Painlevé's paradox is one of the basic difficulties for solving LCP of dynamic systems subjected to unilateral constraints.A bi-nonlinear parameterized impact model,consistent with dy- namic principles and ex...Painlevé's paradox is one of the basic difficulties for solving LCP of dynamic systems subjected to unilateral constraints.A bi-nonlinear parameterized impact model,consistent with dy- namic principles and experimental results,is established on the localized and quasi-static impact model theory.Numerical simulations are carried out on the dynamic motion of Painlevé's example.The re- sults confirm'impact without collision'in the inconsistent states of the system.A'critical normal force'which brings an important effect on the future movement of the system in the indeterminate states is found.After the motion pattern for the impact process is obtained from numerical results, a rule of the velocity's jump that incorporates the tangential impact process is deduced by using an approximate impulse theory and the coefficient of restitution defined by Stronge.The results of the jump rule are quite precise if the system rigidity is big enough.展开更多
Sound source recognition is a part of environmental sound recognition,which is one of the most important research areas in pattern recognition.Impact sounds carry much physical information associated with the sound so...Sound source recognition is a part of environmental sound recognition,which is one of the most important research areas in pattern recognition.Impact sounds carry much physical information associated with the sound sources,which makes impact sound based sound source recognition an important approach to improve recognition performance.In this study,the impact sound continuum synthesized with a ball-plate collision model is used for material recognition of the impacted plates.The basis function learning method and time-frequency representation methods,including the short time Fourier transform and the wavelet packet transform,are applied into classification and the recognition results are compared.The result shows that the features obtained by using the basis function learning perform better for material classification of the impacted plates than that by using the short time Fourier transform and the wavelet packet transform.This demonstrates the high efficiency and superiority of this method in material recognition of sound sources.展开更多
基金The project supported by the National Natural Science Foundation of China(10272002)Doctoral Foundation of Educational Ministry of China(20020001032)the foundation(02413200203235)
文摘Painlevé's paradox is one of the basic difficulties for solving LCP of dynamic systems subjected to unilateral constraints.A bi-nonlinear parameterized impact model,consistent with dy- namic principles and experimental results,is established on the localized and quasi-static impact model theory.Numerical simulations are carried out on the dynamic motion of Painlevé's example.The re- sults confirm'impact without collision'in the inconsistent states of the system.A'critical normal force'which brings an important effect on the future movement of the system in the indeterminate states is found.After the motion pattern for the impact process is obtained from numerical results, a rule of the velocity's jump that incorporates the tangential impact process is deduced by using an approximate impulse theory and the coefficient of restitution defined by Stronge.The results of the jump rule are quite precise if the system rigidity is big enough.
基金supported by the National Natural Science Foundation of China(11074202,11574249)
文摘Sound source recognition is a part of environmental sound recognition,which is one of the most important research areas in pattern recognition.Impact sounds carry much physical information associated with the sound sources,which makes impact sound based sound source recognition an important approach to improve recognition performance.In this study,the impact sound continuum synthesized with a ball-plate collision model is used for material recognition of the impacted plates.The basis function learning method and time-frequency representation methods,including the short time Fourier transform and the wavelet packet transform,are applied into classification and the recognition results are compared.The result shows that the features obtained by using the basis function learning perform better for material classification of the impacted plates than that by using the short time Fourier transform and the wavelet packet transform.This demonstrates the high efficiency and superiority of this method in material recognition of sound sources.
