Finite element analysis method and system for fully edentulous removable dentures

Abstract

The present application relates to the field of digital data processing technology, and specifically to a finite element analysis method and system for full-mouth edentulous removable dentures, the method comprising: obtaining a CT image of the patient's oral cavity, constructing a three-dimensional finite element model by finite element analysis, and meshing the three-dimensional finite element model, obtaining the unit size and maximum deviation coefficient of each grid, and the pressure trend vector of each grid during each dynamic occlusion process; determining the shape complexity weight of each grid; determining the pressure difference, force sensitivity, force discreteness, and structural disorder eigenvalue of each grid; obtaining each defective grid; calculating the number of extended neighborhood layers of each defective grid; refining the grid, and optimizing the denture according to the simulation results of the occlusion simulation of the three-dimensional finite element model. The present application can accurately capture local stress changes, improve the accuracy of finite element analysis of denture force analysis, and reduce the pain of patients when biting.

Description

Technical Field

[0001] The present application relates to the technical field of digital data processing, and in particular to a finite element analysis method and system for fully edentulous removable dentures. Background Art

[0002] As an important oral rehabilitation method, with the maturity of implant technology, removable dentures have become the first choice for edentulous patients due to their good retention and stability. Edentulous removable dentures can restore patients' chewing function, pronunciation and facial appearance. Finite element analysis simulates the biomechanical environment in the oral cavity and predicts the stress distribution and behavior of dentures in actual use. Finite element analysis is crucial for optimizing denture design, reducing the risk of complications, and improving the long-term stability and functional performance of dentures. Through finite element analysis, the stress response of dentures of different designs and materials under normal bone and osteoporosis conditions can be compared, thereby achieving personalized and precise denture restoration.

[0003] Finite element analysis transforms continuous structural problems into discrete mathematical problems. By dividing the structure into grids, complex geometric shapes and continuous material properties can be approximated as a finite number of small units. The shape of edentulous removable dentures contains complex geometric features. These features may cause surface connection misalignment during mesh generation, affecting the quality of the mesh. In the critical areas of edentulous removable dentures, finer grids are required to capture detailed changes. The stress changes away from stress concentration areas are not significant, so coarser grids can be used to simplify the analysis process. Therefore, the existing technology for mesh division cannot flexibly adapt to the needs of different areas, and cannot balance the calculation accuracy and resource consumption during mesh generation, resulting in inaccurate force analysis of the denture and causing problems such as bite pain in patients. Summary of the invention

[0004] In order to solve the above technical problems, a finite element analysis method and system for full-mouth edentulous removable dentures are provided to solve the existing problems.

[0005] The solution to the technical problem of the present application is to provide a finite element analysis method and system for a fully edentulous removable denture, comprising the following steps:

[0006] In a first aspect, an embodiment of the present application provides a finite element analysis method for a fully edentulous removable denture, the method comprising the following steps:

[0007] Obtain CT images of the patient's oral cavity, construct a three-dimensional finite element model by finite element analysis, and divide the three-dimensional finite element model into grids to obtain the unit size and maximum deviation coefficient of each grid, as well as the pressure trend vector of each grid during each dynamic occlusion process;

[0008] Based on the offset of the cell size of each grid and in combination with the maximum deviation coefficient, determine the shape complexity weight of each grid;

[0009] Based on the pressure trend vector of each grid in all dynamic occlusion processes, a pressure change matrix of each grid is constructed, and the local change difference between the maximum elements in different rows in the pressure change matrix is ​​analyzed to determine the pressure difference of each grid; combined with the complex conditions of all elements in each row, the force sensitivity of each grid is determined;

[0010] Determine the force discreteness of each grid according to the distribution discreteness of the number of consecutive occurrences of the same element in each row in the pressure change matrix; determine the structural disorder eigenvalue of each grid in combination with the shape complexity weight and the force sensitivity; obtain each defective grid based on the structural disorder eigenvalue;

[0011] The number of extended neighborhood layers of each defective mesh is calculated by the structural disorder characteristic value of each defective mesh; the mesh is refined based on the extended neighborhood layer number, and the denture is optimized based on the refined mesh and the simulation results of the occlusal simulation using a three-dimensional finite element model.

