Fault Signal Processing And Diagnosis Method For Rolling Bearing Of Vibrating Machinery(Vibrating Screen)

At the same time of China's rapid development of science and technology and economic construction,the relevant application fields of vibration machinery and equipment have become more extensive.Among them,the vibrating screen is the most common mechanical system,and in the vibrating screen mechanical system,the vibrating screen rolling bearing is particularly prominent,and its working condition not only affects the normal and stable operation of the equipment components,but also the subsequent overall equipment system.The safety has a direct impact,so monitoring signal analysis and fault diagnosis for the operation of many components of the vibrating screen is critical.In this paper,the related technologies for diagnosing the failure of vibrating screen rolling bearing are briefly described.The categories of vibration equipment are divided.The calculation formulas of vibration characteristics and frequency caused by pitting corrosion of inner and outer rings of rolling bearings are introduced and analyzed.The vibration signals in different states are analyzed and compared.Differences,analysis and comparison of the relevant methods for dealing with non-stationary signals and more common time-frequency analysis methods,and the commonly used empirical mode method(EMD),aggregate empirical mode decomposition method(EEMD)and complete integration empirical mode decomposition The method(CEEMDAN)processed signals were compared and analyzed,and their advantages and disadvantages were explored.However,the obtained vibration signal will inevitably leave residual white noise in the decomposed signal.Based on this,the variational mode decomposition(VMD)method in the fault signal processing of vibrating screen rolling bearing is proposed(the V-S algorithm based on VMD-SVD combined with the V-K algorithm based on VMD and K-L energy operator).Due to the special working principle of the vibration machine,it will cause particularly serious background noise during the working process,and many frequency components are doped in it.Therefore,when the vibration measurement method is used to diagnose the fault,higher robustness is proposed.Demand,through the comparison of experimental data,it can be found that the VS and VK methods in the vibration signal processing of the vibrating screen rolling bearing are more effective than the EMD and EEMD methods,solving the modal aliasing problem and improving the accuracy of fault diagnosis.The fault diagnosis of the equipment is based on the real-time monitoring of multiple normal and abnormally mixed aliasing information.The information analysis is the key to fault diagnosis.In this paper,the vibrating screen rolling bearing is taken as the analysis object,and the inherent modal parameters(IMF)obtained by EEMD decomposition of the measured vibration signal are taken as the fault characteristic parameters,and these characteristic parameters are added to the fault feature layer of the Bayesian network.The information source is added to the information layer of the Bayesian network.A fault diagnosis method for vibrating screen rolling bearing based on EEMD and multi-source information fusion of three-layer Bayesian network is proposed and applied to the fault diagnosis experiment of vibrating screen rolling bearing.The experimental results show that the method can accurately diagnose faults.At the end of the thesis,the shortcomings of the EEMD-TKEO-BSS fusion based on the EEMD-TKEO-BSS fusion algorithm are proposed based on the advantages of the polymerized empirical mode decomposition method(EEMD)and the Teager energy operator(TKEO).The Optimized Operator Algorithm(EDO)is applied to the fault signal processing of vibrating screen rolling bearings.Comparing the results of spectrum analysis of vibration machinery and rotating mechanical bearing faults,it is found that this method is more powerful than the simple Hilbert transform(HT)and Teager energy operator methods,and has high diagnostic efficiency.Experimental tests were carried out to verify the superiority of the proposed method.