A highway traffic construction management method and management system based on a BIM model

Abstract

The application relates to the technical field of data processing, in particular to a highway traffic construction management method and system based on a BIM model, which comprises the following steps: obtaining a corresponding component identity code by performing six-section coding on a to-be-managed highway engineering component, and obtaining an initial BIM model based on three-dimensional geometric information, a component attribute set and the component identity code of each to-be-managed highway engineering component; obtaining reconstruction state information, and performing real-time synchronous updating on the initial BIM model based on the reconstruction state information to obtain a target BIM model; performing superposition coupling analysis on the target BIM model based on safety inspection data, and identifying a hidden danger component from the target BIM model according to the superposition coupling analysis result; determining a hidden danger degree of the hidden danger component based on the target BIM model, and generating hidden danger early warning information based on the hidden danger component and the hidden danger degree. The application facilitates the timeliness and accuracy of hidden danger early warning.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method and system for highway traffic construction management based on BIM models. Background Technology

[0002] With the deepening of the concepts of digital transportation and smart construction, Building Information Modeling (BIM) technology has been widely adopted and deeply implemented in the field of highway transportation construction management. It is gradually replacing traditional two-dimensional drawings, manual ledgers, and experience-based management models, becoming the core support carrier for digital management and control throughout the entire life cycle of highway projects. Relying on the technical advantages of three-dimensional geometric modeling, component attribute integration, and information linkage, BIM technology can realize digital twin replication of engineering components such as highway subgrades, bridges, tunnels, and ancillary facilities. It breaks down data barriers in the design, construction, and operation and maintenance stages, and promotes project management from fragmented offline control to visualized, information-based, and standardized online collaborative management.

[0003] Although BIM technology has significant advantages in highway construction management, existing conventional BIM management schemes suffer from fragmented BIM model versions and inconsistent attribute fields at different stages, leading to a disconnect between the model and the actual construction status. Business data such as progress, quality, and safety cannot be dynamically bound to BIM component-level objects, making it impossible to support component-level progress deviation attribution analysis. As a result, there are prominent problems such as untimely release of hazard warning information, inaccurate assessment results, and high rates of missed and false alarms, making it difficult to meet the actual management needs of precise prevention and control and early warning in complex highway engineering scenarios. Summary of the Invention

[0004] To improve the timeliness and accuracy of hazard warnings, this application provides a highway traffic construction management method and management system based on a BIM model.

[0005] Firstly, this application provides a highway traffic construction management method based on a BIM model, employing the following technical solution: A highway traffic construction management method based on BIM model, comprising: The components of the highway engineering project to be managed are coded in a six-segment manner to obtain the corresponding component identity code. Based on the three-dimensional geometric information, component attribute set and component identity code of each component of the highway engineering project to be managed, an initial BIM model is obtained. Obtain the renovation status information and update the initial BIM model in real time based on the renovation status information to obtain the target BIM model; Based on safety inspection data, an overlay coupling analysis is performed on the target BIM model, and potential hazardous components are identified from the target BIM model based on the results of the overlay coupling analysis. The degree of hazard of the hazardous component is determined based on the target BIM model, and hazard warning information is generated based on the hazardous component and the degree of hazard.

[0006] By adopting the above technical solution, a unique component identity code is formed by encoding the components of the highway engineering project under management using a six-segment coding method. The three-dimensional geometric information of the component, the component attribute set, and the component identity code are deeply integrated to jointly create an initial BIM model. This facilitates the overcoming of the shortcomings of traditional highway engineering management, such as scattered component information, inability to trace identity uniformly, and the separation between geometric models and business attributes. By acquiring reconstruction status information in real time and dynamically updating the initial BIM model, a target BIM model is obtained. This facilitates the accurate mapping of the reconstruction and change status of highway engineering components throughout their entire life cycle, realizing real-time twin linkage between the physical project and the digital BIM model. At the same time, by relying on safety inspection data and the target BIM model to carry out superimposed coupling analysis, the system can intelligently identify components with hidden dangers. After quantifying the degree of danger of the components with hidden dangers, the system can automatically generate corresponding hidden danger warning information, which facilitates the refined judgment of hidden danger risk levels and standardized warning push.

[0007] In one possible implementation, determining the degree of hazard of the hazardous component based on the target BIM model includes: Based on the historical update records of the target BIM model, the update frequency and update magnitude of the hidden danger components are statistically analyzed, and the update anomaly coefficient of the hidden danger components is determined based on the update frequency and update magnitude. Based on the component identity code of the potentially hazardous component, the corresponding correlation analysis scope and component structural importance are determined. Related components and related component information are identified from the correlation analysis scope, and the risk coefficient of the related component is determined based on the related component information. Based on the updated anomaly coefficient, the structural importance of the component, and the risk coefficient of the associated component, the degree of danger of the potentially hazardous component is determined.

[0008] By adopting the above technical solution, the update frequency and magnitude of potentially hazardous components are statistically analyzed based on the historical update records of the target BIM model, and an anomaly coefficient is obtained. This facilitates the objective characterization of the abnormal fluctuation state of the components from the perspective of their long-term historical change behavior. At the same time, the component identification code of the potentially hazardous components is used to accurately delineate the scope of correlation analysis and define the structural importance of the components, which facilitates the rapid identification of surrounding related components and their corresponding information. In this way, the risk coefficient of the related components can be quantitatively solved, which can fully take into account the spatial correlation coupling characteristics and structural hierarchy differences of highway engineering components. Finally, by integrating the update anomaly coefficient, the structural importance of the components, and the risk coefficient of the related components, the degree of potential hazard of the potentially hazardous components is comprehensively determined. This facilitates the collaborative quantitative assessment of the abnormal state of the components themselves, the structural importance level, and the surrounding related risks, making the basis for determining the degree of hazard more sufficient, the evaluation dimensions more comprehensive, and the quantitative results more objective and accurate.

[0009] In one possible implementation, determining the risk coefficient of the associated component based on the associated component information includes: Identify the number of associated components contained in the associated component information; Based on the historical update records of the target BIM model, determine the health degradation rate of each associated component within a preset association analysis time period; Based on the component identification code of the hazardous component and the associated component identification code of each associated component, the spatial partitioning interval and component type correlation degree between each associated component and the hazardous component are determined, and the risk transmission weight corresponding to each associated component is determined. The risk coefficient of the associated component is determined based on the number of associated components, the health decay rate of each associated component, and the risk transmission weight corresponding to each associated component.

