BIM-based building construction risk assessment system and method

Abstract

The invention relates to the technical field of construction risk assessment, in particular to a BIM-based building construction risk assessment system and method, and the system comprises a construction environment dynamic recognition module, an operation flow correlation analysis module, a personnel path optimization module, a mechanical range adaptation module and a risk grading judgment module. According to the method, the construction site environment is comprehensively and dynamically identified, the influence of the environment on the construction operation can be deeply analyzed, the construction plan is adjusted in real time, the operation process is optimized, the construction arrangement is more reasonable, the progress lag problem is reduced, and the construction efficiency is improved. Optimized management of personnel paths effectively reduces path conflicts and potential safety hazards, construction safety and efficiency are guaranteed, precise division of a mechanical operation range improves equipment operation efficiency, resource waste is reduced, the intelligent level of construction management is improved through linkage analysis of environments, procedures, personnel and machines, and the construction safety and efficiency are improved. And efficient, safe and standard operation of construction projects is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of construction risk assessment, and in particular to a BIM-based building construction risk assessment system and method. Background Art

[0002] The technical field of construction risk assessment includes the identification, analysis and evaluation of various risk factors that affect construction safety, progress and quality during the construction process of building projects. The core content of this technical field includes the identification and classification of risks in the construction site environment, work processes, personnel arrangements, material management, machinery use, etc., and the determination of risk levels through quantitative assessment methods. Construction risk assessment relies on risk identification models, original data analysis, expert judgment mechanisms, etc. to predict and warn potential problems in the entire construction process, thereby assisting construction decision-making and safety management. This field has a broad research and application foundation in the informatization, standardization and refinement of construction management, and has gradually formed a systematic analysis framework and evaluation mechanism supported by data.

[0003] Among them, the BIM-based construction risk assessment system refers to a risk assessment system that integrates and correlates three-dimensional modeling technology with risk factors at various stages of the construction process on the basis of the building information model. The theme mainly focuses on the identification, data association and assessment process of various dynamic risks in the construction stage. Specifically, it extracts and analyzes parameters such as the spatial attributes, time arrangements, working conditions, personnel paths, and operating range of construction machinery of the components in the BIM model, and conducts correlation analysis based on the actual information of the construction site such as the construction schedule, weather changes, and personnel flow paths, so as to realize the prediction of potential risk points and the classification of risk levels. It relies on the existing component attributes and construction progress data in the building information model, combines the original risk data and specification requirements, and uses logical judgment and multi-source information matching methods to conduct structured assessment modeling of construction risks in specific time periods and spatial locations.

[0004] Existing technologies rely on traditional risk identification and assessment methods, limited to static data analysis, and overlook the multiple dynamic factors of the construction process. For example, changes in the construction site environment, the dynamics of personnel flow, and the real-time status of machinery and equipment are not fully incorporated into the risk assessment system, resulting in risk predictions that fail to timely reflect the actual on-site situation. Work process assessments often rely on raw data, failing to accurately analyze the resource matching and process connection within the current construction process, which can easily lead to construction schedule delays. Personnel route planning is relatively simple and cannot effectively address the complexities of on-site personnel flow, resulting in personnel congestion and conflicts with work areas, compromising construction safety. The operating range of machinery and equipment is assessed based on fixed parameters, ignoring changing site conditions and failing to accurately delineate suitable areas for machinery, thus affecting equipment efficiency and safety. This leads to lags and deficiencies in early warning mechanisms in construction management, making it impossible to accurately assess risks and make timely adjustments at the most critical moments, resulting in unforeseen safety hazards and resource waste during construction. Summary of the Invention

[0005] In order to solve the technical problems existing in the prior art, the embodiment of the present invention provides a construction risk assessment system and method based on BIM. The technical solution is as follows: In one aspect, a BIM-based construction risk assessment system is provided, comprising: The construction environment dynamic identification module obtains construction site environmental information, including site topographic data, meteorological condition records, and the distribution of surrounding facilities. It analyzes the impact of terrain undulations and meteorological fluctuations on construction operations and generates environmental impact factors. The operation process association analysis module extracts the key nodes and operation sequence in the construction schedule based on the environmental impact factors, analyzes the time difference between the process connection and the matching of resource allocation, and obtains the process adaptation value; The personnel path optimization module extracts the movement paths of construction personnel on site based on the process fitness value, analyzes the relationship between the path coverage and the spatial layout of the work area, and generates a path planning optimization set; The mechanical range adaptation module calls the path planning optimization set, extracts the spatial distribution of the mechanical equipment operating range and component installation positions, analyzes the coupling degree between mechanical accessibility and operating efficiency, and generates mechanical adaptation area division.

[0006] As a further solution of the present invention, the environmental influencing factors include terrain undulation, frequency of weather fluctuations, and interference from surrounding facilities; the process adaptation value includes node connection time difference, resource allocation matching rate, and job priority weight; the path planning optimization set includes path coverage ratio, regional layout matching, and path optimization score; the mechanical adaptation area division includes mechanical accessibility index, operation efficiency adaptation, and space utilization.

[0007] As a further solution of the present invention, the construction environment dynamic identification module includes: The terrain data extraction submodule obtains construction site environmental information, extracts terrain height differences and slope changes, analyzes the impact of terrain undulation on mechanical equipment deployment, and generates terrain undulation. The weather fluctuation analysis submodule extracts the wind speed, precipitation and temperature change values ​​from the weather condition records based on the terrain undulation, analyzes the degree of restriction of weather fluctuations on construction conditions, and generates the weather fluctuation frequency; The facility interference assessment submodule extracts the distribution information of surrounding facilities based on the frequency of meteorological fluctuations, analyzes the scope and frequency of physical interference of facilities on the construction site, and generates environmental impact factors.

