Bridge construction site multi-source linkage management and control method, system, device and storage medium
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA RAILWAY NO 2 ENG GROUP CO LTD
- Filing Date
- 2026-06-03
- Publication Date
- 2026-07-03
Smart Images
Figure CN122334896A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of construction management technology, specifically to a multi-source linkage control method, system, equipment, and storage medium for bridge construction sites. Background Technology
[0002] In the current construction management of high-speed railway bridges, multiple independent systems are typically deployed at the construction site, including video surveillance, personnel positioning, equipment operation monitoring, environmental sensing, and progress, quality, and safety management. However, the data generated by these systems are isolated and lack a stable correlation mechanism with specific bridge components. This makes it difficult to accurately map alarm information, work records, and on-site images to specific segments or blocks. Work progress relies mainly on manual reporting or offline recording, resulting in significant time lags and information discrepancies with actual on-site progress, making real-time and accurate perception of work status impossible. Furthermore, the electronic fences or risk warning zones used for construction safety control are mostly statically defined before construction. Once set, they remain unchanged throughout the entire work cycle and are difficult to update in a timely manner according to dynamic changes in construction conditions such as changes in crane amplitude, water level fluctuations, and adjustments to the work surface elevation. This easily creates blind spots in prevention and control or triggers false alarms.
[0003] The aforementioned deficiencies result in low levels of precision, low real-time response capability, and low efficiency of automated collaboration in the construction management of high-speed railway bridge sites. Specifically, there is a lack of linkage mechanisms between risk warnings and measures such as equipment movement control, rectification dispatch, and the activation and shutdown of environmental protection facilities. After on-site alarms, manual notifications and paper-based document circulation are often relied upon, leading to long closed-loop cycles and difficulty in guaranteeing effective implementation. Furthermore, incident evidence is scattered across instant messaging records, paper documents, and multiple business systems, resulting in inconsistent sources and formats, making it difficult to form a complete and credible chain of evidence for post-event tracing and responsibility determination. Therefore, there is an urgent need for a management method that can accurately link multi-source data with component processes, dynamically define the scope of risk impact, coordinate the execution of response measures, and reliably record key processes to improve the safety, reliability, and management efficiency of bridge construction sites. Summary of the Invention
[0004] This application provides a multi-source linkage control method, system, equipment, and storage medium for bridge construction sites, which can effectively improve the management efficiency of bridge construction sites, thereby improving the safety and reliability of bridge construction site operations.
[0005] Firstly, this application provides a multi-source linkage control method for bridge construction sites, comprising: collecting multi-source heterogeneous data of bridge construction sites, assigning component codes to target components in the bridge construction sites, establishing corresponding process templates, and establishing a bridge component-process-risk constraint model; aligning the multi-source heterogeneous data in time and space, and binding the multi-source heterogeneous data to the target components based on time matching, spatial distance, and semantic consistency conditions; identifying and updating the process status of the target components through multi-source information cross-confirmation based on the bound multi-source heterogeneous data and the status criteria in the process templates; generating dynamic risk zones and calculating fused risk values based on the location of the target components, the updated process status, on-site perception data, and the bridge component-process-risk constraint model; and executing corresponding risk control outputs based on the fused risk values when risk rules are triggered.
[0006] Optionally, binding the multi-source heterogeneous data to the target component includes:
[0007] The multi-source heterogeneous data is converted to a unified time axis and a unified work point coordinate system; when the difference between the data timestamp and the target process execution time window is less than a preset time threshold, the spatial distance between the data corresponding object and the target component work surface is less than a preset distance threshold, and the data semantic category is consistent with the target process allowed object category, the multi-source heterogeneous data is bound to the target component; when the same data simultaneously meets the binding conditions of multiple target components, it is preferentially bound to the target component with the smallest spatial distance and the highest semantic matching degree.
[0008] Optionally, the step of identifying and updating the process status of the target component through cross-verification of multi-source information includes: updating the process status after making at least two identical conclusion judgments on the data bound to the target component within a preset anti-shake time window; wherein, the transition from the preparation state to the construction state requires the simultaneous satisfaction of: personnel belonging to the permitted operator type staying in the corresponding work area of the target component for a period of time reaching a first threshold, and at least one of the video analysis data and equipment operation data indicating that work corresponding to the target process is being carried out.
[0009] Optionally, the dynamic risk zone includes at least one of the following: high-altitude operation risk zone, hoisting risk zone, water-adjacent construction risk zone, or cross-operation risk zone; the dynamic risk zone is dynamically delineated according to at least one of the following: the geometric boundary of the working surface of the target component, the movement range of the construction equipment, environmental parameters, or personnel and equipment distribution data, as the working conditions change.
[0010] Optionally, the calculation of the risk value includes: normalizing the schedule deviation value, quality anomaly value, safety anomaly value, environmental anomaly value, and cross-operation density value respectively, and then weighting and summing them to obtain a basic score; multiplying the basic score by the process sensitivity coefficient and the environmental correction coefficient, mapping it through a monotonic bounded function and comparing it with a preset threshold to determine the risk level.
[0011] Optionally, the method further includes: generating on-chain evidence storage data containing an event number, a component code of the target component, a process status, a timestamp, and an evidence summary, and writing it into a consortium blockchain jointly participated in by the construction unit, the supervision unit, and the construction unit nodes; and writing the returned transaction number and the off-chain file storage address into the evidence storage index in the digital archive of the target component to support querying historical events and handling records by component.
[0012] Optionally, the method further includes: when the target component is selected in the bridge model or digital twin interface, retrieving the on-chain digest and off-chain file according to the evidence index, calculating the hash of the off-chain file and comparing it with the on-chain digest, and then displaying the events and handling records associated with the component in time series.
[0013] Secondly, this application provides a multi-source linkage control system for bridge construction sites, including: The data configuration module is used to collect multi-source heterogeneous data from bridge construction sites, assign component codes to target components in the bridge construction sites, and establish corresponding process templates. The spatiotemporal binding module is used to align the multi-source heterogeneous data in time and space, and then bind the multi-source heterogeneous data to the target component based on time matching, spatial distance and semantic consistency conditions. The process identification module is used to identify and update the process status of the target component based on the bound multi-source heterogeneous data and the status criteria in the process template through cross-confirmation of multi-source information. The risk management module is used to generate dynamic risk zones and calculate fusion risk values based on the location of the target component, the updated process status, and on-site perception data. The control output module is used to execute the corresponding risk control output according to the fused risk value when a risk rule is triggered, and to store the key information of the risk event on the blockchain.
