Bridge construction supervision method and system based on part management

Abstract

The invention relates to the technical field of bridge construction supervision, and discloses a bridge construction supervision method based on part management, and the method comprises the following steps: S1, carrying out the hierarchical decomposition of a construction project, and guaranteeing the clear task, standard and acceptance content of each level from the project type to the process; s2, generating a three-dimensional section graphic model of each part; the invention also discloses a bridge construction supervision system based on part management, and the system comprises a part decomposition and three-dimensional graph generation module which is used for generating the decomposition model and the three-dimensional section graph of the construction project; and the data acquisition and synchronous updating module is used for acquiring construction data in real time and synchronizing the construction data to the three-dimensional section graphic model. By combining a new thought of'part 'and'process' management and utilizing a three-dimensional section graphic model, a dynamic adjustment mechanism and an intelligent supervision system, problems in traditional construction management are solved, the management precision and efficiency are improved, and high efficiency, precision and intelligence of construction management are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge construction supervision, and in particular to a method and system for bridge construction supervision based on location management. Background Art

[0002] In traditional engineering construction, the construction of a project usually consists of multiple "parts" that are subject to acceptance, and each "part" undergoes at least one construction process. Managers have found that almost all engineering problems, especially those related to progress, quality, safety, environmental protection, and team management, are directly or indirectly closely related to the "parts" and "processes" in the construction process. Therefore, only by rooting control in the management of "parts" and "processes" can the above problems be effectively solved and the overall efficiency of construction management be improved.

[0003] At present, in the field of engineering management, many software products and technologies have been proposed and applied, such as BIM (Building Information Model), U-Shield, QR code, OA office system and integrated management platform. These technologies and tools have promoted the modernization and informatization of engineering management to a certain extent, bringing higher efficiency. However, these traditional systems generally have an obvious defect - they fail to truly generate virtual entity sections based on construction drawings and actual construction methods, and fail to accurately control the "parts" and "processes" during the management process. Specifically, the existing technology cannot realize the three-dimensional visualization of each "part" in the construction drawings, resulting in managers being unable to intuitively grasp the key data such as the construction progress, quality, and resource consumption of each "part". In addition, the existing system lacks a clear process management function, which makes the process content unclear and poorly targeted, resulting in inaccurate process management, inadequate execution of inspection tasks, and insufficient frequency, which ultimately affects the quality and efficiency of construction.

[0004] Furthermore, the software tools in traditional management methods usually have problems such as not being easy to operate, relying on manual data updates, and not being responsive enough, which leads to lengthy management processes and difficulty in timely adjustment of construction progress and quality control. This inefficient management method not only reduces construction efficiency, but also increases project risks.

[0005] Therefore, based on the above defects of the prior art, the present invention proposes a bridge construction supervision method and system based on location management. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides a bridge construction supervision method and system based on position management, which solves the problem that traditional construction management cannot accurately control "position" and "process", progress, quality and safety.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A bridge construction supervision method based on location management, comprising the following steps: S1. Decompose the construction project into layers, from project type to process, to ensure that the tasks, standards and acceptance contents of each level are clear; S2. Generate a three-dimensional cross-sectional graphic model of each part, wherein the three-dimensional cross-sectional graphic model is bound to the construction data and is used to display the structural form, size, progress status, quality status and safety monitoring information; S3, obtain the progress, quality, cost and safety data of the construction site in real time through sensors and data acquisition equipment, and update it synchronously with the 3D cross-section graphic model; S4. Use machine learning algorithms to predict construction progress, assess potential risks based on the prediction results, and use operations optimization techniques to dynamically adjust construction plans and resource allocation based on predicted progress delays and risks; S5. Calculate and adjust the inspection frequency of each process using a quality management strategy, wherein the calculation is based on the quality deviation and target quality value of the process, and adjust the quality control task according to the real-time inspection data; S6. Generate a personalized management interface for managers of different roles to display the process content, task status and data feedback related to their responsibilities; S7. Automatically generate construction reports and integrate data into a unified platform for sharing and storage.

[0008] Preferably, the decomposition step in step S1 specifically includes the following steps: S1.1. Decompose construction projects into multiple engineering types, such as bridges, tunnels, roadbed, pavement, traffic safety and electromechanical; S1.2. Decompose each project type into several physical construction sections, each section representing a specific construction area or task; S1.3. Each construction section is further decomposed into multiple construction acceptance locations, each of which has clear construction tasks, acceptance standards and related information; S1.4. Each construction acceptance site is broken down into several processes, each of which includes specific tasks, process requirements and quality inspection standards.