[0008] As a further solution of the present invention, the operation process association analysis module includes: The process node extraction submodule extracts key process nodes in the construction schedule based on the environmental impact factors, analyzes the time intervals and resource requirements between nodes, and generates the node connection time difference; The resource allocation matching submodule extracts the material and equipment supply cycles in resource allocation based on the node connection time difference, analyzes the matching degree between resource supply and process requirements, and generates a resource allocation matching rate; The priority weight calculation submodule calls the resource allocation matching rate, extracts the job priority ranking table, analyzes the impact of the priority ranking on the process connection, and obtains the process adaptation value.

[0009] As a further solution of the present invention, the personnel path optimization module includes: The path coverage extraction submodule extracts the movement trajectory of the construction workers on site according to the process fitness value, analyzes the relationship between the trajectory coverage range and the spatial distribution of the work area, and generates the path coverage ratio; The regional layout matching submodule calls the path coverage ratio, extracts the spatial layout information of the operation area, analyzes the matching degree between the path coverage and the regional layout, and generates the regional layout matching degree; The path optimization scoring submodule analyzes the degree to which path optimization improves construction efficiency based on the regional layout matching degree and generates a path planning optimization set.

[0010] As a further solution of the present invention, the mechanical range adaptation module includes: The mechanical accessibility analysis submodule calls the path planning optimization set, extracts the spatial distribution of the mechanical equipment operating range and component installation positions, analyzes the coverage of the mechanical operating range, and generates a mechanical accessibility index; The operation efficiency adaptation submodule extracts the relationship between the operation efficiency of the mechanical equipment and the component installation time based on the mechanical accessibility index, analyzes the degree of adaptation between the mechanical operation efficiency and the operation requirements, and generates the operation efficiency adaptation degree; The space utilization calculation submodule calls the operation efficiency adaptation degree, extracts the degree of overlap between the machine operation range and the construction site space, analyzes the space utilization efficiency, and generates the machine adaptation area division.

[0011] As a further solution of the present invention, the operating efficiency adaptability is calculated using the formula: ; in, Represents the adaptability of operating efficiency, Representative The unit time efficiency of a kind of mechanical equipment, Representative The time required to install the components, Representative The average operating time used by a type of mechanical equipment to perform the corresponding component installation task, Representative The real-time installation demand response time of various components, Represents the number of machine-component combinations involved in the fitness analysis.

[0012] As a further solution of the present invention, the system also includes a risk classification determination module: The risk classification module is based on the mechanical adaptation area division, combined with the original risk data and specification requirements, to analyze the regional risk occurrence probability and impact intensity, and generate a construction risk level assessment result; The construction risk level assessment results include the risk occurrence probability interval, impact intensity level, and risk score.

[0013] As a further solution of the present invention, the risk classification determination module includes: The risk probability analysis submodule extracts the number of risk occurrences and time distribution in the original risk data based on the mechanical adaptation area division, analyzes the frequency and periodicity of risk occurrence, and generates a risk occurrence probability interval; The impact intensity assessment submodule calls the risk occurrence probability interval, extracts the impact degree of the risk event on the construction progress and quality, analyzes the distribution characteristics of the impact intensity, and generates the impact intensity level; The risk scoring submodule analyzes the distribution pattern of regional risk scores based on the impact intensity level and the risk level classification standards in the specification requirements to generate a construction risk level assessment result.

[0014] In another aspect, a BIM-based construction risk assessment method is provided. The BIM-based construction risk assessment method is performed based on the BIM-based construction risk assessment system, and includes the following steps: S1: Obtain construction site environmental information, including site topographic data, meteorological condition records, and the distribution of surrounding facilities. Extract terrain height differences and slope changes, analyze the degree to which meteorological fluctuations restrict construction conditions, and obtain environmental impact factors. S2: Based on the environmental impact factors, extract the key process nodes and resource allocation plan in the construction schedule, analyze the process connection time difference and resource allocation matching, and generate the process adaptability value; S3: Based on the process adaptation value, the movement path of the construction personnel in the site is extracted, the relationship between the path coverage and the spatial layout of the work area is analyzed, and a path optimization solution set is established; S4: Based on the path optimization solution set, extract the spatial distribution of the mechanical equipment operating range and component installation location, analyze the coupling degree between mechanical accessibility and operating efficiency, and generate mechanical adaptation area division; S5: Based on the mechanical adaptation area division, the risk occurrence frequency and impact range in the original risk data are extracted, and combined with the risk level division standards in the specification requirements, the distribution pattern of regional risk occurrence probability and impact intensity is analyzed to generate the construction risk level assessment result.

