Bearing Fault Diagnosis Method Based on Order Tracking Without Rotational Speed
The variable operating speed of mechanical equipment bearings leads to blurred spectrum of vibration monitoring signals,which to some extent affects the accuracy of bearing fault diagnosis.The current tacholess order tracking technology works well when the rotational speed fluctuation is small and the rotational frequency harmonics do not overlap,but it is difficult to conduct analysis when the bearing rotational frequency harmonics overlap.Aiming at the above problems,this paper proposes a tacholess order tracking fault diagnosis method of bearings based on the generalized demodulation.First,the generalized Fourier transform and the improved cost function-based ridge extraction technology are used to accurately extract the rotational frequency harmonic components of the bearings.At the same time,the fast spectral kurtosis algorithm and a band-pass filter are used to de-noise the bearing vibration signal.Then,the denoised time-domain signal is converted into an angular-domain signal through angle resampling.Finally,the order spectrum information of the bearing is obtained through the envelope spectrum analysis,so as to identify the fault type of the bearing.In addition,the effectiveness of the proposed method is verified using the numerical simulation signal and the actual bearing monitoring signal.The results show that the proposed method has an error of less than 5% in reconstructing the phase and an accuracy of more than 94% in characterizing the order frequency of bearing faults,which can be used for the order tracking fault diagnosis of rolling bearings without rotational speed information.
order trackingfault diagnosisgeneralized Fourier transformcost function
万方数据
维普
