Construction whole-process simulation method for green fabricated comprehensive pipe gallery construction

Abstract

The application relates to the technical field of model lightweight, in particular to a construction whole-process simulation method for green assembly type comprehensive pipe gallery construction, which comprises the following steps: dividing all components in a pipe gallery model into multiple category clusters; obtaining center components of the category clusters; obtaining vertex importance indexes of all vertices according to the density and size of triangular faces at the vertices; obtaining folding delay degrees of all edges according to the average level of the vertex importance indexes of two vertices of the edges, the triangular face included angle of the edges and the edge degree, and then obtaining folding edges in the center components of the category clusters, and then folding the folding edges of the center components; obtaining simplification rates of the center components of the category clusters according to the ratio of the number of triangular faces of the center components of the category clusters before and after folding, and then performing lightweight processing on all components in the category clusters. The simplification rates of the components in the category clusters are adaptively calculated, and the model simplification effect is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of model lightweight, in particular to a construction whole-process simulation method for green assembly type comprehensive pipe gallery construction. BACKGROUND

[0002] With the acceleration of urbanization, underground comprehensive pipe gallery as an important part of modern city infrastructure, its construction demand is growing. Green assembly type comprehensive pipe gallery construction process is mainly to use a variety of construction equipment to splice multiple pipe gallery segments into a whole underground pipe gallery. Because any construction equipment or pipe gallery segment problem in the construction process will affect the construction effect and efficiency of comprehensive pipe gallery, therefore, it is necessary to simulate and construct multiple construction equipment and pipe gallery segments through three-dimensional model simulation technology, and to carry out whole-process experimental simulation of construction through simulation model, so as to achieve the purpose of identifying potential risks in advance, improving construction efficiency and collaborative management level.

[0003] Three-dimensional geometric data is stored in the form of geometric entities in BIM model, an entity is composed of multiple faces, and a face is composed of several triangular facets. The more detailed the model is, the more triangular facets it has. Because the construction process of comprehensive pipe gallery needs to model the complex structure of construction equipment and the number of models is large, the model size has a great influence on the efficiency of construction simulation, therefore, it is necessary to lightweight the model. The existing technology usually adopts the method of whole model or whole layer triangular net thinning to reduce the model size, however, the existing technology does not fully consider that there may be different types of geometric bodies in the same layer, and directly using the same simplification rate may lead to insufficient simplification degree or shape distortion, resulting in poor simplification effect and affecting the accuracy of simulation construction in subsequent construction process. SUMMARY

[0004] In order to solve the above technical problems, the present application provides a construction whole-process simulation method for green assembly type comprehensive pipe gallery construction to solve the existing problems.

[0005] The construction whole-process simulation method for green assembly type comprehensive pipe gallery construction of the present application adopts the following technical scheme:

[0006] One embodiment of the present application provides a construction whole-process simulation method for green assembly type comprehensive pipe gallery construction, which comprises the following steps:

[0007] Obtaining the number of triangular faces and geometric properties of each component in the pipe gallery model;

[0008] According to the geometric properties of each component, all components are divided into multiple size clusters; according to the volume and the number of triangular faces of each component in each size cluster, all components in each size cluster are divided into multiple category clusters; the component corresponding to the center element of each category cluster is recorded as the center component of each category cluster; the fitting plane corresponding to each vertex is obtained according to each vertex and all the remaining vertices on the triangular edge corresponding to each vertex; the vertex importance index of each vertex is obtained according to the distance between each vertex and its fitting plane, the discrete degree and the average level of the area of all triangular faces corresponding to each vertex;

[0009] The maximum angle of each edge is obtained according to the maximum value of the included angle between the normal vectors of all adjacent triangular faces corresponding to each edge; the folding delay of each edge in the center component of each category cluster is obtained according to the average level of the vertex importance index of the two vertices of each edge in the center component of each category cluster, the maximum angle of each edge, and the distance between the midpoint of each edge and the center point of the component where each edge is located; the folding edge in the center component of each category cluster is obtained, and the folding edge of each center component is folded; the simplification rate of the center component of each category cluster is obtained according to the ratio of the number of triangular faces of the center component of each category cluster after folding to the number of triangular faces of the center component of each category cluster before folding, and all components in each category cluster are subjected to lightweight processing.