[0015] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least: By comprehensively and dynamically identifying the construction site environment, combined with topographic data, meteorological conditions, and surrounding facilities, an in-depth analysis of the actual impact of environmental factors on construction operations can be conducted. This analysis enhances sensitivity to environmental changes, enabling real-time adjustments to construction plans and proactively preventing potential risks. Workflow optimization, through adaptive analysis of process transition time differences and resource allocation, streamlines construction scheduling and mitigates schedule delays caused by process disruptions or resource conflicts. Furthermore, personnel routing optimization further refines on-site personnel flow management, effectively reducing safety hazards caused by excessive personnel concentration and routing conflicts, and ensuring construction efficiency and safety. Precise demarcation of machinery operating ranges streamlines equipment operation zones, reduces resource waste, improves equipment efficiency, and ensures maximum equipment utilization during construction. This comprehensive, integrated analysis of the environment, processes, personnel, and machinery provides a novel risk prediction and early warning mechanism. This precise assessment, based on multi-dimensional, comprehensive data, enhances the intelligence of construction management and promotes the efficient, safe, and standardized operation of construction projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 Schematic diagram of a BIM-based construction risk assessment system provided by an embodiment of the present invention; Figure 2 Schematic diagram of the system framework of the present invention; Figure 3 This is a flow chart of the construction environment dynamic identification module in the present invention; Figure 4 This is a flowchart of the operation process association analysis module in the present invention; Figure 5 This is a flow chart of the personnel path optimization module in the present invention; Figure 6 This is a flow chart of the mechanical range adaptation module in the present invention; Figure 7 This is a flow chart of the risk classification determination module in the present invention; Figure 8 This is a flowchart of a BIM-based construction risk assessment method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0019] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0020] In the embodiments of the present invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, when the distinction is not emphasized, the meanings they convey are the same. The terms "of," "corresponding," and "corresponding" may sometimes be used interchangeably. It should be noted that, when the distinction is not emphasized, the meanings they convey are the same.

[0021] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0022] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0023] The embodiment of the present invention provides a BIM-based construction risk assessment system. Figure 1-2 The schematic diagram of the BIM-based construction risk assessment system shown in the figure includes: The construction environment dynamic identification module obtains construction site environmental information, including site topographic data, meteorological condition records, and the distribution of surrounding facilities. It analyzes the impact of terrain undulations and meteorological fluctuations on construction operations and generates environmental impact factors. The operation process association analysis module extracts key nodes and operation sequences in the construction schedule based on environmental impact factors, analyzes the time difference between process connections and the matching of resource allocation, and obtains the process adaptation value; The personnel path optimization module extracts the movement paths of construction personnel on site based on the process adaptation value, analyzes the relationship between the path coverage and the spatial layout of the work area, and generates an optimized path planning set; The mechanical range adaptation module calls the path planning optimization set to extract the spatial distribution of the mechanical equipment operating range and component installation locations, analyzes the coupling degree between mechanical accessibility and operating efficiency, and generates mechanical adaptation area divisions; The risk grading module is based on the mechanical adaptation area division, combined with the original risk data and specification requirements, to analyze the regional risk probability and impact intensity, and generate construction risk level assessment results.

[0024] Environmental influencing factors include terrain undulation, frequency of meteorological fluctuations, and interference from surrounding facilities. Process adaptability values ​​include node connection time difference, resource allocation matching rate, and operation priority weight. Path planning optimization set includes path coverage ratio, regional layout matching, and path optimization score. Mechanical adaptation area division includes mechanical accessibility index, operation efficiency adaptability, and space utilization rate. Construction risk level assessment results include risk probability interval, impact intensity level, and risk score.

[0025] Specifically, if Figure 2 、 3 As shown in Figure 1, the construction environment dynamic identification module includes: The terrain data extraction submodule obtains construction site environmental information, extracts terrain height differences and slope changes, analyzes the impact of terrain undulation on mechanical equipment deployment, and generates terrain undulation. First, collect a digital elevation model (DEM) or field-measured topographic data for the construction site. Determining topographic relief relies on accurate analysis of the terrain. For the construction site, the elevation of various locations is first measured using a digital instrument or handheld GPS. The elevation value for each point is then calculated from this data. Two key parameters are then calculated: the elevation difference and the slope change. The elevation difference is calculated by taking the difference between the maximum and minimum elevations within a given area to assess the site's relief. For example, if the highest point in a construction site is 500 meters above sea level and the lowest is 450 meters, the elevation difference is 50 meters. The slope change is calculated by taking the ratio of the elevation difference between adjacent points to the horizontal distance. A common formula is slope = (elevation difference / horizontal distance) × 100%. If the horizontal distance between two points in the construction area is 100 meters and the elevation difference is 30 meters, the slope is 30%. This data not only reflects the degree of terrain undulation, but also provides a reference for subsequent analysis of the stability of the machinery deployment position. Through parameters, the impact of terrain undulation on equipment layout can be further analyzed. For example, in areas with larger slopes, special equipment support or changes in deployment strategies are required, and then relevant values ​​of terrain undulation are generated as a basis for subsequent decision-making.

[0026] The weather fluctuation analysis submodule extracts wind speed, precipitation, and temperature change values ​​from weather condition records based on terrain undulation, analyzes the degree to which weather fluctuations restrict construction conditions, and generates weather fluctuation frequencies; Based on the terrain relief, raw meteorological data is combined with current wind speed, precipitation, and temperature trends for analysis. For example, when wind speeds exceed a certain threshold, construction site machinery and equipment will be affected. For example, the stability of equipment like tower cranes is affected by wind speed fluctuations. The wind speed threshold can be set through field testing. For example, when wind speeds exceed 15 meters per second, equipment safety and operational efficiency will be significantly impacted. Temperature fluctuations are equally important. Excessively high or low temperatures can affect the curing speed of concrete or the strength of the material. By analyzing various meteorological factors, it is possible to identify which weather fluctuations most significantly restrict construction operations and ultimately calculate the frequency of these fluctuations. For example, if meteorological data records for a particular location indicate that the area experiences an average of five wind speed events exceeding 16 meters per second per year, the frequency of wind speed fluctuations in that area will be calculated as five per year. This data can provide construction site managers with a forecast of the impact of meteorological conditions on construction progress, facilitating effective work planning.

