Bridge construction safety protection state identification method and system

Abstract

The application provides a bridge construction safety protection state recognition method and system, and relates to the technical field of safety monitoring.The method comprises the following steps: collecting original point cloud data of a bridge construction site; preprocessing the original point cloud data; extracting main point cloud data from the preprocessed original point cloud data according to the spatial distribution characteristics of the point cloud, wherein the main point cloud data comprises bridge deck panel point cloud data and beam body point cloud data; establishing a local coordinate system of the bridge construction site according to the main point cloud data; determining a candidate dangerous area according to the bridge deck panel point cloud data and the local coordinate system; segmenting the candidate dangerous area and the bridge deck panel point cloud data; constructing a topological relationship graph of a bridge construction safety object according to the segmentation result; calculating a construction safety hidden danger judgment index according to the topological relationship graph; outputting a hidden danger type and a hidden danger level according to the construction safety hidden danger judgment index and a preset rule; and determining a hidden danger recognition result according to the hidden danger type and the hidden danger level.

Description

Technical Field

[0001] This invention relates to the field of safety monitoring technology, and in particular to a method and system for identifying the safety protection status of bridge construction. Background Technology

[0002] Bridge construction sites typically involve working at heights, working near edges, assembling bridge decks, connecting beam ends, constructing expansion joints, and installing temporary protective facilities. The spatial arrangement of critical components such as bridge edges, safety nets, protective supports, gaps between bridge decks, expansion joints, and their protective panels directly determines the existence of significant safety risks on site, including falls, missteps, impacts from falling objects, and instability of the work surface. To effectively manage construction safety, it is necessary to quickly, comprehensively, and accurately identify and assess the integrity and effectiveness of the aforementioned protective facilities and hazardous areas.

[0003] Currently, on-site safety inspections mainly rely on manual patrols, image capture, video surveillance, and local instrument measurements. UAV lidar can efficiently acquire three-dimensional point cloud data of bridge construction sites, with advantages such as wide coverage, non-contact acquisition, and complete spatial information. Existing related technologies are mostly used for bridge main structure identification, construction progress statistics, point cloud and BIM model fitting deviation analysis, and general bridge defects detection.

[0004] Existing technologies have many problems: First, they mainly rely on construction model comparison, progress monitoring, or geometric deviation detection, and temporary safety protection components during the construction phase lack completeness, continuity, and effectiveness; second, existing bridge hazard identification systems mostly start from macro risks, video images, or generalized monitoring data, and lack a spatial relationship judgment mechanism based on three-dimensional point clouds; in addition, the output of hazard results mostly stays at the level of abnormal prompts or category identification, and lacks quantifiable safety indicators. Summary of the Invention

[0005] To address the following issues: First, existing bridge hazard identification systems primarily rely on construction model comparison, progress monitoring, or geometric deviation detection, resulting in a lack of complete, continuous, and effective temporary safety protection components during the construction phase; second, existing bridge hazard identification systems often focus on macroscopic risks, video images, or generalized monitoring data, lacking a spatial relationship determination mechanism based on 3D point clouds; and third, the output of hazard results often remains at the level of abnormality alerts or category identification, lacking quantifiable safety indicators. Therefore, this invention provides a method and system for identifying the safety protection status of bridge construction.

[0006] The technical solutions provided by the embodiments of the present invention are as follows: The first aspect of this invention provides a method for identifying the safety protection status of bridge construction, comprising: S1: Collect raw point cloud data from the bridge construction site; S2: Preprocess the raw point cloud data; S3: Based on the spatial distribution characteristics of the point cloud, extract the main point cloud data from the preprocessed raw point cloud data. The main point cloud data includes: bridge deck point cloud data and beam body point cloud data. S4: Based on the main point cloud data, establish a local coordinate system for the bridge construction site; S5: Based on the bridge deck point cloud data and local coordinate system, determine the candidate hazardous areas; S6: Segment the candidate hazardous areas and bridge deck point cloud data to obtain the segmentation results; S7: Based on the segmentation results, construct a topological relationship diagram of the bridge construction safety objects; S8: Calculate the indicators for determining construction safety hazards based on the topology diagram; S9: Output the type and level of the hazard based on the construction safety hazard judgment indicators and preset rules; S10: Determine the hazard identification results based on the hazard type and hazard level.

[0007] A second aspect of the present invention provides a bridge construction safety protection status identification system, comprising: processor; A memory storing computer-readable instructions, which, when executed by the processor, implement the bridge construction safety protection status identification method as described in the first aspect.

