnosis
万方数据
维普