[0010] Preferably, the specific process of dividing all components into multiple size clusters according to the geometric properties of each component is: constructing the geometric vector [length, width, height] of each component according to the length-width-height parameters in the geometric properties of each component, and clustering the geometric vectors of all components as the input of the clustering algorithm, and outputting multiple clustering clusters, which are recorded as size clusters.

[0011] Preferably, the specific process of dividing all components in each size cluster into multiple category clusters is: obtaining the volume parameter of each component; constructing the parameter vector [number of triangular faces, volume] of each component; clustering the parameter vectors of all components in each size cluster as the input of the clustering algorithm, and outputting multiple clustering clusters, which are recorded as category clusters.

[0012] Preferably, the specific process of obtaining the fitting plane corresponding to each vertex is: recording all the remaining vertices on each triangular edge corresponding to each vertex as vertices collinear with each vertex; taking the three-dimensional coordinates of each vertex and the three-dimensional coordinates of all vertices collinear with each vertex as the input of the three-dimensional plane fitting algorithm to obtain the three-dimensional fitting plane corresponding to each vertex.

[0013] Preferably, the calculation formula of the vertex importance index of each vertex is: ; in the formula, is the vertex importance index of the u-th vertex, is the first product of the u-th vertex, is the perpendicular distance between the u-th vertex and its corresponding fitting plane, is a preset constant; wherein the first product of the u-th vertex refers to the product of the variance and the mean of the areas of all the triangular faces corresponding to the u-th vertex.

[0014] Preferably, the process of obtaining the maximum included angle of each edge is as follows: when the number of triangular faces corresponding to each edge is greater than or equal to two, the normal vectors of each triangular face corresponding to each edge are obtained, then the normal vector included angles between each adjacent triangular face of each edge are calculated in turn, and the maximum value of all the normal vector included angles is recorded as the maximum included angle of each edge; when an edge has only one triangular face, the maximum included angle of the edge is set to be equal to 180°.

[0015] Preferably, the calculation formula of the folding delay degree of each edge in the center component of each category cluster is as follows: ; in the formula, is the folding delay degree of the v-th edge in the center component of the i-th category cluster, is the mean of the vertex importance indexes of the two vertices of the v-th edge in the center component of the i-th category cluster; is the center distance of the v-th edge in the center component of the i-th category cluster; is the maximum included angle of the v-th edge in the center component of the i-th category cluster; wherein the process of obtaining the center distance of the v-th edge is as follows: the mean of the coordinates of the two vertices of the v-th edge is recorded as the center coordinate of the v-th edge, and the Euclidean distance between the center coordinate of the v-th edge and the center coordinate of the component in which the v-th edge is located is recorded as the center distance of the v-th edge.

[0016] Preferably, the folding edge in the center component of each category cluster refers to the edge in the center component of each category cluster whose folding delay degree is less than a preset segmentation threshold.

[0017] Preferably, the calculation formula of the simplification rate of the center component of each category cluster is as follows: ; in the formula, is the simplification rate of the center component of the i-th category cluster; are respectively the total number of triangular faces after folding and the total number of triangular faces before folding of the center component of the i-th category cluster.

[0018] Preferably, the specific process of performing lightweight processing on all the components in each category cluster is as follows: the simplification rate of the center component of each category cluster is taken as the simplification rate of each component in each category cluster; all the components in each category cluster and the corresponding simplification rates are taken as the input of the edge folding algorithm, and lightweight processing is performed on all the components in each category cluster to obtain all the lightweight processed components in each category cluster.

