A building material whole life cycle data monitoring, tracing and tracking method and system based on a BIM model

Abstract

The application discloses a kind of based on BIM model's building material full life cycle data's monitoring traceability tracking method and system, first obtain the BIM model of building, according to the data of BIM model, various materials in building are classified according to category;By shooting image, each classified building material is collected in situ, obtain the image information of material, the information in the BIM model of material image collected is combined, and three-dimensional BIM image is formed;Based on the three-dimensional BIM image combined, material is detected and analyzed, the state, position and potential quality problem of material are identified, and accurate quality inspection result is provided;Then, by the basic information and quality inspection result of each building material in initial stage obtained, tracking report is generated, detailed information of material full life cycle is provided, and the transparency and traceability of project management are enhanced.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of building material full life cycle data monitoring traceability tracking, and in particular to a building material full life cycle data monitoring traceability tracking method and system based on a BIM model. BACKGROUND

[0002] Building Information Modeling (BIM) as a digital building design and management method has been widely used in the global construction industry in recent years. BIM integrates all relevant information of a building project to create a three-dimensional digital model that includes various aspects of the building. This model is not only a static three-dimensional graphic, but also integrates rich data covering building design, construction, operation and maintenance at various stages. The application of BIM can significantly improve the collaborative management efficiency of building projects, optimize design schemes, reduce errors and waste in the construction process, prolong the service life of buildings, and promote the informatization and intelligent development of the construction industry.

[0003] Although BIM technology has achieved remarkable results in the construction industry, there are still some technical defects and challenges in the management and quality inspection of building materials. Specifically, the quality inspection results of building materials are crucial in the process of monitoring and tracing the full life cycle data of building materials. Currently, the quality inspection of building materials usually relies on manual inspection, on-site sampling and other methods, which cannot achieve comprehensive automatic monitoring and quality analysis.

[0004] Due to the variety of building materials, complex and non-uniform quality standards, quality inspectors often face a large amount of repetitive work, and the accuracy and timeliness of traditional manual quality inspection cannot be guaranteed, making it difficult to achieve more reliable material quality traceability. Subsequently, information-based building material traceability software platforms or methods have appeared on the market, but they still have the following two problems.

[0005] First, the existing building material traceability method mainly evaluates the quality of building materials before construction, and does not continuously monitor and evaluate the quality of building materials during the later construction period and even after a period of use. After all, the contact points are prone to deformation due to the interaction between building materials during the later construction period, and the materials themselves are also prone to deformation, so the traceability of the material quality is more meaningful.

[0006] Second, there is no continuous monitoring and traceability of the connection quality between two structural building materials in the existing technology. For example, modern buildings often use steel structure main frames, in which steel beams and steel columns are connected through welded joints to ensure the load-bearing capacity of the overall structure. However, the building material traceability method in the existing technology does not effectively continuously monitor and evaluate the quality of building materials after deformation. SUMMARY

[0007] The application aims to provide a building material full life cycle data monitoring traceability tracking method and system based on a BIM model, which solves the above technical problems pointed out in the prior art.

[0008] The application provides a building material full life cycle data monitoring traceability tracking method based on a BIM model, comprising the following operation steps:

[0009] Obtain a BIM model; classify building materials based on the BIM model to obtain structural building materials corresponding to each structure in the BIM model ; The i-th structural building material of the X structure in the BIM model;

[0010] Capture structural building material images of each structural building material ; combine each structural building material image based on the BIM model to obtain a plurality of material attribute three-dimensional BIM images;

[0011] Analyze based on the material attribute three-dimensional BIM image to obtain the quality inspection result of each structural building material;

[0012] Obtain initial information of the building material;

[0013] Generate a tracking report based on the initial information and the quality inspection result.

[0014] Correspondingly, the application also provides a building material full life cycle data monitoring traceability tracking system based on a BIM model, comprising a classification module, a combination module, a quality inspection module, an initial information acquisition module and a report generation module;

[0015] The classification module is used to obtain a BIM model; classify building materials based on the BIM model to obtain structural building materials corresponding to each structure in the BIM model ; The i-th structural building material of the X structure in the BIM model;

[0016] The combination module is used to capture structural building material images of each structural building material ; combine each structural building material image based on the BIM model to obtain a plurality of material attribute three-dimensional BIM images;

[0017] The quality inspection module is used to analyze based on the material attribute three-dimensional BIM image to obtain the quality inspection result of each structural building material;

[0018] The initial information acquisition module is configured to acquire initial information of the building material.

[0019] The initial information includes production information, transportation information, maintenance information, and storage information.

[0020] The report generation module is configured to generate a tracking report based on the initial information and the quality inspection result.

[0021] Compared with the prior art, the embodiments of the present application have at least the following technical advantages:

[0022] It can be known from the above-mentioned building material whole life cycle data monitoring and tracing method based on a BIM model provided by the present application that, in specific application, firstly, the BIM model of a building is acquired, and various materials in the building are classified according to the data of the BIM model, each building material corresponds to different structural components (for example, walls, roofs, floors, etc.), which lays a foundation for subsequent material management and analysis; further, each classified building material is collected on site by shooting images, and image information of the material is obtained, the collected material images are combined with the information in the BIM model to form a three-dimensional BIM image with multi-dimensional attributes; further, the material is quality inspected and analyzed based on the combined three-dimensional BIM image, the state, position and potential quality problems of the material are accurately identified through the three-dimensional image, so as to provide accurate quality inspection results for each building material; then, a tracking report is generated by the basic information and the quality inspection result of each building material in the initial stage, which is convenient for monitoring and managing the material in the construction process, provides clear decision basis for project managers, provides detailed information of the whole life cycle of the material, and enhances the transparency and traceability of project management. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 It is a main flow diagram of the building material whole life cycle data monitoring and tracing method based on a BIM model;

[0024] Figure 2 It is a material attribute three-dimensional BIM image simulation diagram in the building material whole life cycle data monitoring and tracing method based on a BIM model;

[0025] Figure 3 It is a building structural material surface rust simulation diagram in the building material whole life cycle data monitoring and tracing method based on a BIM model;

[0026] Figure 4An operation step schematic diagram for analyzing the quality inspection result of each structural building material in a building material whole life cycle data monitoring and traceability method based on a BIM model;

[0027] Figure 5 An operation step schematic diagram for analyzing the connection tightness of two structural building materials connected in a building material whole life cycle data monitoring and traceability method based on a BIM model;

[0028] Figure 6 A simulation schematic diagram of the smoothness and integrity of the connection between structural building materials in a building material whole life cycle data monitoring and traceability method based on a BIM model;

[0029] Figure 7 A simulation schematic diagram of the roughness and unevenness of the surface of a structural building material in a building material whole life cycle data monitoring and traceability method based on a BIM model;

[0030] Figure 8 A schematic diagram of the overall architecture of a building material whole life cycle data monitoring and traceability system based on a BIM model.

