CN115130256A - Three-dimensional pipeline optimization method based on hierarchical bounding box collision detection - Google Patents
Three-dimensional pipeline optimization method based on hierarchical bounding box collision detection Download PDFInfo
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Abstract
The invention provides a three-dimensional pipeline optimization method based on hierarchical bounding box collision detection, which comprises the following steps of: s1: building an AABB bounding box to simulate a real pipeline building scene; s2: designing a collision detection algorithm based on the level bounding boxes, and completing preliminary detection and gradual refinement by traversing each level bounding box to obtain a pipeline collision detection report; s3: determining pipelines needing to be adjusted according to the pipeline collision detection report, and optimizing a pipeline design scheme based on a BIM (building information modeling) of a secondary development platform to obtain optimal space distribution and pipeline arrangement; and S4, performing verification evaluation on the optimized three-dimensional pipeline scheme. The effect is as follows: the method can be applied to newly built, reconstructed and reconstructed medium and large buildings, improves the pipeline construction efficiency of building engineering, reduces the pipeline resource cost, establishes a virtual three-dimensional construction building model by combining a software secondary development platform, and realizes the optimization of space distribution and comprehensive pipeline arrangement through collision detection knowledge.
Description
Technical Field
The invention relates to a static collision detection technology for a complex scene of a building, in particular to a three-dimensional pipeline optimization method based on level bounding box collision detection.
Background
With the proposal of smart cities and digital building concepts, the digital building is widely concerned by the society, and the understanding of digital buildings in various big cities is not a traditional building mode based on drawing design any more, but is supported by core technologies such as internet of things and cloud computing, and comprises the construction of an application layer, a network layer and a perception layer.
At present, the comprehensive performance, complexity and versatility of buildings and pipelines are greatly improved compared with the prior art, which brings about the surge of adaptation layers required by the buildings, and not only reflects the requirements of the shapes of the buildings changing into thousands, but also breaks through the building structures, the high standards of indoor environments and the increasingly advanced and abundant accessory equipment. This makes building design a high standard of challenge at its own level, and the matching pipeline design must be increased. Meanwhile, due to the improvement of the complexity of the building, the industrial division of various industries is required to be more clear. And the requirement and difficulty of comprehensive coordination of all specialties are increased. Currently, the construction industry in China rarely attaches importance to economic factors in scheme design. The general attention of designers is in functional and formal expression, so that the phenomenon that the economic condition is exceeded and the difference between the budget estimate and the final cost is too large occurs in actual engineering. The more serious reality is that the "growth rate" which is not necessary to be hasty is pursued, and the "air force scale" which is not necessary to be laid blindly is achieved. The tremendous building waste is growing at a tremendous cost.
The traditional pipeline design based on drawings often causes a row of problems in actual construction, which not only causes resource waste, but also greatly increases construction time. The aim of the comprehensive pipeline is not to be only to be plugged and not to collide, but also to be a low-level aim of pipeline design, and the pipeline is used as a part of a building and aims to achieve the overall space effect, save the manufacturing cost, efficiently use, meet the human body demand, save the environmental protection and other comprehensive and overall benefits.
Disclosure of Invention
In order to meet the requirements, the invention provides a three-dimensional pipeline optimization method based on hierarchical bounding box collision detection, which can be fully applied to actual building engineering through pipeline and building modeling of a secondary development platform, greatly improves the construction efficiency, saves the building cost and reduces the risk of rework.
In order to achieve the purpose, the invention adopts the following specific technical scheme:
the three-dimensional pipeline optimization method based on the hierarchical bounding box collision detection is characterized by comprising the following steps of:
s1: building an AABB bounding box to simulate a real pipeline building scene;
s2: designing a collision detection algorithm based on the hierarchical bounding boxes, and completing preliminary detection and stepwise refinement by traversing each hierarchical bounding box to obtain a pipeline collision detection report;
s3: determining pipelines needing to be adjusted according to the pipeline collision detection report, and optimizing a pipeline design scheme based on a BIM (building information modeling) of a secondary development platform to obtain optimal space distribution and pipeline arrangement;
and S4, carrying out verification evaluation on the optimized three-dimensional pipeline scheme.