[0014] Thirdly, this application provides a computer device, the computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the methods described above.
[0015] Fourthly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.
[0016] Compared with existing technologies, the beneficial effects of this application are as follows: By establishing codes, process templates, and risk constraint models for bridge target components, and binding multi-source heterogeneous data to specific components after spatiotemporal alignment, a precise mapping from on-site perception to component-level control is achieved; the process status is identified using a multi-source information cross-confirmation method, avoiding misjudgments or delayed reporting caused by a single data source; based on this, risk zones that change with working conditions are dynamically generated and fused risk values are calculated according to component location, process status, and on-site perception data, combined with the risk constraint model, so that the scope of risk impact is no longer static and fixed, but is adjusted in real time according to lifting amplitude, water level, working surface, etc.; when a risk rule is triggered, hierarchical control output is executed based on the fused risk value. Therefore, the management efficiency of bridge construction sites can be effectively improved, thereby enhancing the safety and reliability of bridge construction. Attached Figure Description
[0017] Figure 1 A schematic diagram illustrating the steps of the multi-source linkage control method for bridge construction sites provided in this application embodiment.
[0018] Figure 2 This is a schematic diagram of a bridge component-process-risk constraint model provided in an embodiment of this application.
[0019] Figure 3 A flowchart of spatiotemporal binding of multi-source data provided in the embodiments of this application.
[0020] Figure 4 The flowchart for automatic identification of process status provided in the embodiments of this application is shown.
[0021] Figure 5 A flowchart for dynamic risk zone and fusion risk assessment provided for embodiments of this application.
[0022] Figure 6 The flowchart for control output and trusted closed-loop archiving provided in the embodiments of this application is shown.
[0023] Figure 7 A diagram of a trusted evidence storage structure for a consortium blockchain provided in this application embodiment. Detailed Implementation
[0024] The present application will now be described in further detail with reference to experimental examples and specific embodiments. However, this should not be construed as limiting the scope of the subject matter of the present application to the following embodiments. All technologies implemented based on the content of the present application fall within the scope of protection of the present application.
[0025] In the description of the embodiments of this application, technical terms such as "first" and "second" only distinguish one entity or operation from another, and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary or secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.
[0026] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0027] Please refer to Figure 1 , Figure 1 A schematic diagram illustrating the steps of the multi-source linkage control method for bridge construction sites provided in this application embodiment. The method may include: S1. Collect multi-source heterogeneous data of bridge construction sites, assign component codes to target components in bridge construction sites, establish corresponding process templates, and establish a bridge component-process-risk constraint model.
[0028] S2. After aligning the multi-source heterogeneous data in time and space, bind the multi-source heterogeneous data to the target component based on time matching, spatial distance and semantic consistency conditions.
[0029] S3. Based on the bound multi-source heterogeneous data and according to the status criteria in the process template, identify and update the process status of the target component through cross-confirmation of multi-source information.
[0030] S4. Based on the location of the target component, the updated process status, the on-site perception data, and the bridge component-process-risk constraint model, generate a dynamic risk zone and calculate the fusion risk value.
[0031] S5. When a risk rule is triggered, execute the corresponding risk control output based on the fused risk value.
[0032] In this embodiment, multi-source heterogeneous data refers to a collection of on-site information with varying structures originating from different sensing devices and business systems. Specifically, this includes video analytics data (such as camera identification results of behaviors like not wearing safety helmets or lingering in restricted areas), personnel positioning data (personnel location and dwell time obtained through positioning terminals or access control systems), equipment operation data (such as tower crane slewing angle, lifting radius, and load status), environmental monitoring data (wind speed, water level, dust, noise, etc.), and business data (progress reports, inspection batch acceptance records, hazard rectification orders, etc.). Target components refer to the basic units requiring precise control during the construction of high-speed railway bridges, such as main tower concrete segments, bridge deck hoisting blocks, or waterfront trestle bridge spans. Component coding is a unique identifier assigned to each target component, used to accurately index the component in 3D models, databases, and various business documents. A process template is a digital definition of the various processes a component goes through from preparation to completion, along with its management rules. It includes at least the process sequence, the judgment conditions required to enter each process state, the types of personnel and equipment allowed to work, the geometric and safety parameters required for risk zone generation, and the weights or sensitivity coefficients required for risk assessment.
[0033] Please refer to Figure 2 , Figure 2 This is a schematic diagram of the bridge component-process-risk constraint model provided in the embodiments of this application. The bridge component-process-risk constraint model is an extended model that integrates risk rules on the basis of the process template. It is used to describe the spatial generation rules of the risk impact range of the target component under different process states and the quantitative calculation method of the comprehensive risk value. Specifically, it includes a risk zone generation parameter set (such as the platform extension width for high-altitude operations, the fall impact radius, the swing safety margin for hoisting operations, and the additional bandwidth of water level deviation for water-adjacent operations) and a risk assessment parameter set (such as the weight coefficient of each risk indicator, the process sensitivity coefficient, and the environmental correction coefficient).
[0034] After aligning the collected multi-source heterogeneous data in both time and spatial dimensions, the data is bound to the corresponding target component based on time matching, spatial distance, and semantic consistency conditions. Time alignment involves converting all data to the same timeline reference. Spatial alignment involves uniformly converting video analysis data (using camera calibration parameters), personnel positioning data (using positioning base station parameters), and component positions (using bridge 3D model coordinate parameters) to the local coordinate system of the bridge construction site. The time matching condition requires that the difference between the data timestamp and the target process's preset execution time window be less than a pre-set time threshold. The spatial distance condition requires that the geometric distance between the object corresponding to the data (e.g., personnel, equipment) and the target component's working surface or spatial center be less than a pre-set distance threshold. The semantic consistency condition requires that the data's semantic category (e.g., "formwork worker," "tower crane hoisting") be consistent with the allowed object categories in the current process's template. Only when all three conditions are met simultaneously is the data bound to the target component.
