Information system engineering supervision project risk adaptive assessment method and system

Abstract

The invention provides an information system engineering supervision project risk adaptive assessment method and system. According to the project management scheme, a dynamic knowledge graph is formed by constructing a data model fusing a building information model and a geographic information system. The three-dimensional coordinate track of the construction machinery is captured in real time by using an ultra wide band positioning device array, and the space occupied hot area distribution is generated by using a multipath interference suppression technology. An operation simulation environment is established based on a digital twinning technology, and a space-time risk topology network is established to early warn path conflicts and safety spacing problems. And according to network node density characteristics, dynamically adjusting a risk assessment parameter weight, and assessing an equipment collision probability and a construction process conflict index. Finally, the stress threshold value and the signal sampling frequency are adjusted according to the composite risk level result feedback, and construction management and safety guarantee are optimized. According to the technical scheme provided by the invention, the efficiency and safety of information system engineering supervision project risk adaptive assessment can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of risk adaptive assessment of information system engineering supervision projects, and in particular to a method and system for risk adaptive assessment of information system engineering supervision projects. Background Art

[0002] In modern large-scale construction projects, the construction process is complex and changeable, involving the coordination of multiple professional fields and technical parameters. In order to ensure the safe and efficient progress of the project, a technical solution that can integrate building information models and geographic information systems is needed to achieve effective management of multi-dimensional risk factors such as pipeline pre-buried, load-bearing structure stress thresholds, and equipment installation specifications. In addition, the construction site changes frequently, and real-time monitoring of the position and movement of construction machinery is crucial to avoid collisions and optimize the operation process. At the same time, by simulating and evaluating the risks that may arise during the construction process in advance through digital means, the overall management level and safety of the project can be significantly improved.

[0003] At present, some advanced construction projects have adopted real-time monitoring systems based on IoT sensor networks to track the location and status of construction machinery. The system uses the global positioning system and wireless communication network to transmit the real-time location data of construction machinery to the central management system, and combines it with the building information model to perform preliminary spatial conflict detection. In this way, project managers can identify potential space occupancy conflicts and safety spacing issues at an early stage, so as to adjust construction plans and resource allocation in time and reduce the possibility of on-site accidents.

[0004] Although the real-time monitoring system based on the IoT sensor network provides a certain degree of spatial conflict detection capability, there are still several obvious limitations. First, the global positioning accuracy is limited indoors or in densely populated urban areas, which may lead to large positioning deviations and affect the actual application effect. Second, the system mainly relies on static building information models for conflict detection, lacks the ability to respond to dynamic changes in the construction site in real time, and cannot fully cover all potential risk factors. Finally, due to the lack of integrated ultra-wideband positioning technology or multipath interference suppression algorithm, its ability to accurately capture the trajectory of mobile devices in complex environments is limited, making it difficult to generate reliable mobile device spatial occupancy hotspot distribution data, thereby limiting further risk analysis and optimization potential. Summary of the invention

[0005] The present application provides a method and system for adaptive risk assessment of an information system engineering supervision project, which are used to solve the problems of low efficiency and insufficient security of adaptive risk assessment of an information system engineering supervision project in the prior art.

[0006] In a first aspect, the present application provides a method for adaptively assessing the risks of an information system engineering supervision project, comprising: Construct an engineering management data model that integrates building information model and geographic information system, integrate the multi-dimensional risk factor set of pipeline pre-buried parameters, load-bearing structure stress threshold and equipment installation specification requirements, and form a dynamic knowledge map that includes spatial constraints and construction logic rules; Deploy an array of ultra-wideband positioning devices to capture the three-dimensional coordinate trajectory of construction machinery in real time, eliminate positioning deviations through multipath interference suppression technology, and generate mobile equipment space occupancy hotspot distribution data; Establishing a digital twin-driven operation simulation environment, dynamically coupling the risk factors in the dynamic knowledge graph with the mobile device space occupancy hotspot distribution data, and generating a spatiotemporal risk topology network including network equipment installation path conflict warnings and safety spacing warnings; Based on the node density distribution characteristics of the spatiotemporal risk topological network, the weight allocation strategy of the construction machinery trajectory risk assessment parameters is dynamically adjusted to form a composite risk level assessment result including the equipment collision probability and the construction process conflict index; The stress threshold parameters in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array are reversely adjusted according to the composite risk level assessment result.

[0007] Optionally, the risk factors in the dynamic knowledge graph are dynamically coupled with the mobile device space occupancy hotspot distribution data to generate a spatiotemporal risk topology network including network device installation path conflict warnings and safety spacing warnings, including: Based on the spatial coordinate set of pipeline pre-buried parameters in the dynamic knowledge graph and the safety spacing threshold required by the equipment installation specification, a risk factor association model is established; According to the real-time motion vectors in the mobile device space occupancy hot zone distribution data, the three-dimensional trajectory envelope of each mobile device is calculated in a preset time window, and the device motion trend projection is generated through interpolation prediction; Performing spatiotemporal grid discrete analysis on the spatiotemporal influence domain in the risk factor association model and the projection of the equipment movement trend, calculating the network equipment installation path conflict probability value for each grid unit, the network equipment installation path conflict probability value being obtained by weighting the area ratio of the equipment trajectory penetrating the pipeline influence domain and the time overlap coefficient; A dynamic safety distance threshold function is constructed based on the stress threshold parameters of the load-bearing structure, and the safety distance threshold is adjusted in real time according to the equipment mass parameters and motion acceleration; The network equipment installation path conflict probability value and the safety distance threshold are integrated to construct a spatiotemporal association matrix, and a spatiotemporal risk topology network including network equipment installation path conflict warning and safety distance alarm is generated.

[0008] Optionally, performing spatiotemporal grid discrete analysis on the spatiotemporal influence domain in the risk factor association model and the device movement trend projection, and calculating the network device installation path conflict probability value for each grid unit, includes: Establishing a space-time grid division mechanism aligned with the coordinate system of the risk factor association model, discretizing the three-dimensional space coordinate axis into cubic units, and dividing the time axis into time windows according to the construction progress to obtain space-time grid units; Traversing the space-time grid unit, extracting the trajectory segments of the device movement trend projection, calculating the geometric intersection volume of the trajectory segments, and taking the ratio of the geometric intersection volume to the total volume of the pipeline influence domain as the spatial permeability; Calculate the intersection duration of the trajectory segment within the time window and the pipeline influence domain activation period, and take the ratio of the intersection duration to the preset time window length as the time coverage; Obtaining a preset spatial permeability weight factor and a temporal coverage weight factor according to the pipeline type parameters, linearly combining the spatial permeability and the temporal coverage, and generating a dynamic probability value reflecting the pipeline collision risk; When the device movement trend projection involves a multi-pipeline intersection area, the dynamic probability values ​​of the pipelines in the same spatiotemporal grid unit are superimposed and calculated to generate a network device installation path conflict probability value.

[0009] Optionally, the linear combination of the spatial permeability and the temporal coverage to generate a dynamic probability value reflecting the pipeline collision risk includes: Establish a mapping relationship table of pipeline type parameters, spatial permeability weight factors and time coverage weight factors, set the reference values ​​of spatial permeability and time coverage according to the engineering attribute characteristics, and dynamically modify the reference values ​​according to the current construction stage parameters; According to the corrected benchmark value, a two-dimensional weight vector is constructed, and homogeneous coordinate transformation is performed on the spatial permeability and the temporal coverage to generate a risk vector containing spatiotemporal characteristics; Calculate the risk coupling coefficient according to the pipeline type parameters and the construction machinery type parameters, and perform a tensor product operation on the risk vector and the risk coupling coefficient to obtain an initial probability tensor; The electromagnetic interference intensity parameter of the pipeline intersection area is introduced as an environmental correction factor, and the initial probability tensor is nonlinearly mapped to generate a dynamic probability value reflecting the pipeline collision risk.

[0010] Optionally, the multi-dimensional risk factor set integrating pipeline pre-buried parameters, load-bearing structure stress thresholds and equipment installation specification requirements forms a dynamic knowledge graph containing space constraints and construction logic rules, including: Based on the pipeline pre-buried parameters, a spatial collision rule is generated through the minimum clearance constraint between pipelines, wherein the spatial collision rule includes a three-dimensional buffer zone parameter of the pipeline intersection area; Analyze the time-varying parameters of the stress threshold of the load-bearing structure, establish a stress propagation path model based on the topological relationship of the support points, and generate dynamic constraint conditions including the maximum allowable load based on the mechanical transfer characteristics between the support points; Convert positioning tolerance, tightening torque and heat dissipation spacing parameters in equipment installation specification requirements into a construction logic rule chain, wherein the construction logic rule chain includes process execution priority parameters and mutually exclusive trigger conditions for parallel operations; Based on the spatial coordinate system of the building information model, the spatial collision rules, dynamic constraints and construction logic rule chains are topologically encoded, and a dynamic knowledge graph is formed by defining the spatial interference relationship between pipelines and load-bearing structures, and the logical dependency relationship between construction procedures and equipment trajectories.

[0011] Optionally, the step of converting the positioning tolerance, tightening torque and heat dissipation spacing parameters in the equipment installation specification requirements into a construction logic rule chain includes: Establish a mapping relationship table between equipment types and installation parameters in equipment installation specification requirements, and generate equipment in-place verification rules based on the horizontal deviation threshold and vertical settlement tolerance in the positioning tolerance parameters. The equipment in-place verification rules include linkage constraints on the allowable deviation range and the spacing between adjacent equipment. Analyze the functional relationship between the tightening torque and the equipment quality parameters, establish a torque gradient adjustment model, and generate installation strength rules that include the torque graded loading strategy and the tightening sequence dependency; Based on the thermal radiation attenuation coefficient in the heat dissipation spacing parameters and the equipment power parameters, the dynamic safe heat dissipation distance is calculated to generate the thermal field mutual exclusion triggering rules when the equipment cluster is deployed; The equipment placement verification rules, installation strength rules and thermal field mutually exclusive triggering rules are arranged in time sequence according to the construction process stages to obtain a construction logic rule chain.

[0012] Optionally, the reversely adjusting the stress threshold parameter in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array according to the composite risk level assessment result includes: Based on the equipment collision probability value in the composite risk level assessment result, a dynamic mapping relationship between a collision probability threshold and a load-bearing structure stress threshold is established to generate a stress threshold parameter; Analyze the time distribution characteristics of the construction process conflict index, and divide the construction period into a peak period and an intermittent period in combination with the construction stage parameters. During the peak period, increase the sampling frequency of the ultra-wideband positioning device array according to the deviation amplitude of the mobile device trajectory prediction, and during the intermittent period, reduce the sampling frequency in proportion to the change rate of the hot zone distribution of the mobile device space occupation; Establishing a coupling constraint condition between the stress threshold parameter and the sampling frequency, so that when the stress threshold parameter is lowered and the sampling frequency is increased at the same time, the stress threshold parameter is adjusted so as not to exceed the structural safety boundary; The adjusted stress threshold parameters are reversely injected into the load-bearing structure node attributes of the engineering management data model, and the signal sampling frequency configuration sent to the ultra-wideband positioning device array under the coupling constraint condition is configured.

