Steel bar acceptance system and method based on BIM technology and image recognition technology

Abstract

The invention relates to a reinforcing steel bar acceptance system and method based on a BIM technology and an image recognition technology, and relates to the technical field of project acceptance, and the method comprises the steps: obtaining the acceptance time of reinforcing steel bar meshes of a plurality of regions; if the current time node is the acceptance time of the reinforcing mesh in a certain area, acquiring the reinforcing mesh image for analysis and identification; acquiring actual position coordinates of each reinforcing steel bar in the reinforcing steel bar mesh image through a BIM (Building Information Modeling) technology; according to the actual position coordinates of each steel bar, the distance between the adjacent vertical steel bars and the distance between the adjacent transverse steel bars in the target steel bar mesh are calculated, and acceptance check results about the positions, specifications, lengths and the distances of the steel bars are output. Data resources generated by checking and accepting the reinforcing steel bars can be reduced, and the checking and accepting result of the reinforcing steel bars can be rapidly output.

Description

Technical Field

[0001] The present application relates to the field of engineering acceptance technology, and in particular to a steel bar acceptance system and method based on BIM technology and image recognition technology. Background Art

[0002] Currently, in the construction industry, steel bars are an important component of concrete structures, and their installation quality directly affects the building's bearing capacity, earthquake resistance, and service life. Unqualified steel bar engineering may cause structural cracks, reduced bearing capacity, and even cause building collapse in extreme cases, posing a serious threat to the safety of personnel and property. Therefore, the quality of steel bar engineering is one of the key links to ensure the safety of buildings.

[0003] At present, steel bar detection technology mainly relies on manual visual inspection and basic image recognition methods. Manual visual inspection mainly uses the naked eye to directly observe the appearance of the steel bar to detect whether there are obvious defects such as rust, cracks and deformation, or use auxiliary tools for measurement and observation. The image recognition method uses a camera to capture the image of the steel bar, and then uses image processing software to analyze the shape, size and possible defects of the steel bar, or uses high-speed camera equipment to capture dynamic images to form dynamic videos during the production or processing of steel bars, which can also analyze the processing quality and dynamic characteristics of the steel bar.

[0004] However, the existing technology has deficiencies in versatility, detection efficiency and data processing. When inspecting steel bars manually, a large amount of manpower and material resources are required. When inspecting by image recognition, it is necessary to obtain the shape, size, position, specification, length and spacing of the steel bars in real time. The front end generates a large amount of image data or video data, and the back end needs to perform complex data processing and deep learning analysis on a number of image data or video data, which increases the system's computing resources and data processing capabilities. In particular, when the system's computing power is insufficient due to the simultaneous acceptance of images of several steel bars for analysis, it will cause delays in outputting multiple steel bar acceptance results. Summary of the invention

[0005] The first purpose of this application is to provide a steel bar acceptance method based on BIM technology and image recognition technology, which can reduce the data resources generated by the acceptance of steel bars and realize the rapid output of the acceptance results of steel bars.

[0006] In the first aspect, the present application provides a steel bar acceptance method based on BIM technology and image recognition technology, which adopts the following technical solution: A steel bar acceptance method based on BIM technology and image recognition technology, comprising: Get the acceptance time of steel mesh in several areas; If the current time node is the acceptance time of the steel mesh in a certain area, the steel mesh image is obtained for analysis and identification; Acquire the actual position coordinates of each steel bar in the steel mesh image by using BIM technology; According to the actual position coordinates of each steel bar, the spacing between adjacent vertical steel bars and the spacing between adjacent transverse steel bars in the target steel mesh are calculated, and the acceptance results of the position, specification, length and spacing of the steel bars are output.

[0007] By adopting the above technical solution, at the time of acceptance, the image of the steel mesh is obtained for analysis and identification, and there is no need to monitor the status of the steel mesh in real time, thereby reducing unnecessary front-end data collection and back-end processing burdens, effectively reducing the demand for system computing resources, and improving data processing efficiency, thereby improving the accuracy and timeliness of the output steel bar acceptance results on the position, specification, length and spacing of the steel bars.

[0008] In a preferred example, the present application can be further configured as follows: if the current time node is the acceptance time of the steel mesh in a certain area, the step of obtaining the steel mesh image for analysis and identification includes: If the current time node is the acceptance time of the steel meshes in more than one area, then several steel mesh images reaching the acceptance time are obtained simultaneously; Generating acceptance priorities for the plurality of steel mesh images at the same acceptance time according to the acceptance sequence; According to the acceptance priority, the images are assigned to the image processing queue for identification and analysis.

