Parameterization construction method of BIM model

Abstract

The invention relates to the technical field of building information modeling, and discloses a BIM (Building Information Modeling) parameterization construction method which comprises the following steps: step 1, defining geometric elements of points, lines and surfaces, creating a basic geometric structure of a model, connecting points into lines by using a geometric relationship, closing the lines into an outline, and taking the outline as a foundation for generating a three-dimensional entity; and 2, on the constructed basic geometric model, a three-dimensional geometric entity is generated according to a preset rule, the three-dimensional entity is generated through stretching, rotating and lofting along a path of a closed contour line, the stretched entity is constructed by translating the contour along a normal direction by a fixed distance, and the rotating entity is generated by rotating the contour around a certain rotating shaft by a fixed angle. According to the method, geometric elements of points, lines and surfaces are defined, and a three-dimensional geometric entity is constructed based on a parameterized incidence relation, so that the functions of quickly generating a complex model, dynamically adjusting geometric characteristics and flexibly modifying design are realized, and the effect of remarkably improving modeling efficiency and flexibility is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of building information modeling, and in particular to a parameterized construction method of a BIM model. Background Art

[0002] With the rapid development of building information modeling technology, BIM has become an important technical means for building engineering design, construction and operation management. BIM technology provides digital support for the entire life cycle of engineering design and construction by constructing building models that contain geometric shapes, physical properties and functional information. However, the existing BIM modeling technology faces the following problems:

[0003] Traditional BIM modeling methods rely on manual operations or the use of scripting languages ​​to build models. The modeling efficiency is low and there is a high technical threshold for the generation of complex geometric structures. This is time-consuming and labor-intensive, limits the flexibility and operability of the model, and cannot meet the needs of rapid iterative design and large-scale modeling.

[0004] In the existing technology, BIM models usually need to be built from scratch, and the degree of model reuse is low. Especially when the design changes and similar models of different specifications need to be generated, a lot of time is needed to repeat the modeling. In addition, the lack of association between geometric features and external input parameters makes the model's diversified design support insufficient and its adaptability poor.

[0005] In the existing BIM modeling methods, the control of geometric characteristics mainly relies on manual adjustments by designers. The constraints and adjustments of geometric characteristics lack mathematical descriptions, which leads to errors in complex designs. Especially in nonlinear modeling scenarios, the existing technology lacks effective parameter optimization and geometric constraint solving methods, which affects the accuracy and reliability of modeling.

[0006] The existing BIM modeling method has high requirements on the professional skills of operators. At the same time, it requires a lot of manual adjustment and verification work, which in turn increases the cost of personnel training, prolongs the response time of design and modeling, and increases the overall cost of engineering construction.

[0007] Therefore, those skilled in the art provide a parametric construction method for a BIM model to solve the above-mentioned problems. Summary of the invention

[0008] In view of the deficiencies in the prior art, the present invention provides a parameterized construction method of a BIM model to solve the problems raised in the above background technology.

[0009] To achieve the above objectives, the present invention is implemented through the following technical solutions: A parametric construction method of a BIM model, comprising:

[0010] Step 1: Create the basic geometric structure of the model by defining point, line, and surface geometric elements, use geometric relationships to connect points into lines, close lines into contours, and use contours as the basis for generating three-dimensional entities;

[0011] Step 2: Generate three-dimensional geometric entities according to predetermined rules on the constructed basic geometric model. The three-dimensional entity is generated by stretching, rotating and lofting along the path through the closed contour line. The stretched entity is constructed by translating the contour along the normal direction by a fixed distance. The rotated entity is generated by rotating the contour around a certain rotation axis by a fixed angle. The lofted entity is generated by moving the contour along the path direction and superimposing it. The construction of the three-dimensional entity requires determining the contour, path and parameters to provide a solid object for the establishment of geometric constraint relationships.

[0012] Step 3: Establish geometric constraints between points and points, points and lines, points and surfaces, lines and lines, and lines and surfaces between three-dimensional geometric entities and reference planes. The geometric constraint relationships include fixed constraints of distance, angle, and specific shape parameters. The geometric constraint relationships provide mathematical descriptions for model parameterization solutions.

[0013] Step 4: By introducing parameters into the geometric constraint relationship, the relationship between the geometric features in the model and the external input parameters is established, so that the model can achieve changes in geometric features by adjusting the parameters. The parameters are associated with the vertices, edges, and faces of the geometric entity and participate in solving the constraint relationship.