[0013] In a second aspect, the present application provides an information system engineering supervision project risk adaptive assessment system, comprising: Construction module, build an engineering management data model that integrates building information model and geographic information system, integrates the multi-dimensional risk factor set of pipeline pre-buried parameters, load-bearing structure stress threshold and equipment installation specification requirements, and forms a dynamic knowledge map containing spatial constraints and construction logic rules; The capture module deploys an array of ultra-wideband positioning devices to capture the three-dimensional coordinate trajectory of construction machinery in real time, eliminates positioning deviations through multipath interference suppression technology, and generates mobile equipment space occupancy hot zone distribution data; A coupling module is used to establish a digital twin-driven operation simulation environment, dynamically couple the risk factors in the dynamic knowledge graph with the spatial occupancy hot zone distribution data, and generate a spatiotemporal risk topology network including network equipment installation path conflict warnings and safety spacing warnings; A formation module is provided to dynamically adjust the weight allocation strategy of the construction machinery trajectory risk assessment parameters based on the node density distribution characteristics of the spatiotemporal risk topological network to form a composite risk level assessment result including the equipment collision probability and the construction process conflict index; The adjustment module reversely adjusts the stress threshold parameters in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array according to the composite risk level assessment result.

[0014] In a third aspect, an embodiment of the present application provides a computing device, comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement an information system engineering supervision project risk adaptive assessment method as described in the first aspect above.

[0015] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program, which, when executed by a computer, implements an information system engineering supervision project risk adaptive assessment method as described in the first aspect.

[0016] In an embodiment of the present application, an engineering management data model integrating a building information model and a geographic information system is constructed, and a multi-dimensional risk factor set including pipeline pre-buried parameters, load-bearing structure stress thresholds, and equipment installation specifications is integrated to form a dynamic knowledge graph including spatial constraints and construction logic rules; an ultra-wideband positioning device array is deployed to capture the three-dimensional coordinate trajectory of construction machinery in real time, and positioning deviations are eliminated through multipath interference suppression technology to generate mobile device space occupancy hot zone distribution data; a digital twin-driven operation simulation environment is established, and the risk factors in the dynamic knowledge graph are dynamically coupled with the mobile device space occupancy hot zone distribution data to generate a spatiotemporal risk topology network including network equipment installation path conflict warnings and safety spacing warnings; based on the node density distribution characteristics of the spatiotemporal risk topology network, a weight allocation strategy for construction machinery trajectory risk assessment parameters is dynamically adjusted to form a composite risk level assessment result including equipment collision probability and construction process conflict index; and according to the composite risk level assessment result, the stress threshold parameters in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array are reversely adjusted.

[0017] The technical solution of this application has the following beneficial effects: This application forms a dynamic knowledge graph by integrating pipeline pre-buried parameters, load-bearing structure stress thresholds and equipment installation specification requirements to achieve comprehensive management of multi-dimensional risk factors. This step ensures that the spatial constraints and construction logic rules in the construction process are accurately controlled, and improves the scientificity and systematicness of project management. Using ultra-wideband technology and multipath interference suppression methods, the three-dimensional position information of construction machinery is accurately obtained to generate spatial occupancy hot zone distribution data. This step improves the accuracy of location monitoring of mechanical equipment at the construction site and effectively avoids safety hazards caused by positioning deviations. The risk factors in the dynamic knowledge graph are coupled with the spatial occupancy hot zone distribution data of mobile devices to create a spatiotemporal risk topological network to achieve path conflict warning and safety spacing warning. This step provides accurate risk prediction and timely warning mechanism for the construction process, enhancing the safety of on-site operations. According to the node density distribution characteristics of the spatiotemporal risk topological network, the weight allocation strategy of the construction machinery trajectory risk assessment parameters is dynamically adjusted to form a composite risk level assessment result. This step achieves flexible response to complex situations at the construction site and optimizes the risk management strategy. Based on the composite risk level assessment results, the stress threshold parameters and signal sampling frequency configurations are reversed to continuously improve project management and safety measures. This final step ensures efficient operation and improved safety throughout the construction process.

[0018] Furthermore, this solution establishes a risk factor association model, combines the spatial occupancy hot zone distribution data of mobile devices, generates device movement trend projections using interpolation prediction, calculates the probability value of network device installation path conflict through spatiotemporal grid discrete analysis, adjusts the safety distance based on the dynamic safety distance threshold function, and finally integrates these data to construct a spatiotemporal association matrix to generate a spatiotemporal risk topology network including path conflict warnings and safety distance warnings. The effect is to significantly improve the risk prediction ability and safety management efficiency of the construction site, greatly reduce potential safety accidents and construction conflicts through accurate risk assessment and real-time warning mechanisms, and ensure the smooth progress of the project and the safety of personnel.

[0019] These and other aspects of the present application will become more clearly understood in the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 A flowchart of a risk adaptive assessment method for an information system engineering supervision project provided by the present application is shown; Figure 2 A schematic diagram of the structure of an information system engineering supervision project risk adaptive assessment system provided by the present application is shown; Figure 3 A schematic diagram of the structure of a computing device provided by the present application is shown. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0023] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0024] This solution builds an engineering management data model that integrates building information models and geographic information systems, integrates a multi-dimensional risk factor set of pipeline pre-buried parameters, load-bearing structure stress thresholds, and equipment installation specifications, and forms a dynamic knowledge graph that includes spatial constraints and construction logic rules. By integrating different types of engineering data into a unified data model, comprehensive management and precise control of complex conditions on the construction site are achieved, ensuring that various parameters and rules in the construction process are scientifically and reasonably applied.

[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0026] Figure 1 A flowchart of a method for adaptively assessing the risk of an information system engineering supervision project is provided for an embodiment of the present application. Figure 1 As shown, the method includes: 101. Construct an engineering management data model that integrates building information model and geographic information system, integrates the multi-dimensional risk factor set of pipeline pre-buried parameters, load-bearing structure stress threshold and equipment installation specification requirements, and forms a dynamic knowledge map that includes spatial constraints and construction logic rules; In this step, the dynamic knowledge graph includes a multi-dimensional risk factor set including pipeline pre-buried parameters, load-bearing structure stress thresholds, and equipment installation specification requirements.

[0027] Building Information Model is a digital tool used to create and manage physical and functional characteristic data of construction projects. It includes all geometric shapes, material properties, construction progress and other information of the building. It is used to optimize decision-making during design, construction and operation, and improve the efficiency and quality of the project.

[0028] A Geographic Information System is a system used to capture, store, analyze and display all types of geographic data, including maps, satellite images, terrain data, etc., to support a variety of application areas such as urban planning, environmental management, disaster response, etc.

[0029] The project management data model integrates various project-related data into a unified data structure, including a multi-dimensional risk factor set such as pipeline pre-buried parameters, load-bearing structure stress thresholds, and equipment installation specification requirements. The model is used to comprehensively manage and accurately control various complex situations on the construction site.

[0030] The multi-dimensional risk factor set includes data on pipeline pre-buried parameters, load-bearing structure stress thresholds, equipment installation specifications, etc. These data are used to identify and evaluate possible risk factors during the construction process to ensure construction safety and efficiency.

[0031] Spatial constraints refer to the space restrictions and rules that must be followed during construction, such as the minimum clearance between pipelines, safe spacing for equipment installation, etc. These conditions are used to prevent physical collisions and potential problems during construction.

[0032] Construction logic rules are a series of standards and specifications that guide the execution sequence and dependencies of construction processes, such as positioning tolerances, tightening torques, heat dissipation spacing, etc. These rules ensure that the construction process meets standards and avoids operational errors.

[0033] The pipeline pre-buried parameters include the minimum clearance constraint between pipelines and the three-dimensional buffer parameters, which are used to prevent physical collisions between pipelines.

[0034] The stress threshold of the load-bearing structure establishes a stress propagation path model by analyzing time-varying parameters and generates dynamic constraints for the maximum allowable load.

[0035] The equipment installation specification requirements are converted into a construction logic rule chain, including parameters such as positioning tolerance, tightening torque and heat dissipation spacing, to ensure that the equipment installation process meets the standards.

[0036] In the embodiment of the present application, firstly, the spatial collision rules are generated based on the pre-buried pipeline parameters, and the stress propagation path model is established in combination with the topological relationship of the support points to define the dynamic constraint conditions of the maximum allowable load. Then, the equipment installation specifications are converted into a construction logic rule chain, and topological association encoding is performed in the spatial coordinate system of the building information model. Finally, a dynamic knowledge graph is formed, integrating spatial constraints and construction logic rules, to achieve comprehensive management and precise control of complex conditions on the construction site.

[0037] In a large commercial complex project, all pre-buried pipeline parameters, including the location and size of water pipes and cables, are first collected to generate spatial collision rules. At the same time, the stress threshold of the load-bearing structure is analyzed, and a stress propagation path model is established to ensure the maximum load-bearing capacity of each pillar. According to the equipment installation specification requirements, a detailed construction logic rule chain is formulated, such as the positioning tolerance and tightening torque of elevator equipment. These data are integrated into a unified data model to form a dynamic knowledge graph, providing basic data support for subsequent steps.

[0038] 102. Deploy an array of ultra-wideband positioning devices to capture the three-dimensional coordinate trajectory of construction machinery in real time, eliminate positioning deviations through multipath interference suppression technology, and generate mobile equipment space occupancy hot zone distribution data; In this step, the UWB positioning device array is a group of high-precision positioning devices that capture the 3D coordinate trajectory of objects in real time by sending and receiving UWB signals. These devices are used to accurately monitor the position of mechanical equipment at the construction site to avoid collisions and optimize the work process.

[0039] The three-dimensional coordinate trajectory refers to a data set that records the movement path of an object in three-dimensional space. It includes position information in three directions and is used to accurately describe the movement trajectory of construction machinery or equipment.

[0040] Multipath interference suppression technology is a technology used to reduce the error caused by multipath effects during wireless signal transmission. This technology processes the received signal through an algorithm to eliminate positioning deviation and improve positioning accuracy.

[0041] Positioning deviation refers to the difference between the actual measured position and the true position. At the construction site, positioning deviation may lead to misoperation or collision risk of mechanical equipment, so it needs to be corrected by technical means.