[0031] The reference signs: classification module 10, combination module 20, quality inspection module 30, initial information acquisition module 40, report generation module 50. DETAILED DESCRIPTION

[0032] The technical solutions of the present application will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0033] The present application will be described in further detail below through specific embodiments and in conjunction with the accompanying drawings.

[0034] Embodiment one

[0035] As shown in the drawings, the embodiment one of the present application provides a building material whole life cycle data monitoring and traceability method based on a BIM model, including the following operation steps: Figure 1 Step S10: obtaining a BIM model; classifying building materials based on the BIM model to obtain structural building materials corresponding to each structure in the BIM model

[0036] ; wherein, is the i th structural building material of the X structure in the BIM model;

[0037] ​It should be noted that the above BIM model (Building Information Modeling) is a digital building design management model, which creates a three-dimensional digital model containing various aspects of a building by integrating all relevant information of a building project. This model is not just a static three-dimensional graphic, but a virtual building containing rich data, which can be used for various stages of building design, construction, operation and maintenance. The embodiments of the present application classify building materials to obtain structural building materials corresponding to each structure in the BIM model ; Specifically, each building material is classified according to its properties, uses, etc., and classified into each structure of the BIM model, such as structural building materials for the foundation structure , including concrete, steel bars, etc. Structural building materials for load-bearing structures, such as steel columns, concrete beams, steel structure frames, etc. Through the above classification, the structural building materials of each structure in the BIM model can be intuitively and conveniently monitored, traced, and analyzed for life cycle data, so that the tracing work is orderly, and a building material is not tracked multiple times, thereby improving work efficiency.

[0038] Step S20: capturing and obtaining structural building material images of each structural building material ; based on the BIM model, combining each structural building material image to obtain a plurality of material attribute three-dimensional BIM images;

[0039] Step S30: analyzing the material attribute three-dimensional BIM images to obtain quality inspection results of each structural building material;

[0040] It should be noted that the embodiments of the present application simulate each structural building material to obtain a plurality of material attribute three-dimensional BIM images (as shown in Figure 2 ). In the material attribute three-dimensional BIM image, each structural building material is structured according to its properties and uses to obtain a plurality of material attribute three-dimensional BIM images corresponding to the BIM model; further, the structural building material is structured according to the structural building material in the material attribute three-dimensional BIM image (i.e. the structural building material is connected to the structural building material in the material attribute three-dimensional BIM image, the stronger the structural building material is connected, the smoother and more complete the connection of the structural building material is, and the better the quality of the structural building material is); the image quality of the structural building material (the image quality refers to the corrosion and damage of the structural building material, which can be directly obtained from the image of the structural building material, such as Figure 3The analysis is performed on the three-dimensional BIM image of each structural building material, so as to obtain the quality inspection result of each structural building material, clearly visualize and orderly identify the quality of the structural building material on the three-dimensional BIM image of each material attribute, so as to obtain the quality inspection result of each structural building material.

[0041] Step S40: obtaining initial information of the building material;

[0042] The initial information includes production information (including building material number information), transportation information, maintenance information and storage information;

[0043] Step S50: generating a tracking report based on the initial information and the quality inspection result.

[0044] It should be noted that the above embodiment of the application first obtains the BIM model of the building, classifies various materials in the building according to the data of the BIM model, and each building material corresponds to different structural components (such as walls, roofs, floors, etc.), which lays a foundation for subsequent material management and analysis; further, the image is shot to collect each classified building material on site, and the image information of the material is obtained, the collected material image is combined with the information in the BIM model to form a three-dimensional BIM image with multi-dimensional attributes; further, the material is quality inspected and analyzed based on the combined three-dimensional BIM image, the state, position and potential quality problem of the material are accurately identified through the three-dimensional image, so as to provide accurate quality inspection result for each building material;

[0045] Finally, the number information of the building material is matched by obtaining the basic information (i.e. initial information) of each building material in the initial stage and the quality inspection result, and then all the matched information is summarized to generate a tracking report; the above processing facilitates the monitoring and management of the material during the construction process, provides clear decision basis for the project management personnel, provides detailed information of the material full life cycle, and enhances the transparency and traceability of the project management.

[0046] The embodiment of the application can not only continuously monitor and evaluate the quality of the building material in the later construction stage and even after being used for a period of time, but also continuously monitor and trace the connection quality between two structural building materials, so as to continuously monitor the quality of the building material and trace the information.

[0047] Further research shows that analyzing the image quality of the building structural material and outputting the quality inspection result are the most important technical implementation steps, which are shown in steps S31-S34.

[0048] Specifically, as Figure 4As shown, in step S30, the quality inspection results of each structural building material are obtained based on the analysis of the material attribute three-dimensional BIM image, including the following operation steps:

[0049] Step S31: The material attribute three-dimensional BIM image is preprocessed to obtain a preprocessed material attribute three-dimensional BIM image.

[0050] It should be noted that the preprocessing operation refers to improving the image clarity and image key features by image denoising, image enhancement, and three-dimensional reconstruction optimization, retaining important structural features of the image, optimizing the complexity of the material attribute three-dimensional BIM image, reducing the calculation amount, and improving the subsequent processing efficiency.

[0051] Step S32: Obtain the position information of each structural building material in the preprocessed material attribute three-dimensional BIM image.

[0052] It should be noted that in the process of combining each structural building material image based on the BIM model to obtain a plurality of material attribute three-dimensional BIM images, the position information of each structural building material placed in the BIM model is pre-set and fixed, so in the subsequent processing process, the position information of each structural building material in the preprocessed material attribute three-dimensional BIM image can also be directly obtained according to the BIM.

[0053] Step S33: Based on the position information of the structural building material and the geometric features of each structural building material, the connection tightness of each connected two structural building materials is obtained (here, the connection of the two structural building materials is mainly analyzed); and the defect recognition of each structural building material is performed to obtain the surface defect data of the structural building material (here, it is a material analysis of a single independent material itself);

[0054] It should be noted that the higher the connection tightness in the above embodiment of the present application, the smoother and more complete the connection, which proves that the material structure quality is higher, and vice versa, which may exist connection damage problem; the above embodiment of the present application is through edge detection, contour extraction and morphological processing operation to detect the rust, crack or damage of the surface of the structural building material, which provides strong data support for the quality inspection results of the structural building material.