[0035] After data binding is completed, based on the multi-source heterogeneous data already bound to the target component, and according to the predefined status criteria in the process template of the target component, the current process status of the target component is identified and updated through multi-source information cross-verification. Multi-source information cross-verification means that instead of relying on a single data source, at least two of the following are jointly verified: personnel dwell time, equipment operating status, video recognition results, and business records. The status is only deemed valid when the verification results are consistent. For example, the process status can be divided into preparation, construction, pending acceptance, rectification, and completion. To suppress transient noise or false alarms, the system updates the process status after making at least two identical judgments on multiple data sources bound to the target component within a preset anti-shake time window. Specifically, transitioning from preparation to construction requires the following conditions to be met simultaneously: personnel belonging to the permitted worker type must stay in the work area corresponding to the target component for a period of time reaching a first threshold, and at least one of the video analysis results or equipment operating status indicates that a work activity corresponding to the target process is currently underway.
[0036] Based on the spatial location of the target component in the bridge model, the updated current process status, and on-site perception data (including personnel and equipment distribution data and environmental monitoring parameters), a dynamic risk zone that changes with the construction conditions is generated, and the fusion risk value of the target component is calculated. In this embodiment, the dynamic risk zone no longer uses a static fixed electronic fence, but is a hazardous impact area dynamically delineated based on the current process type (such as high-altitude operation, hoisting operation, water-adjacent operation, or cross-operation), the geometric boundary of the work surface, the movement range of construction equipment, and environmental parameters such as real-time water level or wind speed. For example, for high-altitude operation, the dynamic risk zone can be formed by expanding the horizontal projection outline of the work platform outward by a safe distance, taking the vertical safe margin below the work surface to the height accessible to personnel above to form a columnar range, and then taking the fall impact radius according to specifications or project experience, superimposing the spherical or hemispherical impact range at unfavorable locations such as the platform corners, and merging them into a three-dimensional hazardous zone. The dynamic risk zone is formed by merging the horizontal expansion width of the work platform, the vertical safety margin, and the fall impact radius to form a three-dimensional columnar and spherical combination area. For hoisting operations, the dynamic risk zone is defined by the crane's slewing center and current amplitude, forming a sweeping area on the horizontal plane. The projected load is then expanded outwards according to the swing angle or safety regulations, and the combined area yields the operational risk zone. For operations near water, the dynamic risk zone is offset towards the land side along the water-land boundary by the designed buffer distance, with additional bandwidth added based on changes in the water level relative to the reference level. This area is combined with personnel access and work zones on both sides of the trestle or platform. At night or in severe weather, the environmental correction factor can be increased using templates, or the bandwidth can be widened. For overlapping operations, the dynamic risk zone is defined or its risk level increased according to rules when upper and lower levels or adjacent work surfaces overlap, personnel density is too high at the same time, or machinery trajectories intersect.
[0037] The integrated risk value is a comprehensive quantitative result of multiple risk factors. The system normalizes the progress deviation value, quality anomaly value, safety anomaly value, environmental anomaly value, and cross-operation density value to the same numerical range, and then weights and sums them to obtain a base score. This base score is then multiplied by a sensitivity coefficient corresponding to the current process type and an environmental correction coefficient corresponding to wind speed, water level changes, or nighttime construction. Finally, it is mapped through a bounded monotonic function and compared with a preset threshold to determine the risk level. The integrated risk value normalizes indicators such as progress deviation, quality anomaly, safety violations or alarms, environmental exceedances, and cross-operation congestion to a unified range, then weights and sums them to obtain a base score. This base score is then multiplied by a process sensitivity coefficient and an environmental correction coefficient (such as wind load, water level changes, nighttime construction, etc.), mapped through a monotonic bounded function to a range that is easy to classify, and compared with a preset threshold to obtain the risk level, which is conducive to graded early warning and response.
[0038] When personnel, equipment, or construction events are detected entering the aforementioned dynamic risk zone, or when preset risk rules associated with the current process status are triggered (e.g., entering a high-altitude risk zone without wearing a safety helmet, exceeding environmental monitoring standards, etc.), the corresponding risk control output is executed based on the risk level corresponding to the calculated fused risk value. The control output types can include at least one of the following: on-site audible and visual alarms, mobile terminal message push notifications, area broadcast reminders, rectification work order generation, equipment movement restriction control (e.g., restricting tower crane rotation or hoisting), equipment shutdown control, and activation of environmental treatment equipment (e.g., mist cannons or sprinkler systems). Exceeding environmental standards can also trigger the activation of treatment equipment; the triggering conditions are stored in association with component codes and process status for easy post-event auditing and review.
[0039] Building upon this, the solution provided in this application can further include assigning a unique identifier to each risk event, summarizing information such as component code, process status, time, risk level, executed control outputs, storage path of rectification materials, and acceptance responsibility, and calculating a hash digest. The digest and key fields are written into a consortium blockchain involving construction, supervision, and development nodes, and uploaded to the blockchain in the order of event registration, rectification confirmation, and review confirmation; original images, sensor details, and attachments are stored in off-chain object storage or on the project server. In a BIM or digital twin environment, on-chain transaction identifiers, block information, and off-chain storage addresses are written into the evidence index of the corresponding component's digital file. When querying a component, the system retrieves on-chain and off-chain data based on the evidence index, calculates a hash for the off-chain content, and compares it with the on-chain digest. If they match, the event and handling records are displayed in chronological order; if they do not match, a data integrity error is indicated to support multi-party collaboration and accountability.
[0040] In some embodiments, the step of binding multi-source heterogeneous data to the target component may include: The multi-source heterogeneous data is converted to a unified time axis and a unified work point coordinate system; when the difference between the data timestamp and the target process execution time window is less than a preset time threshold, the spatial distance between the data corresponding object and the target component work surface is less than a preset distance threshold, and the data semantic category is consistent with the target process allowed object category, the multi-source heterogeneous data is bound to the target component; when the same data simultaneously meets the binding conditions of multiple target components, it is preferentially bound to the target component with the smallest spatial distance and the highest semantic matching degree.