[0042] The mobile equipment space occupancy hotspot distribution data shows the space occupancy of construction machinery at different time points, which helps to identify potential collision risks.

[0043] In the embodiment of the present application, an array of ultra-wideband positioning devices is deployed at the construction site, and its high-precision positioning capability is used to capture the three-dimensional coordinate trajectory of the construction machinery. Multipath interference suppression technology is used to process the signal to improve positioning accuracy. The captured data is analyzed to generate the spatial occupancy hot zone distribution data of the construction machinery, showing the activity range and density distribution of the equipment in each time period.

[0044] Continuing with the above commercial complex project, an array of ultra-wideband positioning devices was deployed on site to monitor the movement trajectory of heavy machinery such as tower cranes and excavators in real time. Multipath interference suppression technology was used to ensure that the positioning error was less than 10 cm. The generated spatial occupancy hot zone distribution data showed the activity hotspots of various mechanical equipment in different time periods, providing key data for the next step of risk assessment.

[0045] 103. Establish a digital twin-driven operation simulation environment, dynamically couple the risk factors in the dynamic knowledge graph with the mobile device space occupancy hot zone distribution data, and generate a spatiotemporal risk topology network including network device installation path conflict warning and safety distance warning; In this step, digital twin driving is a technology that uses virtual models to simulate real-world objects. In the construction environment, digital twin driving simulates changes in the construction site through real-time data feedback to help identify and solve potential problems.

[0046] The operation simulation environment is a virtual construction scene built based on digital twin technology, which is used to simulate and predict various situations in the construction process. It includes functions such as equipment movement trajectory and risk warning, helping to optimize construction plans and resource allocation.

[0047] Risk factors refer to factors that may have a negative impact on the construction process, such as pipeline pre-buried parameters, load-bearing structure stress thresholds, equipment installation specification requirements, etc. These factors are used to assess and prevent potential risks in construction.

[0048] Installation path conflict warning is an early warning mechanism generated based on a spatiotemporal risk topology network. It is used to identify potential conflict points in the equipment installation path in advance and issue warnings so that the construction plan can be adjusted in time.

[0049] The safety distance alarm is an early warning mechanism generated based on the dynamic safety distance threshold function. It is used to detect whether the distance between devices or between devices and fixed structures meets the safety standards and issue a warning if it does not meet the requirements.

[0050] The spatiotemporal risk topology network includes network equipment installation path conflict warnings and safety distance warnings, helping to identify and avoid potential risks in construction in advance.

[0051] In the embodiment of the present application, in the digital twin environment, the risk factors in the dynamic knowledge graph are first dynamically coupled with the distribution data of the hot zone of mobile device space occupancy. Through spatiotemporal grid discrete analysis, the probability value of the network equipment installation path conflict for each grid unit is calculated. A dynamic safety spacing threshold function is constructed based on the stress threshold parameters of the load-bearing structure, and a spatiotemporal correlation matrix is ​​generated, ultimately forming a spatiotemporal risk topology network including path conflict warning and safety spacing warning.

[0052] In the aforementioned project, digital twin technology was used to simulate the dynamic changes of the construction site, combining the pre-buried pipeline parameters and equipment installation specification requirements with the actual movement trajectory of the construction machinery. Through spatiotemporal grid discrete analysis, potential equipment installation path conflict points were identified and early warnings were issued. For example, during the pouring of a certain floor slab, the system discovered in advance that the crane's boom might conflict with the laid pipeline, and the construction plan was adjusted in time to avoid accidents.

[0053] 104. Based on the node density distribution characteristics of the spatiotemporal risk topological network, dynamically adjust the weight allocation strategy of the construction machinery trajectory risk assessment parameters to form a composite risk level assessment result including the equipment collision probability and the construction process conflict index; In this step, the node density distribution characteristics refer to the frequency and density of risk events at each node in the spatiotemporal risk topological network. These characteristics are used to dynamically adjust the weight distribution strategy of the construction machinery trajectory risk assessment parameters.

[0054] The construction machinery trajectory risk assessment parameters include factors such as equipment mass, movement speed, acceleration, etc., which are used to evaluate the collision probability of construction machinery in different time periods and the construction process conflict index.

[0055] The weight allocation strategy refers to a method of dynamically adjusting the importance coefficients of various risk assessment parameters based on the node density distribution characteristics. This method is used to optimize risk management strategies and improve the safety of construction sites.

[0056] The equipment collision probability refers to the possibility of collision between construction machines or between construction machines and fixed structures, calculated based on the spatiotemporal risk topological network. This probability is used to assess the risk level during the construction process.

[0057] The construction process conflict index refers to the degree of temporal and spatial conflict between different construction processes calculated based on the spatiotemporal risk topological network. This index is used to evaluate the coordination and efficiency of the construction process.

[0058] The composite risk level assessment result is a comprehensive risk assessment report generated by combining the equipment collision probability and the construction process conflict index. This report is used to guide subsequent risk management and construction scheduling.

[0059] In the embodiment of the present application, the node density distribution characteristics of the spatiotemporal risk topological network are analyzed to determine the risk level of each node. The weight distribution strategy of the construction machinery trajectory risk assessment parameters is adjusted according to the node density, the equipment collision probability and the construction process conflict index are calculated, and a composite risk level assessment result is formed. These results are used to guide subsequent risk management and construction scheduling.

[0060] In the subsequent construction phase of the commercial complex project, by analyzing the node density of the spatiotemporal risk topological network, it was found that some areas had frequent construction machinery activities and a high risk of collision. The system automatically adjusted the risk assessment parameter weights of these areas and increased key monitoring efforts. For example, during the construction of the basement parking lot, the system increased the risk assessment weights for concrete pump trucks and steel bar transporters, effectively preventing multiple potential collision accidents.

[0061] 105. Reversely adjust the stress threshold parameter in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array according to the composite risk level assessment result.

[0062] In this step, the stress threshold parameter refers to the maximum stress value that the load-bearing structure can withstand at different construction stages. This parameter is used to ensure the safety and stability of the structure during the construction process.

[0063] Signal sampling frequency configuration refers to the frequency setting of the ultra-wideband positioning device array to collect data in different time periods. Increasing the sampling frequency during peak periods can improve monitoring accuracy, while reducing the sampling frequency during intermittent periods can save resources.

[0064] In the embodiment of the present application, based on the equipment collision probability value in the composite risk level assessment result, a dynamic mapping relationship between the collision probability threshold and the load-bearing structure stress threshold is established. The time distribution characteristics of the construction process conflict index are analyzed, and the sampling frequency of the ultra-wideband positioning device array is adjusted. The coupling constraint conditions of the stress threshold parameters and the sampling frequency are set to ensure that the adjusted parameters do not exceed the structural safety boundary.

[0065] As the project was drawing to a close, the system appropriately lowered the stress threshold parameters of some load-bearing structures based on the composite risk level assessment results, and increased the sampling frequency of the ultra-wideband positioning device array during peak periods to improve monitoring accuracy. For example, during the installation of the top steel structure, the system detected a high risk of collision and temporarily increased the stress threshold and sampling frequency to ensure construction safety and smooth progress.

[0066] In summary, steps 101 to 105 achieve comprehensive management and precise control of complex construction site conditions by constructing an engineering management data model that integrates building information models and geographic information systems, deploying an array of ultra-wideband positioning devices, establishing a digital twin-driven operation simulation environment, dynamically adjusting construction machinery trajectory risk assessment parameters, and reversely adjusting stress threshold parameters in the engineering management data model according to the composite risk level assessment results. This method not only significantly improves the safety and efficiency of the construction site, but also greatly reduces potential safety accidents and construction conflicts through accurate risk prediction and real-time early warning mechanisms, ensuring the smooth progress of the project and the safety of personnel.

[0067] In order to solve the risk prediction and management problems of complex situations at the construction site, this solution dynamically couples the risk factors in the dynamic knowledge graph with the mobile device space occupancy hot zone distribution data to generate a spatiotemporal risk topological network that includes network equipment installation path conflict warnings and safety spacing warnings. A risk factor association model is established based on the spatial coordinate set of pipeline pre-buried parameters and the safety spacing threshold required by the equipment installation specification, and a spatiotemporal grid discrete analysis is performed in combination with the equipment movement trend projection to calculate the network equipment installation path conflict probability value of each grid unit, thereby achieving accurate prediction and real-time warning of potential risks at the construction site. In some embodiments, step 103 dynamically couples the risk factors in the dynamic knowledge graph with the mobile device space occupancy hot zone distribution data to generate a spatiotemporal risk topological network that includes network equipment installation path conflict warnings and safety spacing warnings, including: 201. Establish a risk factor association model based on the spatial coordinate set of pipeline pre-buried parameters in the dynamic knowledge graph and the safety spacing threshold required by the equipment installation specification; In step 201, the pipeline pre-buried parameters include the specific three-dimensional coordinate position and size information of all pipelines (such as water pipes, cables, etc.) pre-buried in the building. These data are used to determine the minimum clearance between pipelines and avoid physical collisions. The spatial coordinate set refers to the specific coordinate point set of these pipelines in three-dimensional space. The equipment installation specification requirements include various standards and regulations that need to be followed when installing equipment. The safety spacing threshold is the minimum safety distance that needs to be maintained when installing equipment to prevent collisions between equipment or between equipment and fixed structures. The risk factor association model is used to identify and evaluate risk factors that may occur during the construction process.

[0068] In the embodiment of the present application, the pipeline pre-buried parameters in the dynamic knowledge graph are first extracted to determine the specific coordinates and dimensions of each pipeline in three-dimensional space. A risk factor association model is established in combination with the safety spacing threshold required by the equipment installation specification. The model defines the minimum clearance between pipelines and the safety spacing during equipment installation to ensure that no physical collision occurs during construction. Finally, a detailed risk factor association model is generated through these parameters for risk assessment in subsequent steps.

[0069] 202. Calculate the three-dimensional trajectory envelope of each mobile device in a preset time window according to the real-time motion vector in the mobile device space occupation hot zone distribution data, and generate a device motion trend projection through interpolation prediction; In step 202, the real-time motion vector describes the data set of the motion direction and speed of the mobile device within a certain time window. The three-dimensional trajectory envelope is the spatial range that the device may occupy in the future period of time calculated based on the real-time motion vector, and the interpolation prediction uses mathematical methods (such as linear interpolation) to predict the future motion path of the device. The device motion trend projection is the prediction result of the future motion path of the device, and uses mathematical methods (such as linear interpolation) to predict the future motion path of the device.