[0027] The facility interference assessment submodule extracts information on the distribution of surrounding facilities based on the frequency of meteorological fluctuations, analyzes the scope and frequency of physical interference of facilities on the construction site, and generates environmental impact factors; Based on the frequency of meteorological fluctuations, their impact on surrounding facilities is analyzed. Facilities surrounding the construction site, such as high-voltage power lines, communication towers, or transportation facilities, can interfere with construction activities under different meteorological conditions. Interference analysis is performed by obtaining spatial distribution data of surrounding facilities and combining it with meteorological fluctuation frequency data. Specifically, the distance and relative position of each facility to the construction site are determined. For each facility, the degree of interference is assessed based on the impact of meteorological fluctuations. For example, when wind speeds exceed 15 m / s, overhead power lines sway due to the wind, causing some physical interference to on-site operations. In this case, the construction site needs to be adjusted based on the interference range of the facilities to avoid the danger zone. By analyzing the interference range and frequency, an environmental impact factor can be generated, which reflects the intensity of the impact of external facilities on the construction site. For example, if a high-voltage power line is close to the construction site and is frequently affected by wind speed fluctuations, the value of this factor will be high, prompting construction managers to take appropriate protective measures in advance to reduce interference from external facilities on construction.

[0028] Specifically, if Figure 2 、 4 As shown, the operation process association analysis module includes: The process node extraction submodule extracts key process nodes in the construction schedule based on environmental impact factors, analyzes the time intervals and resource requirements between nodes, and generates the node connection time difference; Critical process nodes are identified from the construction schedule. Critical process nodes are processes that have a significant impact on the construction progress, such as foundation engineering and steel structure installation. Based on the specific requirements of each node, such as start time, end time, and required resources, the time intervals between nodes are calculated. Combined with the values ​​of environmental impact factors, the specific implementation impacts of the processes under different environmental conditions are analyzed. For example, if the environmental impact factor at the construction site is high due to adverse weather conditions such as high wind speeds and heavy precipitation, the time intervals between processes need to be appropriately extended, or if there is a high demand for specific equipment or materials, more buffer time needs to be left in the schedule. By analyzing the resource requirements of each process node, the optimal resource allocation can be evaluated, and the node connection time difference can be calculated. For example, if the original time between two process nodes is 7 days, but due to weather conditions, the time delay is increased by 2 days, the final node connection time difference is 9 days. The calculation of this time difference requires a combination of factors, including resource requirements, environmental impacts, and weather fluctuations, to ensure the rationality and feasibility of the construction schedule.

[0029] The resource allocation matching submodule extracts the material and equipment supply cycles in resource allocation based on the node connection time difference, analyzes the matching degree between resource supply and process requirements, and generates the resource allocation matching rate; Based on the time difference between node connections, corresponding resource allocation information, including the supply cycle of materials and equipment, is extracted. The key to this process is understanding the supply cycle of the resources required for each node. For example, the supply cycle of concrete materials required for a construction task is 5 days, while the delivery time for a certain piece of equipment is 3 days. When the time difference between processes (such as the 9 days mentioned above) differs from the resource supply cycle, a matching degree is calculated to ensure that the supply of resources meets construction needs. For example, if the material and equipment supply cycle is relatively long, the material distribution plan is optimized based on the current time difference and resource demand forecast to ensure that all materials and equipment arrive on time. To this end, the cycle times of different resources are compared and the resource allocation matching rate is calculated. For example, if a piece of equipment has a supply cycle of 3 days and a time difference of 9 days, the matching rate for that piece of equipment is 100% (the demand can be fully met within 9 days). If the equipment supply cycle is 10 days, the matching rate is 90% (the demand is fully met within 10 days). Based on this calculation method, a corresponding matching rate is assigned to each resource, and the resource allocation strategy is further adjusted to ensure the rational utilization of resources during construction.

[0030] The priority weight calculation submodule calls the resource allocation matching rate, extracts the job priority ranking table, analyzes the impact of priority ranking on process connection, and obtains the process adaptation value; The activity priority table ranks construction processes based on factors such as the urgency and importance of the project. Higher-priority processes require tighter schedules and greater resource requirements. The activity priority table is first extracted, and then the resource availability of each process is analyzed based on the resource allocation match ratio. For higher-priority processes with a low match ratio, resource allocation adjustments are considered to prioritize the smooth progress of the process. For example, if a process has the highest priority but a resource match ratio of only 80%, the resource match ratio may need to be improved by rescheduling material delivery or equipment scheduling to ensure the completion of the high-priority process. This optimized resource allocation is used to calculate the process's fitness value, which reflects the smooth connection between processes. A higher fitness value indicates a more balanced connection between processes. For example, if a process in the priority ranking has a fitness of 95%, this means that the resource match and time schedule for that process are very reasonable, resulting in a high probability of completion.

