Fault Diagnosis Of Bearing Based On LMD And Wavelet Denoising

The bearing is an important part of the mechanical equipment,and the normal operation of the bearing plays an important role in the safe and stable operation of the whole mechanical equipment.In the actual production process,due to the load of the bearing is large,the operation time is long,the working environment is bad and other reasons,the bearing is prone to failure.According to statistics,in the use of bearings in machinery and equipment,the probability of failure of the bearing is often greater than the probability of failure of other components.Therefore,as soon as possible to find the existence of the fault of the bearing,it can avoid the failure of the bearing caused by the increase caused by greater disaster,so as to cause loss of life and property.In the face of such a severe form,in making a diagnosis of bearing fault,can quickly and accurately detect the running state of the bearings is to ensure the safe operation of the bearing core,based on this,this paper will identify the bearing outer ring,inner ring and ball of the three kinds of common faults make research,according to the characteristics of fault signal of bearing components the in-depth study of its signal denoising process and fault recognition method.The main task of this paper is as follows:(1)the impulse characteristics of bearing fault signal are studied deeply.Based on the bearing structure and the deep study of the moving mechanism,analysis of the bearing fault when its forces and signal characteristics of the established feature of vibration signal model of outer ring and the inner ring and ball fault,and verified by real bearing fault signal acquisition.(2)according to the characteristics of pulse impact in bearing fault signal,the corresponding denoising method is constructed.In the practice of bearing fault signal acquisition,often contain a lot of noise,it is hard to obtain the characteristics of bearing fault signal component included in the face of the problem,through the analysis of the LMD method and the wavelet denoising method and the wavelet threshold number was improved,construct the denoising method of bearing fault signal with wavelet LMD based on the combination of denoising,and validate the denoising method.(3)bearing fault diagnosis method based on spectral kurtosis and envelope analysis.In order to accurately determine the frequency range of the impact features of fault signals in the spectrum,kurtosis of the de noised signal analysis and processing,and then through the analysis of the Hilbert envelope demodulation and spectrum analysis,so as to realize the fault diagnosis of bearing.Finally,this paper puts forward the bearing fault diagnosis of bearing fault diagnosis method is applied to mechanical fault simulation experiment,comparing the results of the diagnosis and diagnosis,using the traditional method of the bearing fault diagnosis results show that the method presented in this paper has obvious advantages in fault diagnosis of bearing.