[0070] In the embodiment of the present application, the real-time motion vector in the hot zone distribution data of the mobile device space occupation is obtained, and the three-dimensional trajectory envelope of each mobile device is calculated using the linear interpolation method within the preset time window. By analyzing the current position and motion vector of the device, its movement trend in the future period is predicted, and the device movement trend projection is generated. These data provide the basis for the subsequent spatiotemporal grid discrete analysis.

[0071] 203. Performing spatiotemporal grid discrete analysis on the spatiotemporal influence domain in the risk factor association model and the projection of the equipment movement trend, and calculating the network equipment installation path conflict probability value for each grid unit, wherein the network equipment installation path conflict probability value is obtained by weighting the area ratio of the equipment trajectory penetrating the pipeline influence domain and the time overlap coefficient; In step 203, the spatiotemporal impact domain refers to the impact range of each risk factor in the risk factor association model in time and space. Spatiotemporal grid discrete analysis is to divide the three-dimensional space and time axis into multiple cells, and calculate the area ratio and time overlap coefficient of the equipment trajectory penetrating the pipeline impact domain for each cell. The path conflict probability value is the possibility of the equipment trajectory penetrating the pipeline impact domain, which is obtained by weighting the area ratio and time overlap coefficient. The time overlap coefficient refers to the time overlap ratio of the equipment trajectory and the activation period of the pipeline impact domain.

[0072] In an embodiment of the present application, a space-time grid division mechanism aligned with the coordinate system of the risk factor association model is established, the three-dimensional space coordinate axis is discretized into cubic units, and the time axis is divided into time windows according to the construction progress. Traverse each space-time grid unit, extract the trajectory fragments of the equipment movement trend projection, and calculate the geometric intersection volume of the trajectory fragments and the pipeline influence domain. According to the ratio of the intersection volume to the total volume of the pipeline influence domain as the spatial permeability, calculate the intersection duration of the trajectory fragment within the time window with the activation period of the pipeline influence domain as the time coverage. Finally, according to the pipeline type parameters, the preset spatial penetration weight factor and time coverage weight factor are obtained to generate a dynamic probability value reflecting the pipeline collision risk.

[0073] 204. Construct a dynamic safety distance threshold function based on the stress threshold parameter of the load-bearing structure, and adjust the safety distance threshold in real time according to the equipment quality parameter and motion acceleration; In step 204, the stress threshold parameter of the load-bearing structure refers to the maximum stress value that the load-bearing structure can withstand at different construction stages. The dynamic safety spacing threshold function is a function constructed based on the stress threshold parameter of the load-bearing structure. The equipment quality parameter refers to the quality and motion characteristics of the equipment, such as mass, acceleration, etc. Motion acceleration refers to the acceleration value generated by the equipment during movement.

[0074] In the embodiment of the present application, a dynamic safety spacing threshold function is constructed according to the stress threshold parameter of the load-bearing structure. The function takes into account the mass and motion acceleration of the equipment and adjusts the safety spacing between the equipment or between the equipment and the fixed structure in real time. The mass and motion acceleration of the equipment are monitored in real time by sensors, and the safety spacing threshold is dynamically adjusted to ensure the safe operation of the equipment during the construction process.

[0075] 205. The network device installation path conflict probability value and the safety distance threshold are integrated to construct a spatiotemporal association matrix, and a spatiotemporal risk topology network including network device installation path conflict warnings and safety distance alarms is generated.

[0076] In step 205, the spatiotemporal correlation matrix combines the network equipment installation path conflict probability value and the safety distance threshold to generate a spatiotemporal risk topology network. The spatiotemporal risk topology network includes a network structure of network equipment installation path conflict warning and safety distance warning, which is used to identify and avoid potential risks in construction in advance.

[0077] In the embodiment of the present application, the network equipment installation path conflict probability value calculated in step 203 is combined with the safety spacing threshold generated in step 204 to construct a spatiotemporal association matrix. The matrix contains the conflict probability value and safety spacing threshold of each spatiotemporal grid unit, forming a spatiotemporal risk topological network. The network can warn of equipment installation path conflicts and insufficient safety spacing in real time, helping to optimize construction plans and resource allocation.

[0078] Here is a specific example: In a large commercial complex project, all pipeline pre-buried parameters, including the location and size of water pipes, cables, etc., are first collected to generate a risk factor association model. The pipeline pre-buried parameters include the specific three-dimensional coordinate position and size information of all pipelines pre-buried in the building. These data are used to determine the minimum clearance between pipelines and avoid physical collisions. At the same time, the ultra-wideband positioning device array is used to monitor the movement trajectory of heavy machinery such as tower cranes and excavators in real time to generate equipment space occupation hot zone distribution data. Next, according to the real-time motion vector of the equipment, the equipment movement trend projection is generated through interpolation prediction. The equipment movement trend projection is the prediction result of the future movement path of the equipment. Then, the network equipment installation path conflict probability value of each grid unit is calculated. Based on the stress threshold parameter of the load-bearing structure, a dynamic safety spacing threshold function is constructed to adjust the safety spacing threshold in real time. Finally, the network equipment installation path conflict probability value and the safety spacing threshold are integrated. During the entire construction process, the system can identify and warn potential equipment installation path conflicts and insufficient safety spacing problems in advance, adjust the construction plan in time, and ensure the smooth progress of the project.

[0079] In summary, steps 201 to 205 achieve comprehensive management and precise control of complex conditions at the construction site. By establishing a risk factor association model, calculating equipment motion trend projection, performing spatiotemporal grid discrete analysis, adjusting the safety spacing threshold in real time, and constructing a spatiotemporal association matrix, a spatiotemporal risk topology network including network equipment installation path conflict warning and safety spacing warning is formed. This method not only significantly improves the safety and efficiency of the construction site, but also greatly reduces potential safety accidents and construction conflicts through accurate risk prediction and real-time warning mechanisms, ensuring the smooth progress of the project and the safety of personnel.

[0080] In order to solve the risk prediction and management problems of complex situations on construction sites, the solution discretizes the three-dimensional space coordinate axes into cubic units by establishing a space-time grid division mechanism aligned with the coordinate system of the risk factor association model, and divides the time window according to the construction progress to obtain space-time grid units. Traverse the space-time grid units to extract the trajectory fragments of the equipment movement trend projection, calculate the geometric intersection volume and time coverage, and obtain the spatial penetration weight factor and time coverage weight factor according to the pipeline type parameters to generate a dynamic probability value reflecting the pipeline collision risk, thereby improving the accuracy and reliability of risk assessment. In some embodiments, step 203 performs a space-time grid discrete analysis on the space-time influence domain in the risk factor association model and the equipment movement trend projection, and calculates the network equipment installation path conflict probability value for each grid unit, including: 301. Establish a space-time grid division mechanism aligned with the coordinate system of the risk factor association model, discretize the three-dimensional space coordinate axis into cubic units, and divide the time axis into time windows according to the construction progress to obtain space-time grid units; In step 301, the space-time grid partitioning mechanism is a method of dividing the three-dimensional space coordinate axis and the time axis into multiple cells. The cube unit is a series of small cubes into which the three-dimensional space coordinate axis is discretized, and each cube represents a specific spatial area. These cube units constitute the basic analysis unit of the three-dimensional space. The space-time grid unit is the smallest analysis unit generated by the above partitioning mechanism and is used for subsequent spatial permeability and time coverage calculations.

[0081] In the embodiment of the present application, a space-time grid division mechanism aligned with the risk factor association model coordinate system is first established, and the three-dimensional space coordinate axis is discretized into cubic units, each of which represents a spatial area. At the same time, the time axis is divided into several time windows according to the construction progress, and each time window represents a period of time. In this way, multiple space-time grid units are formed, each of which contains specific spatial position and time period information. These space-time grid units provide the basis for subsequent trajectory segment analysis.

[0082] 302. Traverse the space-time grid unit, extract the trajectory segments of the device movement trend projection, calculate the geometric intersection volume of the trajectory segments, and use the ratio of the geometric intersection volume to the total volume of the pipeline influence domain as the spatial permeability; In step 302, the trajectory segment is the part of the motion trajectory within a specific spatiotemporal grid unit extracted from the projection of the equipment motion trend. The geometric intersection volume is the overlapping volume between the trajectory segment and the pipeline influence domain. The pipeline influence domain refers to the safe distance range that the pipeline needs to maintain during construction to avoid physical collision with the equipment or structure. The spatial permeability is the ratio of the geometric intersection volume to the total volume of the pipeline influence domain, indicating the degree to which the equipment trajectory penetrates the pipeline influence domain.

[0083] In the embodiment of the present application, each spatiotemporal grid unit is first traversed, then the trajectory segment of the device motion trend projection is extracted, and the geometric intersection volume of the trajectory segment and the pipeline influence domain is calculated. The overlapping volume of the trajectory segment and the pipeline influence domain is determined by a geometric algorithm (such as a Boolean operation). Then, the ratio of the geometric intersection volume to the total volume of the pipeline influence domain is used as the spatial permeability. This step quantifies the degree of influence of the device trajectory on the pipeline in a specific spatiotemporal grid unit.

[0084] 303. Calculate the intersection duration of the trajectory segment within the time window and the pipeline influence domain activation period, and take the ratio of the intersection duration to the preset time window length as the time coverage; In step 303, the intersection duration is the time period that the trajectory segment overlaps with the pipeline influence domain activation period in the time window. The pipeline influence domain activation period refers to the time period when the pipeline is active during the construction process, such as the time period when it is being laid or maintained. The time coverage is the ratio of the intersection duration to the length of the preset time window, which indicates the degree of coverage of the equipment trajectory over the pipeline influence domain in time.

[0085] In the embodiment of the present application, first, the intersection duration of the trajectory segment within the time window and the activation period of the pipeline influence domain is calculated. Then, by comparing the time interval of the trajectory segment with the time interval of the pipeline influence domain, the overlapping time period of the two is found. Then, the ratio of the intersection duration to the length of the preset time window is used as the time coverage. This step quantifies the degree of influence of the device trajectory on the pipeline in the time dimension within a specific space-time grid unit, and provides key data for further risk assessment.

[0086] 304. Obtain a preset spatial permeability weight factor and a temporal coverage weight factor according to the pipeline type parameter, perform a linear combination of the spatial permeability and the temporal coverage, and generate a dynamic probability value reflecting the pipeline collision risk; In step 304, the spatial permeability weight factor is the importance coefficient of the spatial permeability set according to the pipeline type parameter. The temporal coverage weight factor is the importance coefficient of the temporal coverage set according to the pipeline type parameter. The pipeline collision risk refers to the possibility and severity of the equipment trajectory overlapping with the pipeline influence domain in time and space, which is used to evaluate the potential collision risk during the construction process. The dynamic probability value is a probability value reflecting the pipeline collision risk generated by linearly combining the spatial permeability and the temporal coverage.