[0008] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the bridge construction safety protection status identification method as described in the first aspect.

[0009] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: In this invention, firstly, by collecting and preprocessing the original point cloud of the bridge construction site, a local coordinate system is established and candidate hazardous areas such as edges and gaps are located, limiting the analysis scope to key safety protection areas, with the integrity, continuity, and effectiveness of protective components as the core objectives; secondly, by constructing a topological relationship diagram of bridge construction safety objects, the spatial relationships such as adjacency, support, coverage, and continuity between bridge deck edges, protective nets, supports, gaps, and protective panels are clarified, so as to determine a spatial relationship judgment mechanism based on three-dimensional point clouds; in addition, based on the calculation of the topological relationship diagram, the hazard judgment index can be quantified, and then the hazard type and hazard level are obtained according to the quantified index and preset rules. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a method for identifying the safety protection status of bridge construction, as provided in an embodiment of the present invention.

[0012] Figure 2 This is a structural schematic diagram of a bridge construction safety protection status identification system provided in an embodiment of the present invention. Detailed Implementation

[0013] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0014] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0015] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0016] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0017] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0018] Reference manual attached Figure 1 The diagram shows a flowchart of a bridge construction safety protection status identification method provided by an embodiment of the present invention.

[0019] This invention provides a method for identifying the safety protection status of bridge construction. This method can be implemented by a bridge construction safety protection status identification device, which can be a terminal or a server. The processing flow of the bridge construction safety protection status identification method may include the following steps: S1: Collect raw point cloud data from the bridge construction site.

[0020] Specifically, the raw point cloud data includes: bridge deck point cloud data, beam point cloud data, edge protection net point cloud data, protective support rod point cloud data, gap point cloud data between bridge decks, gap protection plate point cloud data, and surrounding environment point cloud data.

[0021] In one possible implementation, S1 specifically involves: using a drone equipped with a lidar to collect point cloud data of the bridge construction site to obtain raw point cloud data.

[0022] In this embodiment of the invention, a drone equipped with LiDAR collects point cloud data of all types at the construction site. Its core advantages lie in its wide sampling range, comprehensive information dimensions, and high data accuracy. This method can simultaneously cover multiple safety objects such as bridge decks, beams, protective netting, supports, and gaps, fully preserving the three-dimensional geometric features of slender, sparse, and partially obstructed components. Furthermore, it can quickly acquire the instantaneous status of the site through non-contact aerial operations, overcoming the limitations of manual inspection's limited perspective and the lack of depth information in two-dimensional images. This lays a high-quality data foundation for subsequent accurate identification of the integrity and continuity of protective measures.

[0023] S2: Preprocess the raw point cloud data.

[0024] In one possible implementation, S2 specifically involves performing operations on the original point cloud data, including coordinate unification, noise point removal, duplicate point deletion, outlier point filtering, point cloud downsampling, and ground background removal.

[0025] In this embodiment of the invention, by performing preprocessing operations on the original point cloud data, redundant interference information can be effectively removed, data benchmarks can be unified, and point cloud quality can be improved. This can avoid noise and anomalies interfering with subsequent bridge deck extraction, object segmentation, and topology modeling, while also reducing the amount of data and improving computational efficiency. This provides clean, regular, and high-quality data support for the subsequent accurate extraction of safety components and reliable identification of hidden dangers.

[0026] S3: Based on the spatial distribution characteristics of the point cloud, extract the main point cloud data from the preprocessed original point cloud data. The main point cloud data includes: bridge deck point cloud data and beam body point cloud data.

[0027] Specifically, methods such as plane fitting, region growing, supervoxel segmentation, machine learning classification, or deep learning semantic segmentation can be used to extract the main point cloud data.

[0028] In this embodiment of the invention, the point cloud of the bridge deck and the main body of the beam is accurately extracted based on the spatial distribution characteristics of the point cloud. This can first lock the core structure of the bridge, eliminate a large number of non-critical interferences, significantly reduce the data range of subsequent safety analysis, effectively reduce the impact of irrelevant point clouds on the identification of protective components, and at the same time provide a stable and reliable structural benchmark for the subsequent establishment of a local coordinate system and extraction of dangerous areas, significantly improving the overall accuracy and computational efficiency of identification.

[0029] S4: Based on the main point cloud data, establish a local coordinate system for the bridge construction site.

[0030] Specifically, a local coordinate system for the bridge construction scenario is established with the longitudinal direction of the bridge as the X-axis, the transverse direction of the bridge deck as the Y-axis, the vertical height as the Z-axis, and the fitted plane of the bridge deck as the height reference plane.