[0010] By adopting the above technical solution, the health degradation rate of each associated component within a preset analysis period is statistically analyzed based on the historical update records of the target BIM model. This facilitates the accurate characterization of the degradation evolution trend of the associated component's performance over time. At the same time, by utilizing the component identity codes corresponding to the hazardous components and each associated component, it is easy to accurately analyze the spatial partitioning interval and component type correlation between the two. This facilitates the accurate determination of the risk transmission weight of each associated component relative to the hazardous component. Based on this, the risk coefficient of the associated component is comprehensively calculated by integrating the number of associated components, the health degradation rate of each associated component, and the risk transmission weight. This makes the solution process of the risk coefficient of the associated component more in line with engineering practice, the calculation logic more rigorous, and the quantitative results more objective.

[0011] One possible implementation also includes: Based on the historical update records of the target BIM model, retrieve the full time-series update log of the hidden danger component and the full time-series update log of each associated component; Based on the full time-series update log of the hidden danger and each associated full time-series update log, multiple hidden danger reconstruction processes and the completion time of each hidden danger reconstruction process are identified, and the efficiency correction factor of the hidden danger component is determined based on each hidden danger reconstruction process and the corresponding hidden danger reconstruction completion time. Based on the full time-series update log of the hidden danger and the full time-series update log of each related component, the status evolution process of the related components after the compliant reconstruction of multiple hidden danger components is identified. Based on the status evolution process of each related component, the standard update improvement rate and violation fallback rate of each related component are determined. Based on the standard update improvement rate and violation fallback rate of each related component, the positive collaboration factor corresponding to the hidden danger component is determined. Based on the efficiency correction factor and the positive synergy factor, the degree of hazard of the hazard component is optimized.

[0012] By adopting the above technical solution, and by retrieving the full-time time-series update logs of the hidden danger components and the related components in the historical update records of the target BIM model, it is convenient to completely retain and trace the time-series data of the status changes of the hidden danger components and related components throughout their entire life cycle. By relying on the full-time time-series update logs to identify multiple hidden danger reconstruction processes of the hidden danger components and the corresponding reconstruction completion time, the efficiency correction factor of the hidden danger components can be determined. This facilitates an objective evaluation of the component's operation and maintenance capabilities from the perspective of the closed-loop timeliness of hidden danger rectification. At the same time, based on the time-series update logs, the state evolution process of each related component after the compliant reconstruction of the hidden danger component is sorted out to obtain a positive collaboration factor. This facilitates the effective characterization of the driving optimization effect of the single-point hidden danger rectification on the operation and maintenance management level of the surrounding related components. Finally, by combining the efficiency correction factor and the positive collaboration factor, the degree of hidden danger of the hidden danger component is optimized and corrected, so that the final degree of hidden danger takes into account both the inherent structural risks and the related transmission risks, thereby improving the accuracy of the degree of hidden danger.

[0013] In one possible implementation, determining the efficiency correction factor for the hazardous component based on each hazardous hazard remediation process and the corresponding hazardous hazard remediation completion time includes: Identify the renovation implementation content and coverage corresponding to each hidden danger renovation process, and determine the corresponding renovation complexity level; Based on the spatial topology information of the target BIM model, the surrounding component layout, road conditions, and coupling degree of related structures of each renovation coverage area are collected, and the environmental interference impact coefficient corresponding to each hidden danger renovation process is determined. Based on the complexity level and environmental interference impact coefficient of each hazard renovation process, the completion time of each hazard renovation process is corrected to obtain the corrected completion time of each hazard renovation process. Calculate the average completion time of all corrections and renovations to obtain the average renovation time corresponding to the component with the hidden danger; Based on the component identification code of the potentially hazardous component, the corresponding baseline completion time is determined; The efficiency correction factor for the potentially hazardous component is determined based on the average renovation time and the baseline completion time.

[0014] By adopting the above technical solutions, the complexity level of the renovation is determined by identifying the content and scope of the renovation implementation, which facilitates the objective differentiation of the difficulty of different renovation processes for potential hazards. The environmental interference impact coefficient corresponding to each renovation process is quantified through the target BIM model, which facilitates the accurate characterization of the objective constraints of the site conditions on the renovation process. By combining the renovation complexity level and the environmental interference impact coefficient, the original renovation completion time is corrected, which facilitates the elimination of time deviations caused by construction difficulty and external environment. The efficiency correction factor is accurately solved by comprehensively comparing and analyzing the average renovation time and the benchmark completion time, which facilitates a significant improvement in the rigor and accuracy of the efficiency correction factor calculation.

[0015] In one possible implementation, the method further includes: The process iterates through all the work components in the target BIM model at preset intervals and calculates the progress deviation value for each work component. The work components are highway engineering components under reconstruction that are to be managed. The progress deviation value is the difference between the actual completion time stamp and the planned completion time stamp. The rendering identifier corresponding to each work project component is determined based on the preset identifier deviation mapping relationship, and the target BIM model is rendered differently based on each rendering identifier to obtain the rendered BIM model. The preset identifier deviation mapping relationship is the correspondence between the schedule deviation value and the rendering identifier. Based on the component identification code of each work project component, the number of target renderings containing target rendering identifiers in each spatial partition is identified from the rendered BIM model, and spatial partitions with target renderings exceeding a preset rendering threshold are identified as target lagging partitions. Retrieve the operation time sequence timestamp data of each delayed operation engineering component within the target delayed partition, and backtrack to locate the initial delayed moment when the progress deviation of each delayed operation engineering component exceeds the preset deviation threshold; Historical reconstruction construction data for each delayed work component is retrieved, and each historical reconstruction construction data is compared and analyzed with the corresponding delayed reconstruction construction data at the initial delayed time to obtain differentiated construction data. The differentiated construction data and the rendered BIM model are then pushed and fed back.

[0016] By adopting the above technical solution, the progress deviation value is calculated by the difference between the actual completion time stamp and the planned completion time stamp, which facilitates the normalized and automated dynamic monitoring of the construction progress of the reconstructed components. Based on the preset deviation mapping relationship, the corresponding rendering identifier is matched and the target BIM model is rendered with differentiated visualization, which makes it easy to intuitively distinguish the work components with different progress deviation levels. By identifying the target lagging zone, and by retrieving the time-series time stamp data, the initial lag time when the progress deviation of each lagging work component in the target lagging zone exceeds the preset deviation threshold is located, which makes it easy to accurately trace the source of the lag. By comparing and analyzing the historical reconstruction construction data with the construction conditions at the initial lag time, differentiated construction data is obtained and pushed back to the rendered BIM model in conjunction with the data. This not only makes it easy to clarify the causes of the progress lag and the differences in the working conditions, but also makes it easy to intuitively present the lag distribution status in a three-dimensional visualization, thereby enabling relevant management personnel to quickly grasp the progress anomalies in the area, accurately judge the root causes, and intervene and control in a timely manner.

[0017] Secondly, this application provides a management system, which adopts the following technical solution: A management system comprising: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute the above-described BIM model-based highway traffic construction management method.

[0018] Thirdly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium includes: a computer program that can be loaded by a processor and execute the above-described BIM model-based highway traffic construction management method.