[0087] In an embodiment of the present application, first, a preset spatial permeability weight factor and a temporal coverage weight factor are obtained according to the pipeline type parameters. Then, a linear combination formula is used to weight the sum of spatial permeability and temporal coverage to generate a dynamic probability value reflecting the pipeline collision risk. For example, the spatial permeability, spatial permeability weight factor, temporal coverage, and temporal coverage weight factor are associated to generate a dynamic probability value. Then, a quantitative collision risk assessment value is generated by comprehensively considering the risk factors in both spatial and temporal dimensions for subsequent risk management and early warning.

[0088] 305. When the device movement trend projection involves a multi-pipeline intersection area, the dynamic probability values ​​of the pipelines in the same space-time grid unit are superimposed and calculated to generate a network device installation path conflict probability value.

[0089] In step 305, the multi-pipeline intersection area is an overlapping area involving multiple pipelines in the same spatiotemporal grid unit. The superposition calculation is to accumulate the dynamic probability values ​​of each pipeline in the same spatiotemporal grid unit when the device movement trend projection involves the multi-pipeline intersection area, and generate the final network device installation path conflict probability value. The network device installation path conflict probability value is the total collision risk probability value after comprehensively considering the influence of all pipelines, and is used to warn of potential conflicts in the device installation path.

[0090] In the embodiment of the present application, first, the multi-pipeline intersection areas involved in the projection of the equipment movement trend are identified. Then, in these areas, the dynamic probability value of each pipeline is calculated separately. Then, the dynamic probability values ​​of each pipeline in the same spatiotemporal grid unit are superimposed and calculated to generate the total network equipment installation path conflict probability value. This step ensures that all potential risk factors are fully considered in a complex environment, thereby providing more accurate risk assessment results, helping to optimize construction plans and reduce potential conflicts.

[0091] Here is a specific example: In a large commercial complex project, assume that the installation of an intelligent parking system in an underground parking lot is in progress. First, a corresponding space-time grid system is established based on the construction site layout and project schedule. Next, for each construction vehicle and the equipment it carries, its expected movement path is drawn, and the spatial permeability and time coverage with the existing underground water supply and drainage pipelines are calculated. Then, appropriate weights are assigned according to the characteristics of each type of pipeline, and the collision risk is comprehensively evaluated. Finally, for those grid cells with high dynamic probability values, preventive measures are taken, such as adjusting the construction sequence or changing the equipment transportation route, thereby effectively avoiding possible collision accidents.

[0092] In summary, steps 301 to 305 achieve comprehensive management and precise control of complex conditions at the construction site. By establishing a spatiotemporal grid division mechanism, calculating the geometric intersection volume and time coverage, a spatiotemporal risk topology network including network equipment installation path conflict warning and safety spacing warning is formed. This method not only significantly improves the safety and efficiency of the construction site, but also greatly reduces potential safety accidents and construction conflicts through accurate risk prediction and real-time warning mechanisms, ensuring the smooth progress of the project and the safety of personnel.

[0093] In order to solve the problem of pipeline collision risk assessment in large-scale commercial complex projects, this solution linearly combines the spatial permeability and time coverage to generate a dynamic probability value that reflects the risk of pipeline collision. By establishing a mapping relationship table of pipeline type parameters, spatial permeability weight factors, and time coverage weight factors, a benchmark value is set for the engineering attribute characteristics and dynamically corrected. Construct a two-dimensional weight vector, perform homogeneous coordinate transformation on the spatial permeability and time coverage, generate a risk vector containing spatiotemporal characteristics, and combine the electromagnetic interference intensity parameters of the pipeline intersection area as an environmental correction factor to generate the final dynamic probability value, thereby improving the comprehensiveness and accuracy of the risk assessment. In some embodiments, the linear combination of the spatial permeability and time coverage described in step 304 to generate a dynamic probability value reflecting the risk of pipeline collision includes: 401. Establish a mapping relationship table of pipeline type parameters, spatial permeability weight factors, and time coverage weight factors, set the reference values ​​of the spatial permeability and time coverage according to the engineering attribute characteristics, and dynamically modify the reference values ​​according to the current construction stage parameters; In step 401, pipeline type parameters are characteristic parameters describing different types of pipelines, such as material, diameter, purpose, etc. The spatial permeability weight factor is the importance coefficient of spatial permeability set according to the pipeline type parameter. The time coverage weight factor is the importance coefficient of time coverage set according to the pipeline type parameter. The mapping relationship table is a table that establishes the correspondence between pipeline type parameters and spatial permeability weight factors and time coverage weight factors. The benchmark value is the basic value of spatial permeability and time coverage set for the engineering attribute characteristics. The construction stage parameter is the specific stage information of the current construction, which is used to dynamically correct the benchmark value.

[0094] In the embodiment of the present application, a detailed pipeline type parameter table is first established, and the corresponding spatial permeability weight factor and time coverage weight factor are set according to different pipeline types (such as water pipes, cables, etc.). Next, according to the characteristics of large-scale commercial complex projects, the initial benchmark values ​​of spatial permeability and time coverage are set. Then, according to the construction progress and the needs of different stages, these benchmark values ​​are dynamically revised to ensure the accuracy and applicability of the data. Finally, these revised benchmark values ​​provide an accurate data basis for subsequent steps.

[0095] 402. Construct a two-dimensional weight vector according to the corrected reference value, perform homogeneous coordinate transformation on the spatial permeability and the temporal coverage, and generate a risk vector containing spatiotemporal characteristics; In step 402, the two-dimensional weight vector includes a spatial permeability weight factor and a temporal coverage weight factor, which are used to represent the spatiotemporal characteristics. Homogeneous coordinate transformation is a mathematical transformation method that converts spatial permeability and temporal coverage into a risk vector containing spatiotemporal characteristics. Spatiotemporal characteristics are used to describe the distribution of underground pipelines in their surroundings and the risk status of these pipelines over time. The risk vector is a vector generated after homogeneous coordinate transformation, which contains information about spatiotemporal characteristics.

[0096] In the embodiment of the present application, a two-dimensional weight vector is constructed based on the corrected reference value, which contains the spatial penetration weight factor and the time coverage weight factor. Then, the spatial permeability and time coverage are converted using the homogeneous coordinate transformation method to generate a risk vector containing spatiotemporal characteristics. Specifically, the original data is converted into a vector in a new coordinate system through matrix operations, so that the information in the spatial and temporal dimensions can be integrated. This step generates a risk vector containing spatiotemporal characteristics, providing basic data for further calculations.

[0097] 403. Calculate the risk coupling coefficient according to the pipeline type parameter and the construction machinery type parameter, and perform a tensor product operation on the risk vector and the risk coupling coefficient to obtain an initial probability tensor; In step 403, the risk coupling coefficient is a coefficient calculated based on the pipeline type parameters and the construction machinery type parameters, and is used to measure the mutual influence between different factors. The tensor product operation is a method of operating the risk vector and the risk coupling coefficient to generate an initial probability tensor. The initial probability tensor is a multidimensional array generated after the tensor product operation, which is used to represent the preliminary risk assessment results.

[0098] In the embodiment of the present application, the risk coupling coefficient is first calculated based on the specific pipeline type and construction machinery type parameters. Then, the risk vector generated previously is combined with the risk coupling coefficient using the tensor product operation method to generate an initial probability tensor. Specifically, the spatiotemporal characteristics in the risk vector are combined with the risk coupling coefficient through tensor operations to generate a multidimensional array, namely the initial probability tensor. This process realizes the fusion of multidimensional data through tensor operations, ensuring the comprehensiveness and accuracy of risk assessment.

[0099] 404. Introduce the electromagnetic interference intensity parameter of the pipeline intersection area as an environmental correction factor, perform nonlinear mapping on the initial probability tensor, and generate a dynamic probability value reflecting the pipeline collision risk.

[0100] In step 404, the electromagnetic interference intensity parameter is the electromagnetic interference intensity existing in the pipeline intersection area, which is used as an environmental correction factor. The environmental correction factor refers to a parameter used to adjust the risk assessment model to reflect the impact of external environmental factors on the assessment results. Nonlinear mapping is a mathematical mapping method that combines the initial probability tensor with the environmental correction factor to generate a final dynamic probability value. The dynamic probability value is the final risk assessment value generated after nonlinear mapping, which reflects the actual risk level of pipeline collision.

[0101] In the embodiment of the present application, the electromagnetic interference intensity parameter of the pipeline intersection area is first introduced as an environmental correction factor. Then, the initial probability tensor is combined with the environmental correction factor using a nonlinear mapping method to generate a final dynamic probability value. Specifically, the environmental correction factor is combined with the initial probability tensor through a nonlinear function to generate a final risk assessment value. This process achieves further correction of the data through a nonlinear function, ensuring the authenticity and reliability of the risk assessment results.

[0102] Here is a specific example: In a large commercial complex project, for various underground pipelines (such as electricity, communications, etc.), the corresponding parameters of each pipeline type and their mapping relationship table with the spatial penetration weight factor and time coverage weight factor were first established. Considering the frequent excavation work in the early stage of the project, the spatial permeability and time coverage were adjusted accordingly. Subsequently, the two-dimensional weight vector was constructed using the adjusted parameters, and the risk vector was generated through homogeneous coordinate transformation. Next, the risk coupling coefficient was calculated according to the type of machinery used at the construction site, and the initial probability tensor was obtained by tensor product operation with the risk vector. Finally, considering the strong electromagnetic interference on site, this was used as an environmental correction factor to perform nonlinear mapping on the initial probability tensor, and a more accurate dynamic probability value of pipeline collision risk was obtained.

[0103] In summary, steps 401 to 404 not only improve the accuracy of risk prediction, but also significantly reduce the potential safety hazards caused by pipeline collisions during construction, thereby improving the construction efficiency and safety of the entire project by systematically quantifying and dynamically adjusting the key parameters in the pipeline collision risk assessment process. In addition, this method can also flexibly adapt to different construction stages and environmental changes, providing a continuously optimized risk management strategy.