[0012] Preferably, determining the shape complexity weight of each grid includes:

[0013] Calculate the mean value of the element size of all meshes in the three-dimensional finite element model, recorded as the average size;

[0014] The ratio of the cell size of each grid to the average size is used as the size similarity of each grid;

[0015] The difference between the size similarity and the value 1 is calculated and recorded as the size deviation; the normalized result of the product of the size deviation and the maximum deviation coefficient is used as the shape complexity weight of each grid.

[0016] Preferably, determining the pressure difference of each grid includes:

[0017] Select the maximum value of all elements in each row of the pressure change matrix, and obtain two minimum values ​​adjacent to the maximum value; and form a local pressure vector with all elements between the two minimum values;

[0018] The maximum value of the difference between the local pressure vectors of any two rows in the pressure variation matrix is ​​used as the pressure difference degree of each grid.

[0019] Preferably, determining the force sensitivity of each grid includes:

[0020] Calculating the fractal dimension of all elements in each row of the pressure variation matrix of each grid;

[0021] Calculating the discrete degree of all the fractal dimensions in the pressure variation matrix of each grid;

[0022] The product of the discrete degree and the pressure difference is used as the force sensitivity of each grid.

[0023] Preferably, the determining of the force discreteness of each grid comprises:

[0024] Dividing the pressure trend vector corresponding to each column in the pressure change matrix of each grid into a plurality of occlusion stages;

[0025] The same elements that appear continuously in each row in each occlusion stage in the pressure change matrix of each grid are recorded as a run, and the number of all elements in each run is obtained and recorded as the run length;

[0026] Calculating the information entropy of all run lengths in each bite stage in the pressure change matrix of each grid;

[0027] The mean value of the information entropy of all occlusion stages in the pressure change matrix of each grid is used as the force discreteness of each grid.

[0028] Preferably, the structural disorder characteristic value of each grid is a normalized result of the product of the shape complexity weight, the force sensitivity and the force discreteness.

[0029] Preferably, the obtaining of each defective mesh includes: recording a mesh whose structural disorder characteristic value is greater than a preset threshold as a defective mesh.

[0030] Preferably, the method for calculating the number of extended neighborhood layers of each defective grid is: ,in, For the The number of extended neighborhood layers of defective grids, is the preset adjustment factor, For the The structural disorder eigenvalues ​​of the defective grid, is the ceiling function, is the preset threshold.

[0031] Preferably, the mesh refinement process includes:

[0032] All grids directly connected to each defective grid are recorded as first-layer neighborhood grids, and all grids directly connected to the first-layer neighborhood grids of each defective grid are recorded as second-layer neighborhood grids, and the process is repeated recursively to obtain each layer of neighborhood grids of each defective grid;

[0033] An adaptive mesh refinement algorithm is used to refine each defective mesh and all layer neighborhood meshes within the extended neighborhood layer number to obtain a refined mesh.

[0034] In a second aspect, an embodiment of the present application further provides a finite element analysis system for a fully edentulous removable denture, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above-mentioned finite element analysis methods for a fully edentulous removable denture when executing the computer program.

[0035] This application has at least the following beneficial effects:

[0036] The present application determines the shape complexity weight of each grid based on the offset of the cell size of each grid in combination with the maximum deviation coefficient, which has the beneficial effect of taking into account the deformation of each grid to reflect the shape complexity of each grid; constructs a pressure change matrix for each grid based on the pressure trend vector of each grid in all dynamic bite processes, analyzes the local change differences between the maximum elements in different rows in the pressure change matrix, and determines the pressure difference of each grid; determines the force sensitivity of each grid in combination with the complexity of all elements in each row, which has the beneficial effect of reflecting the force changes at the corresponding position of the same grid and the changes in the stress concentration area, so as to illustrate the degree of change of the force of each grid when the bite conditions are gradually increased; determines the force discreteness of each grid according to the discrete distribution of the number of consecutive appearances of the same element in each row in the pressure change matrix, which has the beneficial effect of taking into account the randomness of the force of each grid in all dynamic bite simulations at different bite stages during the dynamic bite process, so as to reflect the force of the grid in different dynamic bite simulations. force consistency; combining the shape complexity weight and the force sensitivity, determining the structural disorder eigenvalue of each grid, which has the beneficial effect of taking into account the deformation of the grid shape and the concentration of the force characteristics to reflect the possibility that the corresponding grid is a stress concentration area, so as to subsequently screen the defective grids; based on the structural disorder eigenvalue, obtaining each defective grid; calculating the number of extended neighborhood layers of each defective grid through the structural disorder eigenvalue of each defective grid, which has the beneficial effect of taking into account the strength of the stress concentration of each defective grid, so as to refine the grids in a larger area around it; based on the extended neighborhood layer number, refining the grid, based on the refined grid, according to the simulation results of the occlusal simulation of the three-dimensional finite element model, optimizing the denture, which has the beneficial effect of refining the grid in the stress concentration area so as to be able to capture the local stress changes more accurately, improve the accuracy of the finite element analysis of the denture force analysis, reduce the risk of the denture causing excessive pressure on the alveolar bone and soft tissue, and reduce the pain of the patient when biting. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The finite element analysis method for a fully edentulous removable denture of the present application is further described in detail below in conjunction with the accompanying drawings.