[0031] In this embodiment of the invention, a local coordinate system is established based on the point cloud of the bridge deck and the main beam body, with the longitudinal direction of the bridge as the X-axis, the transverse direction as the Y-axis, the vertical direction as the Z-axis, and the bridge deck fitting plane as the height reference. This system can provide a unified, stable, and engineering-realistic calculation reference for key geometric parameters such as protection height, support spacing, edge distance, gap width, and protective plate coverage. It avoids the deviation and computational complexity caused by global coordinates, making the quantitative judgment of all safety indicators more accurate, standardized, and in line with the logic of on-site inspection.

[0032] S5: Extract candidate hazardous areas based on bridge deck point cloud data and local coordinate system.

[0033] In one possible implementation, S5 specifically involves: constructing edge buffer zones on both sides of the bridge deck edge line based on the bridge deck point cloud data and the local coordinate system, and using the edge buffer zones as candidate hazardous areas.

[0034] Specifically, candidate hazardous areas can be extracted using methods such as two-dimensional projection boundary extraction, concave hull algorithms, edge point detection, normal abrupt change detection, or bridge deck contour fitting. The width of the edge buffer zone can be set according to construction site management requirements or detection accuracy.

[0035] In this embodiment of the invention, full-scene point cloud analysis is transformed into high-risk area analysis near the edge, reducing interference from background points and irrelevant components, and improving the reliability of identifying slender components such as protective nets and support rods.

[0036] S6: Segment the candidate hazardous areas and bridge deck point cloud data to obtain the segmentation results.

[0037] Specifically, the segmentation results include: bridge deck or bridge plate, edge protection net, protective support rods or poles, gaps or expansion joints between bridge plates, gap protection plates, and point clouds of the beam or background.

[0038] Specifically, during segmentation, multi-scale geometric features and prior knowledge of the bridge construction scenario are introduced. Multi-scale geometric features include local linearity of the point cloud, flatness, verticality, normal variation, abrupt changes in point density, height difference, reflection intensity, and distance from the bridge deck edge. Prior knowledge of the bridge construction scenario includes: protective netting is typically located near the bridge deck edge; support rods are usually slender and vertically or obliquely distributed; gaps between bridge decks typically appear as linear low-density areas or geometrically discontinuous areas; and gap protection panels typically cover the gaps and are approximately coplanar with the bridge deck.

[0039] Furthermore, this step can be implemented using traditional geometric algorithms, machine learning classifiers, point cloud deep learning networks, or a combination thereof. To enhance the recognition of slender components, a slender component enhancement strategy can be set during the segmentation process to enhance the features of objects with high linearity, strong vertical distribution, edge proximity, and sparse point cloud characteristics.

[0040] In this embodiment of the invention, precise segmentation of candidate hazardous areas and bridge deck point clouds can be carried out to specifically extract key construction safety objects such as protective nets, protective supports, gaps between bridge decks, and gap protection plates. This effectively distinguishes between the main structure and temporary protective components, avoids the omission or misclassification of sparse and slender protective features, and provides a reliable object basis for subsequent topological relationship modeling and hazard quantification, greatly improving the pertinence and accuracy of safety status identification.

[0041] S7: Based on the segmentation results, construct a topological relationship diagram of the bridge construction safety objects.

[0042] In one possible implementation, the nodes in the topology diagram specifically include: bridge deck edge segments, protective netting segments, protective supports, gap segments between bridge decks, and gap protection plates.

[0043] Edges between nodes represent spatial relationships, which specifically include: adjacency, covering, supporting, and continuation relationships.

[0044] Specifically, an adjacency relationship is established between "bridge deck edge segment and protective net segment" to determine whether the protective net is continuously laid along the edge.

[0045] Establish a support relationship between "protective netting segments and protective support rods" to determine whether the protective netting has sufficient support.

[0046] Establish the adjacency relationship between "bridge plate-gap segment" to locate dangerous openings between bridge plates.

[0047] Establish the coverage relationship between the "gap segment and the protective plate" to determine whether the gap is effectively covered.

[0048] Establish continuity relationships between adjacent protective netting segments, adjacent protective supports, and adjacent protective panels to identify gaps, interruptions, and insufficient coverage.

[0049] In this embodiment of the invention, a topological relationship graph is constructed based on the segmentation results, which includes nodes such as bridge deck edges, protective nets, protective supports, gaps, and protective panels, as well as spatial relationships such as adjacency, coverage, support, and continuity. This can transform isolated point cloud objects into inferable spatial relational structures, accurately determine whether the protection is continuous, whether the support is reliable, and whether the gaps are effectively covered, upgrading from simply identifying objects to judging safety effectiveness, and providing a scientific and rigorous logical basis for hazard identification.