[0041] Please refer to Figure 3 , Figure 3This document provides a flowchart for the spatiotemporal binding of multi-source data in embodiments of this application. The unified timeline refers to incorporating the timestamps carried by video analysis data, personnel positioning data, equipment operation data, environmental monitoring data, and business data into the same time base after clock synchronization processing, enabling data from different sources to be compared and correlated at the same time. The unified work site coordinate system refers to using the local coordinate system of the bridge work site as the spatial reference. Video analysis data is mapped from pixel coordinates to the local work site coordinate system through camera calibration parameters; personnel positioning data is mapped from signal space to the local work site coordinate system through positioning base station parameters; and the position of target components is directly transformed to the same local coordinate system through the coordinate parameters of the bridge's 3D model. After unifying the spatiotemporal reference, binding conditions are determined for each piece of multi-source heterogeneous data, and this determination depends on matching conditions in three dimensions.
[0042] The first dimension is the time matching condition, which checks whether the difference between the timestamp of the data and the execution time window of the target process corresponding to the current or planned execution of the target component is less than a pre-set time threshold. The execution time window of the target process refers to the allowed construction period planned for that process in the process template. The time threshold is used to control the accuracy of the time correlation between the data and the process. Only when the data occurrence time is close enough to the planned construction period is the data considered to have a time correlation with the process.
[0043] The second dimension is the spatial distance condition, which checks whether the geometric distance between the object corresponding to the data (e.g., the worker carried by a personnel positioning tag, the work vehicle identified by video, or the tower crane corresponding to the equipment operation data) and the target component's working surface or spatial center in the local coordinate system of the work site is less than a pre-set distance threshold. The working surface of the target component refers to the spatial area occupied by the component in the actual construction operation in the 3D model, such as the platform range of the main tower segment, the projection area of the bridge deck block, or the bridge deck range of the waterfront trestle. The distance threshold is configured separately in the process template or bridge component-process-risk constraint model according to the process type and risk level, and is used to determine the spatial proximity required for data binding.
[0044] The third dimension is the semantic consistency condition, which checks whether the semantic category of the data (e.g., "formwork installation worker" identified by video, "steel rebar worker" reported by the personnel positioning system, "tower crane hoisting operation" in equipment operation data) is consistent with the allowed object categories (e.g., allowed worker types, allowed equipment types) in the current process template of the target component. Only when a piece of multi-source heterogeneous data simultaneously meets the above time matching condition, spatial distance condition, and semantic consistency condition is the data bound to the corresponding target component, thereby establishing a spatiotemporal semantic association between the data and a specific component and a specific process.
[0045] When the same set of data (such as the same personnel positioning coordinates or the same equipment operation record) simultaneously meets the binding conditions of multiple different target components, the data is preferentially bound to the target component with the smallest spatial distance and the highest semantic matching degree. The smallest spatial distance means that after comparing the geometric distances between the object corresponding to the data and the working surfaces of multiple candidate components, the component with the smallest distance value is selected as the priority binding object. The highest semantic matching degree means that, based on the degree of matching between the semantic category of the data and the allowed object categories of the current process of each candidate component, the component with the most matching fields or the highest matching confidence is selected.
[0046] In some embodiments, the step of identifying and updating the process status of the target component through cross-verification of multi-source information may specifically include: Within a preset anti-shake time window, the process status is updated after the data bound to the target component is judged at least twice with the same conclusion. The process status is updated after the process status is changed from the preparation status to the construction status. The following conditions must be met simultaneously: the time that personnel of the permitted operation type stay in the operation area corresponding to the target component reaches a first threshold, and at least one of the video analysis data and equipment operation data indicates that an operation corresponding to the target process is being carried out.
[0047] Please refer to Figure 4 , Figure 4 This document provides a flowchart for the automatic identification of process status in an embodiment of this application. First, the process status of the target component can be divided into five stages: preparation, construction, pending acceptance, rectification, and completion. To prevent incorrect state transitions caused by instantaneous signal fluctuations or single mis-triggered events, a de-jittering time window can be pre-configured in each process template. The de-jittering time window is a fixed-duration window that starts timing from the first observation that the state change conditions are met. Within this time window, all data bound to the target component is repeatedly judged to the same conclusion. Only when two or more consecutive judgments within the de-jittering time window are completely consistent is the process status of the target component allowed to change from the current state to the next state.
[0048] Specifically, the critical transition from the preparation state to the construction state requires simultaneous verification of two independent conditions, neither of which can be omitted. The first condition is personnel presence: based on personnel location data bound to the target component, it is determined whether personnel belonging to the permitted worker type defined by the current process template of the target component exist (e.g., the template process requires template workers rather than concrete workers), and whether the continuous stay time of these personnel within the corresponding work area of the target component reaches a pre-set first threshold. The work area refers to the permissible work range delineated in the local coordinate system of the work site based on the geometric boundaries of the target component in the 3D model and its construction process requirements. The first threshold is configured in the process template according to the degree of danger and the continuity requirements of the operation; for example, it can be set to 3 minutes for the main tower template installation process.
[0049] The second condition is the work activity verification condition: Checking the video analysis data and equipment operation data bound to the target component, at least one item indicates that a work activity corresponding to the target process of that component is currently in progress. For video analysis data, this means that cameras deployed around the work area, through image recognition algorithms, show work behaviors matching the characteristics of the target process, such as workers tightening formwork bolts or tying rebar. For equipment operation data, this means that the operating status records of construction equipment related to the target process (such as tower cranes, construction hoists, concrete pump trucks, etc.) show that the equipment is performing an operation matching that process; for example, tower crane lifting and slewing records indicate that formwork or rebar hoisting is underway. Only when both the personnel presence condition and the work activity verification condition are met simultaneously will a "permit to switch to construction" judgment be accumulated once within the anti-shake time window.
[0050] If the same "Allow to switch to construction" judgment is obtained more than twice consecutively within the anti-shake time window, the process status of the target component will be updated from "Preparation" to "Construction". Conversely, if the personnel stay condition does not reach the first threshold in any judgment within the anti-shake time window, or if neither the video analysis data nor the equipment operation data indicates that the operation is in progress, the judgment conclusion will be "Do not allow to switch to construction", the status update will not be performed, and the anti-shake time window will be reset.
[0051] In some embodiments, the spatial reference of the risk zone is determined based on the three-dimensional spatial position of the target component in the local coordinate system of the work site; the corresponding risk zone generation rule is selected based on the updated process status (e.g., high-altitude operation, hoisting operation, water-adjacent operation, or cross-operation); the risk zone boundary is dynamically adjusted based on information such as personnel and equipment distribution, wind speed, and water level in the on-site perception data; and specific calculations are performed based on the risk zone generation parameter set (e.g., outward expansion width, fall radius, swing margin, water level offset bandwidth, etc.) pre-stored in the bridge component-process-risk constraint model.