[0009] By adopting the above technical solution, resources can be reasonably allocated according to the acceptance order of the steel mesh, effectively avoiding delays in important steel bar acceptance due to unreasonable resource allocation, thereby improving the efficiency and reliability of the overall acceptance work.

[0010] In a preferred example, the present application can be further configured as follows: the step of generating acceptance priorities according to the acceptance order for the plurality of steel mesh images at the same acceptance time includes: By using BIM technology, the number of key stress-bearing parts of the steel bar model corresponding to the steel mesh images is determined; The plurality of steel mesh images are sorted from most to least according to the number of key stress-bearing locations, and an acceptance priority is generated.

[0011] By adopting the above technical solution, BIM technology can be used to determine the key stress-bearing parts in the steel bar model and obtain the number of key stress-bearing parts of each steel mesh image, so as to reasonably arrange the acceptance priority of the steel mesh. This not only improves the efficiency of steel bar acceptance, but also ensures that the steel bars in key stress-bearing parts are inspected first, further improving the quality of steel bar projects and reducing safety hazards caused by failure to timely accept key stress-bearing parts of steel bars.

[0012] In a preferred example, the present application may be further configured as follows: before the step of obtaining the acceptance time of the steel meshes in several areas, the step further includes: Set the inspection time of the steel mesh in each area before the acceptance time of the steel mesh in several areas; If the current time node is the inspection time of the steel mesh in a certain area, the steel mesh image of the area is obtained, the steel mesh image is identified and analyzed, and through BIM analysis, the difference in acceptance time of the steel mesh in several areas is obtained, and the acceptance time of the steel mesh is updated.

[0013] By adopting the above technical solution, an inspection time is set before the acceptance time of the steel mesh. The inspection time is used to confirm the steel mesh and update the acceptance time of the steel mesh again before acceptance, so that the acceptance time of the steel mesh is more accurate, and the situation where the steel mesh installation is delayed but it is recognized as completed at the acceptance time and mistakenly accepted is avoided, thereby reducing the resources for identifying and analyzing the mistakenly accepted steel mesh images is reduced.

[0014] In a preferred example, the present application can be further configured as follows: if the current time node is the inspection time of the steel mesh in a certain area, the steel mesh image of the area is obtained, the steel mesh image is identified and analyzed, and the difference in the acceptance time of the steel mesh in several areas is obtained through BIM analysis, and the step of updating the acceptance time of the steel mesh includes: During the inspection, the actual position coordinates of each steel bar in the current steel mesh image are obtained through BIM technology, and the number of steel bars installed corresponding to the actual position coordinates is obtained; The actual position coordinates of each steel bar are compared with the steel bar model in the BIM technology to obtain the position coordinates of the missing steel bars in the steel mesh image; Obtain the number of missing steel bars corresponding to the position coordinates of the missing steel bars; Calculate and obtain the steel bar installation efficiency according to the steel bar installation quantity and the steel bar installation time; Calculate and obtain the remaining installation time according to the steel bar installation efficiency and the number of missing steel bars; The remaining installation time is added after the inspection time, and the acceptance time of the steel mesh is updated.

[0015] By adopting the above technical solution, the missing steel bars of the steel mesh can be discovered in time during the inspection, the steel bar installation efficiency and the remaining installation time can be calculated, and the acceptance time of the steel mesh can be reasonably adjusted, thereby improving the accuracy of the steel mesh acceptance and enhancing the overall efficiency and reliability of the steel mesh acceptance.

[0016] In a preferred example, the present application may be further configured as follows: after the step of generating acceptance priorities according to the acceptance order for the plurality of steel mesh images at the same acceptance time, the present application may further include: Determine whether there is a steel mesh image whose updated acceptance time is later than the acceptance time before the update among the plurality of steel mesh images listed in the acceptance priority; If there is a steel mesh image, the acceptance order of the steel mesh image is set to the highest acceptance priority; If there is more than one steel mesh image, the acceptance priority is updated in descending order based on the difference between the acceptance time before the update and the current time node.

[0017] By adopting the above technical solution, the problem of acceptance order confusion caused by acceptance time adjustment during steel bar acceptance can be effectively solved. Among them, by judging whether the steel mesh images included in the acceptance priority have updated acceptance time, the steel mesh images with delayed acceptance time are given priority, thereby ensuring the continuity and efficiency of the acceptance work and effectively avoiding the steel mesh acceptance delay affecting the progress of the entire construction.