[0031] Specifically, if Figure 2 、 5 As shown in the figure, the personnel path optimization module includes: The path coverage extraction submodule extracts the movement trajectory of construction workers on site based on the process adaptation value, analyzes the relationship between the trajectory coverage range and the spatial distribution of the work area, and generates the path coverage ratio; Based on the process adaptation value, key work areas within the construction site are determined. The work areas are determined based on factors such as the complexity of the work, equipment layout, and material storage. The actual movement trajectories of construction workers within the construction site are extracted. The trajectory data comes from GPS data collected by positioning devices or sensors worn on site, and the data reflects the specific movement routes of the personnel. On this basis, by comparing the movement trajectories of the construction workers with the spatial distribution of the work area, the trajectory coverage is analyzed to determine which areas of the work path are fully covered and which areas are undercovered. For example, if the work area of ​​a construction site is 1,000 square meters, and the construction workers move an area of ​​900 square meters during the work process, then the trajectory coverage ratio of this area is 90%. The path coverage ratio is obtained, and the coverage area is calculated based on the trajectory data and compared with the total area of ​​the work area to obtain a percentage that reflects whether the workers can effectively cover the entire work area, thereby providing data support for subsequent path optimization.

[0032] The regional layout matching submodule calls the path coverage ratio, extracts the spatial layout information of the operation area, analyzes the matching degree between the path coverage and the regional layout, and generates the regional layout matching degree; First, path coverage ratio data is required. This data is derived from the calculated trajectory coverage ratio and used as input. Based on the spatial layout of the work area, the path coverage is analyzed to determine whether it matches the actual layout of the area. The spatial layout of the work area refers to the distribution of work units, material storage areas, and equipment deployment locations within the area. In practice, if a construction worker's movement trajectory covers most of the work area, but some areas are not effectively covered due to improper equipment placement or material stacking, this will result in a path-layout mismatch. For example, if a construction worker's movement trajectory fails to cover a particularly narrow area within the work area, even with a high path coverage ratio, the work area still cannot achieve maximum efficiency. By analyzing the degree of match between the path and the area layout, the area layout match can be calculated. For example, if the total area of ​​the work area is 1000 square meters and the path covers 900 square meters, but due to layout issues, only 850 square meters are fully covered, the layout match for this area is 85%. This match analysis can generate a more reasonable work area plan and help optimize the construction site layout.

[0033] The path optimization scoring submodule analyzes the degree to which path optimization improves construction efficiency based on the regional layout matching degree and generates a path planning optimization set; Based on the regional layout matching degree, the construction site's work areas and personnel path coverage are analyzed. The optimization potential of the current path is first assessed. The calculated layout matching degree is then used to determine whether there is room for improvement in the path design. For example, if the path coverage of a particular work area is low and the layout matching degree is also poor, optimizing the path can significantly improve the coverage efficiency of that area. The optimization path parameters are considered, including the shortest distance traveled by personnel and the transportation routes of equipment and materials. The efficiency improvement achieved by the optimized path can be calculated. For example, if the optimized path reduces walking distance by 10%, the construction worker's work efficiency will increase by 10%. Based on this analysis, a series of specific optimized path solutions are proposed, and the efficiency improvement value of each solution is calculated. In a practical example, if the optimized path reduces work time by 2 hours compared to the original path and improves work efficiency by 10%, the optimized solutions are integrated into a path planning optimization set, which serves as the basis for subsequent path adjustments.

[0034] Specifically, if Figure 2 、 6 As shown, the mechanical range adaptation module includes: The mechanical accessibility analysis submodule calls the path planning optimization set to extract the spatial distribution of the mechanical equipment operating range and component installation locations, analyzes the coverage of the mechanical operating range, and generates a mechanical accessibility index; To determine the working range of mechanical equipment, a common calculation method involves inputting parameters such as the maximum operating radius and working angle of the equipment, combining them with the motion of the robotic arm or the equipment itself, and mapping the working area into three-dimensional space using a spatial coordinate system. This process involves spatial geometry calculations, demarcating the area where the dynamic range of the mechanical equipment overlaps with its actual installation location. For example, consider a large lifting device with a working radius of 15 meters and a working angle of 180 degrees. Using the equipment parameters and spatial data from the construction site, the spatial range that the mechanical equipment can cover is calculated. The installation locations of components on the construction site, determined through pre-construction planning and 3D modeling, are then spatially overlapped. The intersection between the mechanical equipment's working range and the component installation locations is calculated, ultimately yielding the mechanical coverage area. This area is then used to assess the mechanical equipment's applicability and operational capability. By quantifying this spatial overlap, a mechanical accessibility index is generated, which measures the mechanical equipment's ability to cover construction site tasks; higher values ​​indicate higher coverage.