[0052] Dynamic risk zones are categorized in several ways depending on the type of work process. For high-altitude work risk zones, the bottom area is first determined by extending the projected boundary of the work platform on the horizontal plane as a reference, according to the width preset in the risk zone generation parameter set. Then, in the vertical direction, a columnar area is formed by extending from the preset safety margin height below the work surface to the maximum height that personnel can reach above the work surface. Next, a spherical or hemispherical area is generated with the component edge or platform corner as a reference point and the fall impact radius as the radius. Finally, the columnar area and the spherical or hemispherical area are geometrically merged to obtain a three-dimensional area used to determine whether personnel have entered the high-altitude danger zone. For hoisting risk zones, the hoisting object projection range is extended outward based on the rotation center coordinates of the tower crane or crawler crane, the current horizontal projection reachable range of the boom, and the ground projection outline of the hoisted object, combined with the preset swing safety margin in the risk zone generation parameter set. The above three ranges are then merged to obtain the hoisting no-go zone. For waterfront construction risk areas, a basic buffer zone is obtained by offsetting the riverbank or embankment interface towards the landward at a preset distance, using the riverbank or embankment interface as the baseline. Then, based on the difference between the measured water level and the baseline water level, an additional offset is added according to the additional width corresponding to each unit water level preset in the risk area generation parameter set. Finally, this area is merged with the personnel activity areas on both sides of the trestle or work platform to obtain the waterfront risk area. For cross-operation risk areas, dynamic delineation is carried out based on whether the work surfaces of upper and lower layers or adjacent processes overlap on the vertical projection plane, whether the personnel density reflected by the location data bound in the same time period exceeds the threshold, and whether the operating trajectories of multiple machines intersect.
[0053] After generating the dynamic risk zone, the integrated risk value of the target component is calculated. The integrated risk value is a quantitative indicator that comprehensively reflects the degree of risk of the current construction activities in multiple dimensions such as progress, quality, safety, environmental protection, and cross-operations. The weight coefficients of each item are read from the risk assessment parameter set in the bridge component-process-risk constraint model; progress deviation values and quality anomalies are obtained from business data; safety anomalies are obtained from safety alarm records; environmental anomalies are obtained from environmental monitoring data; and cross-operation density values are calculated from personnel location and equipment operation data.
[0054] Please refer to Figure 5 , Figure 5 A flowchart illustrating the dynamic risk zone and fusion risk assessment provided for embodiments of this application. The specific expression of the fusion risk assessment formula is as follows:
[0055] in, This indicates the total number of risk indicators involved in the risk assessment, such as schedule deviation, quality anomaly, safety anomaly, environmental anomaly, and cross-operation density, totaling five indicators. These are the index numbers of the risk indicators, ranging from 1 to n, corresponding to each specific risk dimension. Indicates the first The dimensionless values obtained after normalization of each risk indicator are: The value range is [0,1], where 0 represents no risk in this dimension and 1 represents the highest risk in this dimension. Indicates the first The weighting coefficients of each risk indicator in the integrated assessment are pre-configured by the risk assessment parameter set in the bridge component-process-risk constraint model according to the current process type (e.g., the safety weight of a high-altitude process is higher than the schedule weight), and the sum of all weighting coefficients is 1. The first term in the formula... This is the weighted summation part, which multiplies the value of each risk indicator by its corresponding weight and then sums them up to obtain a linear basic risk score. The second term... This is the product correction part, which transforms each risk indicator: 1 and... After adding them together, the weight of the indicator is used. The exponent is raised to the power of the index, and then the results of all the indicators are multiplied together. This product term introduces a coupling effect between indicators on top of the linear weighting; when multiple risk indicators are simultaneously high, the product term will significantly amplify the effect. The value of this value reflects the nonlinear growth characteristic of comprehensive risk caused by the superposition of multiple risk factors. Adding the weighted summation term to the product correction term yields the aggregated value of the basic risk. .
[0056] Aggregate the basic risk value When input into a monotonically bounded mapping function, the formula is expressed as:
[0057] In the formula, represents the final fusion risk value, with its range compressed to the (0,1) interval for easy comparison with the preset risk level threshold. The sigmoid function is an S-shaped curve function, and its mathematical form is: It can map any real number input to the interval (0,1). The slope control coefficient is a positive real number, configured by the risk assessment parameter set in the bridge component-process-risk constraint model according to the hazard sensitivity of the process. The larger the value, the steeper the slope of the function curve near zero, i.e., the higher the risk value. The more sensitive to changes; The smaller the value, the flatter the curve. The offset coefficient is a real number used to adjust the center position of the entire function, so that... Output at a certain typical value It can fall precisely near the preset medium-risk threshold. The calculated... Substitute into the formula and first calculate the linear transformation. The result is then used as input to the sigmoid function, and the final output is the fusion risk value. .Will By comparing the risk level of the target component with the low-risk, medium-risk, and high-risk thresholds preset in the bridge component-process-risk constraint model, the risk level of the current target component is determined. This risk level will serve as the direct basis for subsequent execution control outputs.
[0058] In some embodiments, after completing the dynamic risk zone generation and risk value calculation, the method provided in this application further performs trusted evidence storage and traceability query operations to form a complete closed loop from risk identification to handling and record-keeping. The method provided in this application may also include: Generate on-chain evidence storage data containing event number, component code of the target component, process status, timestamp, and evidence summary, and write it into a consortium blockchain jointly participated in by the construction unit, supervision unit, and construction unit nodes; write the returned transaction number and off-chain file storage address into the evidence storage index in the digital archive of the target component to support querying historical events and handling records by component.
[0059] Please refer to Figure 6 , Figure 6 This is a flowchart illustrating the control output and trusted closed-loop archiving process provided in this application embodiment. The process sequentially includes eight stages: risk event triggering, risk level determination, control output, rectification execution, review and confirmation, evidence digest generation, consortium blockchain uploading, and archive write-back.
[0060] A risk event is triggered when personnel, equipment, or construction events are detected entering the dynamic risk zone, or when the fused risk value exceeds a preset threshold. The risk level is determined based on the calculated range of the fused risk value: the fused risk value is compared with preset low-risk, medium-risk, and high-risk thresholds in the bridge component-process-risk constraint model to determine whether the current risk event belongs to a low-risk, medium-risk, or high-risk level. Different risk levels correspond to different handling strategies.