Optionally, step S2 includes a preliminary detection stage and a detailed detection stage, where the detailed detection stage is further divided into a gradual refinement step and an intersection test step;
in the preliminary detection stage, an object which is not collided in the virtual system is quickly eliminated by using a collision detection algorithm, and an object which is likely to be collided is found out;
the gradual refinement link is used for further reducing the area where collision is likely to occur;
and the intersection testing link is used for judging whether collision really occurs.
Optionally, the AABB bounding box model employs an axial bounding box R, and is defined as:
R＝{(x，y，z)|X min ≤x≤X max ，Y min ≤y≤Y max ，Z min ≤z≤Z max }
wherein: x min Represents the minimum of the projection of the pipeline on the x-axis; x max Represents the maximum value of the projection of the pipeline on the x-axis; y is min Represents the minimum of the projection of the pipeline on the y-axis; y is max Represents the maximum value of the projection of the pipeline on the y-axis; z min Represents the minimum of the projection of the pipeline on the z-axis; z max Representing the maximum projected value of the pipeline on the z-axis.
Optionally, after the axial bounding box performs preliminary filtering on the comprehensive pipeline, performing shortest distance collision detection on the pipeline which is likely to collide, and calculating the shortest distance between space-limited line segments, where the specific process is as follows:
let P be a point on the straight line AB, the coordinate of point A being (x) 1 ，y 1 ，z 1 ) And the coordinate of the point B is (x) 2 ，y 2 ，z 2 ) Then the P point coordinates (X, Y, Z) can be expressed as:
when the parameter s is more than or equal to 0 and less than or equal to 1, P is a point on the line segment AB, when s is less than 1, P is a point on the extended line of BA, and when s is more than 1, P is a point on the extended line of AB;
similarly, let Q be a point on the straight line CD, C (x) 3 ，y 3 ，z 3 )，D(x 4 ，y 4 ，z 4 ) The coordinate (U, V, W) of the point Q can be represented by coordinates of 2 points C, D and a parameter t;
the square of the distance between these 2 points for PQ is then:
f(S，t)＝PQ 2 ＝[(x 1 -x 3 )+S(x 2 -x 1 )-t(x 4 -x 3 )] 2 +[(y 1 -y 3 )+s(y 2 -y 1 )-t(y 4 -y 3 )] 2
+[(z 1 -z 3 )+s(z 2 -z 1 )-t(z 4 -z 3 )] 2
if s is more than or equal to 0 and less than or equal to 1 and t is more than or equal to 0 and less than or equal to 1, the point P is on the line segment AB, the point Q is on the line segment CD, and the length of PQ is the shortest distance between AB and CD;
if the parameters obtained by the above formula do not satisfy s is not less than 0 and not more than 1 and y is not less than 0 and not more than 1, the point P cannot be found in the line segment AB and the point Q cannot be found in the line segment CD, so that the length of PQ is the shortest distance between the AB and the CD; in this case, the shortest distance from point a to line segment CD, the shortest distance from point B to line segment CD, the shortest distance from point C to line segment AB, and the shortest distance from point D to line segment AB are obtained, and then 4 distances are compared, where the smallest distance is the shortest distance between AB and CD.
Optionally, in step S4, a simulation experiment is performed by using a secondary software platform, the stability of the optimized model is detected according to the average absolute error and the mean square error, and the detection accuracy is evaluated by using the average detection rate as an evaluation index.
The invention has the technical effects that:
the invention mainly aims at the problems of reworking and resource waste caused by unreasonable design of geographic spatial positions and pipeline types in smart cities and digital building design, and provides a three-dimensional pipeline optimization method based on collision detection of a hierarchical bounding box, which can be applied to newly built, reconstructed and reconstructed medium and large buildings, improves the pipeline construction efficiency of building engineering and reduces the pipeline resource cost. The research combines a software secondary development platform to establish a virtual three-dimensional construction building model and realize the optimization of space distribution and comprehensive pipeline arrangement through collision detection knowledge.
Drawings
FIG. 1 is a general framework for collision detection in an embodiment of the invention;
FIG. 2 is a schematic diagram of an axial bounding box in an embodiment of the present invention;
FIG. 3 is a schematic diagram of the intersection of triangles in three-dimensional space;
FIG. 4 is a flow chart of a collision detection algorithm;
FIG. 5 is a graph of pipeline alignment before and after;
FIG. 6 is a flow chart of a pipeline optimization algorithm.