[0038] Figure 1 A flowchart of the steps of a finite element analysis method for a fully edentulous removable denture provided in an embodiment of the present application;

[0039] Figure 2 A flowchart of the steps of a method for obtaining the force sensitivity of each grid provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the finite element analysis method and system for a fully edentulous removable denture proposed in the present application are further described in detail below in conjunction with the accompanying drawings and implementation examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0041] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0042] See also Figure 1 , which shows a flowchart of the steps of a finite element analysis method for a fully edentulous removable denture provided by an embodiment of the present application, the method comprising the following steps:

[0043] Step 1: Obtain a CT image of the patient's oral cavity, construct a three-dimensional finite element model through the finite element analysis method, and mesh the three-dimensional finite element model to obtain the unit size and maximum deviation coefficient of each mesh, as well as the pressure trend vector of each mesh during each dynamic occlusion process.

[0044] The patient's maxillofacial region was scanned by cone beam CT (CBCT) to obtain CT images of the patient's maxillofacial region. Based on the upper and lower dentition, alveolar bone morphology, jaw relationship, soft tissue condition and occlusal relationship in the maxillofacial CT images, a three-dimensional solid model was established by CAD software. The established three-dimensional solid model was analyzed by finite element method to construct a three-dimensional finite element model of the full-mouth edentulous removable denture.

[0045] Preferably, in this embodiment, ABAQUS finite element analysis software is used to construct a three-dimensional finite element model, wherein the method of constructing the three-dimensional finite element model is a well-known technology and will not be repeated here. As other implementation methods, the implementer can use other software of the prior art to perform finite element analysis, such as SolidWorks finite element software, etc. This embodiment does not impose any special restrictions on this.

[0046] The constructed three-dimensional finite element model is meshed using the Advancing Front algorithm;

[0047] Preferably, in this embodiment, the geometric shape of the divided grid is a quadrilateral. As other implementations, the implementer may divide the grid into triangles, hexagons, etc., and this embodiment does not impose any special limitation on this.

[0048] It should be noted that the Advancing Front algorithm is a well-known technology and will not be described in detail here.

[0049] The cell size and maximum deviation coefficient of each grid are calculated by ABAQUS software;

[0050] It should be noted that the calculation of the unit size and the maximum deviation coefficient is a well-known technique and will not be described in detail here.

[0051] ABAQUS software is used to apply a gradually increasing bite force, and the three-dimensional finite element model is subjected to N dynamic bite simulations, and the pressure data of each grid that changes continuously with time from the beginning to the end of each dynamic bite are obtained, and the pressure trend vector of each grid in each dynamic bite process is formed, and the obtained pressure data are normalized;

[0052] Preferably, in this embodiment, the three-dimensional finite element model is subjected to 10 dynamic occlusion simulations. As other implementation modes, the implementer can set it according to the actual situation; secondly, the process of dynamic occlusion simulation using ABAQUS software is a well-known technology and will not be repeated here; secondly, the maximum and minimum normalization method is used for normalization processing. As other implementation modes, the implementer can adopt other methods of the prior art, such as Z-score normalization method, etc. This embodiment does not impose any special restrictions on this.

[0053] At this point, the pressure trend vector of each grid in each dynamic occlusion process, as well as the cell size and maximum deviation coefficient of each grid are obtained.