[0014] Step 5: According to the geometric constraint relationship and the parameterized association relationship, the constraint conditions are converted into a set of algebraic equations. Each geometric constraint generates a corresponding mathematical equation, and the parameterized variables are substituted into the equation to form a nonlinear equation set, which will be solved by calculation in the subsequent steps.

[0015] Step 6: For the constructed nonlinear equation group, the parameter solution is obtained by using the solving algorithm. The parameter solution is directly applied to the vertices, edges, and faces of the geometric entity to update the coordinates, position, size, and angle of the entity. The updated parameters regenerate the basic geometric structure of the model through geometric relationships, and gradually construct a complete three-dimensional geometric entity to complete the construction of parametric modeling.

[0016] Preferably, in step 1, the position of the point is uniquely determined by the three-dimensional coordinates (x, y, z), the line segment is formed by connecting two points, and the length L of the line segment is calculated according to the following formula:

[0017]

[0018] Among them, x 1 ,y 1 、z 1 and x 2 ,y 2 、z 2are the coordinates of the two end points of the line segment, and L represents the length of the line segment;

[0019] The plane passes through the point (x p ,y p , z p ) and the normal vector (n x , n y , n z ) is determined, the plane equation is:

[0020] n x ·(xx p )+n y ·(yy p )+n z ·(zz p )=0,

[0021] Among them, n x 、n y 、n z is the component of the plane normal vector, (x p ,y p , z p ) is a reference point on the plane, (x, y, z) is an arbitrary point on the plane, and by default x=0, y=0, z=0 are all fixed reference planes.

[0022] Preferably, in step 2, the stretched entity is generated by translating the closed contour along the normal direction, and the height H of the stretched entity is determined by the following formula: H = h 2 -h 1 ,

[0023] Among them, h 1 and h 2 are the starting and ending heights of the stretched entity, and H is the height of the stretched entity;

[0024] In step 2, the rotation entity is formed by rotating the closed contour around the rotation axis, and the rotation angle a is determined by the following formula:

[0025] a=a 2 -a 1 ,

[0026] Among them, a 1 and a 2 are the starting and ending angles of the rotating entity, and a is the rotation angle.

[0027] Preferably, the distance constraint between points in step 3 is determined by the following formula:

[0028]

[0029] Among them, d is the distance between points, x1 ,y 1 、z 1 and x 2 ,y 2 、z 2 are the coordinates of the points;

[0030] The distance constraint between the point and the surface in step 3 is determined by the following formula:

[0031]

[0032] Among them, d point-plane Represents the distance between the point and the surface, n x 、n y 、n z are the components of the plane normal vector, (x, y, z) are the coordinates of the point, (x p ,y p , z p ) is a plane reference point;

[0033] The angle θ between the lines in step 3 is determined by the following formula:

[0034] in, and is the direction vector of the two lines, θ is the angle between the two lines, and is the magnitude of the direction vector.

[0035] Preferably, in step 5, the geometric constraint relationship is converted into a nonlinear equation group, which includes a description of parameterized variables and geometric relationships, and is used to obtain a parameter solution through a solution algorithm and update the three-dimensional model;

[0036] The nonlinear equations are solved by constructing a Jacobian matrix, and each element of the Jacobian matrix is ​​determined by the first-order partial derivative of the geometric constraint equation with respect to the parameter, and is used to iteratively solve the parameter solution of the three-dimensional geometric model.

[0037] Preferably, during the iterative solution of the nonlinear equations, the parameter solution is obtained by the following improved LM algorithm:

[0038] Initialization parameters k = 0, v = 2, x = x 0 , τ=1, and set the initial Jacobian matrix J and error threshold □;

[0039] Construct error vector f and gradient vector g = J T f, calculate the update matrix A = J T ·J;

[0040] Introducing the damping factor μ=τ·max(Aii ) and calculate the update direction:

[0041] Δx=-(A+μ·I) -1 g,

[0042] Update parameter x k+1 =x k +Δx, if |Δx|<□, the solution is considered to have converged.

[0043] Among them, x is the parameter variable vector, f is the error vector, J is the Jacobian matrix, μ is the damping factor, and □ is the error threshold.

[0044] Preferably, the Jacobian matrix in the iterative solution is stored and optimized by a sparse matrix optimization method, wherein the sparsity of the Jacobian matrix is ​​determined by the following formula:

[0045] Where S is the sparsity rate, m and n are the number of rows and columns of the matrix, and the number of non-zero elements represents the number of non-zero elements in the Jacobian matrix;

[0046] The non-zero elements and indices are recorded using the sparse matrix compression storage method.