[0104] In order to solve the conflicts and risks in the collaborative design and construction process of multiple disciplines in construction projects, the solution integrates a multi-dimensional risk factor set of pipeline pre-buried parameters, load-bearing structure stress thresholds, and equipment installation specifications to form a dynamic knowledge graph containing spatial constraints and construction logic rules. Spatial collision rules are generated based on pipeline pre-buried parameters, and the equipment installation specifications are converted into construction logic rule chains. Topological association encoding is performed through the spatial coordinate system of the building information model to define the spatial interference relationship between pipelines and load-bearing structures and the logical dependency relationship between construction procedures and equipment trajectories, thereby achieving comprehensive risk factor integration and management. In some embodiments, the multi-dimensional risk factor set of pipeline pre-buried parameters, load-bearing structure stress thresholds, and equipment installation specifications described in step 101 forms a dynamic knowledge graph containing spatial constraints and construction logic rules, including: 501. Based on the pipeline pre-buried parameters, a spatial collision rule is generated by constraining the minimum clearance between pipelines, wherein the spatial collision rule includes a three-dimensional buffer zone parameter of the pipeline intersection area; In step 501, the pipeline pre-buried parameters refer to the technical parameters such as size, location, material, etc. of various pipelines (such as water supply and drainage pipes, cable pipes, etc.) determined during the architectural design stage. The minimum clearance constraint refers to the minimum distance that must be maintained between different pipelines to avoid mutual interference or damage. The three-dimensional buffer parameter defines the safety range of the pipeline intersection area to ensure that there are no other pipelines or obstacles in this area.

[0105] In the embodiment of the present application, different types of pipelines and their required safety spacing are analyzed, and the pipeline layout is planned using building information modeling technology, and a collision detection algorithm is used to identify possible spatial conflicts. The minimum clearance between each pair of pipelines is determined in combination with the physical size and functional requirements of the pipelines, thereby generating spatial collision rules. The final result is a three-dimensional model that includes the safety distance requirements between all pipelines.

[0106] 502. Analyze the time-varying parameters of the stress threshold of the load-bearing structure, establish a stress propagation path model based on the topological relationship of the support points, and generate dynamic constraint conditions including the maximum allowable load based on the mechanical transfer characteristics between the support points; In step 502, the time-varying parameters of the stress threshold of the load-bearing structure refer to the changes in the maximum stress value of the building's load-bearing structure under different use conditions, and these parameters are adjusted over time. The support point topological relationship describes the connection mode and interaction relationship between each support point in the load-bearing structure. The stress propagation path model simulates the process of stress being transferred from one support point to another, helping to understand the distribution and transfer path of force.

[0107] In the embodiment of the present application, first, a detailed mechanical analysis of the building structure is performed to obtain the initial design data and expected load of each support point. Then, the finite element analysis method is used to calculate the stress distribution of each support point under different working conditions. Then, based on the law of stress propagation, a mechanical transfer network between the support points is constructed to simulate the process of stress transfer from one support point to another. Through the iterative optimization algorithm, the maximum allowable load of each node is determined and converted into a dynamic constraint condition, and finally a stress propagation path model containing the maximum allowable load is formed and integrated into the dynamic knowledge graph.

[0108] 503. Convert the positioning tolerance, tightening torque and heat dissipation spacing parameters in the equipment installation specification requirements into a construction logic rule chain, wherein the construction logic rule chain includes a process execution priority parameter and a mutually exclusive trigger condition for parallel operations; In step 503, the positioning tolerance refers to the position deviation range allowed during the installation of the device to ensure that the device can be installed correctly and operate normally. The tightening torque refers to the tightening force required for bolts or fixings during the installation process to ensure that the device is firm and stable. The heat dissipation spacing refers to the space that needs to be reserved around the device to effectively dissipate heat and prevent overheating from affecting the performance or life of the device.

[0109] In the embodiment of the present application, first, according to the equipment installation manual and technical standards provided by the manufacturer, key parameters such as positioning tolerance, tightening torque and heat dissipation spacing are extracted. Then, these parameters are converted into specific construction logic rule chains, and detailed installation guidelines are formulated. Then, the workflow engine is used to convert these guidelines into executable task sequences, and process priorities and mutually exclusive conditions are set. Finally, by simulating the operating procedures of the construction site, the rationality and feasibility of the task sequence are verified, and these construction logic rule chains are integrated into the dynamic knowledge graph to ensure that the construction process is orderly and efficient.

[0110] 504. Based on the spatial coordinate system of the building information model, the spatial collision rules, dynamic constraint conditions and construction logic rule chains are topologically encoded, and a dynamic knowledge graph is formed by defining the spatial interference relationship between pipelines and load-bearing structures and the logical dependency relationship between construction procedures and equipment trajectories.

[0111] In step 504, the spatial coordinate system of the building information model refers to a three-dimensional coordinate system established based on the building information model technology, which is used to accurately locate the position of building components and equipment. Topological association coding encodes different building elements (such as pipelines, load-bearing structures) and their relationships for computer processing and analysis. Logical dependency describes the sequence or parallel relationship between construction processes to ensure that the construction process is reasonable and efficient. Dynamic knowledge graph is a knowledge system based on building information model and related data sources, which includes spatial constraints and construction logic rules.

[0112] In the embodiment of the present application, first, all building elements are accurately spatially positioned based on the spatial coordinate system of the building information model. Next, the topological association coding technology is used to encode the spatial interference relationship between pipelines and load-bearing structures and the logical dependency relationship between construction procedures and equipment trajectories. Then, by defining these relationships, a dynamic knowledge graph framework is constructed. Finally, the spatial collision rules, dynamic constraints and construction logic rule chains in the previous steps are integrated to form a complete dynamic knowledge graph to support the full life cycle management of the project.

[0113] Here is a specific example: In a large commercial complex project, the design information of architecture, structure and electromechanical was first integrated through building information modeling software, and potential conflicts in pipeline layout were discovered and resolved using collision detection technology. Then, stress analysis was performed on the main load-bearing components to optimize the support structure design. Subsequently, a detailed construction plan was prepared in accordance with the equipment installation specifications to ensure smooth on-site operations. Finally, a dynamic knowledge graph was constructed based on the above results to support the full life cycle management of the project.

[0114] In summary, steps 501 to 504 achieve risk control and efficiency improvement in the entire process of building engineering from design to construction. Through precise space planning and reasonable construction arrangements, the number of engineering changes and rework is reduced, and the overall quality and economic benefits of the project are improved. This solution not only enhances the operability and safety of the project, but also provides strong support for subsequent maintenance and management.

[0115] In order to solve the precision control and safety problems in the equipment installation process in construction projects, this solution converts the positioning tolerance, tightening torque and heat dissipation spacing parameters in the equipment installation specification requirements into a construction logic rule chain. By establishing a mapping relationship table between equipment type and installation parameters, equipment positioning verification rules, installation strength rules and thermal field mutual exclusion trigger rules are generated, and they are arranged in sequence according to the construction process stage to form a complete construction logic rule chain. This process ensures that each link in the equipment installation process can follow strict standards and sequences to avoid potential operational errors and safety hazards. In some embodiments, the conversion of the positioning tolerance, tightening torque and heat dissipation spacing parameters in the equipment installation specification requirements into a construction logic rule chain as described in step 503 includes: 601. Establish a mapping relationship table between equipment types and installation parameters in equipment installation specification requirements, and generate equipment in-place verification rules according to the horizontal deviation threshold and the vertical settlement tolerance in the positioning tolerance parameters. The equipment in-place verification rules include linkage constraints of the allowable deviation range and the spacing between adjacent equipment. In step 601, the mapping relationship table between equipment type and installation parameters contains detailed information of different equipment types and their corresponding installation parameters, such as positioning tolerance, tightening torque, etc. The horizontal deviation threshold is the maximum distance that the equipment is allowed to deviate from the design position in the horizontal direction. The vertical settlement tolerance is the maximum distance that the equipment is allowed to settle in the vertical direction. The equipment in-place verification rules are rules generated based on the above deviation thresholds, which are used to ensure that the equipment is installed correctly and take into account the spacing constraints between adjacent equipment.

[0116] In the embodiment of the present application, firstly, the design data and installation manuals of all the equipment involved are collected, and a mapping relationship table between the equipment type and the installation parameters is established. Then, according to the horizontal deviation threshold and the vertical settlement tolerance in the positioning tolerance parameters, the equipment in-place verification rules are generated using geometric modeling technology. Then, by analyzing the layout of adjacent equipment, the minimum safe spacing between adjacent equipment is calculated and determined to form linkage constraints. The final result is a set of verification rules that include all equipment installation accuracy requirements.

[0117] 602. Analyze the functional relationship between the tightening torque and the equipment quality parameters, establish a torque gradient adjustment model, and generate installation strength rules including the torque graded loading strategy and the tightening sequence dependency; In step 602, the functional relationship between the tightening torque and the equipment mass parameter describes how the tightening torque is adjusted as the equipment mass changes. The torque gradient adjustment model simulates the change law of the tightening torque required for equipment of different masses to ensure that the equipment is firm and stable. The torque graded loading strategy applies different tightening torques in stages according to the equipment mass and installation requirements; the tightening sequence dependency specifies the order in which the components are tightened during the equipment installation process to avoid stress concentration or structural deformation.

[0118] In the embodiment of the present application, the relationship between the tightening torque and the equipment quality parameters provided by the equipment manufacturer is first analyzed, and a torque gradient adjustment model is established using a regression analysis method. Next, a torque graded loading strategy is generated based on the model to ensure that different quality equipment can obtain appropriate tightening torques. Then, a detailed tightening sequence dependency is formulated to ensure that each tightening point is operated in the correct order. Finally, these rules are integrated to form an installation strength rule that includes a torque graded loading strategy and a tightening sequence dependency.

[0119] 603. Based on the thermal radiation attenuation coefficient in the heat dissipation spacing parameter and the device power parameter, the dynamic safe heat dissipation distance is calculated, and the thermal field mutual exclusion triggering rules when the device cluster is deployed are generated; In step 603, the thermal radiation attenuation coefficient describes the attenuation rate of heat when it propagates in the air, which affects the heat dissipation distance between devices. The device power parameter refers to the amount of heat generated when the device is running. The dynamic safe heat dissipation distance is a safe heat dissipation distance calculated based on factors such as device power and ambient temperature to ensure that overheating does not occur when the device cluster is deployed. The thermal field mutual exclusion trigger rule defines the minimum heat dissipation distance that should be maintained between devices to prevent equipment from overheating and failure due to heat accumulation.

[0120] In the embodiment of the present application, the power parameters and thermal radiation attenuation coefficients of the equipment are first collected, and the dynamic safe heat dissipation distance of each device is calculated using the heat conduction model. Next, combined with the actual layout plan of the equipment cluster, the thermal radiation impact between each device is evaluated, and the thermal field mutual exclusion triggering rules are generated. Then, by simulating the heat dissipation effect under different equipment layout plans, the thermal field mutual exclusion triggering rules are verified and optimized. The final result is a complete solution that includes the thermal field mutual exclusion triggering rules when the equipment cluster is deployed.