[0055] Step S34: Based on the target connection tightness and the surface defect data, the quality inspection results of the structural building material are obtained.

[0056] It should be noted that the quality inspection results in the above embodiment of the present application are obtained by weighted summation of the connection tightness and the surface defect data;

[0057] The embodiments described above first improve image quality through preprocessing, making it more suitable for subsequent structural analysis, defect detection, and other processing, thus reducing computational burden. Furthermore, by acquiring the location information of each structural building material, subsequent analysis is ensured to be based on accurate spatial positioning, providing crucial evidence for calculating connection tightness and defect detection. Further, through edge detection, contour extraction, and morphological processing, potential defects (such as rust, cracks, or damage) on the surface of the structural building materials are detected, providing important data support for subsequent quality inspection and ensuring sufficient stability and safety of the building materials during use. By analyzing connection tightness and identifying surface defects, comprehensive data support is provided for the quality inspection of each structural building material, evaluating its stability and durability. Finally, by using a weighted summation method, considering both connection tightness and defect status, a quantitative quality inspection result is obtained, providing data basis for subsequent quality assessment of the structural building materials.

[0058] Specifically, such as Figure 5 As shown, in step S33, the connection tightness between each pair of structural building materials is obtained by analyzing the location information and geometric characteristics of the structural building materials, including the following steps:

[0059] Step S331: Establish a connection relationship matrix M based on the location information of each of the structural building materials; each element in the connection relationship matrix M This indicates the location information of the connection between structural building material i and structural building material j;

[0060] Step S332: Based on the connection images corresponding to each element in the connection relationship matrix M, identify and analyze to obtain the connection tightness of the structural building materials corresponding to the element.

[0061] It should be noted that the above-described embodiment of this application first establishes a connection relationship matrix based on the location information of each structural building material. Therefore, each element in the matrix constitutes a connection relationship. Specifically, based on the location information of each structural building material, the above-described embodiment of this application checks whether two building materials with connected or overlapping location information have a connection relationship. Then, each pair of structural building materials with a connection relationship forms a connection relationship based on their location (that is, each element in the connection relationship matrix can also represent two structural building materials with a connection relationship at the corresponding position M). The connection image is extracted from the connection position of structural building material i and structural building material j determined in step S331 (the connection image is the image of the two structural building materials that constitute a connection relationship at the connection point). Then, by analyzing the connection between the two structural building materials on the connection image, the connection tightness of the two structural building materials is obtained.

[0062] Specifically, in step S332, the connection tightness of the structural building material corresponding to each element in the connection relationship matrix M is obtained by performing recognition analysis on the connection image corresponding to the element, including the following operation steps:

[0063] Step S3321: obtaining the edge of the structural building material based on the connection image through edge detection recognition; and obtaining the contour point of the structural building material based on the edge of the structural building material;

[0064] It should be noted that, in the above embodiment of the present application, the edge (or edge contour line) of the structural building material is obtained by performing edge detection on the connection image of each two structural building material connection places, and then the contour of the two structural building materials is obtained based on the edge of the structural building material, which is helpful to recognize the specific shape of the material boundary and provides a basis for subsequent defect detection.

[0065] Step S3322: obtaining the alignment degree of the connection point based on the contour point of the structural building material;

[0066] The alignment degree of the connection point includes the distance between the contact points and the angle between the contact points;

[0067] It should be noted that the connection tightness of each two structural building materials in the above embodiments of the present application is affected by the distance between the contact points of the structural building materials and the angle between the contact points, because the distance and angle between the contact points (the angle between the contact points refers to calculating the normal vector of each contact point to the contact surface, and then calculating the angle of the normal vectors of the two contact points, i.e. the angle between the contact points, specifically, by calculating the included angle between the two normal vectors, the angle between the contact surfaces can be obtained, if the included angle between the two normal vectors is close to zero (i.e. their directions are close to the same), it means that the two contact surfaces are approximately parallel, the contact angle is appropriate, the connection is stable, if the included angle is larger, it means that the angle between the contact surfaces is not appropriate, which may cause unstable connection, affecting the connection quality and stability, when the included angle between the normal vectors of the contact surfaces is too large, the two structural building materials may not be completely in contact, resulting in a decrease in the contact area at the connection, increasing the gap between the contact points, thereby making the connection unstable or prone to cracks, if the contact surfaces almost coincide and the included angle is very small, it proves that the connection of the two structural materials is very tight, and the quality is better) directly affects the connection stability and structural integrity between the building materials, if the distance between the contact points is small and the angle is appropriate, it means that the connection of the two structural building materials is tighter and more stable, and the quality of the connection is higher, on the contrary, if the distance is too large or the angle is not appropriate (angle is not appropriate means that the angle is too large, which means that the angle between the contact surfaces is not appropriate, which may cause unstable connection, affecting the connection quality and stability, when the included angle between the normal vectors of the contact surfaces is too large, the two structural building materials may not be completely in contact, resulting in a decrease in the contact area at the connection, increasing the gap between the contact points, thereby making the connection unstable or prone to cracks), the connection tightness is lower, which may cause a decrease in the strength of the connection or potential quality problems; by analyzing the alignment of the contact points of each two connected materials, the tightness of the material connection can be accurately evaluated to ensure the safety and durability of the building structure, and this analysis method plays a key role in improving the quality control and quality detection of buildings, which helps to ensure that each link in the construction process meets the quality standards;

[0068] However, in the design and manufacture of building materials, the connection between structural building materials must be smooth and complete, as shown in Figure 6 For example, in steel structure buildings (steel structure buildings are commonly used in modern buildings), steel beams and steel columns are connected through welded joints to ensure the load-bearing capacity of the overall structure. This method uses high temperature to locally melt and combine metal materials together to form a solid connection. Referring to Figure 6In a normal state, the distance between the contact points of each two structural building materials and the angle of the contact points are ideally less than the set distance threshold and angle threshold, respectively. Therefore, the connection tightness can be more intuitively identified and analyzed by identifying and analyzing the distance between the contact points and the angle of the contact points, so that the quality inspection result of the structural building materials can be more accurately identified and analyzed.

[0069] Step S3323: calculating the connection tightness based on the contact point alignment degree.

