Mechanical assembly has its own dynamic quality directly affecting the dynamic quality of whole product and should be considered in quality inspection and estimation of mechanical assembly. Based on functional relatio...Mechanical assembly has its own dynamic quality directly affecting the dynamic quality of whole product and should be considered in quality inspection and estimation of mechanical assembly. Based on functional relations between dynamic characteristics involved in mechanical assembly, the effects of assembling process on dynamic characteristics of substructural components of an assembly system are investigated by substructuring analysis. Assembly-coupling dynamic stiffness is clarified as the dominant factor of the effects and can be used as a quantitative measure of assembly dynamic quality. Two computational schemes using frequency response functions（FRFs） to determine the stiffness are provided and discussed by inverse substructuring analysis, including their applicable conditions and implementation procedure in application. Eigenvalue analysis on matrix-ratios of FRFs before and after assembling is employed and well validates the analytical outcomes and the schemes via both a lumped-parameter model and its analogic experimental counterpart. Applying the two schemes to inspect the dynamic quality provides the message of dynamic performance of the assembly system, and therefore improves conventional quality inspection and estimation of mechanical assembly in completeness.展开更多
Dynamic Quality of Service(QoS)prediction for services is currently a hot topic and a challenge for research in the fields of service recommendation and composition.Our paper addresses the problem with a Time-aWare se...Dynamic Quality of Service(QoS)prediction for services is currently a hot topic and a challenge for research in the fields of service recommendation and composition.Our paper addresses the problem with a Time-aWare service Quality Prediction method(named TWQP),a two-phase approach with one phase based on historical time slices and one on the current time slice.In the first phase,if the user had invoked the service in a previous time slice,the QoS value for the user calling the service on the next time slice is predicted on the basis of the historical QoS data;if the user had not invoked the service in a previous time slice,then the Covering Algorithm(CA)is applied to predict the missing values.In the second phase,we predict the missing values for the current time slice according to the results of the previous phase.A large number of experiments on a real-world dataset,WS-Dream,show that,when compared with the classical QoS prediction algorithms,our proposed method greatly improves the prediction accuracy.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.51475211)
文摘Mechanical assembly has its own dynamic quality directly affecting the dynamic quality of whole product and should be considered in quality inspection and estimation of mechanical assembly. Based on functional relations between dynamic characteristics involved in mechanical assembly, the effects of assembling process on dynamic characteristics of substructural components of an assembly system are investigated by substructuring analysis. Assembly-coupling dynamic stiffness is clarified as the dominant factor of the effects and can be used as a quantitative measure of assembly dynamic quality. Two computational schemes using frequency response functions（FRFs） to determine the stiffness are provided and discussed by inverse substructuring analysis, including their applicable conditions and implementation procedure in application. Eigenvalue analysis on matrix-ratios of FRFs before and after assembling is employed and well validates the analytical outcomes and the schemes via both a lumped-parameter model and its analogic experimental counterpart. Applying the two schemes to inspect the dynamic quality provides the message of dynamic performance of the assembly system, and therefore improves conventional quality inspection and estimation of mechanical assembly in completeness.
基金supported by the National Natural Science Foundation of China (No.61872002)the National Natural Science Foundation of Anhui Province of China (No.1808085MF197)the Philosophy and Social Science Planned Project of Anhui Province (No. AHSKY2015D67)
文摘Dynamic Quality of Service(QoS)prediction for services is currently a hot topic and a challenge for research in the fields of service recommendation and composition.Our paper addresses the problem with a Time-aWare service Quality Prediction method(named TWQP),a two-phase approach with one phase based on historical time slices and one on the current time slice.In the first phase,if the user had invoked the service in a previous time slice,the QoS value for the user calling the service on the next time slice is predicted on the basis of the historical QoS data;if the user had not invoked the service in a previous time slice,then the Covering Algorithm(CA)is applied to predict the missing values.In the second phase,we predict the missing values for the current time slice according to the results of the previous phase.A large number of experiments on a real-world dataset,WS-Dream,show that,when compared with the classical QoS prediction algorithms,our proposed method greatly improves the prediction accuracy.