[0009] Preferably, the three-dimensional cross-section graphic model in step S2 includes the following binding content: The geometric structure information of each construction site, including size, location and shape; Real-time updated progress data, including start time, end time and current status; Quality data, including inspection records, nonconformities and rectification information; Safety data, including risk markers, safety inspection times and monitoring records; Cost data, including material, equipment and labor costs.

[0010] Preferably, the S4 step comprises the following steps: S4.1. Collect real-time construction progress data current and planned progress P planned , calculate the current progress deviation: ΔP = P planned -P current ; S4.2. Use machine learning algorithms to predict possible subsequent schedule delays based on historical data and current deviations; S4.3. Adjust resource allocation based on the optimization model. The optimization goal is: Among them, R i,required is the amount of resources required for a process, R i,allocated The amount of resources allocated.

[0011] Preferably, the quality management in step S5 is achieved by the following steps: S5.1. Calculate the process inspection frequency f check , the calculation formula for inspection frequency is: Among them, f initial is the initial frequency, ΔQ is the mass deviation, Q target is the target quality value; S5.2. Dynamically adjust inspection frequency and generate inspection tasks based on real-time quality inspection data; S5.3. The inspection results are updated synchronously with the three-dimensional cross-section graphic model. When unqualified items occur, warning marks are displayed in the graphics and rectification tasks are generated.

[0012] Preferably, the S3 step specifically includes the following contents: S3.1. Real-time collection of safety data on the construction site, including equipment status, personnel distribution and environmental monitoring data; S3.2. Generate risk alarms based on the deviation between safety data and set standards. The alarm condition formula is: Among them, S j,actual is the actual monitoring value, S j,allowed is the standard value, W j is the weight factor; S3.3. The alarm information is fed back to the three-dimensional cross-sectional graphic model, and the associated risk areas are displayed with warning marks.

[0013] Preferably, the construction report automatically generated in step S7 includes: Construction logs, including records of construction task completion times, schedule deviations, and important events; Quality inspection report, including records of the items, results and rectification status of each quality inspection; Safety inspection records, including the frequency, content and risk items of safety inspections; Expense reporting, including recording actual expenses, budget variances, and material consumption.

[0014] A bridge construction supervision system based on location management, used in conjunction with the above-mentioned bridge construction supervision method based on location management, comprises: The part decomposition and 3D graphics generation module is used to generate decomposition models and 3D cross-sectional graphics of construction projects; Data collection and synchronization update module, used to collect construction data in real time and synchronize it to the three-dimensional cross-section graphic model; Intelligent analysis and optimization module, used for progress forecasting, quality management and resource optimization based on construction data; Personalized management interface module, used to generate dynamic management interfaces for different roles; Automatic report generation module for generating construction logs, inspection records and expense reports; The data integration and sharing module is used to integrate and store construction data and provide shared access functions to managers.

[0015] The present invention provides a method and system for bridge construction supervision based on location management, which has the following beneficial effects: 1. The present invention decomposes the construction project from engineering type to process in a hierarchical manner through innovative "part" and "process" management, ensuring that the tasks, standards and acceptance contents of each level are clarified and detailed, and by generating a virtual three-dimensional cross-sectional graphic model, each "part" and its associated process are visualized during the construction process, which greatly improves the intuitiveness and pertinence of construction management, avoids the problems of "unclear process content" and "unsophisticated decomposition" in traditional methods, and realizes precise control of construction tasks and standards.

[0016] 2. The present invention introduces a dynamic adjustment mechanism to calculate and adjust the inspection frequency of each process in real time, ensuring the real-time and accuracy of quality management. The system automatically adjusts the inspection frequency according to the construction data collected in real time, ensuring the effectiveness of quality inspection and safety control. At the same time, the combination of three-dimensional cross-sectional graphic model and automatic data synchronization update ensures that management personnel can obtain construction data in real time and respond quickly, avoiding the problems of "untimely inspection" and "inefficient management" in traditional methods, and significantly improving the overall efficiency of construction management by reducing manual intervention and improving information updating efficiency.