[0019] The present application has at least the following beneficial effects:

[0020] The present application aims at the problem that the prior art does not fully consider the influence of the demand difference of different types of geometric bodies on the simplification rate, thereby causing poor simplification effect and affecting the construction simulation precision. By clustering according to the attribute characteristics of the components, different types of components can be more accurately distinguished, avoiding confusion of components with consistent size but different types, thereby improving the subsequent lightweight precision. By constructing a vertex importance index, the key degree of the vertex in the component geometry can be reflected, representing the importance of the area where the vertex is located to the model geometry feature retention. By constructing a folding delay degree, the importance of the edge in the component and its folding priority can be reflected, ensuring that the key feature area is not oversimplified. Then, the Otsu threshold method is combined to retain the key feature area, so that the component volume can be reduced while retaining the key features, thereby obtaining the most suitable simplification rate for each component, improving the simplification effect of each component in the simulation model, and thereby ensuring the precision of the construction simulation. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the drawings needed in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0022] Figure 1 The step flow chart of the construction whole-process simulation method for green assembly type comprehensive pipe gallery construction provided by the present application;

[0023] Figure 2 The structure diagram of the triangular face corresponding to any triangular edge provided by the present application; wherein 1, 2 and 3 are triangular faces, and v is a triangular edge. DETAILED DESCRIPTION

[0024] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the construction whole-process simulation method for green assembly type comprehensive pipe gallery construction according to the present application, its specific implementation, structure, features and effects are described in detail as follows by combining with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0026] The application provides a construction whole-process simulation method for green fabricated comprehensive pipe gallery construction.

[0027] The application provides a construction whole-process simulation method for green fabricated comprehensive pipe gallery construction. Figure 1 The method comprises the following steps:

[0028] Step one: obtaining the number of triangular faces and geometric properties of each component in the pipe gallery model.

[0029] The application takes a completed pipe gallery segment model as an example for lightweight processing. The geometric properties GeometryElement of each component in the pipe gallery segment model are traversed by the building model processing software Revit to obtain the geometric entity (Solid) of each component; then the geometric entity is decomposed into a triangular mesh form by face.Triangulate(), and the three-dimensional vertex coordinates of each triangular face are obtained. Finally, the number of triangular faces of each component is counted. The triangular mesh decomposition of the BIM model and the counting of the number of triangular faces are known technologies, and will not be described here.

[0030] Step two: dividing all components into multiple size clusters according to the geometric properties of each component; dividing all components in each size cluster into multiple category clusters according to the volume and number of triangular faces of each component in each size cluster; taking the component corresponding to the center element of each category cluster as the center component of each category cluster; obtaining the fitting plane corresponding to each vertex according to all the remaining vertices on the triangular edge of each vertex; and obtaining the vertex importance index of each vertex according to the distance between each vertex and its fitting plane, the discrete degree and average level of the area of all triangular faces corresponding to each vertex.

[0031] Because the construction and construction process of the green fabricated comprehensive pipe gallery is complex, and the construction equipment and building models involved are numerous, the model needs to be lightweight processed to achieve efficient simulation of the construction process. However, for large-scale BIM models, it is unacceptable to calculate the importance of each triangular face of each component and then process it one by one. Therefore, the mainstream method for actual lightweight processing of BIM models is to directly use a triangular mesh simplification algorithm and set a simplification parameter to achieve automatic batch efficient simplification. In order to further improve the precision of component lightweight processing and enhance the construction simulation effect of the comprehensive pipe gallery, it is necessary to classify the components according to their geometric shape characteristics, so as to select more suitable simplification parameters for different types of components, and maximize the model precision and simplification efficiency.

[0032] According to the length, width and height parameters in the geometric properties of each component, the geometric vectors [length, width, height] of each component are constructed, and the geometric vectors of all components are clustered as inputs of a clustering algorithm to preliminarily cluster and distinguish the components according to the geometric sizes. The output of the clustering algorithm is a plurality of clustering clusters, denoted as size clusters. The clustering algorithm is not limited to the K-means algorithm and the DPC algorithm. In this embodiment, the DPC algorithm is used for three-dimensional clustering, and the cross-validation method is used to obtain the cut-off distance of the DPC clustering algorithm.

[0033] It is considered that the clustered components may have consistent length, width and height size parameters but inconsistent types, such as rectangular components and circular components, and therefore further analysis of the size clusters is required.

