A construction structure offset monitoring method and system using BIM technology

Abstract

This invention relates to the field of construction monitoring technology, specifically to a method and system for monitoring structural offsets using BIM technology. The method involves using a multi-source sensor cluster to collect real-time location information of multiple components within the construction structure, obtaining real-time monitoring data. Based on the real-time monitoring data and the preset coordinates of the components in the BIM model, a first offset evaluation index for the target component is calculated. The component importance is then obtained. The first offset evaluation index is corrected based on the component importance score to obtain a second offset evaluation index. This second offset evaluation index is compared with a preset offset threshold to determine monitoring and early warning information. This approach enables dynamic assessment of offset risks, establishes an early identification mechanism for potential problems, and optimizes the early warning system. It can dynamically capture offset trends and comprehensively consider them, achieving early risk identification and optimized early warning, thereby improving the accuracy and efficiency of construction structures.

Description

Technical Field

[0001] This invention relates to the field of construction monitoring technology, specifically to a method and system for monitoring structural offsets using BIM technology. Background Technology

[0002] During construction, with the continuous expansion of project scale and significant increase in technological complexity, the safety control of construction structures faces increasingly severe challenges. Currently, monitoring structural offsets mainly relies on multi-source sensor networks to collect real-time displacement data of components and perform simple comparisons with design models or reference coordinates to determine whether there are any excessive offsets. The widespread application of Building Information Modeling (BIM) technology enables the digital integration and management of the geometric information, material properties, and spatial relationships of structural components, providing a technological foundation for the visualization of monitoring data, precise component positioning, and attribute correlation analysis. Simultaneously, construction site management is increasingly focusing on factors such as the differences in importance of different components, the ease of repair, and adjustment costs to assist in optimizing engineering decisions.

[0003] However, existing monitoring methods are limited to static judgments of whether the offset of a single point exceeds the limit, and cannot effectively capture the trend characteristics of the offset over time. This makes it difficult to identify potential structural risks in the early stages. In addition, focusing only on the offset data itself fails to incorporate key engineering management factors such as the impact range of component offsets at different locations on the overall structure and the differences in the economic costs of repair intervention into the comprehensive consideration system, resulting in a single early warning mechanism and a vague priority of handling. Summary of the Invention

[0004] To overcome the technical bottleneck of static judgment of whether the offset of a single point exceeds the limit, this invention provides a method and system for monitoring the offset of construction structures using BIM technology. This allows for dynamic capture of offset trends and comprehensive consideration of the importance of components, enabling early risk identification and optimization warning, and improving the accuracy and efficiency of construction structure safety monitoring.

[0005] To achieve the above objectives, firstly, this application proposes a method for monitoring the offset of construction structures using BIM technology. This method is applied to a construction structure offset monitoring system, which includes a BIM model and a multi-source sensor cluster. The method includes: By using a multi-source sensor cluster, real-time location information of multiple different components in the construction structure is collected to obtain real-time monitoring data; Based on real-time monitoring data and the preset coordinates corresponding to the components in the BIM model, the first offset evaluation index of the target component is calculated; wherein, the target component is any component in the construction structure, and the first offset evaluation index is obtained by integrating the cumulative offset distribution and offset change trend of different components. Obtain the component importance of the target component; whereby the component importance is determined based on the mechanical properties of the target component, historical rework data, and economic impact information; The first offset evaluation index of the target component is corrected based on the component importance score to obtain the second offset evaluation index. The second offset evaluation index is compared with a preset offset threshold to determine the monitoring and early warning information.

[0006] In one embodiment, before the step of acquiring real-time location information of multiple different components in the construction structure through a multi-source sensor cluster to obtain the corresponding real-time monitoring data, the method further includes: A cluster of multi-source sensors is set up within the monitoring area corresponding to the construction structure; among them, at least one multi-source sensor is set up for each key component or sensitive area in the construction structure. The mapping relationship between multi-source sensors and corresponding target components in the construction structure is written into the BIM model to record the mapping relationship between target components and corresponding multi-source sensors in the BIM model.

[0007] In one embodiment, the step of inputting real-time monitoring data into BIM and calculating the first offset evaluation index of the target component in the construction structure includes: In the mapping table between the target components and multi-source sensors corresponding to the BIM model, the target components corresponding to the monitoring data are determined, and the preset standard coordinate information of the target components is obtained; Calculate the corresponding cumulative offset distribution based on the standard coordinate information and real-time monitoring information of the target component; Calculate the trend of the target component's offset change based on the cumulative offset distribution of the target component; The first offset evaluation index of the target component is obtained by multiplying the cumulative offset distribution with the offset change trend.