[0047] Preferably, the distance constraint between points is defined by a constraint optimization function as:

[0048]

[0049] Among them, E d is the distance constraint error function, d i is the expected distance value,

[0050] (x i1 ,y i1 , z i1 ) and (x i2 ,y i2 , z i2 ) are the coordinates of the point pair, and n is the number of columns in the matrix.

[0051] Preferably, the distance constraint between the point and the surface is described by the following optimization function:

[0052]

[0053] Among them, E p is the error function of the distance between the point and the surface, d p is the expected distance from the point to the surface,

[0054] (x i ,y i , zi ) is the coordinate of the point, (x pi ,y pi , z pi ) are the coordinates of the plane reference point,

[0055] n xi 、n yi 、n zi are the components of the plane normal vector.

[0056] Preferably, the angle constraint between the lines is defined by the following optimization function:

[0057]

[0058] Among them, E line-angle is the line-to-line angle error function, cosθ i is the cosine of the desired angle, and are the direction vectors of the line, and is the magnitude of the direction vector.

[0059] The present invention provides a parametric construction method of a BIM model, which has the following beneficial effects:

[0060] 1. The present invention defines geometric elements of points, lines and surfaces, and constructs three-dimensional geometric entities based on parametric association relationships, thereby realizing the functions of quickly generating complex models, dynamically adjusting geometric characteristics and flexibly modifying designs, thereby significantly improving modeling efficiency and flexibility.

[0061] 2. The present invention associates geometric model features with external input parameters and combines a variety of geometric construction methods such as stretching, rotation, and lofting to achieve rapid reuse of models and diversified support for designs, thereby improving the reusability and adaptability of the model.

[0062] 3. The present invention introduces geometric constraints, transforms geometric characteristics into a set of nonlinear equations, and uses an improved LM algorithm to solve them, thereby achieving the functions of accurate description of geometric characteristics and parameter optimization, thereby improving modeling accuracy and reducing human errors.

[0063] 4. The present invention drives the model update through parameterization, combines the characteristics of automated constraint solving and dynamic adjustment, realizes rapid response to design changes and reduces dependence on personnel's technical level, thereby saving modeling time and cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0065] In order to make the technical personnel in the technical field understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly and completely described below in combination with the drawings in the embodiment of the present invention. Obviously, the described embodiment is a partial embodiment of the present invention, not a complete embodiment. Based on the embodiment of the present invention, other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present invention.

[0066] The present invention is described in detail below in conjunction with the accompanying drawings:

[0067] Embodiment 1:

[0068] Please refer to the attached Figure 1 , an embodiment of the present invention provides a parameterized construction method of a BIM model, comprising:

[0069] Step 1: Create the basic geometric structure of the model by defining point, line, and surface geometric elements, use geometric relationships to connect points into lines, close lines into contours, and use contours as the basis for generating three-dimensional entities;

[0070] Step 2: Generate three-dimensional geometric entities according to predetermined rules on the constructed basic geometric model. The three-dimensional entity is generated by stretching, rotating and lofting along the path through the closed contour line. The stretched entity is constructed by translating the contour along the normal direction by a fixed distance. The rotated entity is generated by rotating the contour around a certain rotation axis by a fixed angle. The lofted entity is generated by moving the contour along the path direction and superimposing it. The construction of the three-dimensional entity requires determining the contour, path and parameters to provide a solid object for the establishment of geometric constraint relationships.

[0071] Step 3: Establish geometric constraints between points and points, points and lines, points and surfaces, lines and lines, and lines and surfaces between three-dimensional geometric entities and reference planes. The geometric constraint relationships include fixed constraints of distance, angle, and specific shape parameters. The geometric constraint relationships provide mathematical descriptions for model parameterization solutions.

[0072] Step 4: By introducing parameters into the geometric constraint relationship, the relationship between the geometric features in the model and the external input parameters is established, so that the model can achieve changes in geometric features by adjusting the parameters. The parameters are associated with the vertices, edges, and faces of the geometric entity and participate in solving the constraint relationship.

[0073] Step 5: According to the geometric constraint relationship and the parameterized association relationship, the constraint conditions are converted into a set of algebraic equations. Each geometric constraint generates a corresponding mathematical equation, and the parameterized variables are substituted into the equation to form a nonlinear equation set, which will be solved by calculation in the subsequent steps.

[0074] Step 6: For the constructed nonlinear equation group, the parameter solution is obtained by using the solving algorithm. The parameter solution is directly applied to the vertices, edges, and faces of the geometric entity to update the coordinates, position, size, and angle of the entity. The updated parameters regenerate the basic geometric structure of the model through geometric relationships, and gradually construct a complete three-dimensional geometric entity to complete the construction of parametric modeling.