Detailed Description
The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, which are given solely for the purpose of illustration and are not to be construed as limitations of the invention, including the drawings which are incorporated herein by reference and for illustration only and are not to be construed as limitations of the invention, since many variations thereof are possible without departing from the spirit and scope of the invention.
As shown in fig. 1 to 6, the present embodiment provides a three-dimensional pipeline optimization method based on hierarchical bounding box collision detection, including the following steps:
s1: building an AABB bounding box to simulate a real pipeline building scene;
s2: designing a collision detection algorithm based on the hierarchical bounding boxes, and completing preliminary detection and stepwise refinement by traversing each hierarchical bounding box to obtain a pipeline collision detection report;
s3: determining pipelines needing to be adjusted according to the pipeline collision detection report, and optimizing a pipeline design scheme based on a BIM (building information modeling) of a secondary development platform to obtain optimal space distribution and pipeline arrangement;
and S4, performing verification evaluation on the optimized three-dimensional pipeline scheme.
For better detection of collisions and design of pipeline tuning optimization algorithms, collision detection is divided into two steps, the first step being preliminary detection and the second step being detailed detection. The detailed testing further includes an intersection test. In the initial detection stage, the collision detection algorithm can quickly eliminate objects which do not collide in the virtual system, simplify the collision detection problem, find out the objects which may collide for further judgment. In the detailed detection stage, the objects which are likely to collide and rotate are refined step by step, the regions which are likely to collide are reduced, an intersection test is performed to judge whether collision occurs or not, and the frame is shown in fig. 1.
In specific implementation, given the axial bounding box AABB of the three-dimensional pipeline drawing, the bounding box is defined as a minimum hexahedron, and the AABB and AABB bounding boxes are shown in fig. 2:
R＝{(x，y，z)|X min ≤x≤X max ，Y min ≤y≤Y max ，Z min ≤z≤Z max }
wherein: x min Represents the minimum of the projection of the pipeline on the x-axis; x max Represents the maximum value of the projection of the pipeline on the x-axis; y is min Represents the minimum of the projection of the pipeline on the y-axis; y is max Represents the maximum value of the projection of the pipeline on the y-axis; z min Represents the minimum of the pipeline's projection on the z-axis; z is a linear or branched member max Representing the maximum projected value of the pipeline on the z-axis.
And after the comprehensive pipelines are preliminarily filtered by the axial bounding box algorithm, carrying out shortest distance collision detection on the pipelines which are likely to collide, and calculating the shortest distance between the space limited line segments. And then, carrying out accurate collision detection on the pipeline model through three-dimensional intersection test, and selecting geometric elements of the object for calculation. And finally, designing a pipeline adjustment optimization algorithm according to the collision detection report, and performing modeling verification on a secondary development platform.
After the axial bounding box carries out preliminary filtering to the comprehensive pipeline, carry out shortest distance collision detection to the pipeline that probably collides, calculate the shortest distance between the finite line segment in space, the concrete process is as follows:
let P be a point on the straight line AB, the coordinate of point A being (x) 1 ,y 1 ,z 1 ) And the coordinate of the point B is (x) 2 ,y 2 ,z 2 ) The P point coordinates (X, Y, Z) can then be expressed as:
when the parameter s is more than or equal to 0 and less than or equal to 1, P is a point on the line segment AB, when s is less than 1, P is a point on the extended line of BA, and when s is more than 1, P is a point on the extended line of AB;
similarly, let Q be a point on the straight line CD, C (x) 3 ，y 3 ，z 3 )，D(x 4 ，y 4 ，z 4 ) The coordinates (U, V, W) of the point Q can be represented by coordinates of two points C, D and a parameter t;
the square of the distance between these 2 points for PQ is then:
f(S，t)＝PQ 2 ＝[(x 1 -x 3 ))+S(x 2 -x 1 )-t(x 4 -x 3 )] 2 +[(y 1 -y 3 )+s(y 2 -y 1 )-t(y 4 -y 3 )] 2 +[(z 1 -z 3 )+s(z 2 -z 1 )-t(z 4 -z 3 )] 2
if s is more than or equal to 0 and less than or equal to 1 and t is more than or equal to 0 and less than or equal to 1, the point P is on the line segment AB, the point Q is on the line segment CD, and the length of PQ is the shortest distance between AB and CD;
if the parameter solved by the above formula does not satisfy s is more than or equal to 0 and less than or equal to 1, and t is more than or equal to 0 and less than or equal to 1, the point P cannot be found in the line segment AB, and the point Q cannot be found in the line segment CD, so that the length of PQ is the shortest distance between AB and CD; in this case, the shortest distance from point a to line segment CD, the shortest distance from point B to line segment CD, the shortest distance from point C to line segment AB, and the shortest distance from point D to line segment AB are obtained, and then 4 distances are compared, where the smallest distance is the shortest distance between AB and CD.