[0017] 3. The present invention can obtain various data of the construction site in real time by integrating the real-time data collection and synchronous update system, and ensure timely warnings when safety hazards occur through intelligent analysis and automatic alarm mechanisms. By combining with the three-dimensional graphic model, the safety risk area can be displayed in real time, which improves the real-time and accuracy of safety management. In addition, the data integration and sharing platform ensures that all management data of the construction site can be synchronized and shared in real time, improves the collaborative work efficiency among various managers, and fundamentally solves the problems of "safety management lag" and "information islands" in traditional construction management, ensuring that safety and collaboration during the construction process are more efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flow chart of the method of the present invention; Figure 2 It is a framework diagram of the system of the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Please refer to the attached Figure 1 The embodiment of the present invention provides a bridge construction supervision method based on location management, comprising the following steps: S1. Decompose the construction project into layers, from project type to process, to ensure that the tasks, standards and acceptance contents of each level are clear; S2. Generate a three-dimensional cross-sectional graphic model of each part, which is bound to the construction data to display the structural form, size, progress status, quality status and safety monitoring information; S3, obtain the progress, quality, cost and safety data of the construction site in real time through sensors and data acquisition equipment, and update it synchronously with the 3D cross-section graphic model; S4. Use machine learning algorithms to predict construction progress, assess potential risks based on the prediction results, and use operations optimization techniques to dynamically adjust construction plans and resource allocation based on predicted progress delays and risks; S5. Use quality management strategies to calculate and adjust the inspection frequency of each process, calculate process-based quality deviations and target quality values, and adjust quality control tasks based on real-time inspection data; S6. Generate a personalized management interface for managers of different roles to display the process content, task status and data feedback related to their responsibilities; S7. Automatically generate construction reports and integrate data into a unified platform for sharing and storage.

[0021] The decomposition step in step S1 specifically includes the following steps: S1.1. Decompose construction projects into multiple engineering types, such as bridges, tunnels, roadbed, pavement, traffic safety and electromechanical; S1.2. Decompose each project type into several physical construction sections, each section representing a specific construction area or task; S1.3. Each construction section is further decomposed into multiple construction acceptance locations, each of which has clear construction tasks, acceptance standards and related information; S1.4. Each construction acceptance site is broken down into several processes, each of which includes specific tasks, process requirements and quality inspection standards.

[0022] Specifically, in view of the above content, the decomposition process of step S1 is aimed at fine management of construction projects in a hierarchical manner. The process starts with the type of project and decomposes the construction project into several major categories; then, each project type is further refined and divided into specific construction sections, and each section is further decomposed into construction acceptance locations and processes, thus forming a systematic and hierarchical management model. This management method ensures that the tasks and standards at each level are refined and implemented by decomposing layer by layer and clarifying the tasks, standards and acceptance contents, providing strong support for the refined management of the construction process.

[0023] In this embodiment, step S1 first decomposes the construction project into multiple engineering types, such as bridges, tunnels, roadbeds, pavements, traffic safety, and electromechanical, etc. Each engineering type represents a construction field. Different engineering types involve different construction requirements, resource allocation, and acceptance criteria. Therefore, first classifying helps managers to deal with construction tasks in different fields in a targeted manner. In this way, construction management work can be carried out separately according to different engineering types, ensuring that the tasks and goals of each engineering type can receive full attention.

[0024] In step S1.2, each project type is further decomposed into multiple physical construction sections. Each construction section represents a specific construction area or task. These sections can be physical geographical areas or task areas divided according to different stages of the construction process. By dividing the construction project into sections, the specific construction tasks, schedule arrangements and resource allocation involved in each section can be clarified, so as to manage the construction progress and quality more meticulously.

[0025] In step S1.3, each construction section is further subdivided into multiple construction acceptance locations. Each acceptance location has clear construction tasks, acceptance standards and related information. The division of acceptance locations takes into account the various work contents and their standards during the construction process, and can flexibly adjust the tasks, resources and time arrangements of each location according to the actual construction situation. The purpose of this step is to ensure that each construction location has specific goals during the construction process and has clear standards for inspection and acceptance.

[0026] In step S1.4, each construction acceptance site is further decomposed into several processes, each of which defines specific construction tasks, process requirements and quality inspection standards. The division of processes is the most specific decomposition of construction tasks, and each process has a detailed process flow, quality standards and inspection requirements. Through this decomposition, construction managers can more accurately control the execution of each task, ensure the high-quality completion of each process, and promptly discover and correct deviations in construction.

[0027] The core purpose of this decomposition step is to enable each construction task to proceed in an orderly manner through a refined management system, and to be able to carry out effective quality control and progress control at each level, and ultimately achieve the smooth completion of the entire construction project. Through hierarchical decomposition, each stage, each task and each standard can be clarified, avoiding the phenomenon of loose management and unclear tasks in traditional methods, and greatly improving the transparency of the construction process and the accuracy of control.

[0028] The 3D cross-section graphics model in step S2 includes the following binding contents: The geometric structure information of each construction site, including size, location and shape; Real-time updated progress data, including start time, end time and current status; Quality data, including inspection records, nonconformities and rectification information; Safety data, including risk markers, safety inspection times and monitoring records; Cost data, including material, equipment and labor costs.