[0070] It should be noted that the connection tightness is calculated by first normalizing the distance between the contact points and the angle between the contact points, and then weighting and summing. The stronger the connection tightness, the better the quality of the connection part of the two structural building materials corresponding to the connection image.

[0071] The embodiment of the present application first detects the edge of the connection image, identifies the edge of the structural building material, and provides basic data for subsequent contour extraction. Then, the contour of the structural building material is extracted based on the edge data, and the specific shape of the material is obtained to help identify the contact condition and position between each two materials. The contour of the structural building material is obtained through image processing technology to ensure accurate identification of the shape of the connection part of the building material and provide accurate basic information for subsequent steps. Further, the tightness of the material connection is evaluated by analyzing the distance and angle between the contact points at the connection, and the tightness of the connection is accurately evaluated by analyzing the contact point alignment degree to ensure that the building structural material meets the safety and quality standards. Further, the tightness of the material connection is calculated based on the contact point alignment data (i.e., the distance and angle of the contact points) to provide a basis for subsequent quality detection, defect identification, and structural strength evaluation. Through comprehensive calculation of the contact point alignment degree, a specific connection tightness value is obtained to quantify the quality of the material connection, so that the quality of each structural building material can be more accurately judged.

[0072] In the specific implementation process of the above embodiment of the present application, the skilled person finds that, as shown in Figure 7 Due to the different roughness or unevenness of the surface of the structural building material, the boundary of the contact point is not clear, which increases the difficulty of identification, or the surface of the material may be rusted or damaged, which may affect the definition of the contact point and thus affect the accuracy of the measurement. Therefore, in the process of analyzing and identifying the distance between the contact points and the angle of the contact points, the influence of the surface factors of the structural building material should be avoided to obtain accurate distance between the contact points and angle of the contact points, and thus the subsequent quality inspection result of the structural building material is more accurate. For details, see subsequent processing steps 33221-33226.

[0073] Specifically, in step S3322, the alignment degree of the connection points is obtained based on the structural building material contour points, including the following steps:

[0074] Step S33221: obtaining a first contour pixel point and a second contour pixel point based on the structural building material contour points of each two structural building materials in the connection image; obtaining a first position vector and a second position vector by respectively quantifying the position information of the first contour pixel point and the position information of the second contour pixel point; ; and simultaneously obtaining a first normal vector of the first position vector and a second normal vector of the second position vector;

[0075] It should be noted that, in the above embodiment of the present application, the first contour pixel point and the second contour pixel point are obtained based on the structural building material contour points of each two structural building materials in the connection image; that is, one of the two structural building materials in the connection image that form a connection relationship is randomly selected as a first structural building material, and the other structural building material is determined as a second structural building material; then, the structural building material contour point of the first structural building material is selected as the first contour pixel point, and the structural building material contour point of the second structural building material is selected as the second contour pixel point (the contour point is a pixel point);

[0076] In the above embodiment of the present application, the contour pixel points of the structural building material contour points of each two structural building materials in the connection image are quantified based on their positions to obtain a first position vector of the first contour pixel point and a second position vector of the second contour pixel point.

[0077] Step S33222: initializing an iteration parameter; the iteration parameter includes an iteration counter and an iteration maximum number threshold, and an acceleration factor α; the iteration number of the iteration counter is initially 0.

[0078] It should be noted that the role of the acceleration factor α in the above embodiment of the present application is to adjust the rate of data optimization in the iteration process.

[0079] Step 33223: traversing each first position vector , and traversing each second position vector based on the first position vector , and calculating the distance d between the first position vector and the second position vector ; at the same time, based on the first position vector ​First normal vector The second normal vector of the second position vector The included angle is calculated. ;

[0080] It should be noted that the distance d in the above embodiments of this application is calculated by using the first position vector. With the second position vector The Euclidean distance between them is obtained;

[0081] Step S33224: Based on the first position vector Construct a distance vector matrix D based on the corresponding distance d; and based on the first position vector The corresponding included angle The included angle matrix R is obtained by constructing it.

[0082] It should be noted that the above embodiments of this application use a first position vector. With each second position vector The distance vector matrix D is constructed by the distance d between them; and the distance vector is obtained by the first position vector. With each second position vector The angle between The resulting included angle matrix R;

[0083] Step S33225: Based on the distance d and the included angle The first position vector is obtained by calculating the distance vector matrix D and the included angle matrix R. With each of the second position vectors The docking matching degree F;

[0084] The docking matching degree F is calculated as follows:

[0085] ;

[0086] In the formula, These are connection weights; It refers to connection strength; and It is the exponent of nonlinear transformation (the influence of adjusting distance and angle on docking matching degree); It is the second position vector The total quantity;

[0087] Step S33226: Determine whether the docking matching degree F is greater than or equal to a preset docking matching degree threshold. If so, output the distance d and the included angle corresponding to the maximum docking matching degree F. is the distance and the included angle corresponding to the maximum docking matching degree Fmax in the current iteration number, and the iteration number of the iteration counter is increased by one to obtain the current iteration number, and the above operation is returned until the connection point alignment degree is output. is the distance and the included angle corresponding to the maximum docking matching degree Fmax in the current iteration number, and the iteration number of the iteration counter is increased by one to obtain the current iteration number, and the above operation is returned until the connection point alignment degree is output. After the acceleration factor a is updated, an updated acceleration factor a' is obtained, the first position vector is updated based on the updated acceleration factor a', and the second position vector is updated based on the updated acceleration factor a'. and the second position vector , a new first position vector and a new second position vector are obtained, and the iteration number of the iteration counter is increased by one to obtain the current iteration number, and the above operation is returned until the connection point alignment degree is output.

[0088] It should be noted that the above embodiment of the present application first obtains two position vectors based on the profile pixel points of two building materials in the connection image by quantizing the positions, and further extracts the normal vector. By introducing the normal vector, interference caused by irregular profile shape, rough surface, etc. can be avoided, and the accuracy of the measurement result is ensured. Further, the relationship (distance and included angle) between the position vectors is accurately calculated, which provides data support for subsequent optimization and docking matching degree calculation. By calculating the Euclidean distance, the distance between the contact points can be quantified, and the alignment degree of the two position vectors can be measured by the included angle. Further, the distance and the included angle information are converted into a matrix form to facilitate subsequent optimization calculation and docking matching degree evaluation. At the same time, the introduction of the matrix can systematically represent the relationship between multiple position vectors. Further, by using a reasonable calculation method, the docking matching degree evaluation value between each element is obtained by combining distance, included angle, weight and other factors to measure the alignment accuracy of the contact points. Finally, the docking matching degree is iteratively fed back and optimized to search for the best second position vector of each first position vector (that is, the best second structure building material profile point corresponding to the first structure building material profile point), so as to obtain the distance between the contact points and the angle between the contact points of the two structure building materials in the connection image, and further obtain the connection point alignment degree, so that the subsequent analysis and recognition of the connection tightness of the two structure building materials are more accurate.