[0008] In one embodiment, the step of calculating the corresponding cumulative offset distribution based on the standard coordinate information and real-time monitoring information of the target component includes: Acquire multiple real-time monitoring data points for the target component at multiple monitoring times; Based on each real-time monitoring data and standard coordinate information, the instantaneous offset vector of the target component at each monitoring time is calculated, resulting in a sequence of instantaneous offset vectors of the target component at multiple monitoring times; The cumulative offset distribution of the target component is calculated based on the instantaneous offset vector sequence.

[0009] In one embodiment, the step of obtaining the component importance of the target component includes: Determine the economic impact, rework probability, and stress condition of the target component; The importance of the target component is calculated based on the economic impact value, rework probability, and stress conditions.

[0010] In one embodiment, the step of determining the economic impact value of the target component includes: Obtain historical data on the target component's deviation and rework during the historical construction process; the historical data includes the time spent on rework, the cost of rework, and the total number of reworks; The economic impact value of the target component is calculated based on the time spent on rework, the cost of rework, and the total number of reworks.

[0011] In one embodiment, the step of determining the rework probability of the target component includes: From the historical construction database, retrieve a set of historical cases with the same or similar degree of offset as the target component to obtain the target historical data; the target historical data includes the total number of cases with the same or similar degree of offset and the number of times rework occurred; Based on the total number of cases and the number of reworks, the rework probability of the target component is calculated.

[0012] In one embodiment, the step of determining the stress state of the target component includes: Based on the geometric and material properties of the target component in the BIM model, finite element analysis is performed on the target component and its associated structures. The maximum stress value of the target component under preset working conditions is extracted from the results of the finite element analysis to determine the stress condition of the target component.

[0013] In one embodiment, after correcting the first offset evaluation index of the target component based on the component importance score to obtain the second offset evaluation index, the construction structure offset monitoring method using BIM technology further includes: For a group of interconnected components consisting of multiple mechanically related components in a construction structure, calculate the linkage risk value of the interconnected component group. The linkage risk value is compared with the preset linkage threshold. When the linkage risk value exceeds the linkage threshold, a regional linkage early warning information is generated.

[0014] Secondly, this application proposes a construction structure offset monitoring system utilizing BIM technology, comprising: a memory and a processor; the memory is connected to the processor; the memory is used to store program instructions; the processor is used to implement any construction structure offset monitoring method utilizing BIM technology when the program instructions are executed.

[0015] One or more technical solutions proposed in this application have, but are not limited to, the following technical effects: The construction structure offset monitoring method proposed in this application is applied to a construction structure offset monitoring system that includes a BIM model and a multi-source sensor cluster. The system collects real-time location information of multiple components within the construction structure using a multi-source sensor cluster, obtaining real-time monitoring data. Based on the real-time monitoring data and the preset coordinates corresponding to the components in the BIM model, a first offset evaluation index for the target component is calculated. The target component can be any component in the construction structure, and the first offset evaluation index is obtained by fusing the cumulative offset distribution and offset change trends of different components. The component importance of the target component is then obtained, determined based on its mechanical properties, historical rework data, and economic impact information. The first offset evaluation index is corrected based on the component importance score to obtain a second offset evaluation index. Finally, the second offset evaluation index is compared with a preset offset threshold to determine monitoring and early warning information. In this way, by calculating the first offset assessment index, including the cumulative offset distribution and the offset change trend, the importance of the component is obtained and corrected to obtain the second offset assessment index. Then, it is compared with the preset threshold to generate early warning information, thereby dynamically assessing the offset risk, identifying potential problems in the early stage, and optimizing the early warning mechanism. It can dynamically capture the offset trend and comprehensively consider the importance of the component, realize early risk identification and optimized early warning, and improve the accuracy and efficiency of construction structure safety monitoring. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the first embodiment of the construction structure offset monitoring method utilizing BIM technology in this application;

[0017] Figure 2 This is a flowchart illustrating the second embodiment of the construction structure offset monitoring method utilizing BIM technology in this application;

[0018] Figure 3 This is a flowchart illustrating the third embodiment of the construction structure offset monitoring method utilizing BIM technology in this application;

[0019] Figure 4 This is a flowchart illustrating the fourth embodiment of the construction structure offset monitoring method utilizing BIM technology in this application;

[0020] Figure 5 This is a flowchart illustrating the fifth embodiment of the construction structure offset monitoring method utilizing BIM technology in this application;

[0021] Figure 6 This is a structural schematic diagram of the construction structure offset monitoring system 60 provided in this application. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0023] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0024] To make the technical solutions and advantages in the embodiments of this application clearer, the existing related technologies are described below.