[0034] If the geometric types of the components are different, even if the length, width and height size parameters are consistent, the volumes will also be different, and therefore the Solid.Volume attribute of the component can be further read to obtain the volume parameter of the component.

[0035] In addition, the number of triangular faces after decomposition of the component can also reflect the complexity of the surface of the component. The more features and the more complex the shape of the surface of the component, the more the number of triangular faces after decomposition, and therefore the number of triangular faces of the component can be combined to further distinguish the complexity of the component.

[0036] The number of triangular faces of all components is normalized to improve the accuracy of subsequent clustering and distinction. Similarly, the volume parameters of all components are normalized. According to the normalized number of triangular faces and volume parameters, the parameter vectors [number of triangular faces, volume] of each component are constructed. The normalization method is not limited to the maximum and minimum value normalization and the z-score normalization. In this embodiment, the maximum and minimum value normalization is used.

[0037] Taking any one size cluster as an example, the parameter vectors of all components in the size cluster are clustered as inputs of a clustering algorithm, and the output of the clustering algorithm is a plurality of clustering clusters, denoted as category clusters. In the same way, the components in all size clusters are clustered twice to divide each size cluster into a plurality of category clusters.

[0038] So far, the components have been preliminarily distinguished according to the length, width and height size parameters of the components, and then the components with consistent sizes have been further distinguished according to the attribute features of the components, so as to avoid confusing components with different types but consistent sizes and affecting the accuracy of subsequent component individual simplification.

[0039] Further, after the individualization according to the component features, the simplification degree of the components in each category cluster can be analyzed to select the most suitable simplification parameter for each category of components.

[0040] The center element of each category cluster is denoted as the center component of the category cluster. Taking the u-th vertex in the i-th category cluster as an example, the analysis is performed.

[0041] Since the density of triangular faces is usually high and the area is small in the key regions of the component, such as holes, edges, grooves, etc., the geometric details of the component are finely displayed, and the feature loss of the model is large when this part is simplified, so the simplification degree needs to be small. In the ordinary plane region, the density of triangular faces is usually low and the area is large, and the feature loss of the model is small when this part is simplified, so the simplification degree can be increased.

[0042] The area of each triangular face containing the u-th vertex is calculated, and the product of the dispersion degree and the mean value of all triangular face areas corresponding to the u-th vertex is denoted as the first product of the u-th vertex. The smaller the dispersion degree, the more consistent the area of the triangular faces near the u-th vertex, and the smaller the mean value, the smaller the area of the triangular faces near the u-th vertex; therefore, the smaller the first product, the greater the possibility that the u-th vertex is located at a local feature-rich position such as a hole edge or a groove, and the greater the importance of the u-th vertex, which cannot be simplified arbitrarily. The dispersion degree is not limited to variance, standard deviation, or coefficient of variation, and the variance is used in this embodiment.

[0043] Further, the remaining vertices on all triangular edges corresponding to the u-th vertex are denoted as vertices collinear with the u-th vertex; the three-dimensional coordinates of the u-th vertex and the three-dimensional coordinates of all vertices collinear with the u-th vertex are used as the input of a three-dimensional plane fitting algorithm to perform three-dimensional fitting of the plane. The three-dimensional plane fitting algorithm is not limited to the least squares method or RANSAC, and the least squares method is used in this embodiment.

[0044] As a preferred embodiment, the vertex importance index of each vertex is obtained according to the distance between each vertex and its fitting plane, the dispersion degree and the average level of the area of all triangular faces corresponding to each vertex, which is used to represent the importance of each vertex.

[0045] In this embodiment, the vertex importance index of the u-th vertex is denoted as , and the expression is: ; in the formula, is the vertex importance index of the u-th vertex, is the first product of the u-th vertex, is the perpendicular distance between the u-th vertex and its corresponding fitting plane, is a preset constant, and in order to avoid a denominator of 0, the value range is (0.001, 0.01), the value has little effect on the calculation and can be ignored, and in this embodiment 0.005 is taken, and the implementer can take the value.

[0046] The value is greater, the greater the possibility of the u-th vertex being in a critical feature region, and the greater the importance of the u-th vertex. The value is greater, the greater the possibility of the u-th vertex being in a critical feature region, and the greater the importance of the u-th vertex.