[0035] The operation efficiency adaptation submodule extracts the relationship between the operation efficiency of mechanical equipment and the component installation time based on the mechanical accessibility index, analyzes the degree of adaptation between the mechanical operation efficiency and the operation requirements, and generates the operation efficiency adaptation degree; Extract the relationship between mechanical operation efficiency and component installation time. This relationship is obtained through the original data of the construction site, operation logs, and expert experience. For example, under specific operating conditions, the average time required for a certain mechanical equipment to move a component is 5 minutes. The operation efficiency of this equipment can be expressed by the number of moves or the rate at which the assembly task is completed. Combined with the data, the adaptability between the mechanical operation efficiency and the actual construction needs is further analyzed. The operation efficiency adaptability is determined by calculating the degree of match between the operation efficiency of the mechanical equipment and the construction time requirements. During the execution process, the operation efficiency needs to be dynamically evaluated. If the efficiency of the equipment is low during operation, the factors affecting the efficiency are analyzed by comparing the original data, and the operation method is adjusted, including adding auxiliary equipment, adjusting the operation path, or improving the operator's proficiency. Finally, the operation efficiency adaptability is calculated as a measure of the ability of the mechanical equipment to adapt to the site needs. This process involves adjusting the mechanical operation efficiency and matching the construction needs. By establishing a fitness function and performing calculations based on actual data, the fitness value is obtained to guide equipment use and resource allocation. The adaptability of operation efficiency is calculated using the formula: ; in, Represents the adaptability of operating efficiency, Representative The unit time efficiency of a kind of mechanical equipment, Representative The time required to install the components, Representative The average operating time used by a type of mechanical equipment to perform the corresponding component installation task, Representative The real-time installation demand response time of various components, Represents the number of machine-component combinations involved in the fitness analysis; Operational efficiency adaptability is a comprehensive indicator used to measure the degree of match between the actual operational efficiency of mechanical equipment and the operational response requirements set by the project when performing component installation operations. This indicator reflects the overall performance of mechanical equipment in meeting operational timeliness requirements by numerically calculating the deviation between the efficiency output and time requirements generated by multiple sets of mechanical-component combinations during the actual installation process. Smaller values ​​indicate a closer match between equipment efficiency and requirements, and higher adaptability. Conversely, higher values ​​indicate significant efficiency redundancy or deficiency, requiring optimization of equipment configuration or adjustment of operational processes to achieve a reasonable coordination between mechanical resources and operational requirements. The following is a detailed explanation of the formula parameters, along with instructions for the calculation derivation process, parameter acquisition, and dimensional normalization: After monitoring, collecting and standardizing parameters such as machine efficiency, component installation time, and response time, the parameters are imported into the formula and the fitness value is gradually derived; Set the number of analysis objects (Three machine-component combinations), the following expands on each parameter acquisition and example calculation process: Continuously monitor and collect the operating efficiency of each piece of machinery per unit time, using the on-site production monitoring system for statistics. The reference range is 30–100 pieces / hour (for example, an average of 50 pieces / hour). Based on the original operating data, the value is 50 pieces / hour. The unit is pieces / hour, and no normalization is required. The component installation recording system calculates the installation time required, with a reference to the HVAC component installation time interval of 4–8 hours. The monitoring record values ​​are taken as an actual average of 6 hours, with the unit being hours, and no normalization is required. The average actual operation time of the corresponding component is calculated through the equipment operation log. Refer to the installation process and system log. The value is 5 hours. The dimension is hour. No normalization is required. The statistical range is 4-8 hours. The response target time from the construction planning system is set and monitored through the project management system. The reference response time target is generally set to 6 hours, with a value of 6 hours. The dimension is hours, and no normalization is required. , indicating the analysis of three groups of combinations; All Keep the dimensions consistent (hours or pieces / hour) and no further normalization is required. If normalization is required later, the range method can be used: , there is no normalization operation here; Step 2: Substitute the example into the calculation and calculate item by item: For combination 1: ; Calculate the interior of a molecule: ; Find the absolute value of the deviation: ; Combination 2: Assuming it comes from another pair of mechanical components, the collection results are: Pieces / hour, hour, hour; calculate: ; deviation: ; Combination 3: Pieces / hour, hour; calculate: ; deviation: ; The sum of the deviations is then divided by : ; The results show that there is an average deviation of about 35.54 hours per unit per piece between the efficiency and demand of the three types of machines and components. This value represents the average deviation between the actual efficiency of the equipment and the response demand. The lower the value, the smaller the deviation, but no further normalization is required at present.

[0036] The space utilization calculation submodule uses the operating efficiency adaptation degree to extract the overlap between the machine operating range and the construction site space, analyzes the space utilization efficiency, and generates the machine adaptation area division; Obtain the spatial layout of the construction site and its physical boundaries, including information such as the working area, passages, and stacking areas. This process obtains data through equipment sensors, site modeling, and geographic information systems (GIS), and inputs it into the relevant configuration in the form of a coordinate system. By comparing the overlap between the mechanical operating range and the spatial area, the spatial occupancy of the mechanical equipment in the construction site is calculated. For example, if the operating range of a certain mechanical equipment at the construction site overlaps with the equipment or construction area, it is necessary to consider replanning the operating path or adjusting the operating sequence to improve the efficiency of space utilization. In this process, it is necessary to use a spatial allocation algorithm to take into account the coordination and non-interference requirements of multiple equipment operations, calculate the spatial adaptation area of ​​each equipment, and thus determine the space utilization rate of the entire construction site. By comparing the utilization efficiency under different spatial layouts, the mechanical adaptation area division is finally obtained to ensure that the equipment operation does not conflict with the equipment or construction tasks, and improve the efficiency of on-site space utilization.

[0037] Specifically, if Figure 2 、 7 As shown, the risk classification determination module includes: The risk probability analysis submodule is based on the mechanical adaptation area division, extracts the number of risk occurrences and time distribution in the original risk data, analyzes the frequency and periodicity of risk occurrence, and generates the risk probability interval; By dividing the mechanical adaptation area, the risk distribution of each area can be clarified, providing basic data for subsequent analysis. In each divided area, the number of risk occurrences and time intervals in the original data are extracted. The specific operation is to first collect past risk data in the area, record the exact time when the risk event occurred, generate time series data, and calculate the number of risk events in each period based on the time series data, and further evaluate the frequency of occurrence. For example, if a certain mechanical area has experienced 10 risk events in the past month, then the frequency of risk occurrence in this area is 10 times / month. On this basis, the periodic characteristics of risks in different time periods are calculated, and the periodicity is evaluated by the length of the time period. Periodic analysis uses autocorrelation analysis to evaluate the repetitive patterns of time series data in different time periods. For example, if the risk in the area occurs more frequently within two weeks, the pattern can be automatically identified and marked as a high-risk period for the area. The data can be aggregated and corresponding risk probability intervals can be generated according to different frequency intervals. The specific interval settings can be adjusted according to the distribution of the original data. For example, the frequency can be divided into high, medium and low levels. The low-frequency risk occurrence interval is 0-2 times / month, the medium frequency is 3-7 times / month, and the high frequency is 8 times / month and above. The generated probability interval is convenient for subsequent risk assessment.