[0054] Step 2: Based on the offset of the cell size of each grid and the maximum deviation coefficient, determine the shape complexity weight of each grid; based on the pressure trend vector of each grid in all dynamic bite processes, construct a pressure change matrix for each grid, analyze the local change differences between the maximum elements in different rows of the pressure change matrix, and determine the pressure difference of each grid; combined with the complexity of all elements in each row, determine the force sensitivity of each grid.

[0055] The geometry of fully edentulous removable dentures is very complex, containing many irregular grooves and holes, which results in low quality of the generated mesh, unsatisfactory shape of the mesh elements, excessive stretching or distortion, and affects the accuracy of finite element analysis. The Advancing Front algorithm can effectively align with the seed points when meshing, but when dealing with narrow or complex areas, in order to accurately adapt to each seed point, the mesh will be deformed, thereby reducing the overall shape quality of the mesh. That is, the shape quality of the mesh is directly related to the shape complexity of the area where the mesh is located.

[0056] Secondly, the maximum deviation coefficient reflects the deformation of the grid. The maximum deviation coefficient usually involves factors such as the angle and side length ratio of the grid unit. The smaller the maximum deviation coefficient, the closer the grid unit is to the ideal shape and the better the grid quality. The grid unit with a large maximum deviation coefficient may have an irregular shape and be over-stretched or distorted. Therefore, in order to improve the accuracy of finite element analysis, it is necessary to refine the divided grid to more accurately capture the local stress and stress changes.

[0057] Based on the above analysis, since mesh division may cause deformation of some meshes, the shape complexity weight is determined in combination with the unit size and the maximum deviation coefficient to reflect the irregularity of each mesh, specifically:

[0058] Calculate the mean value of the element size of all meshes in the three-dimensional finite element model, recorded as the average size;

[0059] The ratio of the cell size of each grid to the average size is used as the size similarity of each grid;

[0060] It should be noted that the size similarity reflects the relative size of each grid unit and the overall grid size. The closer the size similarity is to 1, the closer the unit size of the corresponding grid is to the average size of the overall grid. Conversely, it means that there is a large deviation between the unit size of the corresponding grid and the average size of the overall grid.

[0061] The difference between the size similarity and the value 1 is calculated and recorded as the size deviation; the normalized result of the product of the size deviation and the maximum deviation coefficient is used as the shape complexity weight of each grid;

[0062] Preferably, in this embodiment, the absolute value of the difference between the dimensional similarity and the value 1 is calculated and recorded as the dimensional deviation.

[0063] Preferably, in this embodiment, the calculation method of the shape complexity weight of each grid is: ,in, For the The shape of the grid is complex weighted, For the The cell size of the grid, is the average size, For the The maximum deviation coefficient of the grid, is a normalization function. In this embodiment, a sigmoid function is used for normalization. The sigmoid function is a well-known technology and will not be described in detail here. As other implementation methods, the implementer may use other methods of the prior art, such as the tanh function, etc. This embodiment does not impose any special restrictions on this. Secondly, For similarity in size, is the size deviation.

[0064] It should be noted that the larger the size deviation is, the greater the deformation degree of the corresponding grid is, and the larger the resulting shape complexity weight is, the higher the shape complexity of the corresponding grid is, and the grid is more likely to be located in a location with more irregular grooves and holes in the three-dimensional finite element model.

[0065] Furthermore, stress may be concentrated in irregular areas of the denture surface, such as grooves, holes or sharp edges. This stress concentration may lead to material fatigue, which may cause damage or breakage of the denture in the long term, and may exert excessive pressure on the alveolar bone and soft tissue, causing pain.

[0066] Secondly, in multiple dynamic occlusal simulations, the contact between dentures is a complex process. In dynamic occlusal simulations, the loading method mainly involves the direction and location of the bite force applied to the denture. Applying different bite forces will result in different pressures on the grid, and different loading methods also have a direct impact on the pressure on the grid. Secondly, the direction and location of the force between different grids will also lead to different stress concentration areas and distributions in a grid, that is, the pressure on the same grid will change locally in different dynamic occlusal processes. Based on the above analysis, the force sensitivity is determined by analyzing the force changes of the grid during all dynamic occlusal processes. The step flow chart of the method for obtaining the force sensitivity of each grid provided in the embodiment of the present application is as follows. Figure 2 shown.

