Abstract
Shock pulse method is a widely used technique for condition monitoring of rolling bearing. However, it may cause erroneous diagnosis in the presence of strong background noise or other shock sources. Aiming at overcoming the shortcoming, a pulse adaptive time-frequency transform method is proposed to extract the fault features of the damaged rolling bearing. The method arranges the rolling bearing shock pulses extracted by shock pulse method in the order of time and takes the reciprocal of the time interval between the pulse at any moment and the other pulse as all instantaneous frequency components in the moment. And then it visually displays the changing rule of each instantaneous frequency after plane transformation of the instantaneous frequency components, realizes the time-frequency transform of shock pulse sequence through time-frequency domain amplitude relevancy processing, and highlights the fault feature frequencies by effective instantaneous frequency extraction, so as to extract the fault features of the damaged rolling bearing. The results of simulation and application show that the proposed method can suppress the noises well, highlight the fault feature frequencies, and avoid erroneous diagnosis, so it is an effective fault feature extraction method for the rolling bearing with high time-frequency resolution.
Highlights
As the most common part in the rotating machinery, rolling bearing is most vulnerable to damage
Considering that the shock modulation is an important feature when any fault arises in the rolling bearing, the fault feature frequency can be extracted by demodulating the vibration signals, so as to realize the fault diagnosis of the rolling bearing
The remainder of the paper is organized as follows: the working principle and diagnosis method of shock pulse method (SPM) are introduced in Section 2; on the basis of SPM, Section 3 proposes the PATFTM; through simulation and application analysis, PATFTM is validated in Section 4; and based on the analysis results, Section 5 draws the study conclusions and makes suggestions for further studies in this regard
Summary
As the most common part in the rotating machinery, rolling bearing is most vulnerable to damage. Following the phenomenon that the shock signal of wide range may arouse resonance, and the vibration signal rarely produces resonance [9], SPM and RDM both modulate the low frequency shock signal to high frequency one, perform such processes as filtering and envelope demodulation, and diagnose the working condition of the rolling bearing. Though the method does not have the problem of RDM whose filtering center frequency and bandwidth can be hardly selected, as it adopts the fixed filtering center frequency and bandwidth, performs the envelope detection which is characterized by nonlinear transformation, and bases the diagnosis on the amplitude information of the resonance demodulation wave alone, without any further analysis or processing, it cannot arrive at desired diagnosis results in the presence of the strong background noise or other shock sources. The remainder of the paper is organized as follows: the working principle and diagnosis method of SPM are introduced in Section 2; on the basis of SPM, Section 3 proposes the PATFTM; through simulation and application analysis, PATFTM is validated in Section 4; and based on the analysis results, Section 5 draws the study conclusions and makes suggestions for further studies in this regard
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