The structure of a high-speed maglev guideway is taken as the research object.With the aim of identifying the inconsistency of modal parameters between the simulation model and the actual model,and based on the 600 km...The structure of a high-speed maglev guideway is taken as the research object.With the aim of identifying the inconsistency of modal parameters between the simulation model and the actual model,and based on the 600 km/h high-speed maglev vehicle and the high-speed maglev test line,the arrangement of sensors and the vibration acceleration data collection of the 12.384 m concrete guideway were conducted.The modal parameters were identified from the guideway response signal using wavelet transform,after which the wavelet ridge was extracted by using the maximum slope method.Next,the vibration modes and frequency parameters of the interaction vibration characteristics of the high-speed maglev guideway and 600 km/h maglev vehicle were analyzed.The updating objective function for the finite element model of the guideway was established,and the initial guideway finite element model was modified and updated by repeatedly iterating the parameters.In doing so,the model structure of the high-speed maglev guideway was obtained,which is consistent with the actual structure.The accuracy of the updated guideway model in the calculation of the dynamic response was verified by combining this with the vehicle-guideway coupling dynamic model of the high-speed maglev system with 18 degrees of freedom.The research results reveal that the model update method based on the wavelet transform and the maximum slope method has the characteristics of high accuracy and fast recognition speed.This can effectively obtain an accurate guideway model that ensures the correctness of the vehicle-guideway coupling dynamic analysis and calculation while meeting the parameters of the measured structure model.This method is also suitable for updating other structural models of high-speed maglev systems.展开更多
In this study, we propose and compare stochastic variants of the extra-gradient alternating direction method, named the stochastic extra-gradient alternating direction method with Lagrangian function（SEGL） and the s...In this study, we propose and compare stochastic variants of the extra-gradient alternating direction method, named the stochastic extra-gradient alternating direction method with Lagrangian function（SEGL） and the stochastic extra-gradient alternating direction method with augmented Lagrangian function（SEGAL）, to minimize the graph-guided optimization problems, which are composited with two convex objective functions in large scale.A number of important applications in machine learning follow the graph-guided optimization formulation, such as linear regression, logistic regression, Lasso, structured extensions of Lasso, and structured regularized logistic regression. We conduct experiments on fused logistic regression and graph-guided regularized regression. Experimental results on several genres of datasets demonstrate that the proposed algorithm outperforms other competing algorithms, and SEGAL has better performance than SEGL in practical use.展开更多
基金The National 13th Five-Year Science and Technology Support Program of China(No.2016YFB1200602).
文摘The structure of a high-speed maglev guideway is taken as the research object.With the aim of identifying the inconsistency of modal parameters between the simulation model and the actual model,and based on the 600 km/h high-speed maglev vehicle and the high-speed maglev test line,the arrangement of sensors and the vibration acceleration data collection of the 12.384 m concrete guideway were conducted.The modal parameters were identified from the guideway response signal using wavelet transform,after which the wavelet ridge was extracted by using the maximum slope method.Next,the vibration modes and frequency parameters of the interaction vibration characteristics of the high-speed maglev guideway and 600 km/h maglev vehicle were analyzed.The updating objective function for the finite element model of the guideway was established,and the initial guideway finite element model was modified and updated by repeatedly iterating the parameters.In doing so,the model structure of the high-speed maglev guideway was obtained,which is consistent with the actual structure.The accuracy of the updated guideway model in the calculation of the dynamic response was verified by combining this with the vehicle-guideway coupling dynamic model of the high-speed maglev system with 18 degrees of freedom.The research results reveal that the model update method based on the wavelet transform and the maximum slope method has the characteristics of high accuracy and fast recognition speed.This can effectively obtain an accurate guideway model that ensures the correctness of the vehicle-guideway coupling dynamic analysis and calculation while meeting the parameters of the measured structure model.This method is also suitable for updating other structural models of high-speed maglev systems.
基金supported by the National Natural Science Foundation of China(No.61303264)the National Key Research and Development Program of China(No.2016YFB1000401)
文摘In this study, we propose and compare stochastic variants of the extra-gradient alternating direction method, named the stochastic extra-gradient alternating direction method with Lagrangian function（SEGL） and the stochastic extra-gradient alternating direction method with augmented Lagrangian function（SEGAL）, to minimize the graph-guided optimization problems, which are composited with two convex objective functions in large scale.A number of important applications in machine learning follow the graph-guided optimization formulation, such as linear regression, logistic regression, Lasso, structured extensions of Lasso, and structured regularized logistic regression. We conduct experiments on fused logistic regression and graph-guided regularized regression. Experimental results on several genres of datasets demonstrate that the proposed algorithm outperforms other competing algorithms, and SEGAL has better performance than SEGL in practical use.