For the three-dimensional intersection test, the three-dimensional pipeline stereogram to be adjusted is subdivided into triangles for intersection test, and the subdivided triangles ABC and triangle PQR are shown in FIG. 3:
for a given point A, B, C, the determinant function det (a, B, C) of the square matrix is used to determine A, B, C whether the triangle can be constructed and whether the triangle ADC is clockwise or counterclockwise can be determined.
If det (A, B, C) > 0, A, B, C is in counterclockwise order;
if det (A, B, C) < 0, A, B, C is in clockwise order;
if det (a, B, C) ═ 0, A, B, C are collinear and cannot form a triangle.
det (A, B, C) is calculated as follows:
let the supporting plane of the triangle ABC be Ψ, the plane Ψ divides the entire virtual space into two parts, denoted as Ψ L And Ψ R 。Ψ L And Ψ R Satisfies the following formula:
the triangle is a closed figure, and when three vertexes of the triangle PQR are positioned at the same side of the support plane Ψ, the triangle PQR does not intersect Ψ, and the triangle is
Or
Triangle PQR does not intersect triangle ABC, since triangle ABC is located in support plane Ψ. Further judgment is needed when the three vertices of the triangle PQR are located at both sides of the support plane. Let the support plane be psi, with the normal of psi
And order
The algorithm for judging whether the triangle ABC and the triangle PQR intersect is as follows:
step 1: calculating values of sp, sq and sr, if the three values are positive values or negative values, judging P, Q, R to be positioned on the same side of the support plane psi, and ending the algorithm when the triangle ABC does not intersect with the triangle PQR; otherwise Step2 is executed.
Step 2: if sp, sq and sr are all 0, the triangle ABC and the triangle PQR are coplanar, whether the two triangles are intersected or not is judged by using an intersection test in a two-dimensional plane, and the algorithm is ended; otherwise, Step3 is executed.
Step 3: if one of sp, sq, and sr is 0 and the other two are both positive or negative, then one vertex of triangle PQR lies on support plane Ψ and triangle PQR does not intersect or intersect triangle ABC. Therefore, the intersection test of the two-dimensional plane point and the triangle can be used for judging whether the point is in the triangle ABC or not, and the algorithm is ended; otherwise, Step4 is executed.
Step 4: if two of sp, sq and sr are 0 and the other is not 0, let sp and sq be 0, then
On support plane Ψ, and triangle PQR intersects triangle ABC either
Therefore, the intersection test of the line segment and the triangle in the two-dimensional plane can be used for judging whether the two triangles are intersected, and the algorithm is ended; otherwise, Step5 is executed.
Step5: and judging that the triangle PQR intersects with the support plane, and calculating the intersection point of the triangle PQR and psi. If P is opposite to Q, R, then
Intersecting Ψ, and setting the intersection points to F and G, respectively, the intersection point F and the intersection point G can be found using the following equation.
t f ＝sp/(sp-sq) t g ＝sp/(sp-sr)
Step 6: and judging whether the intersection line intersects with the triangle ABC. Because the intersection line and the triangle ABC are located on the same plane, the intersection test of the line segment and the triangle in the two-dimensional plane can be used to judge that the two triangles are intersected, the algorithm is ended, and the specific detection flow is shown in FIG. 4.
Aiming at the adjustment and optimization of the pipeline, the pipeline is adjusted on a secondary development software platform through collision detection of a virtual three-dimensional pipeline diagram according to a pipeline avoiding principle (a small pipe enables a large pipe, a pressure pipeline avoids a no-pressure pipeline, a cold water pipeline avoids a hot water pipeline and the like) so as to meet the engineering design specification. The pipeline adjustment optimization algorithm is as follows:
step 1: the pipeline to be adjusted is determined from the above collision detection report, and the end point coordinates A, D, M, N of the 2 pipelines to be adjusted are obtained, as shown in fig. 5.