[0075] Benefits of step 1: By defining point, line, and surface geometric elements, the basic units for building models are provided, making the geometric expression of the model more systematic and standardized. By constructing closed contours, clear basic rules are provided for the generation of three-dimensional entities, improving the accuracy and flexibility of modeling;

[0076] Benefits of step 2: Through various geometric construction methods such as stretching, rotation, and lofting, three-dimensional geometric entities can be quickly generated to meet the construction requirements of complex models in different scenarios. By determining the contour, path, and parameters, users can flexibly control the shape and size of the model, improving the efficiency and adaptability of modeling;

[0077] Benefits of step 3: By defining geometric constraints between points, lines, surfaces, lines, and surfaces, the consistency and logic of the model's geometric characteristics are ensured. The establishment of geometric constraint relationships provides a mathematical description for subsequent parametric solutions and improves the accuracy of model modification and adjustment;

[0078] Benefits of step 4: By introducing parameters and establishing associations between geometric features and external input parameters, the model can be dynamically adjusted according to parameter changes. The parametric design method improves the versatility and reusability of the model and meets the needs of quickly generating and modifying models in different scenarios.

[0079] Benefits of step 5: By converting geometric constraints into a set of algebraic equations, mathematical description of geometric characteristics and parameters can be achieved. The formation of a set of algebraic equations enables complex geometric relationships to be automatically solved by computers, reducing the complexity and error rate of manual adjustments;

[0080] Benefits of step 6: By using the algorithm for solving nonlinear equations to obtain parameter solutions, the parameter solutions are directly applied to the update of geometric entities to ensure the accuracy and consistency of the model. The automatic update function of the model enables parameter changes to be quickly reflected in the three-dimensional entity, significantly improving the response speed of design changes.

[0081] In step 1, the position of the point is uniquely determined by the three-dimensional coordinates (x, y, z), the line segment is formed by connecting two points, and the length L of the line segment is calculated according to the following formula:

[0082]

[0083] Among them, x 1 ,y1 、z 1 and x 2 ,y 2 、z 2 are the coordinates of the two end points of the line segment, and L represents the length of the line segment;

[0084] The plane passes through the point (x p ,y p , z p ) and the normal vector (n x , n y , n z ) is determined, the plane equation is:

[0085] n x ·(xx p )+n y ·(yy p )+n z ·(zz p )=0,

[0086] Among them, n x 、n y 、n z is the component of the plane normal vector, (x p ,y p , z p ) is a reference point on the plane, (x, y, z) is an arbitrary point on the plane, and by default x=0, y=0, z=0 are all fixed reference planes.

[0087] As the most basic geometric element in three-dimensional space, points are uniquely positioned by three-dimensional coordinates to ensure the accuracy and logical consistency of model geometry construction. Clear definitions enable points to serve as the construction basis for other geometric elements and provide a standardized reference for the establishment of subsequent geometric relationships.

[0088] By using the Euclidean distance formula to calculate the length of the line segment, a rigorous mathematical definition is provided. The precise calculation method ensures high-precision measurement in geometric modeling, lays the foundation for the subsequent definition of geometric relationships, and avoids errors caused by inaccurate measurements during the modeling process.

[0089] In summary, through the geometric definition and formula calculation of points, line segments and planes, the present invention provides a standardized basic description in geometric modeling.

[0090] The position of a point is uniquely determined by three-dimensional coordinates to ensure the accuracy of geometric construction. Line segments are formed by connecting points, and the length is calculated using formulas to provide a basis for the quantification of geometric relationships. Planes are determined by reference points and normal vectors, and equation representation provides rigorous theoretical support for subsequent geometric constraints and mathematical solutions. Overall, basic definitions and mathematical formulas provide a solid theoretical foundation and implementation path for parametric modeling and geometric construction.

[0091] In step 2, the extruded entity is generated by translating the closed contour along the normal direction. The height H of the extruded entity is determined by the following formula: H = h 2 -h 1 ,

[0092] Among them, h 1 and h 2 are the starting and ending heights of the stretched entity, and H is the height of the stretched entity;

[0093] In step 2, the rotation entity is formed by rotating the closed contour around the rotation axis, and the rotation angle a is determined by the following formula:

[0094] a=a 2 -a 1 ,

[0095] Among them, a 1 and a 2 are the starting and ending angles of the rotating entity, and a is the rotation angle.