[0018] In a preferred example, the present application can be further configured as follows: the step of obtaining the acceptance time of the steel meshes in several areas includes: Through BIM technology, the construction drawings are converted into three-dimensional models, and the installation progress of the steel mesh is simulated according to the construction drawings. The time when the steel mesh installation is completed in each area is obtained according to the installation progress, and set as the acceptance time of the steel mesh in the area.

[0019] By adopting the above technical solution, the steel bar acceptance time is set according to the construction drawings to simulate the installation progress of the steel mesh, and the steel bars are accepted at the acceptance time, which reduces the data resources generated by real-time monitoring of the steel bar conditions, and can quickly output the steel bar acceptance results.

[0020] In a preferred example, the present application can be further configured as follows: the step of calculating the spacing between adjacent vertical steel bars and the spacing between adjacent transverse steel bars in the target steel mesh according to the actual position coordinates of each steel bar, and outputting the acceptance results of the position, specification, length and spacing of the steel bars includes: Determine whether the position, specification, length and spacing of the steel bar image are the same as the position, specification, length and spacing of the steel bar model generated by BIM technology within the allowable error range; If they are the same, the output is that the steel bar meets the acceptance criteria; If they are not the same, the output result is that the steel bars do not meet the acceptance criteria.

[0021] By adopting the above technical solution, the actual position, specification, length and spacing of the steel bars are compared with the allowable error range of the steel bar model generated by BIM technology, which can effectively determine whether the steel bars meet the acceptance standards, reduce the subjectivity and errors of manual visual inspection, and effectively avoid acceptance errors caused by human factors, thereby improving the quality of steel bar projects and enhancing the safety and stability of buildings.

[0022] In a preferred example, the present application can be further configured as follows: if the current time node is the acceptance time of the steel mesh in a certain area, after the step of acquiring the steel mesh image for analysis and identification, the following steps are included: Comparing the steel mesh image with a standard steel bar image to determine whether the steel mesh image has rust, cracks, and deformation; If it exists, the steel mesh image is prevented from obtaining the actual position coordinates of each steel bar through BIM technology, and a result that the steel bar does not meet the acceptance criteria is output; If it does not exist, the steel mesh image is used through BIM technology to obtain the actual position coordinates of each steel bar.

[0023] By adopting the above technical solution, only when there are no obvious defects in the steel mesh image will the actual position coordinates of each steel bar be obtained through BIM technology, which reduces unnecessary data processing burden on the front end and improves the speed and reliability of the entire acceptance process, ensuring that subsequent acceptance steps can proceed smoothly.

[0024] In the second aspect, the present application provides a steel bar acceptance system based on BIM technology and image recognition technology, which adopts the following technical solutions: A steel bar acceptance system based on BIM technology and image recognition technology, including: Time acquisition module: used to obtain the acceptance time of steel mesh in several areas; Image recognition module: used to obtain the image of the steel mesh for analysis and recognition if the current time node is the acceptance time of the steel mesh in a certain area; Coordinate acquisition module: used to obtain the actual position coordinates of each steel bar in the steel mesh image through BIM technology; Rebar acceptance module: It is used to calculate the spacing between adjacent vertical steel bars and the spacing between adjacent transverse steel bars in the target steel mesh according to the actual position coordinates of each steel bar, and output the acceptance results on the position, specification, length and spacing of the steel bars.

[0025] In summary, this application has the following beneficial technical effects: This application obtains the image of the steel mesh for analysis and identification only at the set acceptance time, effectively avoiding the large amount of data collection and processing requirements brought about by real-time monitoring of the steel mesh status, significantly reducing the frequency of front-end data collection and the burden of back-end data processing, and thus being able to output the acceptance results of the position, specification, length and spacing of the steel bars more quickly, improving the accuracy and timeliness of the acceptance process. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a steel bar acceptance method based on BIM technology and image recognition technology in one of the embodiments of the present application.

[0027] Figure 2 It is a sub-step flow chart of step S2 in one embodiment of the present application.

[0028] Figure 3 It is a sub-step flow chart of step S21 in one embodiment of the present application.

[0029] Figure 4 This is a flowchart of steps added before step S1 in one of the embodiments of the present application.

[0030] Figure 5 It is a sub-step flow chart of step S11 in one embodiment of the present application.

[0031] Figure 6 This is a flowchart of steps added after step S21 in one embodiment of the present application.

[0032] Figure 7 It is a sub-step flow chart of step S1 in one embodiment of the present application.

[0033] Figure 8 It is a sub-step flow chart of step S4 in one embodiment of the present application.

[0034] Fig. 9 This is a flowchart of steps added after step S2 in one embodiment of the present application.

