Fault Diagnosis Of Rolling Element Bearing Under Variable Speed Conditions Based On Order Tracking And Improved STFT

Rolling bearings play a critical part in the functioning of rotating machinery by supporting loads and facilitating transmission.However,complex working conditions such as variable speeds,heavy loads,overloads,and harsh environments(high temperatures,humidity,and dust)can decrease their reliability.Under variable speed conditions,signals become more complex compared to constant speed conditions.The research on fault diagnosis under variable speed rolling bearings is of great importance.This paper focuses on variable speed rolling bearings,analyzing their vibration signal characteristics under both constant and variable speed conditions.The study proposes three fault diagnosis methods of variable speed rolling bearings,which are validated using simulation and experimental signals.The research in this paper can be summarized as follows:(1)Aiming at the problem that the fault diagnosis methods of rolling bearing under constant speed conditions are no longer applicable to the variable speed conditions,the structure and fault vibration mechanism of rolling bearing are analyzed,and the fault vibration models under constant speed and variable speed conditions are established in this paper.Through simulation signals,the vibration signal characteristics in each domain are analyzed under both conditions,and the challenges of research under variable speed conditions are identified.It lays a theoretical foundation for the subsequent research on fault diagnosis methods of rolling bearing under variable speed conditions.(2)Aiming at the problem of "spectrum ambiguity" caused by speed fluctuation under variable speed conditions,the fault diagnosis method of variable speed rolling bearing based on PSO-VMD-MCKD and order tracking is proposed that combines Variational Modal Decomposition(VMD)for noise reduction and Maximum Correlated Kurtosis Deconvolution(MCKD)for highlighting continuous pulses hidden by noise.Particle Swarm Optimization(PSO)is used to solve the problem that the parameters of VMD and MCKD are difficult to determine.Through the analysis of simulation signals and experimental signals,it is verified that the proposed method can effectively solve the problems of "spectrum ambiguity" caused by speed fluctuation,difficulty in parameter selection and poor diagnosis effect caused by overlapping fault pulses.(3)Aiming at the problems such as envelope distortion easily caused by order tracking,a fault diagnosis method for variable speed rolling bearings based on PSO-VMD and Short-Time Fourier Transform(STFT)is proposed.The method utilizes time-frequency analysis advantages.By altering the window direction,the Linear Chirplet Transform(LCT)and General Linear Chirplet Transform(GLCT)are combined with PSO-VMD to acquire the instantaneous frequency of variable speed rolling bearing,respectively.Through the analysis and discussion of simulation and experiment,it is verified that the proposed method can diagnose the fault type of rolling bearing under the variable speed conditions to a certain extent.(4)Aiming at the problems of low energy concentration,strong background noise interference and longtime consumption in the existing STFT window function improvement method,the relationship between the down-modulation frequency and the energy concentration under the variable speed conditions is studied.A fault diagnosis method of rolling bearing under variable speed conditions based on PSO-VMD and Adaptive Window Rotation Optimization Short-Time Fourier Transform(AWROSTFT)is proposed in this paper.The simulation and experimental results show that the proposed method solves the problem that the window rotation degree is difficult to determine in STFT,LCT and GLCT methods,enhances the application scope of the algorithm,and can accurately diagnose the fault type of rolling bearing under variable speed conditions.