[0047] Step three: obtain the maximum angle of each edge according to the maximum value of the angle between the normal vectors of all adjacent triangular faces corresponding to the edge; obtain the folding delay of each edge in the center component of each category cluster according to the average level of the vertex importance index of the two vertices of each edge in the center component, the maximum angle of each edge, and the distance between the midpoint of each edge and the center point of the component in which the edge is located, and then obtain the folding edge in the center component of each category cluster, and then fold the folding edge of each center component; obtain the simplification rate of the center component of each category cluster according to the ratio of the number of triangular faces after folding to the number of triangular faces before folding of the center component of each category cluster, and then perform lightweight processing on all components in each category cluster.

[0048] Further, after calculating the importance of each vertex, the importance of each edge of the triangular face needs to be analyzed to determine whether it is suitable for being folded and whether the region is suitable for being simplified.

[0049] Taking the v-th edge in the center component of the i-th category cluster as an example for analysis.

[0050] In a triangular mesh, an edge usually corresponds to multiple triangular faces; when the normal vectors of two adjacent triangular faces are more parallel, i.e., the angle is smaller, it indicates that the region corresponding to the edge is smoother and less important; if the angle between the normal vectors is larger, it indicates that the edge is more likely to be a sharp corner or an edge line, and the possibility of causing distortion of the component after folding is greater.

[0051] Since the component is in three-dimensional form, it is possible that an edge belongs to multiple triangular faces at the same time, such as Figure 2As shown, it is a structural schematic diagram of the triangular face corresponding to any triangular edge. When the number of triangular faces corresponding to the vth edge is greater than or equal to two, the normal vector included angle between adjacent triangular faces is calculated: the normal vector of each triangular face corresponding to the vth edge is obtained by the normal vector calculation method, then the normal vector included angle between each adjacent triangular face is calculated in turn, and the maximum value of all normal vector included angles is recorded as the maximum included angle of the vth edge. The normal vector calculation method is not limited to the cross product method, the slope difference method, and the embodiment adopts the cross product method for calculation; the included angle between the normal vectors is a known technology, which will not be described here. The maximum included angle can reflect whether the vth edge is a clear corner or an edge, and the greater the value, the greater the importance of the vth edge.

[0052] It should be noted that: if the vth edge has only one triangular face, the edge is a boundary edge, which will cause serious distortion of the model boundary after folding, and is very important, so the maximum included angle of the edge is equal to 180°.

[0053] At the same time, since the edges close to the center of the model often have less influence on the overall shape, and the edges located in the edge and protruding part of the model often have greater influence on the appearance and function after being removed, the importance of each edge can be further analyzed by calculating the distance of each edge relative to the center position of the component.

[0054] The average of the coordinates of the two vertices of the vth edge is recorded as the center coordinate of the vth edge, and the Euclidean distance between the center coordinate of the vth edge and the center coordinate of the component where the vth edge is located is recorded as the center distance of the vth edge. The center distance can reflect whether the vth edge is located on the contour edge of the component, and the greater the value, the greater the possibility that the vth edge is located on the contour edge of the component, the greater the influence of the vth edge on the contour of the component after folding, and the greater the importance of the vth edge, which cannot be folded arbitrarily.

[0055] As a preferred embodiment, the folding delay degree of each edge in the center component of each category cluster is obtained according to the average level of the vertex importance index of the two vertices of each edge in the center component of each category cluster, the maximum included angle of each edge, and the distance between the midpoint of each edge and the center point of the component where the edge is located, which is used to represent the importance of each edge in the center component of each category cluster.

[0056] In this embodiment, the folding delay degree of the vth edge in the center component of the i th category cluster is recorded as , and its expression is: ; in the formula, is the folding delay degree of the vth edge in the center component of the i th category cluster, is the average of the vertex importance index of the two vertices of the vth edge in the center component of the i th category cluster; is the center distance of the vth edge in the center component of the i th category cluster. is the maximum included angle of the vth edge in the center component of the ith category cluster.