[0025] Traditional structural offset monitoring technologies rely primarily on static judgment mechanisms based on whether single-point offsets exceed limits. This makes it difficult to effectively capture the trend of offset evolution over time, resulting in the failure to identify potential structural risks early. Furthermore, the monitoring process lacks comprehensive quantitative analysis of key engineering management factors such as the impact of component offsets at different locations on the overall structure and the differences in repair intervention costs after offset. This leads to a simplistic early warning logic and insufficient criteria for prioritizing actions, thus affecting the timeliness of risk warnings and the rationality of resource allocation. More fundamentally, the problem lies in the lack of correlation between offset monitoring data and structural system behavior. This prevents monitoring results from reflecting the transmission effect of component offsets within the structural system and the dynamic changes in repair costs, thereby hindering the refinement of construction safety management.

[0026] For example, during the construction of the core tube of a super high-rise building, multi-source sensors deployed at key nodes of the core tube wall continuously collect displacement data. When the wall experiences slow but continuous displacement, the single-point monitoring value consistently falls below a preset threshold, and existing methods fail to identify the abnormal growth characteristics of the displacement trend. Furthermore, because the impact of this core tube component on the overall structural stability and the complexity of the resources required for repair are not included in the assessment system, the monitoring system cannot distinguish the priority of handling this component from non-critical components, leading to delayed risk warnings. Specifically, the cumulative effect of the displacement trend is ignored in this scenario, and the component importance information is not integrated into the monitoring logic, resulting in a lack of holistic understanding of structural system risks in construction management decisions, leading to an imbalance in the allocation of monitoring resources and insufficient targeting of intervention measures.

[0027] If the above problems are not addressed, the monitoring system will be unable to identify abnormal trends before the offset reaches the excessive threshold, rendering the structural risk early warning mechanism ineffective and potentially leading to the accumulation and spread of safety hazards. In particular, unclear priority handling will result in both insufficient monitoring of critical components and excessive intervention in non-critical components, leading to wasted monitoring resources and reduced construction management efficiency. Furthermore, the lack of quantitative analysis of the transmission and amplification effects of component offset within the structural system will weaken the overall structural risk management capability, thereby affecting the systematic nature of construction safety control and the stability of construction progress.

[0028] To make the technical solutions and advantages of the embodiments of this application clearer, the exemplary embodiments of this application will be described in further detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not an exhaustive list of all embodiments.

[0029] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0030] Based on this, this application provides a method for monitoring the offset of construction structures using BIM technology. This method is applied to a construction structure offset monitoring system, which includes a BIM model and a multi-source sensor cluster. Please refer to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the construction structure offset monitoring method utilizing BIM technology in this application.

[0031] In this embodiment, the above-mentioned method for monitoring the offset of construction structures using BIM technology includes steps S10 to S50: Step S10: Real-time location information of multiple components in the construction structure is collected through a multi-source sensor cluster to obtain real-time monitoring data.

[0032] Building Information Modeling (BIM) is a digital modeling and management method that integrates information throughout the entire lifecycle of a building project. By creating virtual models that include attributes such as geometry, materials, structure, and function, it provides a unified platform for information sharing, collaborative management, and data analysis during the construction process.

[0033] Here, the BIM model is the core carrier of BIM technology. It is a digital three-dimensional model containing information on all components of the building structure and their attributes. In this model, each component has a unique identifier, geometry, material properties, and preset spatial coordinates.

[0034] It should be noted that a multi-source sensor cluster can refer to a network system composed of various types of sensors, such as displacement sensors, tilt sensors, acceleration sensors, GNSS receivers, total stations, or laser scanners, used to collect real-time status data of components in the construction structure from different dimensions and with different levels of precision.

[0035] Furthermore, components can refer to the basic units that make up the construction structure, such as beams, columns, slabs, walls, trusses, etc. Each component has its corresponding digital representation in the BIM model.

[0036] Real-time location information refers to the actual spatial coordinate data of a component collected by sensors at a specific monitoring time. Real-time location information is used to reflect the dynamic position of the component during the construction process.

[0037] As an example, a pre-installed multi-source sensor cluster can be used, and based on the multi-source sensors corresponding to multiple components in the multi-source sensor cluster, the key points of each component can be measured, their three-dimensional coordinates recorded, and then these data can be transmitted to the BIM model.