[0121] 604. Arrange the equipment in-place verification rules, installation strength rules and thermal field mutual exclusion triggering rules in time sequence according to the construction process stages to obtain a construction logic rule chain.

[0122] In step 604, the construction process phase refers to different phases in the equipment installation process, such as foundation preparation, equipment hoisting, fastener installation, etc. The timing arrangement arranges various construction logic rules in chronological order to ensure that each task is carried out in an orderly manner. The construction logic rule chain integrates all equipment in-place verification rules, installation strength rules, and thermal field mutually exclusive triggering rules to form a complete construction process guidance plan.

[0123] In the embodiment of the present application, the various process stages in the equipment installation process are first sorted out to clarify the tasks and goals of each stage. Then, the equipment in place verification rules, installation strength rules and thermal field mutually exclusive trigger rules are arranged in sequence according to the process stages to ensure that each task is completed on time and without conflict. Then, the entire construction process is simulated and optimized using project management software to ensure that all rules can be effectively executed. Finally, all content is integrated to obtain a complete construction logic rule chain to support the efficient implementation of the project.

[0124] Here is a specific example: In a large commercial complex project, the design information is first integrated through the building information modeling software to establish a mapping relationship table between equipment types and installation parameters. Then, the geometric modeling technology is used to generate equipment placement verification rules, and the linkage constraints are determined by analyzing the layout of adjacent equipment. Then, the relationship between the tightening torque and the equipment quality parameters is analyzed to generate the torque graded loading strategy and the tightening sequence dependency. At the same time, the equipment power parameters and thermal radiation attenuation coefficients are collected, the dynamic safe heat dissipation distance is calculated, and the thermal field mutual exclusion trigger rules are generated. Finally, all rules are arranged in time sequence according to the construction process stage to form a complete construction logic rule chain to ensure that the equipment installation process is efficient and safe.

[0125] In summary, steps 601 to 604 achieve high-precision control and safety assurance during the equipment installation process. Through precise space planning and reasonable construction arrangements, installation errors and equipment overheating risks are reduced, and the overall quality and economic benefits of the project are improved. This solution not only enhances the operability and safety of the project, but also provides strong support for subsequent maintenance and management. The application of dynamic knowledge graphs makes the construction process more intelligent and automated, greatly improving the efficiency and accuracy of engineering management.

[0126] In order to solve the problem of dynamic adjustment after composite risk assessment in construction projects, the scheme reversely adjusts the stress threshold parameters in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array according to the composite risk level assessment results. The stress threshold parameters are generated by establishing a dynamic mapping relationship between the collision probability threshold and the stress threshold of the load-bearing structure, and the sampling frequency is adjusted according to the time distribution characteristics of the construction process conflict index. The sampling frequency is increased during peak periods to improve accuracy, and the sampling frequency is reduced during intermittent periods to save resources. At the same time, coupling constraints between the stress threshold parameters and the sampling frequency are set to ensure the safety and efficiency of the construction process. In some embodiments, the reverse adjustment of the stress threshold parameters in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array according to the composite risk level assessment results in step 105 includes: 701. Based on the equipment collision probability value in the composite risk level assessment result, a dynamic mapping relationship between a collision probability threshold and a load-bearing structure stress threshold is established to generate a stress threshold parameter; In step 701, the composite risk level assessment result is a risk assessment result obtained by comprehensively considering multiple factors such as equipment collision probability and construction process conflict index. The equipment collision probability value refers to the possibility of collision between different equipment during the construction process. The collision probability threshold sets a critical value. When the actual collision probability exceeds this value, the corresponding adjustment measures are triggered. The load-bearing structure stress threshold refers to the maximum stress value that the building's load-bearing structure is allowed to withstand under different working conditions. The stress threshold parameter is a parameter generated based on the collision probability threshold for controlling the safety of the load-bearing structure.

[0127] In the embodiment of the present application, the historical data of the equipment collision probability and the design parameters of the current project are first collected. Then, the collision probability threshold is determined by statistical analysis methods, and a dynamic mapping relationship between it and the stress threshold of the load-bearing structure is established. Then, the structural safety under different stress conditions is calculated using finite element analysis technology to generate stress threshold parameters. The final result is a solution that can reflect the equipment collision risk in real time and adjust the stress threshold.

[0128] 702. Analyze the time distribution characteristics of the construction process conflict index, divide the construction period into a peak period and an intermittent period in combination with the construction stage parameters, increase the sampling frequency of the ultra-wideband positioning device array according to the deviation amplitude of the mobile device trajectory prediction during the peak period, and reduce the sampling frequency in proportion to the change rate of the mobile device space occupation hot zone distribution during the intermittent period; In step 702, the time distribution characteristics of the construction process conflict index describe the frequency and time distribution of conflicts in each stage of the construction process. The peak period and the off-peak period of the construction cycle divide the construction process into a high-load working period (peak period) and a low-load working period (off-peak period). The mobile device trajectory prediction deviation amplitude refers to the position prediction error range caused by the movement of the device during the peak period.

[0129] In the embodiment of the present application, the time distribution characteristics of the construction process conflict index are first analyzed, and the construction period is divided into peak period and intermittent period in combination with the construction stage parameters. Next, during the peak period, the sampling frequency of the ultra-wideband positioning device array is increased according to the deviation amplitude of the mobile device trajectory prediction to improve the position tracking accuracy. Then, during the intermittent period, the sampling frequency is proportionally reduced according to the change rate of the hot zone distribution of the mobile device space occupancy to save resources. The final result is to dynamically adjust the signal sampling frequency of the ultra-wideband positioning device according to the construction progress to ensure efficient and economical equipment tracking.

[0130] 703. Establish a coupling constraint condition between the stress threshold parameter and the sampling frequency, so that when the stress threshold parameter is reduced and the sampling frequency is increased at the same time, the stress threshold parameter is adjusted so as not to exceed the structural safety boundary; In step 703, the coupling constraint of the stress threshold parameter and the sampling frequency ensures that the structural safety margin is not exceeded when the stress threshold and the sampling frequency are adjusted simultaneously. The structural safety margin refers to the maximum stress and minimum safety factor allowed for the load-bearing structure of the building. The coupling constraint defines the relationship between the reduction of the stress threshold and the increase of the sampling frequency to prevent excessive adjustment from affecting the overall safety.

[0131] In the embodiment of the present application, firstly, a coupling constraint condition is established between the stress threshold parameter and the sampling frequency to ensure that the adjustment of the two does not exceed the structural safety boundary. Next, an optimization algorithm is used to simulate the impact of different adjustment strategies on structural safety and equipment positioning accuracy to find the optimal balance point. Then, detailed adjustment rules are formulated so that when the stress threshold parameter is lowered and the sampling frequency is increased at the same time, the stress threshold parameter adjustment does not exceed the structural safety boundary. The final result is a coupling constraint mechanism that can both ensure structural safety and improve equipment positioning accuracy.

[0132] 704. Reversely inject the adjusted stress threshold parameter into the load-bearing structure node attribute of the engineering management data model, and configure the signal sampling frequency sent to the ultra-wideband positioning device array under the coupling constraint condition.

[0133] In step 704, the adjusted stress threshold parameter refers to a new stress threshold generated according to the composite risk level assessment result. The load-bearing structure node attributes of the engineering management data model include the design parameters and stress thresholds of each load-bearing node. The signal sampling frequency configuration sent to the ultra-wideband positioning device array under the coupling constraint condition applies the adjusted coupling constraint condition to the actual operation of the ultra-wideband positioning device.

[0134] In the embodiment of the present application, the adjusted stress threshold parameters are firstly reversely injected into the load-bearing structure node attributes of the engineering management data model to update the safety index of each node. Next, the signal sampling frequency configuration sent to the ultra-wideband positioning device array under the coupling constraint condition ensures that the sampling frequency can be dynamically adjusted in actual construction. Then, the building information model system is used to monitor the entire process, verify the adjustment effect and make necessary fine-tuning. The final result is a fully integrated engineering management solution that can maintain efficiency and safety in a dynamic environment.

[0135] Here is a specific example: In a large commercial complex project, firstly, according to the equipment collision probability value in the composite risk level assessment result, a dynamic mapping relationship between the collision probability threshold and the stress threshold of the load-bearing structure is established to generate the stress threshold parameter. Then, the time distribution characteristics of the construction process conflict index are analyzed. During the peak period, the sampling frequency of the ultra-wideband positioning device array is increased according to the deviation amplitude of the mobile device trajectory prediction. During the intermittent period, the sampling frequency is proportionally reduced according to the change rate of the hot zone distribution of the mobile device space occupation. Then, the coupling constraint condition of the stress threshold parameter and the sampling frequency is established to ensure that the stress threshold parameter adjustment does not exceed the structural safety boundary. Finally, the adjusted stress threshold parameter is reversely injected into the load-bearing structure node attribute of the engineering management data model to ensure the construction process is efficient and safe.

[0136] In summary, steps 701 to 704 realize dynamic adjustment after composite risk assessment in construction projects, improve the accuracy of the project management data model and the efficiency of the ultra-wideband positioning device array. Through accurate risk assessment and real-time adjustment, the potential risks in the construction process are reduced, and the overall quality and economic benefits of the project are improved. This solution not only enhances the operability and safety of the project, but also provides strong support for subsequent maintenance and management. The application of dynamic knowledge graphs makes the construction process more intelligent and automated, greatly improving the efficiency and accuracy of project management.

[0137] Figure 2 A schematic diagram of a structure of an information system engineering supervision project risk adaptive assessment system is provided for the present application embodiment. Figure 2 As shown, the system includes: Construction module 21, constructing an engineering management data model that integrates the building information model and the geographic information system, integrating the multi-dimensional risk factor set of pipeline pre-buried parameters, load-bearing structure stress thresholds and equipment installation specification requirements, and forming a dynamic knowledge graph that includes spatial constraints and construction logic rules; Capture module 22 deploys an array of ultra-wideband positioning devices to capture the three-dimensional coordinate trajectory of the construction machinery in real time, eliminates positioning deviations through multipath interference suppression technology, and generates mobile equipment space occupation hot zone distribution data; A coupling module 23 is used to establish a digital twin-driven operation simulation environment, dynamically couple the risk factors in the dynamic knowledge graph with the spatial occupancy hot zone distribution data, and generate a spatiotemporal risk topology network including network equipment installation path conflict warnings and safety spacing warnings; Forming module 24, dynamically adjusting the weight distribution strategy of the construction machinery trajectory risk assessment parameters based on the node density distribution characteristics of the spatiotemporal risk topological network, and forming a composite risk level assessment result including the equipment collision probability and the construction process conflict index; The adjustment module 25 reversely adjusts the stress threshold parameters in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array according to the composite risk level assessment result.