[0067] First, the differences in the pressure on each grid during all sub-dynamic occlusion processes are analyzed, specifically:

[0068] The pressure trend vectors of each grid in all sub-dynamic occlusion processes are used to form a pressure change matrix of each grid;

[0069] It should be noted that each column in the pressure change matrix represents the pressure trend vector of each grid in each dynamic bite process; for ease of understanding, the pressure change matrix is ​​scaled to a 4×3 matrix. The pressure trend vector of the grid in the first dynamic bite process is , No. The pressure trend vector of the grid in the second dynamic bite process is , No. The pressure trend vector of the grid in the third dynamic bite process is: , then the pressure change matrix is .

[0070] Calculating the fractal dimension of all elements in each row of the pressure variation matrix of each grid;

[0071] Preferably, in this embodiment, the box counting method is used to calculate the fractal dimension, wherein the box counting method is a well-known technology and will not be described in detail here. As other implementation methods, the implementer can adopt other methods of the prior art, such as the Hurst exponent method, the Higuchi algorithm, etc. This embodiment does not impose any special restrictions on this.

[0072] Calculating the discrete degree of all the fractal dimensions in the pressure variation matrix of each grid;

[0073] Preferably, in this embodiment, the degree of discreteness is calculated by calculating the coefficient of variation of all the fractal dimensions in the pressure change matrix, wherein the method for calculating the coefficient of variation is a well-known technique and will not be described in detail herein. As other implementation methods, implementers may adopt other methods of the prior art, such as standard deviation, variance, etc., and this embodiment does not impose any special restrictions on this.

[0074] It should be noted that the degree of discreteness reflects the degree of change in the force on each grid in multiple dynamic bite simulations. The greater the degree of discreteness, the greater the difference in the pressure on each grid during different dynamic bite processes, reflecting that the location of the grid is more sensitive to changes in stress distribution bite conditions, that is, the more unstable the change in pressure on the grid during the dynamic bite process.

[0075] Furthermore, when dynamic occlusion simulation is performed, the maximum stress is often the place where the stress of the mesh is most concentrated, reflecting the situation where the denture is in the closest contact with the alveolar bone or other teeth. The pressure change in this case is extremely important for the force sensitivity analysis of the mesh. Therefore, by analyzing the changes in the maximum stress at the same position in multiple dynamic occlusion simulations, the pressure difference is determined, specifically:

[0076] Select the maximum value of all elements in each row of the pressure change matrix, and obtain two minimum values ​​adjacent to the maximum value; and form a local pressure vector with all elements between the two minimum values;

[0077] Preferably, in this embodiment, an extreme point detection algorithm is used to obtain the minimum value, wherein the extreme point detection algorithm is a well-known technology and will not be described in detail here. As other implementation methods, the implementer can adopt other methods of the existing technology, such as the differential method, etc. This embodiment does not impose any special restrictions on this.

[0078] The maximum value of the difference between the local pressure vectors of any two rows in the pressure change matrix is ​​used as the pressure difference degree of each grid;

[0079] Preferably, in this embodiment, the maximum value of the DTW distance between the local pressure vectors of all any two rows in the pressure change matrix is ​​recorded as the pressure difference of each grid; wherein, the calculation of the DTW distance is a well-known technology and will not be repeated here. As other implementation methods, the implementer can adopt other methods of the prior art, such as Euclidean distance, etc., and this embodiment does not impose any special restrictions on this.

[0080] It should be noted that the pressure difference reflects the maximum difference in the stress concentration area during different dynamic occlusion processes. The larger the pressure difference, the more significant the change in the stress concentration area during different dynamic occlusion processes, which reflects that the force response of the denture during dynamic occlusion simulation is more inconsistent, that is, the greater the difference in the force sensitivity of the grid under different occlusion conditions.

[0081] Further, based on the discrete degree and the pressure difference, the force sensitivity is determined, specifically:

[0082] The product of the discrete degree and the pressure difference is used as the force sensitivity of each grid;

[0083] It should be noted that the force sensitivity reflects the force sensitivity of each mesh in the three-dimensional finite element model corresponding to the denture. The greater the force sensitivity, the greater the difference in the force response of the corresponding mesh under the same occlusal conditions. That is, after 10 different dynamic occlusal simulations, gradually increasing the changes in occlusal conditions will cause more significant changes in the force of the mesh, and the higher the force sensitivity of the mesh.