Step 2: calculating the space equation of the central line from the coordinates of the end points of the pipeline to obtain the foot O (O) of the intersection point of the central line or the common vertical line on the central line of the adjusting pipeline x ,O y ,O z ) For the convenience of maintenance, a certain maintenance space l is reserved during the pipeline design 0 Then, the following relationship exists between the adjustment length and the adjustment height:
in the formula:
l-adjusting the length of the pipeline;
h, adjusting the height of the pipeline;
d 1 、d 2 diameter of pipe to be adjusted (and d) 1 ＞d 2 )。
Step 3: extracting the related belief (type, diameter, material, etc.) of the pipeline to be adjusted, parameterizing the pipeline engineering design principle, comparing the engineering design principle with the extracted relevant information of the pipeline, determining the pipeline to be adjusted, and assuming P 2 Is the pipeline to be adjusted.
Step 4: let the coordinate of point A be (A) x ,A y ,A z ) The coordinate of the point D is (D) x ,D y ,D z ) B (B) if L BO | ═ CO | ═ L/2, | BB '| ═ CC' | ═ H, BB '| AD, CC' | AD are satisfied, then B (B) x ,B y ,B z )， C(B x ,B y ,B z ) Can be expressed as:
step5 suppose pipeline P 2 Is β from the plane XOY and is γ from the plane Y0Z, the coordinate of B' can be expressed as:
B′ x ＝B x +Hsin(β)sin(γ)
B′ y ＝B y +Hsin(β)cos(γ)
B′ z ＝B z +Hcos(β)
similarly, the coordinate of C 'can be obtained as (C' x ,C′ y ,C′ z )。
Step 6: according to the coordinates of the 6 points A, B, B ', C' and C, D, 5 pipelines are drawn in sequence, and the original pipeline is deleted, and the specific process can be seen in FIG. 5.
For simulation experiments and algorithm performance analysis, simulation experiments are carried out on a secondary software platform, the stability of a detection model is detected according to the average absolute error and the mean square error, and the detection precision is evaluated by using the average detection rate as an evaluation index. The Mean Absolute Error (MAE) characterizes the accuracy of the algorithm's estimation, and the formula is as follows:
in the formula:
m-detecting the number of collisions;
Z i -testing the actual collision distance interval for the ith time;
Mean Square Error (MSE) characterizes the stability of the algorithm estimate, and the formula is as follows:
in the formula:
m-detecting the number of collisions;
Z i testing the actual collision distance interval at the ith time;
In summary, the invention provides a three-dimensional pipeline optimization method based on hierarchical bounding boxes, which is mainly used for solving the problems of reworking and resource waste caused by unreasonable design of geographical spatial positions and pipeline types in smart cities and digital building designs, can be applied to newly built, reconstructed and reconstructed medium and large buildings, improves the pipeline construction efficiency of building engineering and reduces the pipeline resource cost. The research is combined with a software secondary development platform to establish a virtual three-dimensional construction building model and realize optimization of space distribution and comprehensive pipeline arrangement through collision detection knowledge.
Finally, it should be noted that the above-mentioned embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above-mentioned embodiments, and any other changes, modifications, substitutions, combinations and simplifications which do not depart from the spirit and principle of the present invention should be regarded as equivalent substitutions and are included in the protection scope of the present invention.
Claims (5)
1. A three-dimensional pipeline optimization method based on hierarchical bounding box collision detection is characterized by comprising the following steps of:
s1: building an AABB bounding box to simulate a real pipeline building scene;
s2: designing a collision detection algorithm based on the hierarchical bounding boxes, and completing preliminary detection and stepwise refinement by traversing each hierarchical bounding box to obtain a pipeline collision detection report;
s3: determining pipelines needing to be adjusted according to the pipeline collision detection report, and optimizing a pipeline design scheme based on a BIM (building information modeling) of a secondary development platform to obtain optimal space distribution and pipeline arrangement;
and S4, performing verification evaluation on the optimized three-dimensional pipeline scheme.