[0061] Based on the determined risk level, corresponding control outputs are executed. These control outputs include five types: 1) Audible and visual alarms: flashing lights and alarm sounds are emitted from alarm lights and buzzers deployed on-site to warn personnel to immediately leave the danger zone; 2) Message push: notifications containing the location, risk level, and component information of the risk event are sent to project managers, safety officers, or team leaders via mobile terminal messaging services; 3) Broadcast reminders: risk warnings are broadcast to all personnel in a specific work area via a regional broadcast system deployed on-site; 4) Rectification work order generation: a work order containing a risk event description, target component code, responsible department, rectification deadline, and closure requirements is automatically created in the rectification work order system and assigned to a designated person; 5) Equipment restriction or shutdown control: instructions are sent to the control systems of machinery such as tower cranes and construction hoists through the equipment control interface to restrict their rotation, lifting, or other actions, or to directly stop equipment operation. The above five control output methods can be combined and executed according to the risk level. For example, at a high risk level, sound and light alarms, message push, broadcast reminders, rectification work order generation and equipment shutdown control are triggered simultaneously. At a medium risk level, message push and rectification work order generation are triggered but equipment shutdown is not triggered.
[0062] After the control output is completed, the rectification execution process is tracked. Rectification execution refers to the assigned person responsible for rectification organizing on-site rectification according to the requirements specified in the rectification work order after receiving it. This includes tasks such as clearing out personnel who have illegally entered the risk area, reinforcing edge protection facilities, adjusting the hoisting operation range, or starting environmental protection equipment. After completing the on-site rectification, the person responsible for rectification uploads rectification completion confirmation materials to the rectification work order system, including photos of the rectified site, a description of the rectification measures, and the rectification completion time.
[0063] After rectification is completed, the process moves to the review and confirmation stage. Review and confirmation refers to the on-site verification or document review conducted by relevant personnel from the supervision unit or construction unit to determine whether the rectification has met the expected safety standards. If the review and confirmation is successful, the reviewer fills in the review comments, review time, and uploads the review signature record in the system. If the review and confirmation is unsuccessful, the system returns the rectification work order to the person responsible for rectification, requiring re-rectification and resubmission for review.
[0064] After the review and confirmation are passed, the evidence digest generation operation is performed. A globally unique event number is assigned to this risk event, and key information fields are extracted from the entire processing flow, including the event number, the component code of the target component, the current process status, the timestamp of the risk event trigger, the risk level, the control output type, the rectification conclusion, the review conclusion, and the location information of the on-site attachments. The on-site attachments include the file path of the video clip when the alarm was triggered in off-chain storage, the file address of the sensor abnormal data record, the storage address of the photos before and after rectification, and the storage path of the review signature record. The above key fields are concatenated into a string, and a hash operation is performed on the string to obtain a fixed-length evidence digest. The hash operation is a one-way encryption transformation; any slight modification to the original data will result in a completely different hash value. Therefore, the evidence digest is used to subsequently verify the integrity and tamper-proof nature of the original evidence.
[0065] The generated evidence summary, along with key fields such as event number, component code of the target component, process status, and timestamp, constitutes on-chain evidence storage data and is written to the consortium blockchain. The consortium blockchain is a blockchain network jointly maintained by construction unit nodes, supervision unit nodes, and construction unit nodes. Following the business sequence of first registering the event, then confirming rectification, and finally confirming review, the evidence storage data is written to the consortium blockchain in three stages: The first write occurs after a risk event is triggered and control output is executed, registering basic event information; the construction unit node initiates the transaction, which is confirmed by consensus among the supervision and construction unit nodes. The second write occurs after rectification is completed and the person responsible for rectification submits confirmation materials; the evidence summary of the rectification conclusion and rectification attachments is appended to the on-chain record corresponding to the event number, initiated by the construction unit node and confirmed by the supervision unit node. The third write occurs after review confirmation; the evidence summary of the review conclusion and review attachments is written to the blockchain. After each write operation, the consortium blockchain returns the transaction number corresponding to this transaction and the block information packaged for that transaction.
[0066] While the data is uploaded to the consortium blockchain, complete original evidence data is stored off-chain. Off-chain storage refers to storing large amounts of original files (such as complete video clips triggered by alarms, high-frequency sensor detail data, high-resolution photos before and after rectification, etc.) on the project's local object storage server or dedicated file server, rather than directly writing these large files to the blockchain. A unique off-chain file storage address is generated for each original file stored off-chain.
[0067] Finally, the file write-back operation is performed. File write-back refers to writing the transaction number, block information, and off-chain file storage address returned by the consortium blockchain into the evidence index in the digital file of the target component. The digital file of the target component is a digitized collection of all management information of the component throughout its entire lifecycle. The evidence index is a structured data object in the digital file specifically used to store trusted evidence-related information. It records a list of evidence information for all risk events associated with the component. Each evidence information entry includes the event number, transaction number, block height, off-chain file storage address, and write time.
[0068] Furthermore, the method provided in this application may also include: When the target component is selected in the bridge model or digital twin interface, the on-chain digest and off-chain file are retrieved according to the evidence index. After the hash of the off-chain file is calculated and compared with the on-chain digest, the events and handling records associated with the component are displayed in time series.
[0069] Please refer to Figure 7 , Figure 7 This is a diagram illustrating the trusted evidence storage structure of a consortium blockchain provided in this application embodiment. After completing the aforementioned on-chain evidence storage and file write-back operations, the method provided in this application can further support historical event tracing and querying based on a bridge model or digital twin interface. When a user selects a target component in the bridge 3D model or digital twin interface displayed on the management platform by clicking or touching, the management platform reads the corresponding evidence storage index from the digital archive based on the component code of the selected target component.