[0084] At this point, the force sensitivity of each grid is obtained.

[0085] Step 3, determining the force discreteness of each grid according to the distribution discreteness of the number of consecutive appearances of the same element in each row in the pressure change matrix; and determining the structural disorder eigenvalue of each grid in combination with the shape complexity weight and the force sensitivity.

[0086] Furthermore, under dynamic occlusion simulation, if the occlusion is not performed and the occlusion is completed, the occlusion force is 0, and from the beginning to the end of the occlusion, the change of the occlusion force shows a fluctuation characteristic of slow rise-steady-steep drop-slow drop, which indicates that the model will experience different dynamic response stages during the occlusion process. For each grid, when the occlusion is not performed and the occlusion is completed, although the occlusion force is 0, each grid may be affected by the force of other grids; in order to analyze the force characteristics of each grid during different occlusion simulations, the pressure change matrix is ​​divided into different stages, specifically:

[0087] Dividing the pressure trend vector corresponding to each column in the pressure change matrix of each grid into different occlusion stages;

[0088] Preferably, in this embodiment, the natural breakpoint method is used to divide the pressure trend vector corresponding to each column in the pressure change matrix into 6 bite stages, corresponding to the non-bite stage, the bite force slow rise stage, the bite force stable stage, the bite force steep drop stage, the bite force slow drop stage and the bite end stage, among which the natural breakpoint method is a well-known technology and will not be repeated here.

[0089] The same elements that appear continuously in each row in each occlusion stage in the pressure change matrix of each grid are recorded as a run, and the number of all elements in each run is obtained and recorded as the run length;

[0090] It should be noted that, for ease of understanding, it is assumed that in a certain occlusal stage The elements of the row are ,but , , , Each represents a run. The run length is 2, and the run length The run length is 3, the run length The run length is 1, and the run length The run length is 5.

[0091] Calculating the information entropy of all run lengths in each bite stage in the pressure change matrix of each grid;

[0092] It should be noted that the calculation of information entropy is a well-known technology and will not be described in detail here.

[0093] The mean value of the information entropy of all the occlusal stages in the pressure change matrix of each grid is used as the force discreteness of each grid;

[0094] It should be noted that the force discreteness reflects the consistency of the force trend of the mesh in different occlusion simulations. The larger the force discreteness, the worse the consistency of the force trend of the mesh in different occlusion simulations, and the higher the randomness of the force characteristics.

[0095] Furthermore, based on the shape complexity weight, the force sensitivity and the force dispersion, a structural disorder characteristic value is determined to reflect the complexity of the grid shape and the disorder of the grid force, specifically:

[0096] The normalized result of the product of the shape complexity weight, the force sensitivity and the force dispersion is used as the structural disorder eigenvalue of each grid;

[0097] Preferably, in this embodiment, a sigmoid function is used for normalization processing. As other implementations, implementers may use other methods in the prior art, such as a tanh function, etc. This embodiment does not impose any special restrictions on this.

[0098] It should be noted that, the larger the shape complexity weight is, the larger the size deviation and shape deviation of the grid unit are, the more complex the shape is, the more complex the shape of the grid is, and the more likely the grid is located in more irregular grooves and holes in the modeling; the larger the force sensitivity and the force discreteness are, the greater the difference in force response of the grid under the same occlusal condition is, the higher the force sensitivity of the grid is, and not only the force response of the grid under different occlusal conditions varies greatly, but also the variation is highly random, indicating that the behavior of the grid under force is unstable and unpredictable, that is, the more disordered the force state of the grid is; the larger the obtained structural disorder eigenvalue is, the worse the shape and force characteristics of the grid are, the more disordered the structural characteristics of the grid are, and the grid is not sufficient to accurately simulate the actual force conditions, resulting in inaccurate results of the finite element analysis, inability to achieve uniform stress distribution, and increased risk of stress concentration. Damage to the denture or excessive pressure on the alveolar bone and soft tissue by the denture will cause pain to the patient when biting.

[0099] At this point, the structural disorder eigenvalue of each grid is obtained.