[0019] Fourthly, this application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program that, when executed by a processor, implements the aforementioned BIM model-based highway traffic construction management method.

[0020] In summary, this application includes at least one of the following beneficial technical effects: By using a six-segment coding system to create unique component identification codes for highway engineering components under management, and deeply integrating the component's three-dimensional geometric information, component attribute set, and component identification codes to jointly create an initial BIM model, the shortcomings of traditional highway engineering management, such as fragmented component information, inability to trace unified identification, and separation between geometric models and business attributes, can be overcome. By acquiring reconstruction status information in real time and dynamically updating the initial BIM model, a target BIM model can be obtained, which can accurately map the reconstruction and change status of highway engineering components throughout their entire life cycle. This enables real-time twin linkage between the physical project and the digital BIM model. At the same time, by relying on safety inspection data and the target BIM model to carry out superimposed coupling analysis, the system can intelligently identify components with hidden dangers. After quantifying the degree of danger of the components with hidden dangers, the system can automatically generate corresponding hidden danger warning information, which can facilitate the refined judgment of hidden danger risk levels and standardized warning push. By retrieving the full-time time-series update logs of hazardous components and related components from the historical update records of the target BIM model, it is possible to completely retain and trace the time-series data of status changes of hazardous components and related components throughout their entire lifecycle. By relying on the full-time time-series update logs, multiple hazardous component renovation processes and corresponding renovation completion times are identified, thereby determining the efficiency correction factor for hazardous components. This facilitates an objective evaluation of the component's operation and maintenance capabilities from the perspective of the closed-loop timeliness of hazardous rectification. At the same time, based on the time-series update logs, the state evolution process of each related component after the compliant renovation of the hazardous component is sorted out to obtain a positive collaboration factor. This facilitates the effective characterization of the driving and optimization effect of the rectification of a single hazardous point on the operation and maintenance management level of surrounding related components. Finally, by combining the efficiency correction factor and the positive collaboration factor, the hazardous degree of the hazardous component is optimized and corrected, so that the final hazardous degree takes into account both the inherent structural risks and the related transmission risks, thereby improving the accuracy of the hazardous degree. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating a highway traffic construction management method based on a BIM model, as described in an embodiment of this application. Figure 2 This is a schematic diagram of a process for optimizing the degree of potential hazards in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a management system according to an embodiment of this application. Detailed Implementation

[0022] The following is in conjunction with the appendix Figures 1 to 3 This application will be described in further detail.

[0023] After reading this specification, those skilled in the art may make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0024] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] It should be noted that, in the optional embodiments of this application, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this application involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0026] Specifically, this application provides a highway traffic construction management method based on a BIM model, executed by a management system. This management system can be a server or a terminal device. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any limitations on this.

[0027] refer to Figure 1 , Figure 1 This is a flowchart illustrating a highway traffic construction management method based on a BIM model, as described in this application. The method includes steps S110-S140, wherein: Step S110: Perform a six-segment coding on the components of the highway engineering project to be managed to obtain the corresponding component identity code, and obtain the initial BIM model based on the three-dimensional geometric information, component attribute set and component identity code of each component of the highway engineering project to be managed.

[0028] Specifically, the highway engineering components to be managed can be independent digitally modeled, constructed, and operated and maintained entities in highway traffic construction projects, including but not limited to roadbed embankment sections, bridge pile foundations, abutments, box girder segments, tunnel lining rings, guardrail posts, and traffic signs. In accordance with the unified identification requirements for the entire lifecycle of highway engineering, a globally unique and tamper-proof six-segment coding structure can be defined for each highway engineering component to be managed: Project Code (4 digits) + Professional Type Code (2 digits) + Spatial Partition Code (3 digits) + Component Type Code (3 digits) + Serial Number (4 digits) + Check Code (1 digit). This code can be forcibly written into the component attribute set through a modeling plugin and solidified as a GlobalId extended field when exporting IFC4.3 format files, ensuring cross-platform recognizability.

[0029] Commonly used BIM modeling software for highway engineering, such as Civil 3D, Revit, and Tekla, can be used to create 3D solid models of each highway engineering component to be managed in advance, obtaining accurate 3D geometric information such as shape, spatial coordinates, dimensional parameters, and topological relationships. Standardized attribute information can be configured for each highway engineering component to be managed. The component attribute set includes, but is not limited to, design parameters, material type, structural grade, construction requirements, testing standards, and zone affiliation. The 3D geometric information and component attribute set of each highway engineering component to be managed can be uploaded to the management system in advance by relevant technical personnel.

[0030] Using a six-segment component identification code as a unique index, the three-dimensional geometric information and component attribute set of each highway engineering component to be managed are bound one-to-one, establishing a triplet index library of "component ID - geometry - attribute," forming an initial BIM model covering the entire road segment, all component types, and multidisciplinary collaboration. The initial BIM model can also undergo code uniqueness verification, geometric integrity verification, and attribute standardization verification. After passing the verification, it is stored in a lightweight BIM middleware, serving as the basic data carrier for subsequent model updates, hazard identification, and schedule management. This lightweight BIM middleware is deployed between the management system and the initial BIM model to store the initial BIM model and maintain component index relationships, uniformly managing the model's basic data as the foundational data carrier for subsequent model updates, hazard identification, and schedule management. The lightweight BIM middleware is a lightweight server-side engine that supports IFC4.3 format parsing. It has the capabilities of component code verification, triplet index library construction, and model version snapshot management. It also provides a RESTful API interface for relevant construction parties, supervision parties, and acceptance parties to call. When writing business data, all business systems use a six-segment component identity code as a foreign key to bind with the corresponding highway engineering component to be managed.

[0031] Step S120: Obtain the renovation status information and update the initial BIM model in real time based on the renovation status information to obtain the target BIM model.

[0032] Specifically, renovation status information can be collected through multiple channels, including on-site mobile data collection terminals, the supervision web system, and synchronous agent services. For example, on-site personnel can report construction status, renovation content, and completion time by scanning codes (RFID / NFC / QR codes); the supervision end can submit unstructured texts such as rectification notices and inspection records. After spatial semantic parsing by the Highway-BERT model, the location, type, sequence, and renovation requirements of components are extracted to form structured renovation status data, including component renovation content, construction status, timestamps, rectification results, and on-site images. The method of obtaining renovation status information is not specifically limited in this embodiment.