[0050] S8: Calculate the indicators for determining construction safety hazards based on the topology diagram.

[0051] Specifically, for edge protection status, the calculation includes the total length of the edge, the length that has been protected, the length that has not been protected, the protection continuity rate, the maximum length of protection interruption, the distance between the protective net and the edge of the bridge deck, the protection height, the spacing between the supports, the tilt angle of the supports, and the number of missing supports.

[0052] For the protection status of gaps and expansion joints between bridge decks, calculate the gap length, gap width, exposed gap length, exposed gap area, protective plate coverage length, protective plate coverage area, protective plate coverage rate, overlap width between the protective plate and the gap boundary, and the location of missing or misaligned protective plates.

[0053] The formula for the continuity of protection rate is as follows:

[0054] Among them, C e L represents the continuity rate of edge protection. p L represents the length of the adjacent edge that is effectively protected. e This indicates the total length of the adjacent edge to be detected.

[0055] The formula for the coverage rate of the gap protection panel is as follows:

[0056] Among them, C g Indicates gap coverage, A c A represents the effective coverage area of ​​the protective panel over the gap area. g This represents the total area of ​​the gap region.

[0057] In this embodiment of the invention, the construction safety hazard judgment index is calculated based on the topological relationship diagram. This can transform the spatial topological relationship into a quantifiable, comparable, and verifiable safety parameter, realizing the transformation from qualitative judgment to quantitative assessment. This allows the hazard judgment to no longer rely on experience or subjective judgment, significantly improving the objectivity, accuracy, and persuasiveness of the results, and providing reliable data support for subsequent standardized grading and rectification.

[0058] S9: Output the type and level of hazard based on the construction safety hazard judgment indicators and preset rules.

[0059] Specifically, the types of hazards include: lack of edge protection, interruption of edge protection, insufficient height of edge protection, missing or abnormally spaced protective supports, exposed gaps between bridge decks, insufficient coverage of expansion joint protective panels, and misalignment or partial loss of protective panels.

[0060] Specifically, hazard levels can be categorized as general hazards, significant hazards, and major hazards based on project management requirements, construction safety specifications, or company standards. Judgment rules can employ threshold rules, weighted scoring rules, or multi-indicator comprehensive judgment rules.

[0061] For example, when the unprotected length of a certain edge exceeds a set threshold, or the maximum length of the protection interruption exceeds a set threshold, it is determined to be a potential danger of edge protection interruption. When the coverage of the gap protection panel is lower than a set threshold, or the width or length of the exposed gap exceeds a set threshold, it is determined to be a potential danger of insufficient gap protection.

[0062] It should be noted that those skilled in the art can set preset rules and threshold values ​​according to actual needs, and this invention does not impose any limitations on these settings.

[0063] In this embodiment of the invention, the type and level of a hazard are automatically output based on quantitative hazard judgment indicators and preset rules. This can transform abstract point cloud data and topological relationships into intuitive, standardized, and directly usable safety judgment results, avoiding the subjectivity and variability of manual judgment, realizing the automation, standardization, and unification of hazard identification, and greatly improving the efficiency and authority of on-site safety management.

[0064] S10: Determine the hazard identification results based on the hazard type and hazard level.

[0065] Specifically, the hazard identification results include: hazard number, hazard type, hazard location coordinates, hazard impact range, corresponding geometric parameters, hazard level, 3D point cloud visualization annotation results, rectification suggestions, and inspection report.

[0066] In one possible implementation, after S10, the method further includes classifying the hazard identification results according to preset classification conditions.

[0067] The classification results are displayed in different colors, and a list of construction safety hazards is generated.

[0068] It should be noted that those skilled in the art can set preset classification conditions according to actual needs, and this invention does not limit such settings.

[0069] In this embodiment of the invention, by outputting complete identification results including hazard number, location coordinates, geometric parameters, visual annotations, rectification suggestions and inspection reports, and supporting hazard classification by type, display with different colors, and generation of hazard lists, the identification results can be transformed into management results that are intuitive, readable, locatable, verifiable and capable of closed-loop rectification, which greatly improves the efficiency of hazard investigation, facilitates rapid handling and tracking by management personnel, and truly realizes the complete implementation from intelligent identification to safety management.

[0070] Reference manual attached Figure 2 The diagram shows a structural schematic of a bridge construction safety protection status identification system provided by the present invention.

