A Method Of Rolling Bearing Fault Diagnosis Based On Improved Energy Operator

The study on rolling bearing condition monitoring and fault diagnosis techniques is of crucial importance for assuring the operation safety of mechanical equipment.The vibration signals of rolling bearing are non-stationary and non-linear.Meanwhile,the weak fault features of the rolling bearing can easily be submerged by the noise,especially in the case of intensive background noise.How to extract features of the signal effectively under the strong background noise and apply it to the engineering field is the core part of the rolling bearing fault diagnosis area.And it is also the current hot research field.Using the improved energy operator as an analysis tool,this paper has studied and developed a new method of fault diagnosis of rolling bearing.The feasibility and validity of this method is verified by both simulation and experiments.The main contents and results of this paper are as follows:1.The structure and vibration characteristics of rolling bearing are introduced.The vibration mechanism and failure mode of rolling bearing are analyzed,and the model of rolling bearing fault signal is studied.2.Based on the conventional energy operator,a new energy operator,Envelope Derivative Energy Operator(EDEO),is proposed.The failure experiment of the rolling bearing shows that the EDEO energy spectrum not only can effectively extract the fault feature of the rolling bearing compared with the envelope spectrum and Teager energy spectrum,but also does not need to carry out EMD decomposition or band pass filtering,which demonstrates that the method is effective and convenient.3.A new demodulation method,Analytic Energy Operator(AEO),is proposed for the shortcomings of Hilbert transform and traditional energy operator demodulation method.The instantaneous frequency and instantaneous amplitude extracted by the Analytic Energy Operator method have better local characteristics and can avoid the oscillation.A fault diagnosis method of rolling bearing based on AEO energy spectrum is proposed.The method can accurately extract the fault characteristic frequency information of rolling bearing under strong noise interference.The simulation and experiments verify the effectiveness and superiority of the method.4.The rolling bearing fault diagnosis method based on AEO Energy Spectrum Sample Entropy and Support Vector Machine is proposed.The AEO Energy Spectrum Sample Entropy of the single component signal obtained by empirical mode decomposition is used as the eigenvector,which can well extract the fault feature information of the vibration information.Support Vector Machine is used to classify and identify the condition,which demonstrates the validity and accuracy of the method.