[0033] The synchronization agent service is a data relay service deployed between the on-site acquisition terminal and the initial BIM model. It is responsible for receiving scanned data, parsing modification information, binding component IDs, triggering model updates, and achieving bidirectional synchronization. When the synchronization agent service receives modification status information, it uses a six-segment component identification code as a unique index to quickly locate the corresponding modification component in the component index library of the lightweight BIM middleware. It then strongly binds the modification status information to the component, ensuring that every modification piece of information can be traced back to a unique modification component. Based on the latest modification status, it automatically updates the component status field, synchronously triggering a status change event in the initial BIM model. The modification results are then fed back to the initial BIM model, and the display status, attribute information, and construction progress markers of each modification component are refreshed in real time. Simultaneously, a model version snapshot is automatically generated to ensure that the generated target BIM model is consistent with the on-site entity status. That is, the target BIM model is the latest BIM model formed on the basis of the initial BIM model after real-time synchronization of modification status information and dynamic updates of component status, resulting in a complete twin of the on-site entity.

[0034] Step S130: Perform overlay coupling analysis on the target BIM model based on safety inspection data, and identify potential hazards from the target BIM model based on the results of the overlay coupling analysis.

[0035] Specifically, safety inspection data refers to structured and unstructured data generated during on-site inspections and supervisory inspections, including but not limited to defect descriptions, rectification instructions, anomaly records, test results, image data, and inspection texts. The Highway-BERT text parsing service can collect multi-source safety inspection data such as on-site safety inspection records, quality rectification notices, and defect description texts for highway engineering projects. Unstructured text is converted into structured data containing component location, defect type, and anomaly severity. Based on the BIM geometric semantic mapping engine, spatial information such as mileage markers, orientation, and sequence in the safety inspection data is converted into three-dimensional coordinates. Using a six-segment component identification code as a unique index, the corresponding highway engineering component is accurately located in the target BIM model, completing the spatial anchoring of inspection data and BIM components. The safety inspection data is then multi-dimensionally superimposed and coupled with the three-dimensional geometric information, component attribute sets, historical update records, and structural importance of the target BIM model. By comparing the component's design status, historical status, and current inspection anomaly status, it can be determined whether the highway engineering components to be managed in the target BIM model have abnormal changes, performance degradation, defects exceeding standards, or associated risks. Based on the results of the superimposed coupling analysis, components of highway engineering projects under management that exhibit abnormal states, defects, exceeding standards, or risk transmission characteristics can be marked as hazardous components. The type, location, zone, and related component information of the hazardous components can be recorded to complete the automatic identification of hazardous components.

[0036] Step S140: Determine the degree of hazard of the hidden components based on the target BIM model, and generate hazard warning information based on the hidden components and the degree of hazard.

[0037] Specifically, the degree of hazard, that is, the quantitative evaluation result of the safety risk of a hazardous component, can comprehensively reflect the overall impact of the component's own abnormality, structural importance level, and surrounding associated risks. Furthermore, to improve the accuracy of determining the degree of hazard of a hazardous component, the degree of hazard is determined based on the target BIM model, which may specifically include: Based on the historical update records of the target BIM model, the update frequency and magnitude of potentially hazardous components are statistically analyzed, and the update anomaly coefficient of the potentially hazardous components is determined based on the update frequency and magnitude. Based on the component identity code of the potentially hazardous components, the corresponding association analysis scope and component structural importance are determined. Related components and related component information are identified from the association analysis scope, and the risk coefficient of related components is determined based on the related component information. Based on the update anomaly coefficient, component structural importance, and related component risk coefficient, the degree of hazard of the potentially hazardous components is determined.

[0038] Specifically, the historical update record contains a time-series data set of all state changes, reconstruction constructions, attribute modifications, and inspection results of the hazardous components recorded in the target BIM model since modeling. Based on a preset feature recognition algorithm, the update frequency and update magnitude of the hazardous components can be extracted from the historical update record. The update frequency refers to the number of times the hazardous component undergoes state changes, reconstructions, or attribute updates per unit time, reflecting the frequency of changes. The update magnitude is the degree of parameter difference, geometric deviation, or state jump between the design state and the actual updated state of the hazardous component, characterizing the intensity of the change. The update anomaly coefficient of the hazardous component can be determined based on a preset update anomaly coefficient calculation formula, update frequency, and update magnitude. The preset update anomaly coefficient calculation formula is as follows: ; Where F is the update anomaly coefficient of the component with potential defects; a and b are preset abnormal weights, which can be set in advance by relevant technical personnel according to actual needs; For update range; f0 represents the baseline update frequency of historical reference components of the same type as the component with the potential hazard. Based on the professional type code and component type code in the component identification code of the component with the potential hazard, historical reference components of the same project, professional, type, and structural level as the component with the potential hazard are selected to form a sample set of components of the same type. Then, the historical update records of all historical reference components in the sample set of components of the same type throughout their entire life cycle are retrieved, including but not limited to historical status changes, historical reconstruction and construction, historical attribute modifications, historical inspection and rectification, and other historical time-series data. For each historical reference component, the number of updates per unit time is calculated according to a preset statistical period to obtain the actual historical update frequency of the historical reference component. The actual historical update frequencies of all historical reference components are averaged to obtain the stable update frequency of this type of component under normal working conditions, which is determined as the baseline update frequency f0.

[0039] Based on the six-segment component identity code of the hazardous component, the spatial partition code and component type code can be parsed out. The current partition position is determined based on the spatial partition code. The association analysis range is obtained by expanding the adjacent segments forward and backward with the current partition position of the hazardous component as the center. The component type similarity of any two highway projects to be managed within the association analysis range is not lower than the preset similarity threshold. The specific value of the preset similarity threshold is not specifically limited in this application embodiment.

[0040] The structural importance of a component refers to its level of importance in highway engineering, categorized by its function, stress, and scope of influence. This importance can be determined based on both component type code and professional type code. Different combinations of parameter values ​​for component type codes and professional type codes correspond to different structural importance levels. This can be further determined based on a pre-defined structural importance mapping relationship, which is the correspondence between the parameter combinations of component type codes and professional type codes and the structural importance of the component. Within the defined scope of the correlation analysis, using component identification codes as the retrieval basis, the target BIM model is traversed to identify related components that have spatial, structural, or procedural connections with the potentially hazardous component. Information such as the identification code, historical update records, health status, spatial partition intervals, and component type correlation degree of each related component is extracted. Through comprehensive analysis of the related component information, the associated component risk coefficient can be obtained. The associated component risk coefficient is a quantitative indicator derived from the comprehensive correlation scale, its own deterioration degree, and the intensity of risk transmission, used to characterize the overall risk superposition effect of surrounding components on the potentially hazardous component.

[0041] Furthermore, to improve the accuracy of determining the risk coefficient of related components, the risk coefficient of related components is determined based on the information of related components, which may specifically include: The process involves identifying the number of associated components within the associated component information; determining the health degradation rate of each associated component within a preset association analysis period based on the historical update records of the target BIM model; determining the spatial partitioning interval and component type association degree between each associated component and the hazardous component based on the component identification code of the hazardous component and the associated component identification code of each associated component, and determining the risk transmission weight corresponding to each associated component; and determining the risk coefficient of the associated component based on the number of associations, the health degradation rate of each associated component, and the risk transmission weight corresponding to each associated component.