[0057] The folding postponement degree can reflect the importance of the u th edge in the center component of the ith category cluster, the greater the value, the greater the importance, and the more it should be postponed or preserved as much as possible to ensure the key features of the center component of the ith category cluster.

[0058] In the same way, the folding postponement degrees of all edges in the center component of the ith category cluster are calculated, and then all the folding postponement degrees are taken as the input of the Otsu threshold method, and the output of the Otsu threshold method is a segmentation threshold, which is recorded as a preset segmentation threshold. All edges with a folding postponement degree less than the preset segmentation threshold are recorded as folding edges in the center component of the ith category cluster. In the center component of the ith category cluster, all the folding edges are folded by the edge folding algorithm, that is, the two endpoints are merged into a new point and the adjacent triangular faces are reconstructed, so as to realize the lightweight processing of the component. The edge folding algorithm is a known technology and will not be described here.

[0059] Further, the simplification rate of the center component of the ith category cluster is calculated, and the calculation formula is: ; in the formula, is the simplification rate of the center component of the ith category cluster; respectively, the total number of triangular faces after folding and the total number of triangular faces before folding of the center component of the ith category cluster.

[0060] Then, the simplification rate of the center component of the ith category cluster is taken as the simplification rate of each component in the ith category cluster; each component in the ith category cluster and the corresponding simplification rate are taken as the input of the edge folding algorithm, and all the components in the ith category cluster are subjected to lightweight processing to obtain all the lightweight processed components in the ith category cluster.

[0061] In the same way, the simplification rate parameters of each category cluster are calculated, and the components in each category cluster are subjected to lightweight processing by the edge folding algorithm to obtain all the lightweight processed components in all the category clusters. Through the differential lightweight processing of the model by partition, the data volume of the model can be reduced while ensuring the geometric accuracy of the key features of the components, so as to reduce the calculation pressure and resource consumption required in the simulation and simulation process of the construction of the green assembly comprehensive pipe gallery, improve the construction simulation speed and response ability, and help to realize large-scale, multi-device, and multi-process collaborative simulation.

[0062] The whole-process simulation of the construction and building of the green assembly type comprehensive pipe gallery is as follows: firstly, a modeling personnel uses a modeling software such as Revit to model various construction equipment and buildings in three dimensions according to construction requirements; after modeling, the model is processed by the lightweight method described in the application to improve the efficiency of subsequent whole-process simulation of construction; finally, combined with the construction process, the equipment layout, component hoisting, pipeline installation, assembly connection and other multi-link whole-process construction dynamic simulation are carried out through a construction simulation platform such as Bentley Synchro according to the equipment model and the building model, and the construction data during the whole-process simulation of construction are recorded and used as reference data during the actual construction, so that the actual construction process is safer, more efficient and stable.

[0063] It should be noted that the above sequence of the embodiments of the application is only for description, and does not represent the advantages and disadvantages of the embodiments. Moreover, the above describes specific embodiments of the present specification. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

[0064] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other. Each embodiment focuses on the difference from other embodiments.

[0065] The above-described embodiments are only used to illustrate the technical solutions of the present application, but not limit them; the technical solutions described in the above embodiments are modified, or some technical features are replaced, without changing the essence of the corresponding technical solutions out of the scope of the technical solutions of the embodiments of the present application, which should be included in the protection scope of the present application.