[0096] In step 2, the present invention realizes the rapid generation of regular geometric bodies and symmetrical geometric bodies through the construction method of stretching entities and rotating entities. The stretching entity is formed by translating the closed contour along the normal direction, and the height H is calculated by the height of the starting point and the end point, providing a simple and efficient regular body generation method. The rotating entity is generated by rotating the closed contour around the rotation axis, and the adjustment of the rotation angle θ makes the construction of complex curved surface geometric bodies flexible and efficient. The method combines parametric control to lay the foundation for the rapid construction and flexible adjustment of geometric models, effectively improving the efficiency and adaptability of building information modeling.

[0097] The distance constraint between points in step 3 is determined by the following formula:

[0098]

[0099] Among them, d is the distance between points, x 1 ,y 1 、z 1 and x 2 ,y 2 、z 2 are the coordinates of the points;

[0100] The distance constraint between the point and the face in step 3 is determined by the following formula:

[0101]

[0102] Among them, d point-plane Represents the distance between the point and the surface, n x 、n y 、nz are the components of the plane normal vector, (x, y, z) are the coordinates of the point, (x p ,y p , z p ) is a plane reference point;

[0103] The angle θ between the lines in step 3 is determined by the following formula:

[0104] in, and is the direction vector of the two lines, θ is the angle between the two lines, and is the magnitude of the direction vector.

[0105] The distance constraint between points provides a clear geometric quantitative relationship and can accurately describe the spatial distance between points. The mathematical distance description ensures the accuracy of geometric characteristics in geometric modeling and provides a basis for the dynamic adjustment and precise control of subsequent complex models. At the same time, the definition of the formula provides a computable mathematical description for subsequent optimization and nonlinear equation solving.

[0106] The distance constraint between points and planes describes the shortest distance relationship between points and planes. It performs mathematical calculations based on the coordinates of the points and the plane normal vector to ensure the accuracy of the geometric relationship. Through the formula, the distance between points and planes can be dynamically adjusted to ensure that the point positions are within the spatial range of the design constraints, providing mathematical support for the construction and adjustment of complex models.

[0107] The mathematical description of the angle between lines defines the angle constraint between lines through the dot product of the direction vector and the modulus length relationship. The constraint provides an accurate quantitative method for angle control and is applicable to the design of a variety of complex geometric structures. The angle constraint can ensure the consistency of the model in terms of geometric relationships and provide support for the spatial relationship and functional design of the architectural model.

[0108] In step 5, the geometric constraint relationship is converted into a nonlinear equation group, which includes a description of parameterized variables and geometric relationships, and is used to obtain a parameter solution through a solving algorithm and update the three-dimensional model;

[0109] The nonlinear equations are solved by constructing the Jacobian matrix. Each element of the Jacobian matrix is ​​determined by the first-order partial derivatives of the geometric constraint equations with respect to the parameters, and is used to iteratively solve the parameter solutions of the three-dimensional geometric model.

[0110] During the iterative solution of the nonlinear equations, the parameter solution is obtained by the following improved LM algorithm:

[0111] Initialization parameters k = 0, v = 2, x = x 0 , τ=1, and set the initial Jacobian matrix J and error threshold □;

[0112] Construct error vector f and gradient vector g = J T f, calculate the update matrix A = J T ·J;

[0113] Introducing the damping factor μ=τ·max(A ii ) and calculate the update direction:

[0114] Δx=-(A+μ·I) -1 g,

[0115] Update parameter x k+1 =x k +Δx, if |Δx|<□, the solution is considered to have converged.

[0116] Among them, x is the parameter variable vector, f is the error vector, J is the Jacobian matrix, μ is the damping factor, and □ is the error threshold.

[0117] The Jacobian matrix in the iterative solution is optimized for storage and operation by using the sparse matrix optimization method, where the sparsity of the Jacobian matrix is ​​determined by the following formula:

[0118] Where S is the sparsity rate, m and n are the number of rows and columns of the matrix, and the number of non-zero elements represents the number of non-zero elements in the Jacobian matrix;

[0119] The non-zero elements and indices are recorded using the sparse matrix compression storage method.

[0120] By converting geometric constraints into nonlinear equations, the constraints between geometric elements can be accurately described in mathematical form. The introduction of nonlinear equations transforms the construction problem of complex geometric models into a problem of solving parameter optimization, thereby realizing parametric control of geometric models. This method provides a unified mathematical framework for dynamic adjustment of the model, ensuring the accuracy of calculation and the controllability of the model.

[0121] The Jacobian matrix provides the first-order partial derivative information of the error function with respect to the parameter variables in the nonlinear equations, which is used to guide the iterative solution process. By constructing the Jacobian matrix, the solution process can be converged quickly, while ensuring that the geometric constraints of the model are accurately satisfied. The application of the Jacobian matrix makes the solution of complex models feasible and provides mathematical support for geometric optimization.