[0042] Specifically, the number of associated components can be identified from the associated component information based on a preset feature recognition algorithm. The specific preset feature recognition algorithm is not limited in this embodiment. Based on historical update records, the number of abnormal updates, defect records, state degradation magnitude, and number of unclosed rectification items for each associated component within a preset association analysis time period are statistically analyzed. These statistical data are compared with the standard state parameters of similar components under normal operating conditions to calculate the degree of state deviation of the associated components. According to preset decay calculation rules, the frequency of abnormal updates, the severity of defects, and the state degradation magnitude are normalized and weighted to obtain the health decay rate of each associated component within the preset association analysis time period. The health decay rate is used to quantitatively characterize the rate at which the performance of the associated component deteriorates, its state worsens, defects increase, or abnormal fluctuations intensify within a certain period. A higher value indicates a faster decline in the component's health status. The preset association analysis time period is a period prior to the current moment, and the corresponding association analysis duration can be 24 hours or 36 hours; the specific duration is not limited in this embodiment.

[0043] For any associated component, the component identification code of the component with potential defects and the associated component identification codes of each associated component are analyzed. The spatial partition code and component type code are extracted. Then, based on the difference in spatial partition codes between the component with potential defects and the associated components, the spatial partition interval between them is calculated and determined; a smaller interval indicates a closer spatial location. Based on the component type codes of the component with potential defects and the associated components, their structural functions, stress relationships, and engineering attributes are compared to determine the component type correlation degree; the closer the types, the higher the correlation degree. Based on the above method, the spatial partition interval and component type correlation degree between each associated component and the component with potential defects can be obtained.

[0044] According to the preset weight allocation rules, based on the principle that the smaller the spatial partition interval and the higher the correlation between component types, the greater the risk transmission weight, a corresponding risk transmission weight is calculated and assigned to each associated component. Finally, the number of associations, the health decay rate of each associated component, and the risk transmission weight corresponding to each associated component are imported into the preset associated component risk coefficient calculation formula to obtain the associated component risk coefficient. The preset associated component risk coefficient calculation formula is as follows: ; Where R is the risk coefficient of the associated component; N is the number of associations; μ i The risk transmission weight for the i-th associated component; H i Let be the health decay rate of the i-th associated component.

[0045] By integrating the number of associated components, the health decay rate of each associated component, and the risk transmission weight, the risk coefficient of associated components is calculated comprehensively. This makes the solution process of the risk coefficient of associated components more in line with engineering practice, the calculation logic more rigorous, and the quantitative results more objective.

[0046] After obtaining the risk coefficients of associated components, the updated anomaly coefficients, structural importance of components, and risk coefficients of associated components can be imported into a preset hazard level calculation formula to obtain the hazard level of the hazardous components. The preset hazard level calculation formula is as follows: S = C × (F + R); Where S represents the degree of hidden danger; C represents the structural importance of the component; F represents the update anomaly coefficient of the hidden component; and R represents the risk coefficient of the associated component.

[0047] By integrating multiple factors such as the updated anomaly coefficient, the structural importance of the component, and the risk coefficient of related components, the degree of hidden danger of the component is determined. This facilitates the coordinated quantitative assessment of the component's own abnormal state, structural importance level, and surrounding related risks, making the basis for judging the degree of hidden danger more sufficient, the evaluation dimensions more comprehensive, and the quantitative results more objective and accurate.

[0048] Based on the numerical value of the hazard level, the warning level corresponding to the hazard component is determined by comparing it with the preset multi-level warning level threshold. The component location information, component type, and structural importance of the hazard component can be determined based on the component identification code. The above information is then integrated based on the warning level and structured and packaged in a unified format to generate hazard warning information containing complete risk information. Finally, the generated hazard warning information can be pushed to the management terminal, supervision platform, or relevant business system to realize the visual display and rapid notification of the warning information.

[0049] In this embodiment, a unique component identity code is formed by encoding the components of the highway engineering project to be managed using a six-segment coding method. The three-dimensional geometric information of the component, the component attribute set, and the component identity code are deeply integrated to jointly create an initial BIM model. This approach overcomes the shortcomings of traditional highway engineering management, such as fragmented component information, inability to trace identity uniformly, and separation between geometric models and business attributes. By acquiring reconstruction status information in real time and dynamically updating the initial BIM model, a target BIM model is obtained. This facilitates a true mapping of the reconstruction changes throughout the entire lifecycle of highway engineering components, enabling real-time twin linkage between the physical project and the digital BIM model. Simultaneously, by relying on safety inspection data and the target BIM model for overlay and coupling analysis, intelligent identification of hazardous components is achieved. After quantifying the degree of hazard of hazardous components, corresponding hazard warning information is automatically generated, facilitating refined judgment of hazard risk levels and standardized warning push.

[0050] Furthermore, to further improve the accuracy of the hazard level assessment, the method provided in this application embodiment may also include steps S210-S240, such as... Figure 2 As shown, where: Step S210: Based on the historical update records of the target BIM model, retrieve the full-time update log of the hidden danger components and the full-time update log of each associated component.

[0051] Specifically, the six-segment component identification code of the hazardous component and its related components can be used as a unique retrieval index to perform precise searches in the time-series database of the target BIM model. From the historical update records corresponding to the target BIM model, all time-series data of the hazardous component since its modeling, including all status changes, reconstruction construction, inspection results, defect records, and rectification closures, can be retrieved to form a full-scale time-series update log for the hazardous component. That is, a complete log of full-cycle status changes and handling, recorded chronologically, with the hazardous component as the object. Similarly, the complete historical update data of each related component within the same analysis period can be retrieved to form its corresponding full-scale time-series update log. That is, a complete log of full-cycle status changes and handling, recorded chronologically, with each related component as the object.

[0052] Step S220: Based on the full time-series update log of the hidden danger and each associated full time-series update log, identify multiple hidden danger reconstruction processes and the completion time of each hidden danger reconstruction process, and determine the efficiency correction factor of the hidden danger component based on each hidden danger reconstruction process and the corresponding hidden danger reconstruction completion time.

[0053] Specifically, the hazard remediation process is a complete, interconnected remediation and handling process that starts with a hazardous component and is triggered by the hazard. It includes the remediation of the hazardous component itself and the remediation of all related components affected by it, until all related components are closed in a loop. The entire process is considered as one workflow. The hazardous component can be identified as the starting point, and the remediation of the hazardous component itself plus the coordinated remediation of all related components can be considered a complete hazard remediation process. The complete event chain of this process can be identified from the time-series log: hazardous component remediation initiated - related components remediated sequentially - the last related component's remediation completed and accepted. To determine the hazard remediation completion time, the moment the hazardous component begins remediation can be taken as the workflow start time, and the moment the last related component completes remediation and closes the loop can be taken as the workflow end time. The time difference between the start and end times is calculated as the hazard remediation completion time corresponding to this hazard remediation process. Following this method, all independent handling events are traversed from the full time-series update log of the hazard and each related full time-series update log to identify multiple non-overlapping hazard remediation processes, and the hazard remediation completion time corresponding to each hazard remediation process is calculated separately.

