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Research On The Method Of Characterizing The Mechanical Properties Of Liver Soft Tissue Under Compression

Posted on:2022-06-12Degree:MasterType:Thesis
Country:ChinaCandidate:J F BiFull Text:PDF
GTID:2480306353474844Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
With the rise of virtual surgery systems,how to obtain an accurate soft tissue physical model has become a key technical problem that determines the training effect.Therefore,research on the mechanical properties of soft tissues can not only complement this technology,but also has a huge medical application prospect.In this paper,pig liver is used as the experimental object,and the research is carried out from two parts of mechanical experiment and physical modeling.Three-dimensional compression and stress relaxation experiments are carried out,focusing on the influence of liver lobule structure on the overall mechanical properties of the liver.Aiming at the inversion problem of soft tissue constitutive model parameters,there different parameter inversion methods are proposed for different use conditions.On the basis of linear motors and tension pressure sensors,a single-axis,dual-axis and three-axis compression measurement platform is designed.Based on VC,a motion control and data acquisition program for acquiring mechanical parameters is written.Aiming at the noise interference problem in the data acquisition process,a noise reduction method with improved threshold function is proposed based on wavelet theory.This method can compensate for the softness to a certain extent.,The defects of the hard threshold function.And the comparison of the data before and after the noise reduction of the sensor used in this paper verifies the effectiveness of the noise reduction method.Aiming at the selection problem of physical modeling,COMSOL software was used to compare the fitting effects of commonly used one-dimensional constitutive models,and the best model form was selected,and then geometric correction items and geometric correction items were added according to the real contact state of soft tissue in the mechanical experiment.The stress correction item is used to correct it,and it is verified that the corrected model effectively improves the parameter fitting results when the tissue is small in one-dimensional deformation;the Ogden and Neo-Hookean models are corrected respectively for the two-dimensional and three-dimensional experiments of the tissue Data Fitting.Uniaxial,biaxial and triaxial compression and stress relaxation experiments were carried out with pig liver as the experimental object.The former is used to study the mechanical properties of three directions,and the latter is used to obtain the mechanical model parameters of soft tissue.The experimental results point out that the internal structure of pig liver has varying degrees of influence on its external mechanical response in different dimensions,but they all show certain transverse isotropic characteristics.Solving the stable relaxation stress of soft tissue,using three different constitutive models in three dimensions to characterize the compressive mechanical properties of pig liver.To solve the non-linear solution problem in the physical modeling of soft tissue,the basic genetic algorithm is adaptively improved.This method has good optimization and convergence capabilities.It verifies the feasibility and uses it for the parameter inversion of the two-dimensional constitutive model of soft tissue;Based on COMSOL and numerical analysis software,a joint parameter inversion method program was written.This method takes into account the optimization ability and can build a more realistic simulation environment.It verifies the effectiveness of the method and uses it for the parameters of the soft tissue three-dimensional constitutive model In the inversion,the two methods have their own advantages and disadvantages,and they need to be selected according to specific requirements.
Keywords/Search Tags:Soft tissue, Mechanical experiment, Wavelet denoising, Physical modeling, Parameter inversion
PDF Full Text Request
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