[0038] Step S20: Calculate the first offset evaluation index of the target component based on the real-time monitoring data and the preset coordinates corresponding to the component in the BIM model.

[0039] The target component is any component in the construction structure, and the first offset evaluation index is obtained by integrating the cumulative offset distribution and offset change trend of different components.

[0040] Here, the preset coordinates can refer to the coordinates of the design position or reference position defined for each component in the BIM model. These coordinates serve as a reference for determining whether a component has shifted.

[0041] The first offset assessment index can be a comprehensive numerical value used to initially quantify the degree of offset and risk of the target component. This index is calculated by integrating information such as the cumulative offset distribution and offset change trend of the component.

[0042] As an example, the distance between the real-time monitored component location and its design location in the BIM model can be calculated to obtain the instantaneous offset. Then, by performing a simple average or weighted average of the instantaneous offsets over a period of time, a value reflecting the cumulative offset can be obtained. Simultaneously, by comparing the instantaneous offsets at adjacent monitoring times, it can be determined whether the offset is increasing or decreasing, thus obtaining a simple trend of offset change. A linear combination of these two values ​​yields the first offset evaluation index.

[0043] Step S30: Obtain the component importance of the target component.

[0044] The importance of a component is determined based on its mechanical properties, historical rework data, and economic impact information.

[0045] Here, component importance can be a quantitative indicator that measures the criticality of a target component in the overall structure and the degree of impact of its offset on structural safety and project economy. Component importance can comprehensively consider the component's mechanical properties, historical rework data, and economic impact information.

[0046] As an example, the load-bearing capacity of a component in the structure can be manually assessed by reviewing its design drawings, classifying it into "important" or "general" levels as a reflection of its mechanical properties. Historical rework data can be obtained by reviewing project archives and statistically analyzing the number of times this type of component has been reworked in past projects, serving as a reference for rework probability. Economic impact information can be determined by estimating the direct costs (e.g., material and labor costs) required to rework the component should it shift. A simple weighted sum of these information yields the component's importance.

[0047] Step S40: Correct the first offset evaluation index of the target component based on the component importance score to obtain the second offset evaluation index.

[0048] The second offset assessment index is a more accurate and instructive offset risk assessment value obtained by adjusting the component's importance based on the first offset assessment index. This index reflects the actual risk of component offset and its impact on the project.

[0049] As an example, the first offset assessment index can be simply multiplied by the component importance score, or a table can be used to amplify or reduce the first offset assessment index to different degrees according to the component importance level. This modification assigns a higher weight to the offset risk of important components, thus making it more prominent in the overall risk assessment.

[0050] Step S50: Compare the second offset evaluation index with the preset offset threshold to determine the monitoring and early warning information.

[0051] The offset threshold can be a pre-set critical value used to determine whether the component offset exceeds the safe or acceptable range. When the second offset evaluation index exceeds this threshold, the system will trigger an early warning.

[0052] Here, the monitoring and early warning information refers to the alert information automatically generated by the system and sent to relevant management personnel when the risk of component displacement reaches or exceeds a preset threshold. This information aims to prompt timely intervention measures.

[0053] As an example, a fixed offset threshold can be set. When the second offset evaluation metric exceeds this threshold, an early warning message is generated. This warning message can be a simple text notification indicating that an abnormal offset has occurred in the component. Basic risk identification and early warning can be achieved through comparison.

[0054] For example, suppose a high-rise building construction project requires monitoring the offset of a critical load-bearing column (e.g., component A) in the core tube structure. The challenge of this project is that traditional monitoring methods may only focus on whether the instantaneous offset of component A exceeds the limit, while ignoring its long-term offset trend, the critical role of component A in the entire structure, and the huge economic losses that may result from rework, thus leading to untimely early warnings or unreasonable resource allocation.

[0055] To address this problem, the method of this embodiment was applied to the project. First, a multi-source sensor cluster, such as displacement sensors and tilt sensors, was deployed on component A and other related components. These sensors continuously collected real-time position information of component A and aggregated this data to form real-time monitoring data. For example, every 10 minutes, the X, Y, and Z coordinates and tilt angle data of component A were automatically collected and transmitted to the central monitoring system.