[0054] The completion times of multiple hazard remediation projects can be statistically analyzed, smoothed, and normalized. Weighted by component type and remediation complexity, an efficiency correction factor is obtained to characterize the overall efficiency of the hazard component remediation. Furthermore, to improve the rigor and accuracy of the efficiency correction factor calculation, the specific process of determining the efficiency correction factor for each hazard remediation process and its corresponding completion time can also include: Identify the renovation implementation content and coverage area corresponding to each hazard renovation process, and determine the corresponding renovation complexity level; based on the spatial topology information of the target BIM model, collect the surrounding component layout status, road traffic conditions, and related structural coupling degree of each renovation coverage area, and determine the environmental interference impact coefficient corresponding to each hazard renovation process; based on the renovation complexity level and environmental interference impact coefficient corresponding to each hazard renovation process, correct the hazard renovation completion time corresponding to each hazard renovation process to obtain the corrected renovation completion time corresponding to each hazard renovation process; calculate the average of all corrected renovation completion times to obtain the average renovation time corresponding to the hazard component; based on the component identification code of the hazard component, determine the corresponding baseline completion time; based on the average renovation time and the baseline completion time, determine the efficiency correction factor for the hazard component.

[0055] Specifically, for any hazard remediation process, the remediation implementation content can be clarified based on component identification codes, structural types, construction procedures, and defect types. The remediation implementation content refers to the actual construction operations, maintenance methods, technological steps, and rectification measures performed in a single hazard remediation process. The remediation coverage area involved in the hazard remediation process can be determined based on the spatial zoning, topological relationships, and construction impact range of the target BIM model. The remediation coverage area refers to the affected highway section, the set of components involved, and the construction space boundary in a single hazard remediation process. Based on preset complexity level judgment rules, a comprehensive score can be calculated from dimensions such as construction procedure difficulty, component quantity, structural type, construction technology, rectification depth, and workload, classifying the remediation complexity level into four levels: simple, general, complex, and extremely complex, or directly mapped to a quantitative level coefficient between 0 and 1. Specific preset complexity level judgment rules are not specifically limited in this embodiment.

[0056] The process involves reading the 3D spatial topology information of the redevelopment area from the target BIM model to obtain the positional relationships, overlapping relationships, and stress relationships between each engineering component in the hazard redevelopment process. It also includes collecting data on the layout of surrounding components, including component density, proximity to important structures, presence of overlapping construction, and whether work space is restricted. Road conditions are collected, including whether the road is partially open to traffic, whether it is closed for construction, whether it is subject to traffic diversion restrictions, and whether there is vehicle interference. The coupling degree of related structures is also collected, including the connection strength, stress dependence, and linkage impact range between engineering components in the hazard redevelopment process and structures such as bridges, roadbeds, and tunnels. The layout of surrounding components, road conditions, and the coupling degree of related structures are then normalized and weighted to obtain an environmental interference impact coefficient. A larger coefficient indicates a stronger external environmental interference with construction.

[0057] The determined complexity level of the renovation is converted into a normalized difficulty coefficient W, and the determined environmental interference impact coefficient is denoted as E. The original, uncorrected renovation completion time T of the current hazard renovation process is obtained. When the renovation difficulty is higher and the environmental interference is stronger, the original hazard renovation completion time is reasonably relaxed. 校正 =T÷(W×E)

[0058] Based on the above method, the correction and renovation completion time T corresponding to each hidden danger renovation process can be obtained. 校正 The system collects all valid correction and reconstruction completion times, calculates the arithmetic mean of multiple correction and reconstruction completion times to eliminate random fluctuations from a single construction project, and uses the average value as the average reconstruction time for the component with potential hazards. A preset baseline completion time mapping relationship can be used to determine the baseline completion time corresponding to the component with potential hazards. This preset baseline completion time mapping relationship is the correspondence between the component's identification code and the baseline completion time, and can be determined by relevant technical personnel based on historical experimental data and uploaded to the management system in advance.

[0059] Finally, by comparing the average renovation time with the baseline completion time, the efficiency correction factor can be obtained. The shorter the average renovation time, the higher the efficiency, and the stronger the positive correction for the degree of danger of the hidden components. By combining the renovation complexity level and the environmental interference influence coefficient to correct the original renovation completion time, it is easier to eliminate the time deviation caused by construction difficulty and external environment. By comprehensively comparing and analyzing the average renovation time with the baseline completion time, the efficiency correction factor can be accurately solved, which can significantly improve the rigor and accuracy of the calculation of the efficiency correction factor.

[0060] Step S230: Based on the full time-series update log of the hidden danger and the full time-series update log of each related component, identify the state evolution process of the related components after the compliance modification of multiple hidden danger components is completed. Based on the state evolution process of each related component, determine the standard update improvement rate and violation fallback rate of each related component. Based on the standard update improvement rate and violation fallback rate of each related component, determine the positive collaboration factor corresponding to the hidden danger component.

[0061] Specifically, the status evolution process of related components is the entire process of status changes of related components over time after the compliant modification of the hazardous component is completed. This includes the complete trajectory of standardization improvement, stability maintenance, and non-compliance reduction. Based on the full-volume time-series update log of the hazardous component and the full-volume time-series update log of each related component, the time-series segments of the hazardous component that have completed compliant modification can be selected. At the same time, starting from the time when the compliant modification of the hazardous component is completed, the status change records of each related component after the modification are continuously tracked and extracted to form the status evolution process of related components, including but not limited to the complete evolution trajectory of status stabilization, parameter restoration to normal, gradual elimination of defects, continuous performance improvement, or reappearance of non-compliance indicators.

[0062] For each associated component's status evolution process, stage data on the improvement of its status towards compliance / acceptance after renovation are extracted. The rate of improvement in compliance status, the rate of decrease in defect indicators, and the rate of recovery of performance parameters per unit time are statistically analyzed. This data is then normalized to obtain the standard update improvement rate, which characterizes the speed at which the associated component recovers to a good state after hazard mitigation. Within the same status evolution process, stage data on the re-emergence of anomalies, indicator deterioration, and status decline of the associated component after compliance renovation are identified. The rate of increase in non-compliance indicators, the rate of decrease in health status, and the rate of re-development of defects per unit time are statistically analyzed. This rate of non-compliance decline is calculated, which characterizes the speed at which the associated component deviates from the standard again after hazard mitigation.