[0122] The improved LM algorithm combines the advantages of the gradient descent method and the Newton method to achieve a robust iterative solution process. In the initial stage, the algorithm uses the damping factor μ to maintain robustness. When approaching the global optimal solution, the algorithm dynamically adjusts to the faster Newton direction. Through the algorithm, the efficiency and convergence of solving the nonlinear equations are improved, ensuring that the geometric model can be quickly updated and meets the constraints.

[0123] By constructing the error vector and gradient vector, calculating the update direction and iterating the solution, the error can be reduced in each iteration. If the error is lower than the preset threshold □, it is determined to be converged and the iteration ends automatically. The error control mechanism ensures the accuracy and convergence of the calculation, providing accurate guarantee for the final result of the geometric model.

[0124] The distance constraint between points is defined by the constraint optimization function:

[0125]

[0126] Among them, E d is the distance constraint error function, d i is the expected distance value,

[0127] (x i1 ,y i1 , z i1 ) and (x i2 ,y i2 , z i2 ) are the coordinates of the point pair, and n is the number of columns in the matrix.

[0128] The distance constraint between points and surfaces is described by the following optimization function:

[0129]

[0130] Among them, E p is the error function of the distance between the point and the surface, d p is the expected distance from the point to the surface,

[0131] (x i ,y i , z i ) is the coordinate of the point, (x pi ,y pi , z pi ) are the coordinates of the plane reference point,

[0132] n xi 、n yi 、n zi are the components of the plane normal vector.

[0133] The angle constraint between lines is defined by the following optimization function:

[0134]

[0135] Among them, E line-angle is the line-to-line angle error function, cosθ i is the cosine of the desired angle, and are the direction vectors of the line, and is the magnitude of the direction vector.

[0136] The present invention transforms geometric characteristics into optimization problems in the form of error functions through constraint optimization functions of geometric relationships between points, points and surfaces, and lines. The method has significant advantages in the following aspects:

[0137] By optimizing the error function, the actual distance between point pairs is made close to the design target, ensuring the accuracy and consistency of the point-to-point relationship in the model structure.

[0138] The distance from the point to the plane is dynamically optimized through the error function so that the spatial distribution of points in the model meets the preset design requirements.

[0139] By optimizing the angle between lines through the error function, precise control of the direction relationship can be achieved to meet the angle requirements in complex geometric models.

[0140] The optimization function provides high-precision dynamic adjustment capabilities for geometric models, ensuring the accuracy, flexibility and controllability of constraints in model construction. The model can maintain the consistency of design constraints during dynamic adjustment, significantly improving the efficiency and reliability of modeling.

[0141] Embodiment 2:

[0142] This embodiment provides a BIM model method based on parametric construction, taking a third-order independent foundation as an example to demonstrate the steps of quickly constructing a building geometric model through parametric modeling:

[0143] Step 1: Build the entity:

[0144] a. Draw a square with the origin as the center and a side length of 2800 as the outline on the xy plane, with the stretching start point as 0 and the stretching end point as 400 to generate a first-order basic entity;

[0145] b. Draw a square with the origin as the center and a side length of 1800 as the outline on the xy plane, with the stretching start point at 400 and the stretching end point at 700 to generate a second-order basic entity;

[0146] c. Draw a square with the origin as the center and a side length of 1000 as the outline on the xy plane, with the stretching start point at 700 and the stretching end point at 1700 to generate a third-order basic entity;

[0147] Step 2: Construct constraint relationships:

[0148] Determine three sets of fixed reference plane properties:

[0149] Origin: (0, 0, 0)

[0150] Normal vector of xy plane: (0, 0, 1)

[0151] xz plane normal vector: (0, 1, 0)

[0152] yz plane normal vector: (1, 0, 0)

[0153] Set geometric constraints for the contour vertices of each order of basic entities. The vertex coordinates of each contour are as follows: First-order basic entity vertices:

[0154] Point A (xA, yA, zA)

[0155] Point B (xB, yB, zB)

[0156] Point C (xC, yC, zC)

[0157] Point D(xD,yD,zD)

[0158] Second-order basic entity vertices:

[0159] Point E(xE,yE,zE)

[0160] Point F (xF, yF, zF)

[0161] Point G (xG, yG, zG)

[0162] Point H (xH, yH, zH)

[0163] Third-order basic entity vertices:

[0164] Point I (xI, yI, zI)

[0165] Point J: (xJ, yJ, zJ)