Claims

1. A construction whole-process simulation method for green fabricated comprehensive pipe gallery construction, characterized in that, The method comprises the following steps: Obtaining the number of triangular faces and geometric attributes of each component in the pipe gallery model; According to the geometric properties of each component, all components are divided into multiple size clusters, the acquisition process of which is: constructing the geometric vector [length, width, height] of each component according to the length-width-height parameters in the geometric properties of each component, and clustering the geometric vectors of all components as the input of the clustering algorithm, and outputting multiple clustering clusters, which are recorded as size clusters; according to the volume and the number of triangular faces of each component in each size cluster, all components in each size cluster are divided into multiple category clusters, the acquisition process of which is: obtaining the volume parameter of each component; constructing the parameter vector [number of triangular faces, volume] of each component; clustering the parameter vectors of all components in each size cluster as the input of the clustering algorithm, and outputting multiple clustering clusters, which are recorded as category clusters; the component corresponding to the center element of each category cluster is recorded as the center component of each category cluster; according to the vertices of the triangular faces of the center component and all the remaining vertices on the corresponding triangular edges, the fitting plane corresponding to each vertex is obtained; according to the distance between each vertex and its fitting plane, the discrete degree and the average level of the area of all triangular faces corresponding to each vertex, the vertex importance index of each vertex is obtained, and the calculation formula of the vertex importance index of each vertex is: ; wherein, is the vertex importance index of the u-th vertex, is the first product of the u-th vertex, is the vertical distance between the u-th vertex and its corresponding fitting plane, is a preset constant; wherein the first product of the u-th vertex refers to the product of the variance and the mean of the area of all triangular faces corresponding to the u-th vertex; The maximum angle of each edge is obtained according to the maximum value of the angle between the normal vectors of all adjacent triangular surfaces corresponding to each edge of the center component; the folding delay of each edge in the center component of each category cluster is obtained according to the average level of the vertex importance indexes of the two vertices of each edge, the maximum angle of each edge, and the distance between the midpoint of each edge and the center point of the component in which each edge is located, and the calculation formula of the folding delay of each edge in the center component of each category cluster is: ; wherein, is the folding delay of the vth edge in the center component of the ith category cluster, is the average value of the vertex importance indexes of the two vertices of the vth edge in the center component of the ith category cluster; is the center distance of the vth edge in the center component of the ith category cluster; is the maximum angle of the vth edge in the center component of the ith category cluster; wherein, the center distance of the vth edge is obtained by taking the average of the coordinates of the two vertices of the vth edge as the center coordinates of the vth edge, and taking the Euclidean distance between the center coordinates of the vth edge and the center coordinates of the component in which the vth edge is located as the center distance of the vth edge; then the folding edges in the center components of each category cluster are obtained, and the folding edges of each center component are folded; the simplification rate of the center component of each category cluster is obtained according to the ratio of the number of triangular surfaces of the center component of each category cluster before folding to the number of triangular surfaces of the center component of each category cluster after folding, and the simplification rate of the center component of each category cluster is taken as the simplification rate of each component in each category cluster; all components in each category cluster and the corresponding simplification rates are taken as the input of the edge folding algorithm, all components in each category cluster are subjected to lightweight processing, and all components in each category cluster after lightweight processing are obtained.

2. The construction whole-process simulation method for green-oriented fabricated utility tunnel building according to claim 1, characterized in that, The specific process of obtaining the fitting plane corresponding to each vertex is as follows: recording all the remaining vertices on the triangular edges corresponding to each vertex as the vertices collinear with each vertex; taking the three-dimensional coordinates of each vertex and all the vertices collinear with each vertex as the input of the three-dimensional plane fitting algorithm to obtain the three-dimensional fitting plane corresponding to each vertex.

3. The construction whole-process simulation method for green-oriented fabricated utility tunnel building according to claim 1, characterized in that, The process of obtaining the maximum included angle of each edge is as follows: when the number of triangular faces corresponding to each edge is greater than or equal to two, obtaining the normal vectors of the triangular faces corresponding to each edge, then sequentially calculating the normal vector included angles between the adjacent triangular faces of each edge, and recording the maximum value in all the normal vector included angles as the maximum included angle of each edge; when an edge has only one triangular face, the maximum included angle of the edge is equal to 180°.

4. The construction whole-process simulation method for green-oriented fabricated utility tunnel building according to claim 1, characterized in that, The folded edge in the central component of each category cluster refers to the edge in the central component of each category cluster whose folding delay is less than a preset segmentation threshold.

5. The construction whole-process simulation method for green-oriented fabricated utility tunnel construction according to claim 1, characterized in that, The calculation formula of the simplification rate of the center member of each category cluster is: ; in the formula, is the simplification rate of the center member of the i-th category cluster; is the total number of triangular faces after folding, and is the total number of triangular faces before folding, respectively, of the center member of the i-th category cluster.

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