[0089] The embodiment of the application can effectively avoid measurement errors caused by rough surface, coating, rust, etc. by quantifying the contour pixel points, introducing the normal vector, and calculating the distance and the included angle. The calculation of the normal vector captures the real geometry of the material surface, preventing the surface factors from affecting the definition of the contact point. By introducing the acceleration factor a and the iteration parameter, the algorithm can converge more quickly when dealing with complex structures by adjusting the updating process of the vector, avoiding slow calculation. By calculating the Euclidean distance and the included angle, combined with the weight and the nonlinear transformation, the alignment degree of the connection point can be calculated more accurately, providing reliable measurement data. The final output of the contact point alignment degree provides higher precision data support for subsequent building material quality inspection, which can better evaluate the quality of the structure and find potential problems.

[0090] Specifically, in step S33226, the distance d and the included angle After updating the acceleration factor a, an updated acceleration factor a' is obtained, and the first position vector and the second position vector are updated based on the updated acceleration factor a'. The new first position vector and the new second position vector

[0091] are obtained, including the following operation steps: Step S332261: obtaining the maximum value of the butt joint matching degree under the current iteration number ; based on the maximum value of the butt joint matching degree and the butt joint matching degree threshold, a butt joint matching degree difference value is calculated.

[0092] Step S332262: based on the butt joint matching degree difference value and the acceleration factor a, an updated acceleration factor a' is calculated.

[0093] The calculation method of the updated acceleration factor a' is as follows:

[0094]

[0095] In the formula, a is the acceleration factor; a' is the updated acceleration factor; is an adjustment coefficient, which controls the rate of acceleration factor adjustment and satisfies .

[0096] Step S332263: based on the updated acceleration factor a' and the first position vector​ a new first position vector is calculated ; based on the updated acceleration factor a' and the second position vector a new second position vector is calculated

[0097] the new first position vector is calculated as follows:

[0098]

[0099] the new second position vector is calculated as follows:

[0100]

[0101] wherein, is a unit vector in the distance direction, pointing to the ideal alignment direction; is a unit vector in the angle adjustment direction, pointing to the ideal alignment direction; is a unit distance vector of the second position vector; is a unit angle vector corresponding to the second position vector.

[0102] It should be noted that the above embodiment of the present application first determines the basis for subsequent analysis and calculation (i.e. the distance d and the angle corresponding to the maximum docking matching degree in the current iteration, and the distance d and the angle are relative to the corresponding other distance d and angle in the current iteration, which are more optimal, and selecting them as the basis for subsequent analysis and calculation can greatly reduce the computational load of subsequent analysis and calculation); further, a new acceleration factor a' is calculated by the docking matching degree difference and the current acceleration factor a, the acceleration factor reflects the updating rate in the iteration process, and the updated acceleration factor a' will be adjusted according to the current docking matching degree difference, when the docking matching degree difference is large, a faster updating strategy (i.e. the introduction of ) is adopted, when the docking matching degree difference is small, a more gentle updating strategy is adopted, to ensure that the change of the acceleration factor is within a reasonable range, and will not cause excessive adjustment or non-convergence, by adjusting the acceleration factor, the iteration step in the optimization process is controlled, to ensure that the system can converge to the optimal solution at an appropriate speed; further, the first position vector and the second position vector are adjusted using the updated acceleration factor a', by dynamically updating the position vector, the alignment degree of the contact point is continuously improved, and the ideal alignment state is approached.

[0103] ​​​The connection tightness is calculated by normalizing and then weighting and summing the distance between the contact points and the angle between the contact points in the alignment of the connection points. The stronger the connection tightness, the better the quality of the connection part of the two structural building materials corresponding to the connected images.

[0104] Since the monitoring and tracing of the building material life cycle data is continuous, it is not comprehensive to use only the real-time connection status of the building material to determine the connection tightness and obtain the quality of the building material to obtain the tracking report. This is because some building materials may have quality problems or installation process differences during initial production and building. These problems are not easy to detect at the beginning and may gradually appear during the later use process due to environmental factors or material aging. Therefore, to comprehensively evaluate the quality of the building material (herein, specifically the connection tightness), historical data (i.e., historical connection tightness at historical time nodes) need to be combined for comprehensive analysis and judgment to obtain a more accurate connection tightness and a more accurate tracking report of the building material.

[0105] Specifically, after obtaining the connection tightness of each connection of the two structural building materials based on the position information of the structural building materials and the geometric characteristics of each structural building material in step S33, the following steps are further included:

[0106] Step S3301: Collecting historical connection tightness at multiple historical time nodes comprehensively analyzing based on the historical connection tightness and the connection tightness to obtain a target connection tightness;

[0107] Then, step S34 of comprehensively analyzing based on the connection tightness (herein, the connection tightness specifically refers to the target connection tightness) and the surface defect data to obtain the quality inspection result of the structural building material is performed.

[0108] It should be noted that the above embodiment of the present application obtains the real-time connection tightness of the current two structural building materials (the real-time connection tightness refers to the connection tightness obtained in step S33), and further includes reacquiring the historical connection tightness at the time nodes before the preset interval period of the current two structural building materials (the historical connection tightness is obtained by setting the collection frequency and interval to record the historical connection tightness at each historical time node), and then comprehensively analyzing based on the historical connection tightness and the real-time connection tightness by adding a time factor to obtain a more accurate target connection tightness, thereby making the analysis of the quality inspection result in subsequent step S34 more accurate and obtaining a more real tracking report.

[0109] Specifically, in step S3301, the historical connection tightness is obtained based on the historical connection tightness The target connection tightness is obtained by comprehensively analyzing the connection tightness, including the following steps:

[0110] Step S33011: Calculate the tightness of each adjacent pair of historical connections. The historical tightness difference; based on the historical tightness difference, the average historical tightness difference is calculated by averaging;

[0111] It should be noted that in the above embodiments of this application, due to environmental or aging reasons during the continuous connection process of structural building materials, the connection tightness gradually decreases. However, the rate of decrease is stable due to natural changes (i.e., natural aging and wear). Therefore, by averaging the historical connection tightness differences, the average historical connection tightness difference can be obtained as the basis for the subsequent target connection tightness. If the target connection tightness differs significantly from the average historical connection tightness difference, it proves that the calculation of the target connection tightness may be incorrect due to noise or other reasons.