[0029] Specifically, the binding content of the 3D cross-section graphic model in step S2 aims to visualize the key information in the construction project and update it synchronously with the real-time data in the construction process to improve management efficiency and accuracy. By combining multi-dimensional data such as geometry, progress, quality, safety, and cost, the 3D cross-section graphic model can provide managers with comprehensive and intuitive construction information. This integrated management method can reflect various data in real time during the construction process, helping managers to promptly identify potential problems, make quick responses and adjustments, and thus ensure the smooth implementation of the project.

[0030] In this embodiment, step S2 comprehensively displays all aspects of the construction project by constructing a three-dimensional cross-sectional graphic model containing multiple dimensional information, specifically including the following contents: Geometric information of each construction site: The model contains detailed geometric information of each construction site, including its size, location and shape. In this way, managers can intuitively view the spatial layout and size of each construction site in a 3D view, so as to accurately understand the construction progress and structural changes.

[0031] Real-time updated progress data: The 3D cross-section graphic model is combined with the construction progress data to update the progress of each construction site in real time. This includes the start time, end time and current construction status of each task. This information can reflect the progress of the project in real time, help managers monitor whether the progress is progressing as planned, and promptly identify problems with progress delays and make adjustments.

[0032] Quality data: Quality control is an important part of construction management. The 3D cross-section graphic model will integrate quality data, including inspection records of each process, unqualified items, and rectification information. By binding with quality data, managers can intuitively see whether each construction site meets quality standards, whether there are any problems, and rectification status. This visual quality control method helps improve the efficiency and transparency of quality management.

[0033] Safety data: The 3D graphic model will also be bound to safety management data to display risk markers, safety inspection times, monitoring records, etc. By displaying safety hazards and safety inspection measures taken in real time, the model can effectively support safety management at the construction site and ensure that safety risks are identified and controlled in a timely manner during the construction process.

[0034] Cost data: Cost data is also reflected in the 3D cross-sectional graphic model, covering information such as material, equipment and labor costs. By combining with cost data, managers can track the cost status of each part in real time during the construction process, facilitating budget control and capital scheduling.

[0035] These binding contents make the 3D cross-section graphic model not only a geometric display tool, but also an integrated, real-time updated construction management platform. In this way, managers can view various project information in the model, and then more accurately control the construction progress, quality, safety, cost and other management work. This integrated management method greatly improves the transparency of construction projects, helps managers make more timely and effective decisions, thereby improving construction management efficiency and reducing project risks.

[0036] The S4 step includes the following steps: S4.1. Collect real-time construction progress data current and planned progress P planned , calculate the current progress deviation: ΔP = P planned -P current ; S4.2. Use machine learning algorithms to predict possible subsequent schedule delays based on historical data and current deviations; S4.3. Adjust resource allocation based on the optimization model. The optimization goal is: Among them, R i,required is the amount of resources required for a process, R i,allocated The amount of resources allocated.

[0037] Specifically, first of all, the system collects the progress data of each construction site and process in real time through integrated monitoring equipment and data acquisition modules, including the actual amount of work completed, time nodes, resource usage, etc. At the same time, the system also stores the planned progress of the project, covering the scheduled start and end time of each process. By comparing the actual progress with the planned progress, the progress deviation of each process is calculated.

[0038] Specifically, the schedule deviation is calculated by the following formula: ΔP i =P i actual -P i planned Where: P i actual represents the actual progress of the ith process, P i planned represents the planned progress of the i-th process, ΔP i Represents the progress deviation of the i-th process.

[0039] Through this calculation, the system can accurately understand which processes are progressing smoothly and which processes are experiencing delays or advances in progress, providing data support for the next step of prediction and adjustment.

[0040] In step S4.2, the system combines historical construction data and current progress deviations to predict possible future progress delays using machine learning algorithms. The system first extracts key data from historical construction projects, such as common progress change trends for each process, external influencing factors, and historical delay patterns. By training the machine learning model, the system is able to generate a progress delay prediction model.

[0041] The model not only considers the current progress deviation, but also combines the rules in historical data to predict possible progress problems in the future. Specifically, the output of the model can be expressed as: P i forecast =f(ΔP i ,D i historical ,C i ) Where: P i forecast is the predicted progress of process i, ΔP i is the current progress deviation, D ihistorical is the historical data, including the trend of changes in various construction progress, C i is the external factor that affects the progress change (such as weather, equipment problems, resource supply, etc.), and f is the machine learning model.

[0042] Through this prediction, the system can identify potential construction delays in advance, provide early warning for schedule management, and help project managers make timely adjustments.

