The elastic parameters of soft tissues are important for medical diagnosis and virtual surgery simulation. In this study, we propose a novel nonlinear parameter estimation method for soft tissues. Firstly, an in-house...The elastic parameters of soft tissues are important for medical diagnosis and virtual surgery simulation. In this study, we propose a novel nonlinear parameter estimation method for soft tissues. Firstly, an in-house data acquisition platform was used to obtain external forces and their corresponding deformation values, To provide highly precise data for estimating nonlinear param- eters, the measured forces were corrected using the constructed weighted combination forecasting model based on a support vector machine （WCFM_SVM）. Secondly, a tetrahedral finite element parameter estimation model was established to describe the physical characteristics of soft tissues, using the substitution parameters of Young＇s modulus and Poisson＇s ratio to avoid solving compli- cated nonlinear problems. To improve the robustness of our model and avoid poor local minima, the initial parameters solved by a linear finite element model were introduced into the parameter estimation model. Finally, a self-adapting Levenberg-Marquardt （LM） algorithm was presented, which is capable of adaptively adjusting iterative parameters to solve the established parameter estimation model. The maximum absolute error of our WCFM SVM model was less than 0.03 Newton, resulting in more accurate forces in comparison with other correction models tested. The maximum absolute error between the calculated and measured nodal displacements was less than 1.5 mm, demonstrating that our nonlinear parameters are precise.展开更多
The estimate model for a nonlinear system of squeeze film damper (SFD) is described.The method of state variable filter (SVF) is used to estimate the coefficients of SFD.The factors which are critical to the estimate...The estimate model for a nonlinear system of squeeze film damper (SFD) is described.The method of state variable filter (SVF) is used to estimate the coefficients of SFD.The factors which are critical to the estimate accuracy are discussed展开更多
In this paper, multimodel and neural emulators are proposed for uncoupled multivariable nonlinear plants with unknown dynamics. The contributions of this paper are to extend the emulators to multivariable non square s...In this paper, multimodel and neural emulators are proposed for uncoupled multivariable nonlinear plants with unknown dynamics. The contributions of this paper are to extend the emulators to multivariable non square systems and to propose a systematic method to compute the multimodel synthesis parameters. The effectiveness of the proposed emulators is shown through two simulation examples. The obtained results are very satisfactory, they illustrate the performance of both emulators and show the advantages of the multimodel emulator relatively to the neural one.展开更多
基金supported by the National Natural Science Foundation of China (Grant No.61373107)Wuhan Science and Technology Program, China (Grant No.2016010101010022)
文摘The elastic parameters of soft tissues are important for medical diagnosis and virtual surgery simulation. In this study, we propose a novel nonlinear parameter estimation method for soft tissues. Firstly, an in-house data acquisition platform was used to obtain external forces and their corresponding deformation values, To provide highly precise data for estimating nonlinear param- eters, the measured forces were corrected using the constructed weighted combination forecasting model based on a support vector machine （WCFM_SVM）. Secondly, a tetrahedral finite element parameter estimation model was established to describe the physical characteristics of soft tissues, using the substitution parameters of Young＇s modulus and Poisson＇s ratio to avoid solving compli- cated nonlinear problems. To improve the robustness of our model and avoid poor local minima, the initial parameters solved by a linear finite element model were introduced into the parameter estimation model. Finally, a self-adapting Levenberg-Marquardt （LM） algorithm was presented, which is capable of adaptively adjusting iterative parameters to solve the established parameter estimation model. The maximum absolute error of our WCFM SVM model was less than 0.03 Newton, resulting in more accurate forces in comparison with other correction models tested. The maximum absolute error between the calculated and measured nodal displacements was less than 1.5 mm, demonstrating that our nonlinear parameters are precise.
文摘The estimate model for a nonlinear system of squeeze film damper (SFD) is described.The method of state variable filter (SVF) is used to estimate the coefficients of SFD.The factors which are critical to the estimate accuracy are discussed
文摘In this paper, multimodel and neural emulators are proposed for uncoupled multivariable nonlinear plants with unknown dynamics. The contributions of this paper are to extend the emulators to multivariable non square systems and to propose a systematic method to compute the multimodel synthesis parameters. The effectiveness of the proposed emulators is shown through two simulation examples. The obtained results are very satisfactory, they illustrate the performance of both emulators and show the advantages of the multimodel emulator relatively to the neural one.