[0112] Step S33012: Determine the connection tightness (the current connection tightness refers to the connection tightness between each pair of structural building materials obtained by analyzing the position information and geometric characteristics of each structural building material during the above operation) as the initial target connection tightness. ;

[0113] Step S33013: Based on the initial target connection tightness The historical connection tightness The target connection tightness is calculated using a preset time decay coefficient t. ;

[0114] The target connection tightness to be determined The calculation method is as follows:

[0115] ;

[0116] Step S33014: Based on the target connection tightness to be determined and the historical connection density corresponding to the previous time point The real-time historical connection tightness difference is calculated. ;

[0117] Step S33015: Determine the difference in real-time historical connection tightness. Real-time difference between the average historical connection tightness difference and the average historical connection tightness difference. Is it less than or equal to a preset difference threshold? If yes, output the target connection tightness as the to-be-determined target connection tightness; if no, update the time decay coefficient t to obtain a new time decay coefficient ; output the new time decay coefficient Return to the above step S33013 for reiteration until the target connection tightness is outputted.

[0118] The new time decay coefficient is calculated in the following manner:

[0119] ;

[0120] In the formula, is a real-time difference value (i.e. a difference value between a current real-time historical connection tightness difference and the average historical connection tightness difference); is a learning rate;

[0121] It should be noted that the above embodiment of the present application firstly considers that the connection tightness of the building material gradually decreases due to natural reasons such as aging and environmental changes over time, and this decrease is relatively stable. Therefore, the average historical connection tightness difference calculated based on the historical data serves as a stable reference value, providing a basis for the calculation of the target connection tightness, thereby effectively identifying whether the target connection tightness is affected by abnormal data such as noise during the calculation process. If the target connection tightness differs greatly from the average historical connection tightness difference, it can be inferred that there may be abnormalities in the calculation process, thereby helping to discover potential problems. Further, by considering the real-time connection tightness as the initial target connection tightness, it is ensured that the target connection tightness can reflect the current actual connection of the material. Further, based on the initial target connection tightness, the historical connection tightness, and the preset time decay coefficient t, the to-be-determined target connection tightness is calculated. By introducing the time decay coefficient, the influence of historical data and real-time data can be flexibly balanced, and a suitable balance between real-time data and historical data is found, so that the to-be-determined target connection tightness can reflect the current true state of the material, without relying too much on early historical data or relying on a single real-time condition. Further, by calculating the real-time historical connection tightness difference, the change trend of the target connection tightness can be monitored, and a basis is provided for subsequent judgment, reflecting the change of the connection tightness of the building material in the current time period. Further, by setting the threshold This effectively eliminates abnormal results caused by noise or calculation errors, thereby ensuring the accuracy of the target connection tightness. Furthermore, by updating the time decay coefficient, it can more flexibly adapt to actual conditions, thereby correcting the influence of historical data on the current calculation, ensuring that the influence of historical data is reasonable during the use of building materials, and maximizing the calculation accuracy of the target connection tightness.

[0122] Example 2

[0123] Based on the same concept of the above method embodiments, this invention also provides a monitoring and traceability system for the entire life cycle data of building materials based on BIM models, used to implement the above method of this invention. Since the principle and method of solving the problem in this system embodiment are similar, it has at least all the beneficial effects brought about by the technical solutions of the above embodiments, and will not be described in detail here.

[0124] like Figure 8 As shown, Embodiment 2 of the present invention provides a monitoring and traceability system for the entire life cycle data of building materials based on a BIM model, including a classification module 10, a combination module 20, a quality inspection module 30, an initial information acquisition module 40, and a report generation module 50;

[0125] The classification module 10 is used to acquire the BIM model; and classify the building materials based on the BIM model to obtain the structural building materials corresponding to each structure in the BIM model. ; The i-th structural building material of structure X in the BIM model;

[0126] The combined module 20 is used to capture and acquire images of each of the structural building materials. Images of structural building materials; based on the BIM model, the images of each structural building material are combined to obtain multiple three-dimensional BIM images of material properties;

[0127] The quality inspection module 30 is used to analyze the three-dimensional BIM image of the material properties to obtain the quality inspection results of each of the structural building materials.

[0128] The initial information acquisition module 40 is used to acquire the initial information of the building materials;

[0129] The initial information includes production information, transportation information, maintenance information, and storage information;

[0130] The report generation module 50 is used to generate a tracking report based on the initial information and the quality inspection results.

[0131] Specifically, the quality inspection module 30 is further configured to pre-process the material attribute three-dimensional BIM image to obtain a pre-processed material attribute three-dimensional BIM image.

[0132] Obtain position information of each structural building material in the pre-processed material attribute three-dimensional BIM image.

[0133] Based on the position information of the structural building material and the geometric characteristics of each structural building material, analyze to obtain the connection tightness of each connected two structural building materials; and perform defect identification on each structural building material to obtain surface defect data of the structural building material.

[0134] Based on the target connection tightness and the surface defect data, perform comprehensive analysis to obtain the quality inspection result of the structural building material.

[0135] The quality inspection module 30 is further configured to establish a connection relationship matrix M based on the position information of each structural building material; each element in the connection relationship matrix M represents the position information of the connection between the structural building material i and the structural building material j.

[0136] Based on the connection image corresponding to each element in the connection relationship matrix M, perform recognition analysis to obtain the connection tightness of the structural building material corresponding to the element.

[0137] The quality inspection module 30 is further configured to obtain the connection tightness of the structural building material corresponding to each element in the connection relationship matrix M based on recognition analysis of the connection image corresponding to the element, including the following operation steps:

[0138] Based on the connection image, perform edge detection recognition to obtain a structural building material edge; based on the structural building material edge, perform contour extraction to obtain a structural building material contour point.

[0139] Based on the structural building material contour point, perform analysis to obtain a connection point alignment degree.

[0140] The connection point alignment degree includes a distance between contact points and an angle between the contact points.

[0141] Based on the connection point alignment degree, calculate to obtain the connection tightness.