[0043] In step S4.3, the system combines the predicted schedule delay information with the optimization model to make reasonable adjustments to the construction resources. The goal of the resource optimization model is to ensure that each process can still obtain sufficient resource support in the event of a schedule delay, thereby eliminating schedule problems caused by insufficient resources as much as possible. The optimization goal is to minimize the difference between the amount of resources required and the amount of allocated resources for each process.

[0044] The specific optimization goal can be expressed by the following formula: Where: R i,required represents the amount of resources required for the i-th process, R i,allocated represents the actual amount of resources allocated to the i-th process, and N is the total number of processes.

[0045] The purpose of this formula is to optimize the allocation of resources by minimizing the deviation between resource allocation and resource demand, so that each process can be completed in the shortest time and reduce the risk of construction delays.

[0046] To achieve this goal, the system will automatically adjust the allocation of resources based on the current progress deviation and progress delay forecast. For example, if a process is behind schedule, the system may increase the resources required (such as adding construction personnel, deploying more equipment, etc.); if a process is ahead of schedule, the system may reduce the resource allocation of the process to avoid waste.

[0047] Through this optimization step, the system can ensure that resources on the construction site are used most effectively, and flexibly respond to progress deviations during the construction process to achieve smooth progress of the construction project.

[0048] Step S4 forms a closed-loop construction progress and resource management mechanism through three major links: progress deviation calculation, progress delay prediction, and resource optimization scheduling. The system can not only monitor the construction progress in real time and predict potential delays, but also reasonably allocate resources through optimization algorithms to ensure that construction tasks are completed on time and improve resource utilization efficiency.

[0049] Quality management in step S5 is achieved through the following steps: S5.1. Calculate the process inspection frequency f check , the calculation formula for inspection frequency is: Among them, f initial is the initial frequency, ΔQ is the mass deviation, Q target is the target quality value; S5.2. Dynamically adjust inspection frequency and generate inspection tasks based on real-time quality inspection data; S5.3. The inspection results are updated synchronously with the three-dimensional cross-section graphic model. When unqualified items occur, warning marks are displayed in the graphics and rectification tasks are generated.

[0050] Specifically, in response to the above content, the quality management in step S5 ensures the accurate implementation of quality control during the construction process through a multi-level dynamic monitoring and adjustment mechanism. First, the system calculates the inspection frequency of each process and adjusts it based on the quality deviation and the target quality value. Then, through the feedback of real-time quality inspection data, the inspection frequency is dynamically adjusted and the corresponding inspection tasks are generated to ensure the real-time and accuracy of quality control. When unqualified items are found in the inspection results, the system will synchronously update the three-dimensional cross-sectional graphic model, display warning marks, and automatically generate rectification tasks. This integrated and automated quality management method greatly improves the quality control efficiency of construction projects, reduces manual intervention, and improves the transparency of the construction process.

[0051] In this embodiment, step S5 includes three key sub-steps: calculation of inspection frequency, dynamic adjustment of inspection tasks, and processing of unqualified items.

[0052] First, the system calculates the inspection frequency of each process based on the quality requirements and actual quality deviation of the process. The calculation formula for the inspection frequency is: Among them, f initial is the initial frequency, ΔQ is the mass deviation, Q target is the target quality value.

[0053] The meaning of this formula is that the inspection frequency of a process is proportional to the quality deviation of the process. The greater the quality deviation, the higher the inspection frequency. Through this mechanism, the system can automatically adjust the quality inspection frequency of each process to ensure that when the process quality deviates, the inspection intensity can be increased, so as to timely discover and solve quality problems.

[0054] In step S5.2, the system dynamically adjusts the inspection frequency of each process based on real-time quality inspection data. If the real-time inspection data shows that the quality deviation of a process is large, the system will automatically increase its inspection frequency and generate new inspection tasks. Inspection tasks will be arranged according to the adjusted frequency to ensure timely detection and handling of quality issues.

[0055] For example, when a process's quality value shows a large deviation, the system will automatically increase the inspection frequency of the process and generate new inspection tasks for quality management personnel. This mechanism can avoid quality risks caused by insufficient inspection frequency in traditional methods, thereby improving the efficiency and accuracy of quality control.

[0056] When the quality inspection results are fed back, the system will update the inspection results and the 3D cross-section graphic model simultaneously. The quality status of each construction site and process will be reflected in the 3D model in real time, and any unqualified items will be displayed with warning marks in the graphics, helping project managers quickly identify problem areas.

[0057] Specifically, if the inspection result of a process fails, the system will display a warning mark at the location of the process in the 3D model, indicating the specific type and location of the unqualified item. At the same time, the system will automatically generate rectification tasks and assign them to relevant responsible personnel for rectification. Rectification tasks include rectification requirements, responsible persons, rectification time nodes, etc., to ensure that rectification work can be completed in a timely and efficient manner.