[0035] Fig.10 It is a structural schematic diagram of a steel bar acceptance system based on BIM technology and image recognition technology in one embodiment of the present application.

[0036] Figure numerals: 1. Time acquisition module; 2. Image recognition module; 3. Coordinate acquisition module; 4. Steel bar acceptance module. DETAILED DESCRIPTION

[0037] The following is combined with Figure 1-10 This application is described in further detail.

[0038] refer to Figure 1 , a steel bar acceptance method based on BIM technology and image recognition technology, specifically including: S1. Obtain the acceptance time of steel mesh in several areas.

[0039] S2. If the current time node is the acceptance time of the steel mesh in a certain area, the steel mesh image is obtained for analysis and identification.

[0040] Among them, only at the acceptance time, the steel mesh image corresponding to the acceptance time is scanned, photographed, or taken by the front-end device. There is no need to monitor the steel bars in real time, which reduces the image data resources generated when accepting the steel bars and speeds up the analysis and recognition efficiency of the steel mesh image. After obtaining the steel mesh image, it is necessary to pre-process the steel mesh image, such as edge detection and contour extraction, to extract the contour information of the steel bars from the collected image, to facilitate the analysis and identification of the steel bars, and to improve the accuracy of the subsequent use of BIM technology for steel mesh images. S3. Obtain the actual position coordinates of each steel bar in the steel mesh image through BIM technology.

[0041] Among them, through BIM technology, the extracted steel bar contour is matched with the pre-established steel bar model to obtain the actual position coordinates of each steel bar. The Canny edge detection algorithm in the OpenCV library can be used to extract the edges of the steel bars, and then the Hough transform is used to determine the straight line segments of the steel bars. By comparing these straight line segments with the steel bar positions in the BIM model, the actual position coordinates of each steel bar can be accurately obtained.

[0042] S4. According to the actual position coordinates of each steel bar, the spacing between adjacent vertical steel bars and the spacing between adjacent transverse steel bars in the target steel mesh are calculated, and the acceptance results of the position, specification, length and spacing of the steel bars are output.

[0043] Among them, each steel bar in the steel mesh image is automatically compared with the corresponding steel bar model in the BIM model to quickly determine whether the position, specification, length and spacing of the steel bars meet the acceptance standards, reducing the error and time consumption of manual comparison.

[0044] In this embodiment, at the acceptance time of the steel mesh, the front end only performs the operation of acquiring the steel bar image of the steel mesh at the acceptance time, and then performs preprocessing and image analysis and recognition, which effectively avoids the redundant data flow caused by continuous monitoring of the front end, reduces the pressure of front-end data acquisition and back-end processing, optimizes the allocation of computing resources, and enables the system to operate more efficiently, making the output of acceptance results on steel bar position, specification, length and spacing faster, thereby improving the overall data processing capability and response speed.

[0045] refer to Figure 2 Further, in one embodiment, step S2 is refined into the following sub-steps: S20. If the current time node is the acceptance time of the steel meshes in more than one area, then simultaneously obtain several steel mesh images that have reached the acceptance time.

[0046] Among them, when the steel meshes in multiple areas reach the acceptance time at the same time, the steel mesh images of these areas are automatically acquired in parallel, so that a batch of steel mesh images at the acceptance time can be processed at the same time, which improves the acceptance efficiency of steel bars and reduces the waste of computing resources for continuous monitoring.

[0047] S21, generating acceptance priorities for a number of steel mesh images with the same acceptance time according to the acceptance sequence.

[0048] Among them, setting acceptance priority optimizes resource allocation and ensures that steel mesh images that need priority acceptance can be processed in advance.

[0049] S22. Allocate to the image processing queue for recognition and analysis according to the acceptance priority.

[0050] Before allocating the steel mesh images, check the current task load of each image processing queue, select the queue with the lowest load or no current tasks for task allocation, so that several steel mesh images can be allocated to idle or low-load queues.

[0051] In this embodiment, by setting the acceptance order of the steel mesh images, the resources for judging and accepting the steel bars are reasonably allocated, and the problem of delays in important steel bar acceptance due to unreasonable resource allocation is reduced, thereby improving the efficiency and reliability of the overall acceptance work.

[0052] In addition, reference Figure 3 Further, in one embodiment, step S21 is refined into the following sub-steps: S210. Determine the number of key stress-bearing locations of the steel bar model corresponding to the plurality of steel bar mesh images by using BIM technology.