[0142] In the specific implementation process, the quality inspection module 30 is configured to, based on the structural building material contour point, perform analysis to obtain a connection point alignment degree, including the following operation steps:

[0143] ​Based on the structural building material contour points of every two structural building materials in the connected image, a first contour pixel and a second contour pixel are obtained; based on the position information of the first contour pixel and the position information of the second contour pixel, a first position vector is obtained accordingly after quantization. With the second position vector And simultaneously obtain the first position vector. First normal vector The second normal vector of the second position vector ;

[0144] Initialize the iteration parameters; the iteration parameters include an iteration counter, a maximum iteration threshold, and an acceleration factor α; the iteration count of the iteration counter is initially set to 0;

[0145] Traverse each of the first position vectors Based on the first position vector Perform traversal of each of the second position vectors Calculate and obtain the first position vector With the second position vector The distance d between them; at the same time, based on the first position vector First normal vector The second normal vector of the second position vector The included angle is calculated. ;

[0146] Based on the first position vector Construct a distance vector matrix D based on the corresponding distance d; and based on the first position vector The corresponding included angle The included angle matrix R is obtained by constructing it.

[0147] Based on the distance d and the included angle The first position vector is obtained by calculating the distance vector matrix D and the included angle matrix R. With each of the second position vectors The docking matching degree F;

[0148] The docking matching degree F is calculated as follows:

[0149] ;

[0150] In the formula, These are connection weights; It refers to connection strength; and It is the exponent of the nonlinear transformation; It is the second position vector The total quantity;

[0151] Determine whether the docking matching degree F is greater than or equal to a preset docking matching degree threshold. If so, output the distance d and the included angle corresponding to the maximum docking matching degree F. If the alignment of the connection points is not specified, then determine whether the number of iterations of the iteration counter is greater than or equal to the maximum number of iterations threshold; if so, output the distance d and the included angle corresponding to the maximum current docking matching degree F. For the alignment of the connection points; otherwise, for the distance d and the included angle when the docking matching degree F is maximized in the current iteration number. After updating the acceleration factor α, the updated acceleration factor α' is obtained, and the first position vector is updated based on the updated acceleration factor α'. and the second position vector This yields the new first position vector. and the new second position vector Meanwhile, the iteration count of the iteration counter is incremented by one to obtain the current iteration count, and the above operation is returned until the alignment of the connection points is output.

[0152] In specific implementation, the quality inspection module 30 is also used to determine the distance d and the included angle based on the maximum docking matching degree F at the current iteration number. After updating the acceleration factor α, the updated acceleration factor α' is obtained, and the first position vector is updated based on the updated acceleration factor α'. and the second position vector This yields the new first position vector. and the new second position vector The operation includes the following steps:

[0153] Get the maximum docking matching degree at the current iteration number. Based on the maximum docking matching degree The docking matching degree difference is calculated by comparing it with the docking matching degree threshold. ;

[0154] Based on the docking matching degree difference The updated acceleration factor α' is obtained by calculating the acceleration factor α.

[0155] The updated acceleration factor α' is calculated as follows:

[0156] ;

[0157] In the formula, As an acceleration factor; The updated acceleration factor; is an adjustment coefficient, controls the rate of adjustment of the acceleration factor, satisfies ;

[0158] Based on the updated acceleration factor alpha' and the first position vector , a new first position vector is calculated by ; based on the updated acceleration factor alpha' and the second position vector , a new second position vector is calculated by

[0159] The calculation method of the new first position vector is:

[0160] ;

[0161] The calculation method of the new second position vector ' is:

[0162] ;

[0163] In the formula, is the unit vector of the distance direction, pointing to the ideal alignment direction; is the unit vector of the angle adjustment direction, pointing to the ideal alignment direction; is the unit distance vector of the second position vector; is the unit angle vector corresponding to the second position vector.

[0164] To sum up, the building material full life cycle data monitoring and tracing method and system based on BIM model proposed in the embodiment of the application, in the specific execution process, first, the image quality is improved through preprocessing, which is more suitable for subsequent structure analysis, defect detection and other processing, reducing the calculation burden; by obtaining the position information of each structural building material, it is ensured that the subsequent analysis can be carried out on the basis of accurate spatial positioning, providing key basis for calculating connection tightness and defect detection; further, through edge detection, contour extraction and morphological processing operation, the possible defects on the surface of the structural building material are detected, providing important data support for subsequent quality inspection, ensuring that the building material has enough stability and safety in use; by analyzing the connection tightness and identifying the surface defects, comprehensive data support is provided for the quality detection of each structural building material, and its stability and durability are evaluated; finally, by means of weighted summation, the connection tightness and defect condition are comprehensively considered, a quantitative quality inspection result is obtained, and data basis is provided for subsequent quality evaluation of structural building materials;

[0165] The tightness of the material connection is evaluated by analyzing the distance and angle between the contact points at the joint, and the tightness of the connection is accurately evaluated by analyzing the contact point alignment, so as to ensure that the building structure material meets the safety and quality standards; further, the tightness of the material connection is calculated based on the contact point alignment data (i.e. the distance and angle of the contact points), which provides a basis for subsequent quality detection, defect identification and structure strength evaluation; through comprehensive calculation of the contact point alignment, a specific connection tightness value is obtained, the quality of the material connection is quantified, and the quality of each structural building material is more accurately judged;