[0100] Step 4, based on the structural disorder eigenvalue, obtain each defective mesh; calculate the number of extended neighborhood layers of each defective mesh through the structural disorder eigenvalue of each defective mesh; based on the number of extended neighborhood layers, refine the mesh, and based on the refined mesh, optimize the denture according to the simulation results of the occlusal simulation of the three-dimensional finite element model.

[0101] Furthermore, the larger the structural disorder eigenvalue is, the more likely the corresponding grid is a stress concentration area, and a finer grid is needed to capture the detail changes. The smaller the structural disorder eigenvalue is, the more likely the corresponding grid is farther away from the stress concentration area, and the stress change of the corresponding grid is not large, so a coarser grid can be used to simplify the analysis process. Therefore, based on the structural disorder eigenvalue, the defective grid is determined, specifically:

[0102] The grids whose structural disorder characteristic values ​​are greater than a preset threshold are recorded as defective grids;

[0103] Preferably, in this embodiment, the preset threshold value is 0.6. As other implementation modes, the implementer can set it according to the actual situation.

[0104] It should be noted that the defective mesh is more likely to be located in grooves, holes or locations with large curvature changes. These locations are often areas of stress concentration. In order to more accurately capture the stress changes in these locations, a finer mesh is needed to capture the detailed changes, so the mesh and its surrounding meshes need to be refined.

[0105] Furthermore, based on the structural disorder eigenvalue of each defective mesh, the shape variation and stress concentration of each defective mesh are analyzed. The defective mesh with a larger structural disorder eigenvalue has a stronger stress concentration of other meshes around the defective mesh, and it is necessary to refine the mesh in a larger area around the defective mesh. Therefore, based on the structural disorder eigenvalue, the number of extended neighborhood layers of each defective mesh is determined, specifically:

[0106] All grids directly connected to each defective grid are recorded as first-layer neighborhood grids, and all grids directly connected to the first-layer neighborhood grids of each defective grid are recorded as second-layer neighborhood grids, and the process is repeated recursively to obtain each layer of neighborhood grids of each defective grid;

[0107] The calculation formula for the number of extended neighborhood layers of each defect grid is: ,in, For the The number of extended neighborhood layers of defective grids, is a preset adjustment factor. In this embodiment, the preset adjustment factor is 2. For other implementations, the implementer can set it according to the actual situation. For the The structural disorder eigenvalues ​​of the defective grid, is the ceiling function, is the preset threshold. In this embodiment, the preset threshold is 0.6.

[0108] It should be noted that the purpose of the preset adjustment factor is to ensure that the mesh is sufficiently refined while avoiding the waste of computing resources caused by over-refinement, and to control the computing cost while ensuring the simulation accuracy; secondly, It reflects the degree of structural disorder of the defective grid relative to the preset threshold. The larger the value is, the greater the degree of structural disorder of the grid is relative to the preset threshold, and the stronger the stress concentration is at the location of the defective grid. It is necessary to refine all grids within a larger range at the location of the defective grid.

[0109] Adopting an adaptive mesh refinement algorithm, each defective mesh and all layer neighborhood meshes within the extended neighborhood layer number are refined to obtain a refined mesh;

[0110] Based on the refined mesh, the occlusal simulation of the three-dimensional finite element model was performed, and the denture was optimized according to the simulation results.

[0111] It should be noted that the refined mesh makes it possible to more accurately capture local stress changes in stress concentration areas of the denture, such as grooves, holes, or locations with large curvature changes, thereby improving the accuracy of the simulation results; secondly, after the mesh of the three-dimensional finite element model is refined, the occlusion simulation is performed again to identify areas that may cause tenderness during the occlusion process, and the designed denture is optimized to reduce or eliminate these discomfort areas, so that the denture model is designed to better fit the patient's oral structure and provide a more comfortable and natural occlusion experience.

[0112] Based on the same inventive concept as the above-mentioned method, an embodiment of the present application also provides a finite element analysis system for fully edentulous removable dentures, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above-mentioned finite element analysis methods for fully edentulous removable dentures when executing the computer program.

[0113] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0114] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0115] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the present application. It should be pointed out that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application without departing from the content of the technical solution of the present application, shall fall within the protection scope of the technical solution of the present application.