[0070] The evidence index records a list of evidence information for all risk events associated with the target component. Each evidence entry includes an event number, on-chain transaction number, block height, and off-chain file storage address. Based on the on-chain transaction number and block height in the evidence index, the management platform initiates a query request to the consortium blockchain composed of construction unit nodes, supervision unit nodes, and construction unit nodes to obtain on-chain summary data for all risk events associated with the target component. The on-chain summary data contains an evidence digest for each risk event. This evidence digest is a fixed-length string obtained by hashing the key fields of the risk event and the location information of on-site attachments. The key fields include the event number, the component code of the target component, the process status, the risk level, the rectification conclusion, and the review conclusion. The location information of on-site attachments points to the off-chain storage path of the original files such as on-site photos, on-site videos, sensor records, rectification records, and review conclusions.
[0071] The management platform also retrieves the corresponding original evidence files from the off-chain object storage based on the off-chain file storage address in the evidence storage index. The original evidence of risk events stored in the off-chain object storage includes, but is not limited to: on-site video clips when alarms are triggered, on-site photos (such as images of personnel illegally entering dynamic risk areas), sensor records (such as time-series data of abnormally high wind speeds or rising water levels), rectification records uploaded during the rectification process (including on-site comparison photos before and after rectification), and review conclusion documents submitted by the supervision unit or construction unit.
[0072] Before presenting the original evidence files to the user, the control platform performs integrity verification on each original evidence file stored off-chain. The control platform recalculates the hash value of each retrieved original evidence file, obtaining a new hash result. The control platform compares this newly calculated hash value with the original hash value in the evidence digest obtained from the consortium blockchain. If the two hash values match exactly, it proves that the original evidence file stored off-chain has not been modified in any way since being written to the off-chain object storage, and data integrity is confirmed. If the two hash values do not match, it indicates that the original evidence file stored off-chain may have been corrupted or tampered with. In this case, the control platform displays a data integrity error message on the interface, requiring the user to contact the IT management personnel to verify the consistency between the off-chain storage and the digest data on the consortium blockchain.
[0073] Provided the hash comparison results are consistent, the management platform displays all events and handling records associated with the target component in a time-series format on the bridge model or digital twin interface. Each record includes the specific time point when the risk event was triggered, the event type, the risk level corresponding to the merged risk value, the type of control output executed, the rectification status, the review conclusion, and a clickable link to the original evidence files. Users can click on any historical event record to view the complete handling process of the event from risk triggering, control output, rectification execution to review confirmation, as well as all original evidence materials verified by hash integrity.
[0074] In the aforementioned implementation process, by establishing codes, process templates, and risk constraint models for bridge target components, and binding multi-source heterogeneous data to specific components after spatiotemporal alignment, precise mapping from on-site perception to component-level control was achieved. The process status was identified using a multi-source information cross-confirmation method, avoiding misjudgments or delayed reporting caused by a single data source. Based on this, risk zones that change with working conditions were dynamically generated and fused risk values were calculated according to component location, process status, and on-site perception data, combined with the risk constraint model. This ensured that the scope of risk impact was no longer static but adjusted in real time according to lifting amplitude, water level, and working surface. When a risk rule was triggered, hierarchical control output was executed based on the fused risk value. Therefore, the management efficiency of bridge construction sites can be effectively improved, thereby enhancing the safety and reliability of bridge construction.
[0075] The following description uses common working conditions at high-speed railway cable-stayed bridge construction sites as an example. Those skilled in the art can make equivalent substitutions for parameters without departing from the spirit of this invention, and this should not be considered a limitation on the scope of protection of this invention. During deployment, pilot projects should be prioritized at construction sites with complex structures and frequent overlapping operations. Verified process templates, along with parameters such as time, distance, and anti-shake, should be compiled into configuration packages for use by other bridge construction sites within the same contract section or in subsequent projects, thereby reducing the costs of redundant development and on-site parameter adjustments.
[0076] Example 1: High-altitude operation of main tower segment The main tower of a cable-stayed bridge is currently under construction, with the Nth tower section denoted as component `CN`. Related procedures include reinforcement inspection, formwork installation, and concrete pouring. Fixed cameras are installed around the perimeter of the work platform, and workers wear positioning terminals. Tower crane operation data and wind speed monitoring are connected to the platform.
[0077] Within the 90-second anti-shake time window, if two consecutive judgments meet the following conditions: the positioning shows that the template operator has stayed on the `CN` platform for more than 3 minutes, and the tower crane has a lifting record or video analysis identifies the template approaching a segment, then the process status of `CN` will be updated to "Template installation in progress". A high-altitude risk zone is generated by extending the platform horizontally by 1.5 m, vertically above the work surface by 2 m, and leaving a 1 m safety margin below, with a fall impact radius of 6 m. If personnel are detected entering this area without wearing safety helmets, an audible and visual alarm is triggered, and a message is pushed to the safety management personnel's mobile terminal, while a rectification work order is generated. After the rectification materials are uploaded and accepted by the supervisor, the evidence summary and on-chain transaction identifier are written into the `CN` digital archive. Selecting `CN` in the model allows querying this event and its handling record.
[0078] Example 2: Bridge Deck Component Lifting and Cross-operation A certain bridge deck component is hoisted and designated as `BM`. The tower crane's slewing angle, amplitude, and the height of the lower edge of the hoisted object above the ground are collected. A slewing sweep zone and the horizontal projection of the hoisted object are generated on the ground, and the projection is extended outward by 1 m according to swing safety requirements. If welding operations are conducted on the lower level at the same time and personnel enter the merged ground restricted area, the risk of cross-operation is considered increased. The merged risk value is increased, an alarm is broadcast, and the tower crane's continued slewing is restricted until personnel are evacuated to a safe area.
[0079] Example 3: Waterfront Operations Near a Riverbank A span of the waterfront trestle is designated as component `WK`. Daily water level gauge data is read; if the water level rises by 0.3 m relative to the dry season baseline, the existing 5 m landside buffer zone is increased by 0.5 m. During nighttime construction, nighttime working condition indicators are activated in the formwork to improve the environmental correction factor. If personnel are detected lingering near the waterside boundary for more than 2 minutes, an evacuation alert is sent to the on-site supervisor's mobile terminal.
[0080] Example 4: Evidence Preservation and Component-Based Query After the incident handling loop is closed, the system concatenates fields such as incident number, component code, process status, risk level, timestamp, and rectification conclusion to calculate a hash value H. The construction unit node submits H and summary information to the consortium blockchain to complete the incident registration; the supervision unit and the construction unit confirm on the blockchain after rectification and review are completed, respectively. The transaction identifier, block height, and attachment storage path returned on the blockchain are written into the JSON format evidence index of the component's digital file. After the user opens the 3D model and selects the component on the terminal, the system retrieves on-chain and off-chain data based on the evidence index, calculates the hash of the attachment, and compares it with the on-chain summary; if they match, the record is displayed on a timeline; if they do not match, the user is prompted to contact the information management personnel to verify the consistency between the stored and on-chain data.