[0058] For example, if unqualified items are found during the concrete pouring inspection of a certain process, the system will highlight the location in the 3D model and generate rectification tasks to ensure that construction personnel can promptly perform rectification operations according to the rectification requirements, thereby avoiding the further spread of quality problems.

[0059] Step S5 forms a complete closed loop of quality management through accurate inspection frequency calculation, dynamic inspection task adjustment and quality status synchronization of 3D models. The system can not only adjust the inspection frequency according to the actual quality deviation, but also display quality problems in real time and generate rectification tasks through the visual management of 3D graphic models, thus ensuring more efficient and transparent quality management during the construction process. Through this integrated and automated quality control method, the quality of the construction project is effectively guaranteed, human intervention is reduced, and construction efficiency is improved.

[0060] The S3 step specifically includes the following: S3.1. Real-time collection of safety data on the construction site, including equipment status, personnel distribution and environmental monitoring data; S3.2. Generate risk alarms based on the deviation between safety data and set standards. The alarm condition formula is: Among them, S j,actual is the actual monitoring value, S j,allowed is the standard value, W j is the weight factor; S3.3. The alarm information is fed back to the three-dimensional cross-sectional graphic model, and the associated risk areas are displayed with warning marks.

[0061] Specifically, in response to the above content, the core of step S3 is to quickly identify potential safety hazards by real-time collection and analysis of safety data at the construction site, and to issue early warnings for abnormal situations through a risk alarm mechanism. Specifically, the system first collects safety-related data, including equipment status, personnel distribution, and environmental monitoring data. Then, based on the set safety standards, the deviation from the standards is calculated to generate a risk alarm. When the alarm conditions are met, the system will trigger the corresponding warning and feedback to the three-dimensional cross-sectional graphic model, displaying the relevant risk areas in the form of warning marks to ensure that safety managers can identify and deal with risks in a timely manner.

[0062] In this embodiment, step S3 is divided into three main sub-steps: safety data collection, risk alarm generation, and alarm information feedback and three-dimensional model synchronization.

[0063] In step S3.1, the system collects various data related to construction site safety in real time through sensors, monitoring equipment and other data acquisition devices. Safety data mainly includes the following aspects: Equipment status: such as the operating status of mechanical equipment, failure rate, equipment temperature, pressure, etc.

[0064] Personnel distribution: including the real-time location and number of construction workers, whether they are wearing necessary safety equipment, etc.

[0065] Environmental monitoring data: such as temperature, humidity, wind speed, noise, gas concentration and other environmental factors. These data can reflect the environmental safety conditions of the construction site.

[0066] These real-time collected data will serve as the basis for subsequent risk alarms and will be summarized and processed through the system's security monitoring platform.

[0067] In step S3.2, the system compares the real-time collected safety data with the pre-set safety standards and calculates the data deviation. When the deviation exceeds the set threshold, the system triggers a risk alarm to remind relevant personnel to take countermeasures.

[0068] The calculation formula of the alarm condition can be expressed as: Among them, S j,actual is the actual monitoring value, S j,allowed is the standard value, W j is the weight factor.

[0069] When the risk value R of a safety indicator exceeds the set threshold, the system will trigger an alarm to remind relevant managers that there is a safety hazard. For example, if the equipment temperature exceeds the safety standard, the system will calculate the risk value based on the temperature weight factor and trigger an alarm. If the distribution of personnel is abnormal or the environmental parameters exceed the standard, the system will also generate corresponding risk alarms according to the same logic.

[0070] When the system generates a risk alarm, the alarm information will be fed back to the 3D cross-section graphic model in real time. The 3D model can accurately locate each part of the construction site, so when a risk occurs in a certain part or area, the system will display a warning mark in the 3D model of that part. This visual risk prompt can help managers discover safety hazards in the first place and take measures to deal with them.

[0071] Specifically, when a safety risk is triggered (such as equipment failure, abnormal personnel distribution, or excessive environmental parameters), the system will highlight the relevant area in the 3D model and attach specific alarm information. In this way, managers can directly view the specific risk area and alarm content in the 3D model, so as to respond quickly.

[0072] For example, if an equipment abnormality is found in a certain area of ​​the construction site, the system will mark the location of the equipment with a warning mark. After clicking the warning mark, the manager can view the specific status of the equipment, fault information and handling suggestions, helping them to make quick decisions.

[0073] The construction report automatically generated in step S7 includes: Construction logs, including records of construction task completion times, schedule deviations, and important events; Quality inspection report, including records of the items, results and rectification status of each quality inspection; Safety inspection records, including the frequency, content and risk items of safety inspections; Expense reporting, including recording actual expenses, budget variances, and material consumption.