Claims

1. A finite element analysis method for fully edentulous removable dentures, characterized in that: The method comprises the following steps: Obtain CT images of the patient's oral cavity, construct a three-dimensional finite element model by finite element analysis, and divide the three-dimensional finite element model into grids to obtain the unit size and maximum deviation coefficient of each grid, as well as the pressure trend vector of each grid during each dynamic occlusion process; Based on the offset of the cell size of each grid and in combination with the maximum deviation coefficient, determine the shape complexity weight of each grid; Based on the pressure trend vector of each grid in all dynamic occlusion processes, a pressure change matrix of each grid is constructed, and the local change difference between the maximum elements in different rows in the pressure change matrix is ​​analyzed to determine the pressure difference of each grid; combined with the complex conditions of all elements in each row, the force sensitivity of each grid is determined; Determine the force dispersion of each grid according to the distribution discreteness of the number of consecutive occurrences of the same element in each row in the pressure change matrix; determine the structural disorder eigenvalue of each grid in combination with the shape complexity weight and the force sensitivity; record the grid whose structural disorder eigenvalue is greater than a preset threshold as a defective grid; All grids directly connected to each defect grid are recorded as the first layer neighborhood grids, and all grids directly connected to the first layer neighborhood grids of each defect grid are recorded as the second layer neighborhood grids, and the same process is repeated recursively to obtain each layer of neighborhood grids of each defect grid. An adaptive grid refinement algorithm is used to refine each defect grid and all layers of neighborhood grids within the extended neighborhood layer to obtain the refined grids. Based on the refined grids and the simulation results of occlusal simulation using a three-dimensional finite element model, the denture is optimized.

2. The finite element analysis method for a fully edentulous removable denture according to claim 1, characterized in that: The determining of the shape complexity weight of each mesh includes: Calculate the mean value of the cell size of all meshes in the three-dimensional finite element model, recorded as the average size; The ratio of the cell size of each grid to the average size is used as the size similarity of each grid; The difference between the size similarity and the value 1 is calculated and recorded as the size deviation; the normalized result of the product of the size deviation and the maximum deviation coefficient is used as the shape complexity weight of each grid.

3. The finite element analysis method for a fully edentulous removable denture according to claim 1, characterized in that: Determining the pressure difference of each grid includes: Select the maximum value of all elements in each row of the pressure change matrix, and obtain two minimum values ​​adjacent to the maximum value; all elements between the two minimum values ​​form a local pressure vector; The maximum value of the difference between the local pressure vectors of any two rows in the pressure variation matrix is ​​used as the pressure difference degree of each grid.

4. The finite element analysis method for a fully edentulous removable denture according to claim 1, characterized in that: The determining of the force sensitivity of each grid comprises: Calculating the fractal dimension of all elements in each row of the pressure variation matrix of each grid; Calculating the discrete degree of all the fractal dimensions in the pressure variation matrix of each grid; The product of the discrete degree and the pressure difference is used as the force sensitivity of each grid.

5. The finite element analysis method for a fully edentulous removable denture according to claim 1, characterized in that: The step of determining the force discreteness of each grid comprises: Dividing the pressure trend vector corresponding to each column in the pressure change matrix of each grid into a plurality of occlusion stages; The same elements that appear continuously in each row in each occlusion stage in the pressure change matrix of each grid are recorded as a run, and the number of all elements in each run is obtained and recorded as the run length; Calculating the information entropy of all run lengths in each bite stage in the pressure change matrix of each grid; The mean value of the information entropy of all occlusion stages in the pressure change matrix of each grid is used as the force discreteness of each grid.

6. The finite element analysis method for a fully edentulous removable denture according to claim 1, characterized in that: The structural disorder characteristic value of each grid is a normalized result of the product of the shape complexity weight, the force sensitivity and the force discreteness.

7. The finite element analysis method for a fully edentulous removable denture according to claim 1, characterized in that: The calculation method of the extended neighborhood layer number is: ,in, For the The number of extended neighborhood layers of defective grids, is the preset adjustment factor, For the The structural disorder eigenvalues ​​of the defective grid, is the ceiling function, is the preset threshold.

8. A finite element analysis system for fully edentulous removable dentures, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the finite element analysis method for a fully edentulous removable denture as described in any one of claims 1-7 are implemented.

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