[0166] Point K: (xK, yK, zK)

[0167] Point L (xL, yL, zL)

[0168] Step 3: Mark parameters and generate equations:

[0169] Label the parameters for each contour:

[0170] First-order basic entity: length = 3000, width = 2800;

[0171] Second-order basic entity: length = 2000, width = 1600;

[0172] Third-order basic entity: length = 800, width = 900;

[0173] Generate a system of equations based on parameters:

[0174] First-order basic entities:

[0175] Similar formulas are used to label geometric relations between second-order and third-order basic entities;

[0176] Step 4: Solution:

[0177] The improved LM algorithm is used to construct a nonlinear equation system and solve the vertex coordinates of each contour;

[0178] Taking the coordinates of the above points as variables and the parameters as constants into the constraint equations, we get the following set of equations:

[0179]

[0180]

[0181]

[0182] Solving the equations gives the coordinates of each vertex:

[0183] First-order basic entity initial coordinates:

[0184] Point A (xA=-1500, yA=1400, zA=0)

[0185] Point B (xB = -1500, yB = -1400, zB = 0)

[0186] Point C (xC = 1500, yC = -1400, zC = 0)

[0187] Point D (xD=1500, yD=1400, zD=0)

[0188] Second-order basic entity initial coordinates:

[0189] Point E (xE=-1000, yE=800, zE=0)

[0190] Point F (xF=-1000, yF=-800, zF=0)

[0191] Point G (xG = 1000, yG = -800, zG = 0)

[0192] Point H (xH=1000, yH=800, zH=0)

[0193] Initial coordinates of the third-order basic entity:

[0194] Point I (xI = -400, yI = 450, zI = 0)

[0195] Point J (xJ=-400, yJ=-450, zJ=0)

[0196] Point K (xK=400, yK=-450, zK=0)

[0197] Point L (xL=400, yL=450, zL=0)

[0198] Step 5: Model generation:

[0199] According to the point coordinates solved above, the third-order foundation entities are superimposed one by one to generate a complete three-dimensional independent foundation model.

[0200] Implementation effect: This embodiment demonstrates how to use parametric modeling to quickly construct a geometric model of a third-order independent foundation, verifying the efficiency, flexibility and accuracy of the present invention in constructing complex building models.

[0201] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A parametric construction method for a BIM model, characterized in that: include: Step 1: Create the basic geometric structure of the model by defining point, line, and surface geometric elements, use geometric relationships to connect points into lines, close lines into contours, and use contours as the basis for generating three-dimensional entities; Step 2: Generate three-dimensional geometric entities according to predetermined rules on the constructed basic geometric model. The three-dimensional entity is generated by stretching, rotating and lofting along the path through the closed contour line. The stretched entity is constructed by translating the contour along the normal direction by a fixed distance. The rotated entity is generated by rotating the contour around a certain rotation axis by a fixed angle. The lofted entity is generated by moving the contour along the path direction and superimposing it. The construction of the three-dimensional entity requires determining the contour, path and parameters to provide a solid object for the establishment of geometric constraint relationships. Step 3: Establish geometric constraints between points and points, points and lines, points and surfaces, lines and lines, and lines and surfaces between three-dimensional geometric entities and reference planes. The geometric constraint relationships include fixed constraints of distance, angle, and specific shape parameters. The geometric constraint relationships provide mathematical descriptions for model parameterization solutions. Step 4: By introducing parameters into the geometric constraint relationship, the relationship between the geometric features in the model and the external input parameters is established, so that the model can achieve changes in geometric features by adjusting the parameters. The parameters are associated with the vertices, edges, and faces of the geometric entity and participate in solving the constraint relationship. Step 5: According to the geometric constraint relationship and the parameterized association relationship, the constraint conditions are converted into a set of algebraic equations. Each geometric constraint generates a corresponding mathematical equation, and the parameterized variables are substituted into the equation to form a nonlinear equation set, which will be solved by calculation in the subsequent steps. Step 6: For the constructed nonlinear equation group, the parameter solution is obtained by using the solving algorithm. The parameter solution is directly applied to the vertices, edges, and faces of the geometric entity to update the coordinates, position, size, and angle of the entity. The updated parameters regenerate the basic geometric structure of the model through geometric relationships, and gradually construct a complete three-dimensional geometric entity to complete the construction of parametric modeling.