[0063] For each associated component, the weighted difference between the rate of standard update and the rate of violation reduction is calculated to obtain the collaborative contribution value of each associated component after the compliant reconstruction of the hazard component. The collaborative contribution values ​​of all associated components within the scope of the association analysis are weighted and summed. At the same time, a second weighting is performed based on the structural importance and spatial partitioning interval of each associated component to finally obtain the positive collaborative factor corresponding to the hazard component. This factor is used to characterize the positive improvement effect and overall stability of the surrounding associated components after the hazard is dealt with.

[0064] Step S240: Optimize the degree of hidden danger of the hidden danger component based on the efficiency correction factor and the positive synergy factor.

[0065] Specifically, the optimized risk level = basic risk level ÷ (efficiency correction factor × positive synergy factor). Based on the basic risk level, two objective correction dimensions, "response efficiency" and "regional synergy and stability effect," are introduced to dynamically optimize the initial risk level, making the final risk assessment more realistic and reasonable.

[0066] In this embodiment of the application, by retrieving the full-time time-series update logs of the hidden danger components and the associated full-time time-series update logs of the related components in the historical update records of the target BIM model, it is convenient to completely retain and trace the time-series data of the status changes of the hidden danger components and related components throughout their entire life cycle. By relying on the full-time time-series update logs to identify multiple hidden danger reconstruction processes of the hidden danger components and the corresponding reconstruction completion time, the efficiency correction factor of the hidden danger components can be determined. This facilitates the objective evaluation of the component's operation and maintenance capabilities from the perspective of the closed-loop timeliness of hidden danger rectification. At the same time, based on the time-series update logs, the state evolution process of each related component after the compliant reconstruction of the hidden danger component is sorted out to obtain a positive collaboration factor. This facilitates the effective characterization of the driving optimization effect of the single-point hidden danger rectification on the operation and maintenance management level of the surrounding related components. Finally, by combining the efficiency correction factor and the positive collaboration factor, the degree of hidden danger of the hidden danger components is optimized and corrected, so that the final degree of hidden danger takes into account both the inherent structural risks and the related transmission risks, thereby improving the accuracy of the degree of hidden danger.

[0067] Furthermore, to facilitate relevant management personnel in quickly grasping abnormal progress situations in the area, the method provided in this application embodiment also includes: The system iterates through all operational engineering components in the target BIM model at preset intervals, calculating the schedule deviation for each component. Operational engineering components are highway engineering components under reconstruction, and the schedule deviation is the difference between the actual completion timestamp and the planned completion timestamp. Based on a preset identifier deviation mapping relationship, a rendering identifier corresponding to each operational engineering component is determined. The target BIM model is then differentiated based on each rendering identifier to obtain a rendered BIM model. The preset identifier deviation mapping relationship is the correspondence between the schedule deviation value and the rendering identifier. Based on the component identification code of each operational engineering component, the rendered BIM model... The model identifies the number of target renders containing target render identifiers within each spatial partition, and defines spatial partitions with target render counts exceeding a preset render threshold as target lag partitions. It retrieves the operation time sequence timestamp data of each lagging work component within the target lag partition, and traces back to locate the initial lag time when the progress deviation of each lagging work component exceeds a preset deviation threshold. It retrieves the historical reconstruction construction data of each lagging work component, compares and analyzes each historical reconstruction construction data with the corresponding lagging reconstruction construction data at the initial lag time, obtains differentiated construction data, and pushes the differentiated construction data and rendered BIM model back to the model.

[0068] Specifically, the preset interval can be 15 minutes or 30 minutes, and the specific interval is not specifically limited in this embodiment. The management system automatically starts the traversal task at the preset interval, identifies the highway engineering components under reconstruction in the target BIM model, and determines the corresponding progress deviation value based on the actual completion timestamp and the planned completion timestamp of the engineering components. The actual completion timestamp of the engineering components can be obtained by scanning and reporting by on-site mobile terminals, real-time transmission by synchronous agent services, confirmation by supervision and acceptance, or collection by IoT devices. The planned completion timestamp can be automatically imported by the management system from the project schedule software, and the specific acquisition method is not specifically limited in this embodiment.

[0069] The preset identifier deviation mapping relationship is the correspondence between the progress deviation value and the rendering identifier. For example, when the progress deviation value exceeds the first preset threshold, it is rendered as a first-level lagging red identifier; when the progress deviation value exceeds the second preset threshold, it is rendered as a second-level lagging flashing red identifier; when the progress deviation value is lower than the preset advance threshold, it is rendered as an early completion light blue identifier. The specific content of the preset identifier deviation mapping relationship, the first preset threshold, the second preset threshold, and the preset advance threshold are not specifically limited in this application embodiment. According to the component identification code and the corresponding rendering identifier of each work engineering component, the target BIM model is differentially rendered to obtain the rendered BIM model, realizing the intuitive display of the progress status on the three-dimensional model. For example, every 15 minutes, all the highway engineering components under management with the status of "under reconstruction" are traversed, and their progress deviation value Δt = actual completion timestamp - planned completion timestamp is calculated. If Δt > +24h, the corresponding work engineering component is rendered as red (first-level lagging) in the target BIM model; if Δt > +72h, it is rendered as flashing red (second-level lagging); if Δt < −12h (early), it is rendered as light blue.

[0070] The process iterates through all operational components, parses their six-segment component identification codes, extracts spatial partition codes, and groups all operational components according to these codes. It then counts the number of components containing the target rendering identifier within each spatial partition, i.e., the target rendering quantity. If the target rendering quantity is greater than or equal to a preset rendering threshold, the corresponding spatial partition is identified as a target lag partition. The target rendering identifier can be a second-level lag flashing red identifier; specific identifiers can be pre-set by relevant personnel based on actual needs. For each delayed operational component within the target lag partition, its complete operational time sequence timestamp data is retrieved from the BIM model time sequence library. The component's status changes are traced back chronologically: planned start - under construction - delayed - lag intensified. The progress deviation values ​​are compared segment by segment to find the earliest time point when the deviation first exceeds the preset deviation threshold, and this time point is determined as the initial lag time for that component.

[0071] Historical reconstruction data for each delayed work component can be retrieved from the time-series database of the lightweight BIM middleware. This includes normal construction dimensions such as resource allocation, machinery usage status, material supply, personnel input, on-site weather conditions, and process execution records from the same historical period. Simultaneously, delayed reconstruction data for the corresponding delayed work component before and after the initial delay time is retrieved, including actual construction dimensions such as resource allocation, machinery usage status, material supply, personnel input, on-site weather conditions, traffic control, and process execution and interruption records from the corresponding time period. The historical reconstruction data and delayed reconstruction data are compared item by item along the same dimensions to extract key discrepancies causing deviations in construction progress, forming differentiated construction data. This differentiated construction data is packaged with the rendered BIM model and automatically pushed to the terminals of relevant management personnel. This allows them to quickly grasp the anomalies in the area's progress, accurately analyze the root causes, and intervene and control in a timely manner. This achieves intelligent processing throughout the entire process—from delay location to time tracking, root cause analysis, and automatic push—significantly shortening the time for problem identification and decision-making.

