Aiming at the non-stationary feattwes of the roller bearing fault vibration signal, a roller bearing fault diagnosis methtxt based on improved Local Mean Decomposition （LMD） and Support Vector Machine （SVM） is pro...Aiming at the non-stationary feattwes of the roller bearing fault vibration signal, a roller bearing fault diagnosis methtxt based on improved Local Mean Decomposition （LMD） and Support Vector Machine （SVM） is proposed. In this paper, firstly, the wavelet analysis is introduced to the signal decomposition and reconstruction; secondly, the LMD method is used to decompose the recomtnion signal obtained by the wavelet analysis into a ntmaber of Product Ftmctions （PFs） that include main fault characteristics, thus, the initial feattwe vector matrixes could be formed automatically; Thirdly, by applying the Singular Valueition （SVD） techniques to the initial feature vector matrixes, the singular values of the matrixes can be obtained, which can be used as the fault feature vectors of the roller bearing and serve as the input vectors of the SVM classifier; Finally, the recognition results can be obtained from the SVM output. The results of analysis show that the propsed method can be applied to roller beating fault diagnosis effectively.展开更多
Time-varying stiffness is one of the most important dynamic characteristics of rolling element bearings.The method of analyzing the elements in the bearing stiffness matrix is usually adopted to investigate the charac...Time-varying stiffness is one of the most important dynamic characteristics of rolling element bearings.The method of analyzing the elements in the bearing stiffness matrix is usually adopted to investigate the characteristics of bearing stiffness.Linear mapping structure of the bearing stiffness matrix is helpful to understand the varying compliance excitation and its influence on vibration transmission.In this study,a method to analyze the mapping structure of bearing stiffness matrix is proposed based on the singular value decomposition of block matrices in the stiffness matrix.Not only does this method have the advantages of coordinate transformation independence and unit independence,but also the analysis procedure involved is geometrically intuitive.The time-varying stiffness matrix of double-row tapered bearing is calculated and analyzed using the proposed method under two representative load cases.The principal stiffnesses and principal axes defined in the method together indicate the dominant and insignificant stiffness properties with the corresponding directions,and the vibration transmission properties are also revealed.Besides,the coupling behaviors between different shaft motions are found during the analysis of mapping structure.The mechanism of the generation of varying compliance excitation is also revealed.展开更多
基金supported by Chinese National Science Foundation Grant(No.50775068)China Postdoctoral Science Foundation funded project(No.20080430154)High-Tech Research and Development Program of China(No.2009AA04Z414)
文摘Aiming at the non-stationary feattwes of the roller bearing fault vibration signal, a roller bearing fault diagnosis methtxt based on improved Local Mean Decomposition （LMD） and Support Vector Machine （SVM） is proposed. In this paper, firstly, the wavelet analysis is introduced to the signal decomposition and reconstruction; secondly, the LMD method is used to decompose the recomtnion signal obtained by the wavelet analysis into a ntmaber of Product Ftmctions （PFs） that include main fault characteristics, thus, the initial feattwe vector matrixes could be formed automatically; Thirdly, by applying the Singular Valueition （SVD） techniques to the initial feature vector matrixes, the singular values of the matrixes can be obtained, which can be used as the fault feature vectors of the roller bearing and serve as the input vectors of the SVM classifier; Finally, the recognition results can be obtained from the SVM output. The results of analysis show that the propsed method can be applied to roller beating fault diagnosis effectively.
基金the Joint Funds of the National Natural Science Foundation of China(Grant No.U1834202).
文摘Time-varying stiffness is one of the most important dynamic characteristics of rolling element bearings.The method of analyzing the elements in the bearing stiffness matrix is usually adopted to investigate the characteristics of bearing stiffness.Linear mapping structure of the bearing stiffness matrix is helpful to understand the varying compliance excitation and its influence on vibration transmission.In this study,a method to analyze the mapping structure of bearing stiffness matrix is proposed based on the singular value decomposition of block matrices in the stiffness matrix.Not only does this method have the advantages of coordinate transformation independence and unit independence,but also the analysis procedure involved is geometrically intuitive.The time-varying stiffness matrix of double-row tapered bearing is calculated and analyzed using the proposed method under two representative load cases.The principal stiffnesses and principal axes defined in the method together indicate the dominant and insignificant stiffness properties with the corresponding directions,and the vibration transmission properties are also revealed.Besides,the coupling behaviors between different shaft motions are found during the analysis of mapping structure.The mechanism of the generation of varying compliance excitation is also revealed.