[0056] After receiving this real-time monitoring data, the monitoring system compares it with the preset design coordinates corresponding to component A in the BIM model. Based on this data, the monitoring system calculates the first offset evaluation index for component A. Specifically, the system can analyze the positional changes of component A over the past few hours or days, calculating its cumulative offset distribution. For example, it may find that component A has continuously offset 5 millimeters in a certain direction over the past 24 hours. Simultaneously, the system will also analyze the trend of its offset changes; for example, it may find that the 5-millimeter offset did not occur all at once, but rather increased steadily at a rate of 0.2 millimeters per hour. By integrating this information, the system obtains the first offset evaluation index for component A, which reflects the current offset status of component A and its development trend.

[0057] Simultaneously, the monitoring system can also determine the importance of component A. Since component A is a major load-bearing column in the core tube structure, its mechanical properties are assessed as highly important. Reviewing historical project data revealed a high probability of rework due to displacement of similar load-bearing columns during construction, which would result in weeks of delays and millions in economic losses. Based on these mechanical properties, historical rework data, and economic impact information, component A is assigned a high component importance score.

[0058] Subsequently, the monitoring system corrects the previously calculated first offset assessment index based on the component importance score of component A. For example, if the first offset assessment index of component A shows that although its offset has not yet reached the traditionally defined limit, its offset trend is accelerating, this correction process will significantly amplify its first offset assessment index due to component A's high importance, resulting in a higher second offset assessment index. This second offset assessment index more comprehensively reflects the actual risk of component A because it considers not only the offset amount and trend but also the criticality of component A.

[0059] Finally, the monitoring system compares the second offset assessment index with a preset offset threshold. Assume the project's offset threshold is set to trigger an alert when the second offset assessment index reaches a specific value. If the corrected second offset assessment index exceeds this threshold, even if the instantaneous offset of component A has not yet reached the traditional "exceeding limit," the system will immediately generate a monitoring alert. This alert will be sent to the project manager and structural engineer, informing them that component A has a potential structural risk and requires immediate inspection and intervention.

[0060] Existing offset monitoring methods often rely solely on whether the instantaneous offset of a component exceeds a preset limit, resulting in a static monitoring logic that struggles to effectively capture the dynamic trends of offset changes over time. For example, in the aforementioned high-rise building project, if the offset of component A has not yet reached the traditional limit, but its offset rate is accelerating, traditional methods may fail to issue a timely warning. This embodiment integrates the cumulative offset distribution and offset change trend when calculating the first offset evaluation index, enabling the system to identify potential risks based on its development trend before the offset reaches a critical value, thus achieving earlier warnings. Furthermore, existing technologies typically focus only on the offset data itself, lacking comprehensive consideration of key engineering management factors such as the component's importance in the overall structure, the scope of its offset's impact on structural safety, and the differences in the cost of repair intervention. This leads to a simplistic warning logic and unclear priority of actions. For instance, in the above example, component A, as a critical load-bearing column of the core tube, has a much higher offset risk than non-load-bearing components, but traditional methods may fail to distinguish this difference. This embodiment obtains the importance of components and quantifies it based on their mechanical properties, historical rework data, and economic impact information. Then, it uses this importance to correct the first offset assessment index, resulting in a second offset assessment index. This correction process ensures that monitoring and early warning information fully reflects the actual risks of components and their impact on the project, thereby providing project managers with more instructive decision-making support and avoiding problems such as delayed early warnings, excessive intervention, or unreasonable resource allocation.

[0061] Therefore, the method in this embodiment integrates multi-dimensional information into the offset risk assessment system by introducing the analysis of offset trends and the quantitative correction of component importance. This method not only improves the accuracy and foresight of offset risk assessment, but also makes the early warning mechanism more intelligent and refined, thereby effectively solving the problems of static monitoring logic, single early warning, and lack of comprehensive consideration in the existing technology, and providing more comprehensive and efficient technical support for the safety management of construction structures.

[0062] Based on the first embodiment of this application, a second embodiment of this application is proposed. Please refer to [link to relevant documentation]. Figure 2 , Figure 2 This is a flowchart illustrating the second embodiment of the construction structure offset monitoring method utilizing BIM technology in this application.

[0063] As an extension of the first embodiment prior to step S10, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, the construction structure offset monitoring method using BIM technology in this application further includes steps S101~S102:

[0064] Step S101: Set up a multi-source sensor cluster within the monitoring area corresponding to the construction structure.

[0065] Among them, at least one multi-source sensor is installed for key components or sensitive areas in the construction structure.