[0038] The impact intensity assessment submodule uses the risk probability interval to extract the impact of risk events on construction progress and quality, analyzes the distribution characteristics of impact intensity, and generates an impact intensity level; After obtaining the risk probability range, the impact intensity of risk events on the construction project's progress and quality is further analyzed within each probability range, combined with the impact of specific risk events on the project's progress and quality. Retrospective analysis of original construction data is used to determine the impact of each risk event type (such as equipment failure and worker error) on the project. This impact assessment encompasses two key areas: construction schedule delay and quality degradation. For example, if, based on past data, equipment failure resulted in an average construction schedule delay of two days and a 2%-5% decline in quality when this event occurred, the impact intensity of this risk event on progress and quality would be recorded as 2 days / 2%-5%. The impact intensity of all risk events is statistically analyzed, and the impact intensity value for each event within each probability range is calculated based on the risk probability range. For example, low-frequency risk events have a minimal impact on the project, while high-frequency risk events have a more significant impact on the construction schedule. Risks within each area are classified into different impact intensity levels based on their frequency and impact. Specifically, the impact intensity can be divided into mild, moderate, and severe, which is determined according to the specific numerical range of the impact intensity. For example, the impact intensity is mild within 1-2 days, moderate within 2-5 days, and severe if it exceeds 5 days.

[0039] The risk scoring submodule analyzes the distribution of regional risk scores based on the impact intensity level and the risk level classification standards in the specification requirements to generate construction risk level assessment results; After analyzing the impact intensity of risk events in each region, regional risk scores are generated based on the impact intensity level and the risk classification criteria specified in the code. Risks of varying impact intensity are then scored based on specific criteria in the code (such as the construction risk classification criteria). Generally speaking, risks with higher impact intensity should be assigned higher risk scores, while risks with lower impact intensity should be assigned lower scores. For example, a risk with a mild impact is scored as 1, a risk with a moderate impact is scored as 3, and a risk with a severe impact is scored as 5. An overall risk score for the region is generated by taking a weighted average of the risk scores for each region. During this process, different risk types should be weighted differently based on their impact on the project. For example, if equipment failure has a greater impact on the project, while human error has a smaller impact, the weight of equipment failure should be set at 0.7, while human error should be weighted at 0.3. In addition to obtaining risk scores for each region, it is also necessary to analyze the distribution of risk scores across regions to determine which areas are more risky and which are relatively safer. This distribution of regional risk scores can be used to generate an overall risk assessment for the construction project. This assessment provides a scientific basis for construction managers to implement effective risk prevention and control measures in high-risk areas.

[0040] See also Figure 8 The BIM-based construction risk assessment method is implemented based on the above-mentioned BIM-based construction risk assessment system and includes the following steps: S1: Obtain construction site environmental information, including site topographic data, meteorological condition records, and the distribution of surrounding facilities. Extract terrain height differences and slope changes, analyze the degree to which meteorological fluctuations restrict construction conditions, and obtain environmental impact factors. S2: Based on environmental impact factors, extract key process nodes and resource allocation plans in the construction schedule, analyze the process connection time difference and resource allocation matching, and generate process fitness values; S3: Based on the process adaptation value, the movement paths of construction workers on site are extracted, the relationship between the path coverage and the spatial layout of the work area is analyzed, and a path optimization solution set is established; S4: Based on the path optimization solution set, the spatial distribution of the mechanical equipment operating range and component installation location is extracted, the coupling degree between mechanical accessibility and operating efficiency is analyzed, and the mechanical adaptation area division is generated; S5: Based on the mechanical adaptation area division, the risk occurrence frequency and impact range in the original risk data are extracted. Combined with the risk level division standards in the specification requirements, the distribution pattern of regional risk occurrence probability and impact intensity is analyzed to generate the construction risk level assessment results.

[0041] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A BIM-based construction risk assessment system, characterized by: The system comprises: The construction environment dynamic identification module obtains construction site environmental information, including site topographic data, meteorological condition records, and the distribution of surrounding facilities. It analyzes the impact of terrain undulations and meteorological fluctuations on construction operations and generates environmental impact factors. The operation process association analysis module extracts the key nodes and operation sequence in the construction schedule based on the environmental impact factors, analyzes the time difference between the process connections and the matching of resource allocation, and obtains the process adaptation value; The personnel path optimization module extracts the movement paths of construction personnel on site based on the process fitness value, analyzes the relationship between the path coverage and the spatial layout of the work area, and generates a path planning optimization set; The mechanical range adaptation module calls the path planning optimization set, extracts the spatial distribution of the mechanical equipment operating range and component installation positions, analyzes the coupling degree between mechanical accessibility and operating efficiency, and generates mechanical adaptation area division.

2. The BIM-based construction risk assessment system according to claim 1, characterized in that: The environmental influencing factors include terrain undulation, frequency of weather fluctuations, and interference from surrounding facilities. The process adaptation value includes node connection time difference, resource allocation matching rate, and job priority weight. The path planning optimization set includes path coverage ratio, regional layout matching, and path optimization score. The mechanical adaptation area division includes mechanical accessibility index, operation efficiency adaptation, and space utilization.