[0053] Among them, BIM technology allows the creation of high-precision three-dimensional steel bar models with model accuracy up to the millimeter level, which meets the precision requirements for cutting steel bar construction. The refined steel bar model created by BIM technology is then expanded into a steel mesh model of an area, which can display each steel bar in each component in detail, including main bars, auxiliary bars, stirrups, etc., so as to accurately identify the number of steel bars in key stress-bearing locations. The steel bar model is then subjected to collision checks to identify the steel bar arrangement in key stress-bearing locations and record the number of key stress-bearing locations.

[0054] S211. Sort a number of steel mesh images according to the number of key stress-bearing locations from large to small, and generate acceptance priorities.

[0055] Among them, when analyzing several steel mesh images with the same acceptance time, the steel mesh images with the largest number of key stress-bearing parts are set as the first priority, and the steel mesh images with the second largest number of key stress-bearing parts are set as the second priority, and so on. BIM software processes several steel mesh images with the same priority in parallel and inputs the acceptance results of several steel mesh images with the same priority, so that computing resources can be allocated more reasonably and the acceptance time of steel bars can be shortened.

[0056] In this embodiment, by using BIM technology, the number of key stress-bearing parts in the steel bar model is identified as reference data for the acceptance order of the steel mesh image, the acceptance priority of the steel mesh is reasonably arranged, and the number of key stress points corresponding to each steel mesh image is accurately counted, so that the steel bars in the key stress-bearing parts are inspected first, reducing the safety hazards caused by the failure to accept the key stress-bearing parts of the steel bars in time.

[0057] In addition, reference Figure 4 Further, in one embodiment, before step S1, steps S10 and S11 are added: S10. Setting the inspection time of the steel mesh in each area before the acceptance time of the steel mesh in several areas.

[0058] Among them, the inspection time is to calibrate the acceptance time of the steel mesh, so that the steel mesh can confirm whether the current installation situation meets the acceptance criteria before the acceptance time. If the acceptance criteria are not met, it will affect the output acceptance result. In one embodiment, the inspection time can simulate the progress of the steel model installation in the construction drawing through BIM technology, and simulate the time required to reach a certain installation progress. For example, the time required to install 90% of the steel bars in the steel mesh of an area is simulated through BIM technology, and this time is set as the inspection time.

[0059] S11. If the current time node is the inspection time of the steel mesh in a certain area, obtain the steel mesh image of the area, identify and analyze the steel mesh image and perform BIM analysis to obtain the difference in acceptance time of the steel mesh in several areas, and update the acceptance time of the steel mesh.

[0060] Among them, when the inspection time arrives, the difference between the actual steel bar installation progress and the simulated steel bar installation progress is confirmed by analyzing the steel mesh image of the actual installation progress, and the acceptance time is updated accordingly, thereby reducing the steel mesh still not meeting the acceptance standard when the initial acceptance time of the steel mesh arrives due to the difference in installation progress.

[0061] In this embodiment, the acceptance time of the steel mesh is updated again, making the acceptance time of the steel mesh more accurate, effectively avoiding the situation where the steel mesh installation is delayed but it is identified as completed at the acceptance time and mistakenly accepted, reducing the inaccuracy of the acceptance results due to delayed installation progress, and reducing the resources for acceptance analysis of steel mesh images that do not meet the acceptance standards.

[0062] In addition, reference Figure 5 Further, in one embodiment, step S11 is refined into the following sub-steps: S110. During the inspection, the actual position coordinates of each steel bar in the current steel mesh image are obtained through BIM technology, and the number of steel bars installed corresponding to the actual position coordinates is obtained.

[0063] Among them, the BIM model is used to identify each steel bar in the steel mesh image, and the actual position coordinates of the current steel mesh model in space are accurately obtained through the three-dimensional coordinate system.

[0064] S111. Compare the actual position coordinates of each steel bar with the steel bar model in the BIM technology to obtain the position coordinates of the missing steel bars in the steel mesh image.

[0065] S112. Obtain the number of missing steel bars corresponding to the position coordinates of the missing steel bars.

[0066] Among them, at the time of inspection, after the actual position coordinate area missing in the current steel mesh model successfully matches the model of a single steel bar, it is recorded as a missing steel bar. By automatically counting the number of missing steel bars, key data is provided for subsequent installation efficiency calculation and remaining installation time prediction.

[0067] S113. Calculate and obtain the steel bar installation efficiency based on the steel bar installation quantity and steel bar installation time.

[0068] Among them, the number of installed steel bars is the difference between the total number of steel bars in the steel bar model and the number of missing steel bars, and the steel bar installation time is the time period from the steel bar installation to the inspection time. Steel bar installation efficiency = number of installed steel bars / steel bar installation time*100%.

