Research On Fault Diagnosis Of Rolling Bearing Based On CEEMDAN

The rolling bearing fault is one of the main factors leading to the fault of rotating machinery.In order to avoid the failure of large rotating machinery equipment can not be handled in a timely manner,resulting in major property casualties of the accident.It is necessary to extract useful fault information and deal with faults in time.Therefore,the fault feature extraction of rolling bearings is the key problem and the main content of this paper.The main research content of this paper is the extraction of rolling bearing fault features,and the fault diagnosis system of rolling bearings is developed by using LabVIEW.In the aspect of fault feature extraction,the internal structure and the vibration mechanism of rolling bearing are mastered.The application of empirical mode decomposition method in fault diagnosis of rolling bearing is studied.The advantages and disadvantages of EMD method,EEMD method,CEEMD method and CEEMDAN method decomposition results of the same rolling bearing fault signal are compared and analyzed with five optimization indicators.Then,based on the CEEMDAN method,the method of establishing the optimal noise reduction correlation model is proposed,and the fault feature of rolling bearing outer ring signal is extracted accurately by this method.Secondly,a rolling bearing fault diagnosis system is developed based on LabVIEW.The system includes login interface,home page,alarm interface and various data analysis interface,and a variety of fault analysis methods are adopted,such as envelope analysis,fast Fourier transform(FFT),trend analysis chart,waterfall graph and so on.The fault location can be judged and the fault deterioration degree can be monitored in real time.The rolling bearing is monitored online and diagnosed offline.Finally,in this system,the rolling bearing outer ring fault,inner ring fault and rolling body fault are respectively monitored online and analyzed offline.In this thesis,the research results show that the rolling bearing fault diagnosis method based on CEEMDAN algorithm to establish the optimal noise reduction correlation model is more effective in extracting fault feature information than the traditional analysis method,and the results are reasonable and effective after experimental verification.The rolling bearing fault diagnosis system developed based on LabVIEW has the advantages of friendly interface,easy construction and short development cycle,and realizes the on-line monitoring and off-line fault diagnosis of rolling bearings.The feasibility of the system is verified by experiments on real rolling bearings.