3. The BIM-based construction risk assessment system according to claim 1, characterized in that: The construction environment dynamic identification module includes: The terrain data extraction submodule obtains construction site environmental information, extracts terrain height differences and slope changes, analyzes the impact of terrain undulation on mechanical equipment deployment, and generates terrain undulation. The weather fluctuation analysis submodule extracts the wind speed, precipitation and temperature change values ​​from the weather condition records based on the terrain undulation, analyzes the degree of restriction of weather fluctuations on construction conditions, and generates the weather fluctuation frequency; The facility interference assessment submodule extracts the distribution information of surrounding facilities based on the frequency of meteorological fluctuations, analyzes the scope and frequency of physical interference of facilities on the construction site, and generates environmental impact factors.

4. The BIM-based construction risk assessment system according to claim 3 is characterized by: The operation process association analysis module includes: The process node extraction submodule extracts key process nodes in the construction schedule based on the environmental impact factors, analyzes the time intervals and resource requirements between nodes, and generates the node connection time difference; The resource allocation matching submodule extracts the material and equipment supply cycles in resource allocation based on the node connection time difference, analyzes the matching degree between resource supply and process requirements, and generates a resource allocation matching rate; The priority weight calculation submodule calls the resource allocation matching rate, extracts the job priority ranking table, analyzes the impact of the priority ranking on the process connection, and obtains the process adaptation value.

5. The BIM-based construction risk assessment system according to claim 4 is characterized in that: The personnel path optimization module includes: The path coverage extraction submodule extracts the movement trajectory of the construction workers on site according to the process fitness value, analyzes the relationship between the trajectory coverage range and the spatial distribution of the work area, and generates the path coverage ratio; The regional layout matching submodule calls the path coverage ratio, extracts the spatial layout information of the operation area, analyzes the matching degree between the path coverage and the regional layout, and generates the regional layout matching degree; The path optimization scoring submodule analyzes the degree to which path optimization improves construction efficiency based on the regional layout matching degree and generates a path planning optimization set.

6. The BIM-based construction risk assessment system according to claim 5, characterized in that: The mechanical range adaptation module includes: The mechanical accessibility analysis submodule calls the path planning optimization set, extracts the spatial distribution of the mechanical equipment operating range and component installation positions, analyzes the coverage of the mechanical operating range, and generates a mechanical accessibility index; The operation efficiency adaptation submodule extracts the relationship between the operation efficiency of the mechanical equipment and the component installation time based on the mechanical accessibility index, analyzes the degree of adaptation between the mechanical operation efficiency and the operation requirements, and generates the operation efficiency adaptation degree; The space utilization calculation submodule calls the operation efficiency adaptation degree, extracts the degree of overlap between the machine operation range and the construction site space, analyzes the space utilization efficiency, and generates the machine adaptation area division.

7. The BIM-based construction risk assessment system according to claim 6, characterized in that: The operational efficiency adaptability is based on the formula: ； in, Represents the adaptability of operating efficiency, Representative The unit time efficiency of a kind of mechanical equipment, Representative The time required to install the components, Representative The average operating time used by a type of mechanical equipment to perform the corresponding component installation task, Representative The real-time installation demand response time of various components, Represents the number of machine-component combinations involved in the fitness analysis.

8. The BIM-based construction risk assessment system according to claim 1, characterized in that: The system also includes a risk classification module: The risk classification module is based on the mechanical adaptation area division, combined with the original risk data and specification requirements, to analyze the regional risk occurrence probability and impact intensity, and generate a construction risk level assessment result; The construction risk level assessment results include the risk occurrence probability interval, impact intensity level, and risk score.

9. The BIM-based construction risk assessment system according to claim 8, characterized in that: The risk classification determination module includes: The risk probability analysis submodule extracts the number of risk occurrences and time distribution in the original risk data based on the mechanical adaptation area division, analyzes the frequency and periodicity of risk occurrence, and generates a risk occurrence probability interval; The impact intensity assessment submodule calls the risk occurrence probability interval, extracts the impact degree of the risk event on the construction progress and quality, analyzes the distribution characteristics of the impact intensity, and generates the impact intensity level; The risk scoring submodule analyzes the distribution pattern of regional risk scores based on the impact intensity level and the risk level classification standards in the specification requirements to generate a construction risk level assessment result.

10. A BIM-based construction risk assessment method, characterized in that: The method is used to implement the BIM-based construction risk assessment system according to any one of claims 1 to 9, comprising the following steps: S1: Obtain construction site environmental information, including site topographic data, meteorological condition records, and the distribution of surrounding facilities. Extract terrain height differences and slope changes, analyze the degree to which meteorological fluctuations restrict construction conditions, and obtain environmental impact factors. S2: Based on the environmental impact factors, extract the key process nodes and resource allocation plan in the construction schedule, analyze the process connection time difference and resource allocation matching, and generate the process adaptability value; S3: Based on the process adaptation value, the movement path of the construction personnel in the site is extracted, the relationship between the path coverage and the spatial layout of the work area is analyzed, and a path optimization solution set is established; S4: Based on the path optimization solution set, extract the spatial distribution of the mechanical equipment operating range and component installation location, analyze the coupling degree between mechanical accessibility and operating efficiency, and generate mechanical adaptation area division; S5: Based on the mechanical adaptation area division, the risk occurrence frequency and impact range in the original risk data are extracted, and combined with the risk level division standards in the specification requirements, the distribution pattern of regional risk occurrence probability and impact intensity is analyzed to generate the construction risk level assessment result.

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