[0069] S114. Calculate and obtain the remaining installation time based on the steel bar installation efficiency and the number of missing steel bars.

[0070] The remaining installation time is the time required to complete the installation of the missing steel bars. Remaining installation time = number of missing steel bars / steel bar installation efficiency.

[0071] S115. Add the remaining installation time after the inspection time and update the acceptance time of the steel mesh.

[0072] In this embodiment, during the inspection time, the steel bar installation efficiency and the remaining installation time are calculated by comparing the actual steel bar missing situation with the inspection time, and the acceptance time of the steel mesh is reasonably adjusted, thereby improving the accuracy of the steel mesh acceptance and enhancing the overall efficiency and reliability of the steel mesh acceptance.

[0073] In addition, reference Figure 6 Further, in one embodiment, after step S21, steps S212, S213, and S214 are added: S212: Determine whether there is a steel mesh image whose updated acceptance time is later than the acceptance time before updating among the plurality of steel mesh images included in the acceptance priority.

[0074] Among them, by real-time monitoring and comparing changes in acceptance time, abnormalities in acceptance time can be discovered in a timely manner, providing a basis for subsequent adjustments to acceptance priorities.

[0075] S213. If there is a steel mesh image, the acceptance order of the steel mesh image is set to the highest acceptance priority.

[0076] S214. If there is more than one steel mesh image, the acceptance priority is updated in descending order based on the difference between the acceptance time before the update and the current time node.

[0077] Among them, by quantifying the urgency of the acceptance time, as well as the sorting algorithm and time difference calculation, the acceptance order of multiple steel mesh images is sorted, which improves the efficiency of steel bar acceptance work.

[0078] In this embodiment, since there is a problem of confusion in the acceptance order due to the update and adjustment of the acceptance time during the steel bar acceptance process, the steel mesh images that require acceptance time to be postponed are processed first, so that the acceptance work of the steel bars can maintain continuity and efficiency, and reduce the situation where the progress of the entire construction is affected by the delayed acceptance of the steel mesh.

[0079] In addition, reference Figure 7 Further, in one embodiment, step S1 is refined into the following sub-steps: S12. Convert the construction drawings into three-dimensional models through BIM technology, simulate the installation progress of the steel mesh according to the construction drawings, obtain the time when the steel mesh installation is completed in each area according to the installation progress, and set it as the acceptance time of the steel mesh in the area.

[0080] Among them, use BIM software such as Revit to import two-dimensional construction drawings, including installation drawings of steel bars. According to the data in the two-dimensional drawings, create basic geometric components in the BIM software, set the materials, parameters and construction information of the components, and then organize and manage the components in the BIM model through a hierarchical structure. Using the 4D simulation function of the BIM software, superimpose the timeline on the three-dimensional model to obtain the estimated installation completion time of the steel mesh in each area, and set the estimated installation time as the acceptance time of the steel mesh.

[0081] In this embodiment, the construction progress of the steel mesh is simulated through construction drawings, the acceptance time of the steel bars is set, and the steel bars are inspected at the acceptance time, thereby reducing the resource consumption of the front-end data required for continuous monitoring of the steel bar status and quickly outputting the acceptance results of the steel bars.

[0082] In addition, reference Figure 8 Further, in one embodiment, step S4 is refined into the following sub-steps: S40, determining whether the position, specification, length and spacing of the steel bar image are the same as the position, specification, length and spacing within the allowable error range of the steel bar model generated by the BIM technology.

[0083] First, the steel bar image is deeply analyzed to extract key parameters such as the position, specification, length and spacing of the steel bars. The extraction methods include but are not limited to deep learning algorithms, image segmentation and feature extraction. Subsequently, these parameters are compared with the allowable error range of the steel bar model generated by BIM technology to determine whether the two are consistent.

[0084] S41. If they are the same, then the output is the result that the steel bars meet the acceptance criteria.

[0085] S42. If they are not the same, the output result is that the steel bars do not meet the acceptance criteria.

[0086] In this embodiment, by comparing the actual position, specification, length and spacing of the steel bars with the allowable error range of the steel bar model, it is possible to determine whether the steel bars meet the acceptance standards at the acceptance time, thereby reducing the judgment error of manual visual inspection and improving the safety of the building structure.

[0087] In addition, reference Fig. 9 Further, in one embodiment, after step S2, there is an additional step: S23, comparing the steel mesh image with the standard steel bar image to determine whether the steel mesh image has rust, cracks and deformation.