[0072] This application provides a management system, such as... Figure 3 As shown, Figure 3 The management system 300 shown includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the management system 300 may also include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one type, and the structure of this management system 300 does not constitute a limitation on the embodiments of this application.

[0073] Processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0074] Bus 302 may include a pathway for transmitting information between the aforementioned components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 302 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The symbol is represented by only one line, but this does not mean that there is only one bus or one type of bus.

[0075] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0076] The memory 303 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0077] The management system includes, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Tablet PCs), PMPs (Portable Multimedia Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. It can also include servers. Figure 3 The management system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0078] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments.

[0079] This application provides a computer program product including a computer program that, when executed by a processor, implements the methods described in any of the above embodiments.

[0080] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0081] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A highway traffic construction management method based on BIM model, characterized in that, include: The components of the highway engineering project to be managed are coded in a six-segment manner to obtain the corresponding component identity code. Based on the three-dimensional geometric information, component attribute set and component identity code of each component of the highway engineering project to be managed, an initial BIM model is obtained. Obtain the renovation status information and update the initial BIM model in real time based on the renovation status information to obtain the target BIM model; Based on safety inspection data, an overlay coupling analysis is performed on the target BIM model, and potential hazardous components are identified from the target BIM model based on the results of the overlay coupling analysis. The degree of hazard of the hazardous component is determined based on the target BIM model, and hazard warning information is generated based on the hazardous component and the degree of hazard.

2. The highway traffic construction management method based on a BIM model according to claim 1, characterized in that, The determination of the degree of hazard of the hazardous component based on the target BIM model includes: Based on the historical update records of the target BIM model, the update frequency and update magnitude of the hidden danger components are statistically analyzed, and the update anomaly coefficient of the hidden danger components is determined based on the update frequency and update magnitude. Based on the component identity code of the potentially hazardous component, the corresponding correlation analysis scope and component structural importance are determined. Related components and related component information are identified from the correlation analysis scope, and the risk coefficient of the related component is determined based on the related component information. Based on the updated anomaly coefficient, the structural importance of the component, and the risk coefficient of the associated component, the degree of danger of the potentially hazardous component is determined.

3. The highway traffic construction management method based on a BIM model according to claim 2, characterized in that, The determination of the risk coefficient of the associated component based on the associated component information includes: Identify the number of associated components contained in the associated component information; Based on the historical update records of the target BIM model, determine the health degradation rate of each associated component within a preset association analysis time period; Based on the component identification code of the hazardous component and the associated component identification code of each associated component, the spatial partitioning interval and component type correlation degree between each associated component and the hazardous component are determined, and the risk transmission weight corresponding to each associated component is determined. The risk coefficient of the associated component is determined based on the number of associated components, the health decay rate of each associated component, and the risk transmission weight corresponding to each associated component.

4. A highway traffic construction management method based on a BIM model according to claim 2, characterized in that, Also includes: Based on the historical update records of the target BIM model, retrieve the full time-series update log of the hidden danger component and the full time-series update log of each associated component; Based on the full time-series update log of the hidden danger and each associated full time-series update log, multiple hidden danger reconstruction processes and the completion time of each hidden danger reconstruction process are identified, and the efficiency correction factor of the hidden danger component is determined based on each hidden danger reconstruction process and the corresponding hidden danger reconstruction completion time. Based on the full time-series update log of the hidden danger and the full time-series update log of each related component, the status evolution process of the related components after the compliant reconstruction of multiple hidden danger components is identified. Based on the status evolution process of each related component, the standard update improvement rate and violation fallback rate of each related component are determined. Based on the standard update improvement rate and violation fallback rate of each related component, the positive collaboration factor corresponding to the hidden danger component is determined. Based on the efficiency correction factor and the positive synergy factor, the degree of hazard of the hazard component is optimized.

5. A highway traffic construction management method based on a BIM model according to claim 4, characterized in that, The efficiency correction factor for determining the hazardous component based on each hazardous hazard remediation process and the corresponding hazardous hazard remediation completion time includes: Identify the renovation implementation content and coverage corresponding to each hidden danger renovation process, and determine the corresponding renovation complexity level; Based on the spatial topology information of the target BIM model, the surrounding component layout, road conditions, and coupling degree of related structures of each renovation coverage area are collected, and the environmental interference impact coefficient corresponding to each hidden danger renovation process is determined. Based on the complexity level and environmental interference impact coefficient of each hazard renovation process, the completion time of each hazard renovation process is corrected to obtain the corrected completion time of each hazard renovation process. Calculate the average completion time of all corrections and renovations to obtain the average renovation time corresponding to the component with the hidden danger; Based on the component identification code of the potentially hazardous component, the corresponding baseline completion time is determined; The efficiency correction factor for the potentially hazardous component is determined based on the average renovation time and the baseline completion time.

6. A highway traffic construction management method based on a BIM model according to claim 1, characterized in that, Also includes: The process iterates through all the work components in the target BIM model at preset intervals and calculates the progress deviation value for each work component. The work components are highway engineering components under reconstruction that are to be managed. The progress deviation value is the difference between the actual completion time stamp and the planned completion time stamp. The rendering identifier corresponding to each work project component is determined based on the preset identifier deviation mapping relationship, and the target BIM model is rendered differently based on each rendering identifier to obtain the rendered BIM model. The preset identifier deviation mapping relationship is the correspondence between the schedule deviation value and the rendering identifier. Based on the component identification code of each work project component, the number of target renderings containing target rendering identifiers in each spatial partition is identified from the rendered BIM model, and spatial partitions with target renderings exceeding a preset rendering threshold are identified as target lagging partitions. Retrieve the operation time sequence timestamp data of each delayed operation engineering component within the target delayed partition, and backtrack to locate the initial delayed moment when the progress deviation of each delayed operation engineering component exceeds the preset deviation threshold; Historical reconstruction construction data for each delayed work component is retrieved, and each historical reconstruction construction data is compared and analyzed with the corresponding delayed reconstruction construction data at the initial delayed time to obtain differentiated construction data. The differentiated construction data and the rendered BIM model are then pushed and fed back.

7. A management system, characterized in that, The management system includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform a highway traffic construction management method based on a BIM model according to any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, include: The computer program is stored and can be loaded by a processor and executed as described in any one of claims 1-6, which is a method for highway traffic construction management based on a BIM model.

9. A computer program product, characterized in that, It includes a computer program, which, when executed by a processor, implements the steps of a highway traffic construction management method based on a BIM model as described in any one of claims 1-6.

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