2. The three-dimensional pipeline optimization method based on hierarchical bounding box collision detection according to claim 1, wherein step S2 includes a preliminary detection stage and a detailed detection stage, and the detailed detection stage is divided into a gradual refinement link and an intersection test link;
in the preliminary detection stage, objects which are not collided in the virtual system are quickly eliminated by using a collision detection algorithm, and the objects which are possibly collided are found out;
the gradual refinement link is used for further reducing the area where collision is likely to occur;
and the intersection testing link is used for judging whether collision really occurs.
3. The three-dimensional pipeline optimization method based on hierarchical bounding box collision detection according to claim 2, wherein the AABB bounding box model adopts an axial bounding box R and is defined as:
R＝{(x，y，z)|X min ≤x≤X max ，Y min ≤y≤Y max ，Z min ≤Z≤Z max }
wherein: x min Represents the minimum of the projection of the pipeline on the x-axis; x max Represents the maximum projected on the x-axis of the pipeline; y is min Represents the minimum of the projection of the pipeline on the y-axis; y is max Represents the maximum projected on the y-axis of the pipeline; z min Represents the minimum of the projection of the pipeline on the z-axis; z max Representing the maximum projected on the z-axis of the pipeline.
4. The three-dimensional pipeline optimization method based on hierarchical bounding box collision detection as claimed in claim 3, wherein the axial bounding box performs the shortest distance collision detection on the pipeline which is likely to collide after performing the preliminary filtering on the comprehensive pipeline, and calculates the shortest distance between the spatially finite line segments, and the specific process is as follows:
let P be a point on the straight line AB, the coordinate of point A being (x) 1 ，y 1 ，z 1 ) And the coordinate of the point B is (x) 2 ，y 2 ，z 2 ) Then the P point coordinates (X, Y, Z) can be expressed as:
when the parameter is more than or equal to 0 and less than or equal to 1, P is a point on the line segment AB, when s is less than 1, P is a point on the extended line of BA, and when s is more than 1, P is a point on the extended line of AB;
similarly, let Q be a point on the straight line CD, C (x) 3 ，y 3 ，z 3 )，D(x 4 ，y 4 ，z 4 ) The coordinate (U, V, W) of the point Q can be represented by coordinates of 2 points C, D and a parameter t;
the square of the distance between these 2 points for PQ is then:
f(s，t)＝PQ 2 ＝[(x 1 -x 3 )+s(x 2 -x 1 )-t(x 4 -x 3 )] 2 +[(y 1 -y 3 )+s(y 2 -y 1 )-t(y 4 -y 3 )] 2 +[(z 1 -z 3 )+s(z 2 -z 1 )-t(z 4 -z 3 )] 2
if s is more than or equal to 0 and less than or equal to 1 and t is more than or equal to 0 and less than or equal to 1, the point P is on the line segment AB, the point Q is on the line segment CD, and the length of PQ is the shortest distance between AB and CD;
if the parameters obtained by the above formula do not satisfy s is not less than 0 and not more than 1 and t is not less than 0 and not more than 1, the point P cannot be found in the line segment AB and the point Q cannot be found in the line segment CD, so that the length of PQ is the shortest distance between the AB and the CD; at this time, the shortest distance from point a to line segment CD, the shortest distance from point B to line segment CD, the shortest distance from point C to line segment AB, and the shortest distance from point D to line segment AB were obtained, and then 4 distances were compared, where the smallest distance was the shortest distance between AB and CD.
5. The three-dimensional pipeline optimization method based on hierarchical bounding box collision detection according to claim 4, wherein in step S4, a secondary software platform is used to perform simulation experiment, the stability of the optimized model is detected according to the mean absolute error and the mean square error, and the detection precision is evaluated by using the mean detection rate as an evaluation index.
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| CN117272488A (en) * | 2023-11-17 | 2023-12-22 | 壹仟零壹艺网络科技(北京)有限公司 | Building construction simulation method and system based on BIM data |
| CN117272488B (en) * | 2023-11-17 | 2024-03-19 | 壹仟零壹艺网络科技(北京)有限公司 | Building construction simulation method and system based on BIM data |
| CN117556522A (en) * | 2024-01-10 | 2024-02-13 | 中国建筑西南设计研究院有限公司 | Assembled wood structure building construction method and system based on three-dimensional scanning and BIM |
| CN117556522B (en) * | 2024-01-10 | 2024-04-02 | 中国建筑西南设计研究院有限公司 | Assembled wood structure building construction method and system based on three-dimensional scanning and BIM |
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