[0088] First, crack images are collected through on-site photography, online search, corrosion tests, etc., and a large-scale image dataset is constructed through data enhancement. A convolutional neural network (CNN) model based on deep learning is used to identify corrosion cracks in reinforced concrete in the image dataset and test the deep learning model to output the locations of steel corrosion, cracks, and deformation. In practical applications, the collected steel mesh images are preprocessed, including splicing, resizing, and contrast enhancement, to improve the model's ability to recognize corrosion, cracks, and deformation. Then the steel mesh image is passed through the model to determine whether the current steel mesh image is corroded, cracked, and deformed, and the locations of steel corrosion, cracks, and deformation are output.

[0089] S24. If it exists, the steel mesh image is prevented from obtaining the actual position coordinates of each steel bar through BIM technology, and the result that the steel bar does not meet the acceptance standard is output.

[0090] S25. If it does not exist, the steel mesh image is used through BIM technology to obtain the actual position coordinates of each steel bar.

[0091] In this embodiment, only when the steel mesh image does not detect steel bar corrosion, cracks and deformation, will BIM technology be further used to obtain the actual position coordinates of each steel bar, effectively reducing the burden of front-end data processing and achieving rapid output of steel bar acceptance results.

[0092] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0093] The embodiment of the present application also provides a steel bar acceptance system based on BIM technology and image recognition technology. The steel bar acceptance system based on BIM technology and image recognition technology corresponds one-to-one to the steel bar acceptance method based on BIM technology and image recognition technology in the embodiment.

[0094] refer to Fig.10 , a steel bar acceptance system based on BIM technology and image recognition technology includes: time acquisition module 1, image recognition module 2, coordinate acquisition module 3, steel bar acceptance module 4. The detailed description of each functional module is as follows: Time acquisition module 1: used to obtain the acceptance time of steel mesh in several areas.

[0095] Image recognition module 2: used to obtain the steel mesh image for analysis and recognition if the current time node is the acceptance time of the steel mesh in a certain area.

[0096] Coordinate acquisition module 3: used to obtain the actual position coordinates of each steel bar in the steel mesh image through BIM technology.

[0097] Steel bar acceptance module 4: It is used to calculate the spacing between adjacent vertical steel bars and the spacing between adjacent transverse steel bars in the target steel mesh according to the actual position coordinates of each steel bar, and output the acceptance results on the position, specification, length and spacing of the steel bars.

[0098] Among them, when the image recognition module 2 detects that the current time node is the acceptance time obtained by the time acquisition module 1, it analyzes and recognizes the obtained steel mesh image, effectively avoiding the large amount of data collection and processing requirements brought by real-time monitoring of the steel mesh status; then the steel bar acceptance module 4 calculates and judges the actual position coordinates of each steel bar obtained by the coordinate acquisition module 3, and outputs the acceptance results of the position, specification, length and spacing of the steel bar. Through the combination of various modules, the frequency of front-end data collection and the burden of back-end processing are significantly reduced, and the computing resources required by the system are effectively reduced, and the data processing efficiency is improved, so that the acceptance results of the position, specification, length and spacing of the steel bars can be output more quickly, ensuring the accuracy and timeliness of the acceptance process.

[0099] For the specific definition of the steel bar acceptance system based on BIM technology and image recognition technology, please refer to the definition of the steel bar acceptance method based on BIM technology and image recognition technology in the context, which will not be repeated here. Each module in the above-mentioned steel bar acceptance system based on BIM technology and image recognition technology can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the electronic device in the form of hardware, or can be stored in the memory of the electronic device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

Claims

1. A steel bar acceptance method based on BIM technology and image recognition technology, characterized in that: include: Get the acceptance time of steel mesh in several areas; If the current time node is the acceptance time of the steel mesh in a certain area, the steel mesh image is obtained for analysis and identification; Acquire the actual position coordinates of each steel bar in the steel mesh image by using BIM technology; According to the actual position coordinates of each steel bar, the spacing between adjacent vertical steel bars and the spacing between adjacent transverse steel bars in the target steel mesh are calculated, and the acceptance results of the position, specification, length and spacing of the steel bars are output.

2. The method according to claim 1, characterized in that If the current time node is the acceptance time of the steel mesh in a certain area, the step of obtaining the steel mesh image for analysis and identification includes: If the current time node is the acceptance time of the steel meshes in more than one area, then several steel mesh images reaching the acceptance time are obtained simultaneously; Generating acceptance priorities for the plurality of steel mesh images at the same acceptance time according to the acceptance sequence; According to the acceptance priority, the images are assigned to the image processing queue for identification and analysis.