[0138] Figure 2 The information system engineering supervision project risk adaptive assessment system can be executed Figure 1 The implementation principle and technical effect of the adaptive risk assessment method for information system engineering supervision project described in the embodiment are not described in detail. The specific way in which each module and unit performs operations in the adaptive risk assessment system for information system engineering supervision project in the above embodiment has been described in detail in the embodiment of the method, and will not be described in detail here.

[0139] In one possible design, Figure 2 An adaptive risk assessment system for information system engineering supervision projects in the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0140] The processing component 32 is used for the above Figure 1 The embodiment provides an adaptive risk assessment method for an information system engineering supervision project.

[0141] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0142] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0143] Of course, the computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0144] The input / output interface provides an interface between the processing component and the peripheral interface module, which may be an output device, an input device, etc.

[0145] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0146] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0147] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The illustrated embodiment is a method for adaptively assessing the risks of an information system engineering supervision project.

[0148] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0149] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0150] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A risk adaptive assessment method for information system engineering supervision projects, characterized in that: include: Construct an engineering management data model that integrates building information model and geographic information system, integrate the multi-dimensional risk factor set of pipeline pre-buried parameters, load-bearing structure stress threshold and equipment installation specification requirements, and form a dynamic knowledge map that includes spatial constraints and construction logic rules; Deploy an array of ultra-wideband positioning devices to capture the three-dimensional coordinate trajectory of construction machinery in real time, eliminate positioning deviations through multipath interference suppression technology, and generate mobile equipment space occupancy hotspot distribution data; Establishing a digital twin-driven operation simulation environment, dynamically coupling the risk factors in the dynamic knowledge graph with the mobile device space occupancy hotspot distribution data, and generating a spatiotemporal risk topology network including network equipment installation path conflict warnings and safety spacing warnings; Based on the node density distribution characteristics of the spatiotemporal risk topological network, the weight allocation strategy of the construction machinery trajectory risk assessment parameters is dynamically adjusted to form a composite risk level assessment result including the equipment collision probability and the construction process conflict index; The stress threshold parameters in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array are reversely adjusted according to the composite risk level assessment result.

2. The method according to claim 1, characterized in that The method of dynamically coupling the risk factors in the dynamic knowledge graph with the mobile device space occupancy hotspot distribution data to generate a spatiotemporal risk topology network including network device installation path conflict warnings and safety spacing warnings includes: Based on the spatial coordinate set of pipeline pre-buried parameters in the dynamic knowledge graph and the safety spacing threshold required by the equipment installation specification, a risk factor association model is established; According to the real-time motion vectors in the mobile device space occupancy hot zone distribution data, the three-dimensional trajectory envelope of each mobile device is calculated in a preset time window, and the device motion trend projection is generated through interpolation prediction; Performing spatiotemporal grid discrete analysis on the spatiotemporal influence domain in the risk factor association model and the projection of the equipment movement trend, calculating the network equipment installation path conflict probability value for each grid unit, the network equipment installation path conflict probability value being obtained by weighting the area ratio of the equipment trajectory penetrating the pipeline influence domain and the time overlap coefficient; A dynamic safety distance threshold function is constructed based on the stress threshold parameters of the load-bearing structure, and the safety distance threshold is adjusted in real time according to the equipment mass parameters and motion acceleration; The network equipment installation path conflict probability value and the safety distance threshold are integrated to construct a spatiotemporal association matrix, and a spatiotemporal risk topology network including network equipment installation path conflict warning and safety distance alarm is generated.

3. The method according to claim 2, characterized in that The step of performing a spatiotemporal grid discrete analysis on the spatiotemporal influence domain in the risk factor association model and the device movement trend projection, and calculating a network device installation path conflict probability value for each grid unit, includes: Establishing a space-time grid division mechanism aligned with the coordinate system of the risk factor association model, discretizing the three-dimensional space coordinate axis into cubic units, and dividing the time axis into time windows according to the construction progress to obtain space-time grid units; Traversing the space-time grid unit, extracting the trajectory segments of the device movement trend projection, calculating the geometric intersection volume of the trajectory segments, and taking the ratio of the geometric intersection volume to the total volume of the pipeline influence domain as the spatial permeability; Calculate the intersection duration of the trajectory segment within the time window and the pipeline influence domain activation period, and take the ratio of the intersection duration to the preset time window length as the time coverage; Obtaining a preset spatial permeability weight factor and a temporal coverage weight factor according to the pipeline type parameters, linearly combining the spatial permeability and the temporal coverage, and generating a dynamic probability value reflecting the pipeline collision risk; When the device movement trend projection involves a multi-pipeline intersection area, the dynamic probability values ​​of the pipelines in the same spatiotemporal grid unit are superimposed and calculated to generate a network device installation path conflict probability value.

4. The method according to claim 3, characterized in that The linear combination of the spatial permeability and the temporal coverage to generate a dynamic probability value reflecting the pipeline collision risk includes: Establish a mapping relationship table of pipeline type parameters, spatial permeability weight factors and time coverage weight factors, set the reference values ​​of spatial permeability and time coverage according to the engineering attribute characteristics, and dynamically modify the reference values ​​according to the current construction stage parameters; According to the corrected benchmark value, a two-dimensional weight vector is constructed, and homogeneous coordinate transformation is performed on the spatial permeability and the temporal coverage to generate a risk vector containing spatiotemporal characteristics; Calculate the risk coupling coefficient according to the pipeline type parameters and the construction machinery type parameters, and perform a tensor product operation on the risk vector and the risk coupling coefficient to obtain an initial probability tensor; The electromagnetic interference intensity parameter of the pipeline intersection area is introduced as an environmental correction factor, and the initial probability tensor is nonlinearly mapped to generate a dynamic probability value reflecting the pipeline collision risk.

5. The method according to claim 1, characterized in that The multi-dimensional risk factor set integrating pipeline pre-buried parameters, load-bearing structure stress thresholds and equipment installation specification requirements forms a dynamic knowledge graph containing spatial constraints and construction logic rules, including: Based on the pipeline pre-buried parameters, a spatial collision rule is generated through the minimum clearance constraint between pipelines, wherein the spatial collision rule includes a three-dimensional buffer zone parameter of the pipeline intersection area; Analyze the time-varying parameters of the stress threshold of the load-bearing structure, establish a stress propagation path model based on the topological relationship of the support points, and generate dynamic constraint conditions including the maximum allowable load based on the mechanical transfer characteristics between the support points; Convert positioning tolerance, tightening torque and heat dissipation spacing parameters in equipment installation specification requirements into a construction logic rule chain, wherein the construction logic rule chain includes process execution priority parameters and mutually exclusive trigger conditions for parallel operations; Based on the spatial coordinate system of the building information model, the spatial collision rules, dynamic constraints and construction logic rule chains are topologically encoded, and a dynamic knowledge graph is formed by defining the spatial interference relationship between pipelines and load-bearing structures, and the logical dependency relationship between construction procedures and equipment trajectories.

6. The method according to claim 5, characterized in that The conversion of positioning tolerance, tightening torque and heat dissipation spacing parameters in the equipment installation specification requirements into a construction logic rule chain includes: Establish a mapping relationship table between equipment types and installation parameters in equipment installation specification requirements, and generate equipment in-place verification rules based on the horizontal deviation threshold and vertical settlement tolerance in the positioning tolerance parameters. The equipment in-place verification rules include linkage constraints on the allowable deviation range and the spacing between adjacent equipment. Analyze the functional relationship between the tightening torque and the equipment quality parameters, establish a torque gradient adjustment model, and generate installation strength rules that include the torque graded loading strategy and the tightening sequence dependency; Based on the thermal radiation attenuation coefficient in the heat dissipation spacing parameters and the equipment power parameters, the dynamic safe heat dissipation distance is calculated to generate the thermal field mutual exclusion triggering rules when the equipment cluster is deployed; The equipment placement verification rules, installation strength rules and thermal field mutually exclusive triggering rules are arranged in time sequence according to the construction process stages to obtain a construction logic rule chain.

7. The method according to claim 1, characterized in that The reversely adjusting the stress threshold parameter in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array according to the composite risk level assessment result includes: Based on the equipment collision probability value in the composite risk level assessment result, a dynamic mapping relationship between a collision probability threshold and a load-bearing structure stress threshold is established to generate a stress threshold parameter; Analyze the time distribution characteristics of the construction process conflict index, and divide the construction period into a peak period and an intermittent period in combination with the construction stage parameters. During the peak period, increase the sampling frequency of the ultra-wideband positioning device array according to the deviation amplitude of the mobile device trajectory prediction, and during the intermittent period, reduce the sampling frequency in proportion to the change rate of the hot zone distribution of the mobile device space occupation; Establishing a coupling constraint condition between the stress threshold parameter and the sampling frequency, so that when the stress threshold parameter is lowered and the sampling frequency is increased at the same time, the stress threshold parameter is adjusted so as not to exceed the structural safety boundary; The adjusted stress threshold parameters are reversely injected into the load-bearing structure node attributes of the engineering management data model, and the signal sampling frequency configuration sent to the ultra-wideband positioning device array under the coupling constraint condition is configured.

8. An adaptive risk assessment system for information system engineering supervision projects, characterized in that: include: Construction module, build an engineering management data model that integrates building information model and geographic information system, integrates the multi-dimensional risk factor set of pipeline pre-buried parameters, load-bearing structure stress threshold and equipment installation specification requirements, and forms a dynamic knowledge map containing spatial constraints and construction logic rules; The capture module deploys an array of ultra-wideband positioning devices to capture the three-dimensional coordinate trajectory of construction machinery in real time, eliminates positioning deviations through multipath interference suppression technology, and generates mobile equipment space occupancy hot zone distribution data; A coupling module is used to establish a digital twin-driven operation simulation environment, dynamically couple the risk factors in the dynamic knowledge graph with the spatial occupancy hot zone distribution data, and generate a spatiotemporal risk topology network including network equipment installation path conflict warnings and safety spacing warnings; A formation module is provided to dynamically adjust the weight allocation strategy of the construction machinery trajectory risk assessment parameters based on the node density distribution characteristics of the spatiotemporal risk topological network to form a composite risk level assessment result including the equipment collision probability and the construction process conflict index; The adjustment module reversely adjusts the stress threshold parameters in the engineering management data model and the signal sampling frequency configuration of the ultra-wideband positioning device array according to the composite risk level assessment result.

9. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement the information system engineering supervision project risk adaptive assessment method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a computer, the information system engineering supervision project risk adaptive assessment method as described in any one of claims 1 to 7 is implemented.

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