[0074] Please see attached Figure 2 A bridge construction supervision system based on location management is used in conjunction with the above-mentioned bridge construction supervision method based on location management, comprising: The part decomposition and 3D graphics generation module is used to generate decomposition models and 3D cross-sectional graphics of construction projects; Data collection and synchronization update module, used to collect construction data in real time and synchronize it to the three-dimensional cross-section graphic model; Intelligent analysis and optimization module, used for progress forecasting, quality management and resource optimization based on construction data; Personalized management interface module, used to generate dynamic management interfaces for different roles; Automatic report generation module for generating construction logs, inspection records and expense reports; The data integration and sharing module is used to integrate and store construction data and provide shared access functions to managers.

[0075] Specifically, in response to the above content, this bridge construction supervision system based on location management combines multiple modules to improve the transparency, accuracy and management efficiency of the construction process. Through comprehensive data collection and intelligent analysis, the system realizes dynamic management and optimization of various indicators such as construction progress, quality, and safety, helping the project management team to promptly identify potential problems and effectively adjust resources and strategies to ensure that the project proceeds smoothly as planned.

[0076] In this embodiment, the system workflow and the functions of each module are as follows: First, the part decomposition and 3D graphics generation module is responsible for the hierarchical decomposition of the entire construction project. This is done by breaking down the project into multiple engineering types (such as bridges, roadbeds, etc.), and further breaking it down into specific construction sections and "parts", each of which includes detailed tasks and acceptance criteria. The core of this process is to generate a virtual 3D section graphic model, so that construction personnel can intuitively understand the tasks and goals of each construction part, providing a basis for subsequent management. Through 3D graphics, managers can view the construction progress, quality status and resource consumption of each part at any time to ensure that every step of the construction process is under control.

[0077] In terms of data collection, the data collection and synchronization update module collects on-site construction data in real time by installing sensors and data terminal equipment. Data types include progress data, quality data, safety data, resource usage, etc. These real-time data are not only summarized in the background system, but also synchronized and updated to the 3D graphic model, so that the status of each part can be reflected in a timely manner. Construction personnel, quality inspectors and project managers can directly obtain the required data from the 3D model and make decisions quickly.

[0078] The intelligent analysis and optimization module combines the real-time collected data to conduct in-depth progress forecasting, quality monitoring and resource optimization. By learning from the historical data of the construction process, the system can predict possible progress delays and issue early warning signals in a timely manner. For example, if the progress of a certain process deviates from the original plan, the system will give a delay forecast in advance and recommend the deployment of more resources to catch up with the progress. In addition, the module can also dynamically optimize resource allocation according to the resource requirements of each process to ensure that each stage of construction can get sufficient support and avoid waste or shortage of resources.

[0079] In order to meet the needs of different managers, the personalized management interface module provides an operation interface customized according to the role. Project managers can view the overall progress, quality control and resource consumption of the entire construction project; quality management personnel can focus on quality inspection of each process and rectification of unqualified items; construction personnel can view their specific tasks and work progress. This personalized interface design ensures that each user only needs to focus on tasks related to their work, improving the usability and efficiency of the system.

[0080] The automatic report generation module automatically converts all construction data and task progress into standardized reports, such as construction logs, quality inspection records, and expense reports. These reports can be automatically generated and sent to relevant managers, avoiding the tediousness and omissions of manual records and ensuring the accuracy and timeliness of reports. For example, quality inspectors can quickly find unqualified items through automatically generated inspection records and generate rectification tasks to prevent quality problems from being ignored.

[0081] Finally, the data integration and sharing module integrates and manages all construction data by establishing a centralized storage platform. Various types of data (such as progress, quality, safety, resources, etc.) are stored in a unified database, and project managers, construction personnel, supervisors, etc. can access relevant data according to their permissions and view updates in real time. This data sharing mechanism greatly improves the efficiency of information transmission, reduces communication costs, and helps various managers work together on the same platform.

[0082] Through the seamless connection and collaborative work of these modules, all data, progress, quality and resources in the entire construction process can be monitored and managed in real time. The system can not only accurately adjust the construction plan and resource allocation, but also help managers identify potential problems in a timely manner through 3D visualization models to ensure efficient execution of construction quality and progress control.