3. The method according to claim 2, characterized in that The step of generating acceptance priorities according to the acceptance sequence for the plurality of steel mesh images at the same acceptance time comprises: By using BIM technology, the number of key stress-bearing parts of the steel bar model corresponding to the steel mesh images is determined; The plurality of steel mesh images are sorted from most to least according to the number of key stress-bearing locations, and an acceptance priority is generated.

4. The method according to claim 1, characterized in that Before the step of obtaining the acceptance time of the steel meshes in several areas, the method further includes: Set the inspection time of the steel mesh in each area before the acceptance time of the steel mesh in several areas; If the current time node is the inspection time of the steel mesh in a certain area, the steel mesh image of the area is obtained, the steel mesh image is identified and analyzed, and through BIM analysis, the difference in acceptance time of the steel mesh in several areas is obtained, and the acceptance time of the steel mesh is updated.

5. The method according to claim 4, characterized in that If the current time node is the inspection time of the steel mesh in a certain area, the steps of obtaining the steel mesh image in the area, identifying and analyzing the steel mesh image and performing BIM analysis to obtain the difference in the acceptance time of the steel mesh in several areas, and updating the acceptance time of the steel mesh include: During the inspection, the actual position coordinates of each steel bar in the current steel mesh image are obtained through BIM technology, and the number of steel bars installed corresponding to the actual position coordinates is obtained; The actual position coordinates of each steel bar are compared with the steel bar model in the BIM technology to obtain the position coordinates of the missing steel bars in the steel mesh image; Obtain the number of missing steel bars corresponding to the position coordinates of the missing steel bars; Calculate and obtain the steel bar installation efficiency according to the steel bar installation quantity and the steel bar installation time; Calculate and obtain the remaining installation time according to the steel bar installation efficiency and the number of missing steel bars; The remaining installation time is added after the inspection time, and the acceptance time of the steel mesh is updated.

6. The method according to claim 2, characterized in that After the step of generating acceptance priorities according to the acceptance sequence for the plurality of steel mesh images of the same acceptance time, the method further includes: Determine whether there is a steel mesh image whose updated acceptance time is later than the acceptance time before the update among the plurality of steel mesh images listed in the acceptance priority; If there is a steel mesh image, the acceptance order of the steel mesh image is set to the highest acceptance priority; If there is more than one steel mesh image, the acceptance priority is updated in descending order based on the difference between the acceptance time before the update and the current time node.

7. The method according to claim 1, characterized in that The step of obtaining the acceptance time of the steel meshes in several areas includes: Through BIM technology, the construction drawings are converted into three-dimensional models, and the installation progress of the steel mesh is simulated according to the construction drawings. The time when the steel mesh installation is completed in each area is obtained according to the installation progress, and set as the acceptance time of the steel mesh in the area.

8. The method according to claim 1, characterized in that The step of calculating the spacing between adjacent vertical steel bars and the spacing between adjacent transverse steel bars in the target steel mesh according to the actual position coordinates of each steel bar, and outputting the acceptance results of the position, specification, length and spacing of the steel bars comprises: Determine whether the position, specification, length and spacing of the steel bar image are the same as the position, specification, length and spacing of the steel bar model generated by BIM technology within the allowable error range; If they are the same, the output is that the steel bar meets the acceptance criteria; If they are not the same, the output result is that the steel bars do not meet the acceptance criteria.

9. The method according to claim 1, characterized in that: If the current time node is the acceptance time of the steel mesh in a certain area, after the step of acquiring the steel mesh image for analysis and identification, the method further comprises: Comparing the steel mesh image with a standard steel bar image to determine whether the steel mesh image has rust, cracks, and deformation; If it exists, the steel mesh image is prevented from obtaining the actual position coordinates of each steel bar through BIM technology, and a result that the steel bar does not meet the acceptance criteria is output; If it does not exist, the steel mesh image is used through BIM technology to obtain the actual position coordinates of each steel bar.

10. A steel bar acceptance system based on BIM technology and image recognition technology, characterized in that: include: Time acquisition module (1): used to obtain the acceptance time of steel mesh in several areas; Image recognition module (2): used to obtain the image of the steel mesh for analysis and recognition if the current time node is the acceptance time of the steel mesh in a certain area; Coordinate acquisition module (3): used to acquire the actual position coordinates of each steel bar in the steel mesh image by using BIM technology; Steel bar acceptance module (4): used to calculate the spacing between adjacent vertical steel bars and the spacing between adjacent transverse steel bars in the target steel mesh according to the actual position coordinates of each steel bar, and output the acceptance results on the position, specification, length and spacing of the steel bars.

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