[0071] The present invention also provides a bridge construction safety protection status identification system 20, applied to the above-mentioned bridge construction safety protection status identification method, comprising: Processor 201.

[0072] The memory 202 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 201, the bridge construction safety protection status identification method as described in the method embodiment is implemented.

[0073] The bridge construction safety protection status identification system 20 provided by the present invention can execute the bridge construction safety protection status identification method described above and achieve the same or similar technical effects. To avoid duplication, the present invention will not elaborate further.

[0074] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0075] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0076] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0077] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0078] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0079] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply 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 invention.

[0080] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0081] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0082] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0083] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0084] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0085] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0086] This invention provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the bridge construction safety protection status identification method as described in the method embodiment.

[0087] The present invention provides a computer-readable storage medium that can implement the steps and effects of the bridge construction safety protection status identification method in the above-described method embodiments. To avoid repetition, the present invention will not elaborate further.

[0088] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0089] The following points need to be explained: (1) The accompanying drawings of the embodiments of the present invention only involve the structures involved in the embodiments of the present invention. Other structures can refer to the general design.

[0090] (2) For clarity, the thickness of layers or regions is enlarged or reduced in the drawings used to describe embodiments of the invention, i.e., these drawings are not drawn to scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being “above” or “below” another element, the element may be “directly” located “above” or “below” the other element or there may be intermediate elements.

[0091] (3) Where there is no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0092] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for identifying the safety protection status during bridge construction, characterized in that, include: S1: Collect raw point cloud data from the bridge construction site; S2: Preprocess the raw point cloud data; S3: Based on the spatial distribution characteristics of the point cloud, extract the main point cloud data from the preprocessed original point cloud data, wherein the main point cloud data includes: bridge deck point cloud data and beam body point cloud data; S4: Based on the main point cloud data, establish a local coordinate system for the bridge construction site; S5: Determine candidate hazardous areas based on the bridge deck point cloud data and the local coordinate system; S6: Segment the candidate hazardous area and the bridge deck point cloud data to obtain the segmentation result; S7: Based on the segmentation results, construct a topological relationship diagram of the bridge construction safety objects; S8: Calculate the construction safety hazard judgment index based on the topology diagram; S9: Based on the construction safety hazard judgment indicators and preset rules, output the hazard type and hazard level; S10: Determine the hazard identification result based on the hazard type and the hazard level.

2. The bridge construction safety protection status identification method according to claim 1, characterized in that, The original point cloud data specifically includes: bridge deck point cloud data, beam point cloud data, edge protection net point cloud data, protective support rod point cloud data, bridge deck gap point cloud data, gap protection plate point cloud data, and surrounding environment point cloud data.

3. The bridge construction safety protection status identification method according to claim 1, characterized in that, Specifically, S1 involves using a drone equipped with a lidar to collect point cloud data of the bridge construction site, thereby obtaining the raw point cloud data.

4. The bridge construction safety protection status identification method according to claim 1, characterized in that, Specifically, S2 involves performing operations on the original point cloud data, including coordinate unification, noise point removal, duplicate point deletion, outlier point filtering, point cloud downsampling, and ground background removal.

5. The bridge construction safety protection status identification method according to claim 1, characterized in that, Specifically, S5 involves: constructing edge buffer zones on both sides of the bridge deck edge line based on the bridge deck point cloud data and the local coordinate system, and using the edge buffer zones as the candidate danger areas.

6. The bridge construction safety protection status identification method according to claim 1, characterized in that, The nodes in the topology diagram specifically include: bridge deck edge segments, protective netting segments, protective supports, gap segments between bridge decks, and gap protection plates; The edges between the nodes represent spatial relationships, which specifically include: adjacency, covering, support, and continuity.

7. The bridge construction safety protection status identification method according to claim 1, characterized in that, The specific results of the hazard identification include: hazard number, hazard type, hazard location coordinates, hazard impact range, corresponding geometric parameters, hazard level, 3D point cloud visualization annotation results, rectification suggestions, and inspection report.

8. The bridge construction safety protection status identification method according to claim 1, characterized in that, Following S10, the following is also included: The hazard identification results are classified according to preset classification conditions; The classification results are displayed in different colors, and a list of construction safety hazards is generated.

9. A bridge construction safety protection status identification system, characterized in that, include: processor; A memory storing computer-readable instructions, which, when executed by the processor, implement the bridge construction safety protection status identification method as described in any one of claims 1 to 8.

10. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions, which, when executed by a processor, implement the steps of the bridge construction safety protection status identification method as described in any one of claims 1 to 8.

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