[0081] Based on the same concept, this application also provides a multi-source linkage control system for bridge construction sites, which may include: The data configuration module is used to collect multi-source heterogeneous data from bridge construction sites, assign component codes to target components in the bridge construction sites, and establish corresponding process templates. The spatiotemporal binding module is used to align the multi-source heterogeneous data in time and space, and then bind the multi-source heterogeneous data to the target component based on time matching, spatial distance and semantic consistency conditions. The process identification module is used to identify and update the process status of the target component based on the bound multi-source heterogeneous data and the status criteria in the process template through cross-confirmation of multi-source information. The risk management module is used to generate dynamic risk zones and calculate fusion risk values based on the location of the target component, the updated process status, and on-site perception data. The control output module is used to execute the corresponding risk control output according to the fused risk value when a risk rule is triggered, and to store the key information of the risk event on the blockchain.
[0082] It should be understood that when the various modules of the system provided in the above embodiments are working, the division of each functional module in the above description is only used as an example. In actual applications, the above functions can be assigned to different functional modules as needed. That is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.
[0083] The functional modules in the above embodiments 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. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of the embodiments of this application.
[0084] Based on the same concept, embodiments of this application also provide a computer device, which may include a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the methods described above.
[0085] Based on the same concept, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.
[0086] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A multi-source coordinated control method for bridge construction sites, characterized in that, include: Collect multi-source heterogeneous data from bridge construction sites, assign component codes to target components in the bridge construction sites, establish corresponding process templates, and establish a bridge component-process-risk constraint model. After aligning the multi-source heterogeneous data in time and space, the multi-source heterogeneous data is bound to the target component based on time matching, spatial distance and semantic consistency conditions; Based on the bound multi-source heterogeneous data and according to the status criteria in the process template, the process status of the target component is identified and updated through cross-confirmation of multi-source information. Based on the location of the target component, the updated process status, the on-site perception data, and the bridge component-process-risk constraint model, a dynamic risk zone is generated and a fused risk value is calculated. When a risk rule is triggered, the corresponding risk control output is executed according to the fused risk value, and the key information of the risk event is stored on the blockchain.
2. The multi-source linkage control method for bridge construction sites according to claim 1, characterized in that, The step of binding the multi-source heterogeneous data to the target component includes: The multi-source heterogeneous data is converted to a unified time axis and a unified work point coordinate system; When the difference between the data timestamp and the target process execution time window is less than a preset time threshold, the spatial distance between the data corresponding object and the target component working surface is less than a preset distance threshold, and the data semantic category is consistent with the target process allowed object category, the multi-source heterogeneous data is bound to the target component. When the same data simultaneously meets the binding conditions of multiple target components, it is preferentially bound to the target component with the smallest spatial distance and the highest semantic matching degree.
3. The multi-source linkage control method for bridge construction sites according to claim 1, characterized in that, The process status identification and updating of the target component through multi-source information cross-verification includes: Within a preset anti-shake time window, the process status is updated after the data bound to the target component is judged with the same conclusion at least twice. Specifically, the transition from the preparation state to the construction state requires the following conditions to be met simultaneously: personnel belonging to the permitted worker type must stay in the work area corresponding to the target component for a period of time reaching a first threshold, and at least one of the video analysis data and equipment operation data must indicate that work corresponding to the target process is being carried out.
4. The multi-source linkage control method for bridge construction sites according to claim 1, characterized in that, The dynamic risk zone includes at least one of the following: high-altitude operation risk zone, hoisting risk zone, water-adjacent construction risk zone, or cross-operation risk zone; the dynamic risk zone is dynamically delineated according to at least one of the following: the geometric boundary of the working surface of the target component, the movement range of the construction equipment, environmental parameters, or personnel and equipment distribution data, as the working conditions change.
5. The multi-source linkage control method for bridge construction sites according to claim 1, characterized in that, The calculation of the fusion risk value includes: The basic score is obtained by normalizing the schedule deviation value, quality anomaly value, safety anomaly value, environmental protection anomaly value, and cross-operation density value respectively and then weighting and summing them. The base score is multiplied by the process sensitivity coefficient and the environmental correction coefficient, and then mapped by a monotonic bounded function and compared with a preset threshold to determine the risk level.
6. The multi-source linkage control method for bridge construction sites according to claim 1, characterized in that, The steps for on-chain notarization of key information regarding risk events include: Generate on-chain evidence storage data containing event number, component code of the target component, process status, timestamp and evidence summary, and write it into a consortium blockchain jointly participated in by the construction unit, supervision unit and construction unit nodes; The returned transaction number and off-chain file storage address are written into the evidence index in the digital file of the target component to support querying historical events and processing records by component.
7. The multi-source linkage control method for bridge construction sites according to claim 6, characterized in that, The method further includes: When the target component is selected in the bridge model or digital twin interface, the on-chain digest and off-chain file are retrieved according to the evidence index. After the hash of the off-chain file is calculated and compared with the on-chain digest, the events and handling records associated with the component are displayed in time series.
8. A multi-source linkage control system for bridge construction sites, characterized in that, include: The data configuration module is used to collect multi-source heterogeneous data from bridge construction sites, assign component codes to target components in the bridge construction sites, and establish corresponding process templates. The spatiotemporal binding module is used to align the multi-source heterogeneous data in time and space, and then bind the multi-source heterogeneous data to the target component based on time matching, spatial distance and semantic consistency conditions. The process identification module is used to identify and update the process status of the target component based on the bound multi-source heterogeneous data and the status criteria in the process template through cross-confirmation of multi-source information. The risk management module is used to generate dynamic risk zones and calculate fusion risk values based on the location of the target component, the updated process status, and on-site perception data. The control output module is used to execute the corresponding risk control output according to the fused risk value when a risk rule is triggered, and to store the key information of the risk event on the blockchain.
9. An electronic device comprising a processor and a memory, wherein the memory stores a computer program, characterized in that, When the computer program is executed by the processor, it implements the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.