[0083] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A bridge construction supervision method based on location management, characterized in that: The following steps are involved: S1. Decompose the construction project into layers, from project type to process, to ensure that the tasks, standards and acceptance contents of each level are clear; S2. Generate a three-dimensional cross-sectional graphic model of each part, wherein the three-dimensional cross-sectional graphic model is bound to the construction data and is used to display the structural form, size, progress status, quality status and safety monitoring information; S3, obtain the progress, quality, cost and safety data of the construction site in real time through sensors and data acquisition equipment, and update it synchronously with the 3D cross-section graphic model; S4. Use machine learning algorithms to predict construction progress, assess potential risks based on the prediction results, and use operations optimization techniques to dynamically adjust construction plans and resource allocation based on predicted progress delays and risks; S5. Calculate and adjust the inspection frequency of each process using a quality management strategy, wherein the calculation is based on the quality deviation and target quality value of the process, and adjust the quality control task according to the real-time inspection data; S6. Generate a personalized management interface for managers of different roles to display the process content, task status and data feedback related to their responsibilities; S7. Automatically generate construction reports and integrate data into a unified platform for sharing and storage.

2. A bridge construction supervision method based on location management according to claim 1, characterized in that: The decomposition step in step S1 specifically includes the following steps: S1.

1. Decompose construction projects into multiple engineering types, such as bridges, tunnels, roadbed, pavement, traffic safety and electromechanical; S1.

2. Decompose each project type into several physical construction sections, each section representing a specific construction area or task; S1.

3. Each construction section is further decomposed into multiple construction acceptance locations, each of which has clear construction tasks, acceptance standards and related information; S1.

4. Each construction acceptance site is broken down into several processes, each of which includes specific tasks, process requirements and quality inspection standards.

3. A bridge construction supervision method based on location management according to claim 1, characterized in that: The three-dimensional cross-section graphic model in step S2 includes the following binding contents: The geometric structure information of each construction site, including size, location and shape; Real-time updated progress data, including start time, end time and current status; Quality data, including inspection records, nonconformities and rectification information; Safety data, including risk markers, safety inspection times and monitoring records; Cost data, including material, equipment and labor costs.

4. A bridge construction supervision method based on location management according to claim 1, characterized in that: The S4 step includes the following steps: S4.

1. Collect real-time construction progress data current and planned progress P planned , calculate the current progress deviation: ΔP = P planned -P current ; S4.

2. Use machine learning algorithms to predict possible subsequent schedule delays based on historical data and current deviations; S4.

3. Adjust resource allocation based on the optimization model. The optimization goal is: Among them, R i,required is the amount of resources required for a process, R i,allocated The amount of resources allocated.

5. A bridge construction supervision method based on location management according to claim 1, characterized in that: The quality management in step S5 is achieved by the following steps: S5.

1. Calculate the process inspection frequency f check , the calculation formula for inspection frequency is: Among them, f initial is the initial frequency, ΔQ is the mass deviation, Q target is the target quality value; S5.

2. Dynamically adjust inspection frequency and generate inspection tasks based on real-time quality inspection data; S5.

3. The inspection results are updated synchronously with the three-dimensional cross-section graphic model. When unqualified items occur, warning marks are displayed in the graphics and rectification tasks are generated.

6. A bridge construction supervision method based on location management according to claim 1, characterized in that: The S3 step specifically includes the following contents: S3.

1. Real-time collection of safety data on the construction site, including equipment status, personnel distribution and environmental monitoring data; S3.

2. Generate risk alarms based on the deviation between safety data and set standards. The alarm condition formula is: Among them, S j,actual is the actual monitoring value, S j,allowed is the standard value, W j is the weight factor; S3.

3. The alarm information is fed back to the three-dimensional cross-sectional graphic model, and the associated risk areas are displayed with warning marks.

7. A method for bridge construction supervision based on location management according to claim 1, characterized in that: The construction report automatically generated in step S7 includes: Construction logs, including records of construction task completion times, schedule deviations, and important events; Quality inspection report, including records of the items, results and rectification status of each quality inspection; Safety inspection records, including the frequency, content and risk items of safety inspections; Expense reporting, including recording actual expenses, budget variances, and material consumption.

8. A bridge construction supervision system based on location management, characterized in that: Used in conjunction with a bridge construction supervision method based on location management as described in any one of claims 1 to 7, comprising: The part decomposition and 3D graphics generation module is used to generate decomposition models and 3D cross-sectional graphics of construction projects; Data collection and synchronization update module, used to collect construction data in real time and synchronize it to the three-dimensional cross-section graphic model; Intelligent analysis and optimization module, used for progress forecasting, quality management and resource optimization based on construction data; Personalized management interface module, used to generate dynamic management interfaces for different roles; Automatic report generation module for generating construction logs, inspection records and expense reports; The data integration and sharing module is used to integrate and store construction data and provide shared access functions to managers.

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