2. A parametric construction method of a BIM model according to claim 1, characterized in that: In step 1, the position of the point is uniquely determined by the three-dimensional coordinates (x, y, z), the line segment is formed by connecting two points, and the length L of the line segment is calculated according to the following formula: Among them, x1, y1, z1 and x2, y2, z2 are the coordinates of the two end points of the line segment, and L represents the length of the line segment; The plane passes through the point (x p ,y p , z p ) and the normal vector (n x , n y , n z ) is determined, the plane equation is: n x ·(xx p )+n y ·(yy p )+n z ·(zz p )=0, Among them, n x 、n y 、n z is the component of the plane normal vector, (x p ,y p , z p ) is a reference point on the plane, (x, y, z) is an arbitrary point on the plane, and by default x=0, y=0, z=0 are all fixed reference planes.

3. The parametric construction method of a BIM model according to claim 1, characterized in that: In step 2, the stretched entity is generated by translating the closed contour along the normal direction, and the height H of the stretched entity is determined by the following formula: H = h2-h1, Where h1 and h2 are the starting and ending heights of the stretched entity, and H is the height of the stretched entity; In step 2, the rotation entity is formed by rotating the closed contour around the rotation axis, and the rotation angle a is determined by the following formula: a=a2-a1, Among them, a1 and a2 are the starting angle and ending angle of the rotating entity, and a is the rotation angle.

4. The parametric construction method of a BIM model according to claim 1, characterized in that: The distance constraint between points in step 3 is determined by the following formula: Among them, d is the distance between points, x1, y1, z1 and x2, y2, z2 are the coordinates of the points; The distance constraint between the point and the surface in step 3 is determined by the following formula: Among them, d point-plane Represents the distance between the point and the surface, n x 、n y 、n z are the components of the plane normal vector, (x, y, z) are the coordinates of the point, (x p ,y p , z p ) is a plane reference point; The angle θ between the lines in step 3 is determined by the following formula: in, and is the direction vector of the two lines, θ is the angle between the two lines, and is the magnitude of the direction vector.

5. The parametric construction method of a BIM model according to claim 1, characterized in that: In step 5, the geometric constraint relationship is converted into a nonlinear equation group, which includes a description of parameterized variables and geometric relationships, and is used to obtain a parameter solution through a solution algorithm and update the three-dimensional model; The nonlinear equations are solved by constructing a Jacobian matrix, and each element of the Jacobian matrix is ​​determined by the first-order partial derivative of the geometric constraint equation with respect to the parameter, and is used to iteratively solve the parameter solution of the three-dimensional geometric model.

6. A parametric construction method of a BIM model according to claim 5, characterized in that: During the iterative solution of the nonlinear equations, the parameter solution is obtained by the following improved LM algorithm: Initialize parameters k=0, v=2, x=x0, τ=1, and set the initial Jacobian matrix J and error threshold □; Construct error vector f and gradient vector g = J T f, calculate the update matrix A = J T ·J; Introducing the damping factor μ=τ·max(A ii ) and calculate the update direction: Δx=-(A+μ·I) -1 ·g, Update parameter x k+1 =x k +Δx, if |Δx|<□, the solution is considered to have converged. Among them, x is the parameter variable vector, f is the error vector, J is the Jacobian matrix, μ is the damping factor, and □ is the error threshold.

7. A parametric construction method of a BIM model according to claim 6, characterized in that: The Jacobian matrix in the iterative solution is optimized for storage and operation by a sparse matrix optimization method, wherein the sparsity of the Jacobian matrix is ​​determined by the following formula: Where S is the sparsity rate, m and n are the number of rows and columns of the matrix, and the number of non-zero elements represents the number of non-zero elements in the Jacobian matrix; The non-zero elements and indices are recorded using the sparse matrix compression storage method.

8. The parametric construction method of a BIM model according to claim 4, characterized in that: The distance constraint between points is defined by the constraint optimization function: Among them, E d is the distance constraint error function, d i is the expected distance value, (x i1 ,y i1 , z i1 ) and (x i2 ,y i2 , z i2 ) are the coordinates of the point pair, and n is the number of columns in the matrix.

9. The parametric construction method of a BIM model according to claim 4, characterized in that: The distance constraint between the point and the surface is described by the following optimization function: Among them, E p is the error function of the distance between the point and the surface, d p is the expected distance from the point to the surface, (x i ,y i , z i ) is the coordinate of the point, (x pi ,y pi , z pi ) are the coordinates of the plane reference point, n xi 、n yi 、n zi are the components of the plane normal vector.

10. A parametric construction method of a BIM model according to claim 4, characterized in that: The angle constraint between the lines is defined by the following optimization function: Among them, E line-angle is the line-to-line angle error function, cosθ i is the cosine of the desired angle, and are the direction vectors of the line, and is the magnitude of the direction vector.

Images