[0166] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; the ordinary skilled in the art can modify the technical solutions described in the above embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for monitoring, tracing, and tracking the entire lifecycle data of building materials based on a BIM model, characterized in that, The following steps are included: Obtain the BIM model; classify the building materials based on the BIM model to obtain the structural building materials corresponding to each structure in the BIM model. ; The i-th structural building material of structure X in the BIM model; Photographing and collecting data on the various structural building materials. Images of structural building materials; Based on the BIM model, the images of each of the structural building materials are combined to obtain multiple three-dimensional BIM images of material properties; The quality inspection results of each of the structural building materials are obtained by analyzing the 3D BIM images of the material properties. Obtain the initial information of the building materials; A tracking report is generated based on the initial information and the quality inspection results; The process of analyzing the 3D BIM images of the material properties to obtain the quality inspection results of each structural building material includes the following steps: The material property 3D BIM image is preprocessed to obtain a preprocessed material property 3D BIM image; Obtain the location information of each structural building material in the preprocessed 3D BIM image of material properties; Based on the location information and geometric characteristics of the structural building materials, the connection tightness between each pair of connected structural building materials is obtained; historical connection tightness data at multiple historical time points are collected. Based on the historical connection tightness and the connection tightness, a comprehensive analysis is performed to obtain the target connection tightness; and defects are identified in each of the structural building materials to obtain surface defect data of the structural building materials. The quality inspection results of the structural building materials are obtained by comprehensively analyzing the target connection tightness and the surface defect data. The based on the historical connection tightness The target connection tightness is obtained by comprehensively analyzing the connection tightness, including the following steps: Calculate the tightness of each two adjacent historical connections The historical tightness difference; based on the historical tightness difference, the average historical tightness difference is calculated by averaging; The connection tightness is determined as the initial target connection tightness. ; Based on the initial target connection tightness The historical connection tightness The target connection tightness is calculated using a preset time decay coefficient t. ; The target connection tightness to be determined The calculation method is as follows: ； Based on the target connection tightness to be determined and the historical connection density corresponding to the previous time point The real-time historical connection tightness difference is calculated. ; Determine the difference in real-time historical connection tightness Real-time difference between the average historical connection tightness difference and the average historical connection tightness difference. Is it less than or equal to a preset difference threshold? ; If yes, then output the target connection tightness to be determined as the target connection tightness; if no, then update the time decay coefficient t to obtain a new time decay coefficient. The new time decay coefficient Return to the above operation and iterate again until the target connection tightness is obtained as the output; The new time decay coefficient The calculation method is as follows: ； In the formula, This is the real-time difference; The learning rate; The method of analyzing the location information and geometric characteristics of each structural building material to obtain the connection tightness of each pair of connected structural building materials includes the following steps: A connection matrix M is established based on the location information of each of the aforementioned structural building materials; each element in the connection matrix M... This indicates the location information of the connection between structural building material i and structural building material j; The connection tightness of the structural building materials corresponding to each element is obtained by identifying and analyzing the connection images corresponding to each element in the connection relationship matrix M; the process of obtaining the connection tightness of the structural building materials corresponding to each element by identifying and analyzing the connection images corresponding to each element in the connection relationship matrix M includes the following steps: The edges of structural building materials are obtained through edge detection based on the connected image; Contour extraction is performed based on the edges of the structural building material to obtain the contour points of the structural building material; The alignment of connection points is obtained by analyzing the contour points of the structural building materials. The alignment of the connection points includes the distance between the contact points and the angle between the contact points; The connection tightness is calculated based on the alignment of the connection points; The process of analyzing and obtaining the alignment of connection points based on the contour points of the structural building materials includes the following steps: Based on the structural building material contour points of every two structural building materials in the connected image, a first contour pixel and a second contour pixel are obtained; based on the position information of the first contour pixel and the position information of the second contour pixel, a first position vector is obtained accordingly after quantization. With the second position vector And simultaneously obtain the first position vector. First normal vector The second normal vector of the second position vector ; Initialize the iteration parameters; the iteration parameters include an iteration counter, a maximum iteration threshold, and an acceleration factor α; the iteration count of the iteration counter is initially set to 0; Based on each of the first position vectors Perform traversal of each of the second position vectors Calculate and obtain the first position vector With the second position vector The distance d between them; at the same time, based on the first position vector First normal vector The second normal vector of the second position vector The included angle is calculated. ; Based on the first position vector Construct a distance vector matrix D based on the corresponding distance d; and based on the first position vector The corresponding included angle The included angle matrix R is obtained by constructing it. Based on the distance d and the included angle The first position vector is obtained by calculating the distance vector matrix D and the included angle matrix R. With each of the second position vectors The docking matching degree F; Determine whether the docking matching degree F is greater than or equal to a preset docking matching degree threshold. If the docking matching degree F is greater than or equal to the preset docking matching degree threshold, then output the distance d and the included angle corresponding to the maximum docking matching degree F. The alignment of the connection points is determined; if the docking matching degree F is less than a preset docking matching degree threshold, then it is determined whether the iteration count of the iteration counter is greater than or equal to the maximum iteration count threshold; if the iteration count of the iteration counter is greater than or equal to the maximum iteration count threshold, then the distance d and the included angle corresponding to the maximum current docking matching degree F are output. For the alignment of the connection points; if the number of iterations of the iteration counter is less than the maximum number of iterations threshold, then the distance d and the included angle are based on the maximum docking matching degree F under the current iteration number. After updating the acceleration factor α, the updated acceleration factor α' is obtained, and the first position vector is updated based on the updated acceleration factor α'. and the second position vector This yields the new first position vector. and the new second position vector Meanwhile, the iteration count of the iteration counter is incremented by one to obtain the current iteration count, and the above operation is returned until the alignment of the connection points is output.

2. The method for monitoring, tracing, and tracking the entire lifecycle data of building materials based on a BIM model according to claim 1, characterized in that, The initial information includes production information, transportation information, maintenance information, and storage information.

3. The method for monitoring, tracing, and tracking the entire lifecycle data of building materials based on a BIM model according to claim 2, characterized in that, The docking matching degree F is calculated as follows: ； In the formula, These are connection weights; It refers to connection strength; and It is the exponent of the nonlinear transformation; It is the second position vector The total number.

4. The method for monitoring, tracing, and tracking the entire lifecycle data of building materials based on a BIM model according to claim 3, characterized in that, The distance d and the included angle when the docking matching degree F is maximized based on the current iteration number. After updating the acceleration factor α, the updated acceleration factor α' is obtained, and the first position vector is updated based on the updated acceleration factor α'. and the second position vector This yields the new first position vector. and the new second position vector The process includes the following steps: Get the maximum docking matching degree at the current iteration number. Based on the maximum docking matching degree The docking matching degree difference is calculated by comparing it with the docking matching degree threshold. ; Based on the docking matching degree difference The updated acceleration factor α' is obtained by calculating the acceleration factor α. Based on the updated acceleration factor α' and the first position vector The new first position vector is obtained through calculation. Based on the updated acceleration factor α' and the second position vector The new second position vector is obtained through calculation. '.

5. The method for monitoring, tracing, and tracking the entire lifecycle data of building materials based on a BIM model according to claim 4, characterized in that, The updated acceleration factor α' is calculated as follows: ； In the formula, As an acceleration factor; The updated acceleration factor; To adjust the coefficients and control the rate of adjustment of the acceleration factor, satisfying... ; The new first position vector The calculation method is as follows: ； The new second position vector The calculation method for ' is as follows: ； In the formula, It is a unit vector in the distance direction, pointing towards the ideal alignment direction; The unit vector that adjusts the direction of the included angle, pointing towards the ideal alignment direction; The unit distance vector to the second position vector; This is the unit angle vector corresponding to the second position vector.

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