[0066] In practice, based on the construction structure's design drawings and BIM model, and combined with the experience of structural engineers, areas requiring focused monitoring can be manually identified, and sensors can be deployed within these areas. Alternatively, structural analysis software can be used to perform mechanical analysis on the BIM model, identifying areas of stress concentration and significant deformation. The analysis results can then guide the automated or semi-automated deployment of the sensor cluster.

[0067] Here, at least one multi-source sensor is installed for key components or sensitive areas in the construction structure, which can prioritize and enhance the monitoring of important parts of the structure.

[0068] Key components typically refer to those that bear the main loads in the structure and have a decisive impact on the overall stability of the structure, such as main beams, main columns, and shear walls.

[0069] Sensitive areas may include foundation settlement observation points, the middle of large-span structures, structural connection nodes, and other parts that are prone to deformation or damage.

[0070] It should be noted that the sensor settings can be adjusted according to the importance level of the component, the complexity of the stress, or historical experience data to ensure that each critical component or sensitive area is monitored by at least one sensor to obtain its critical real-time status information.

[0071] Step S102: Write the mapping relationship between the multi-source sensors and the corresponding target components in the construction structure into the BIM model, so as to record the mapping relationship between the target components and the corresponding multi-source sensors in the BIM model.

[0072] By writing the mapping relationship between multi-source sensors and the corresponding target components in the construction structure into the BIM model, a direct association between sensor data and components in the BIM model can be established.

[0073] One approach is to add a custom attribute field, such as "Associated Sensor ID," to each component in the BIM model and fill it with the unique identifier of the sensor associated with it.

[0074] As another approach, a separate database or table can be created, containing the sensor ID, the BIM coordinates of its installation location, and a unique identifier for the target component it monitors, and interacting with the BIM model via the API interface of the BIM software.

[0075] Recording the mapping relationship between target components and their corresponding multi-source sensors in the BIM model ensures the traceability of monitoring data and the integrity of the BIM model. This mapping relationship can exist as an additional information layer of the BIM model or an external linked database, and can be read, written, and managed through the API interface of the BIM software. For example, when a user selects a component in the BIM model, they can immediately query all the sensors associated with it and their current status.

[0076] Based on the above embodiments, by pre-setting a multi-source sensor cluster within the monitoring area corresponding to the construction structure, and paying particular attention to the deployment of key components or sensitive areas, comprehensive and effective collection of real-time location information is ensured. More importantly, a clear mapping relationship is established between these multi-source sensors and the corresponding target components in the BIM model and recorded in the BIM model, so that the subsequently collected real-time monitoring data can be accurately associated with specific components in the BIM model. This pre-planning and mapping mechanism solves the problem of unclear correspondence between sensor data and BIM model components, providing a reliable data foundation and contextual information for subsequent accurate offset calculation and evaluation based on the BIM model. When the system receives sensor data, it can directly and quickly locate the target component to which the data belongs through the mapping relationship recorded in the BIM model and obtain its preset coordinates, thereby accurately and efficiently calculating the first offset evaluation index and avoiding the tediousness and errors of data misalignment or manual matching.

[0077] For example, to achieve accurate monitoring of structural offsets during construction, a digital twin monitoring system synchronized with the physical world can be constructed first. The core of this system lies in accurately spatially and informationally associating a cluster of multi-source sensors deployed on-site with the BIM design model.

[0078] At the data source level, a dual model benchmark needs to be established. The first is a virtual design model, which is a BIM model built in a computer environment before construction, based on complete design drawings and containing all component geometry, material properties, and topological relationships. This model serves as the ideal state benchmark for monitoring. The second is an actual progress model, which involves periodically (e.g., weekly) using drones equipped with LiDAR and other devices to scan the construction site, generating a 3D point cloud model reflecting the actual construction status. This model is used for macro-level progress verification and overall deformation trend analysis.

[0079] At the physical sensing level, heterogeneous sensor clusters need to be deployed in key structural components and mechanically sensitive areas. These mainly include: displacement sensors (e.g., linear displacement gauges, laser displacement gauges), used to directly capture the linear displacement of components in the X, Y, and Z directions with sub-millimeter accuracy, typically installed at column bases, beam ends, and nodes; tilt sensors (e.g., MEMS tilt meters), used to monitor changes in component tilt angles, installed in tower crane foundations, the middle of tall vertical components, etc.; accelerometers, used to sense instantaneous vibrations or impacts caused by construction activities, installed in areas with significant dynamic loads; and a three-dimensional laser scanning system, used as a periodic full-area scanning method to verify and supplement data from fixed-point sensors. Various sensors are selected and configured based on their physical characteristics (e.g., accuracy, range, sampling frequency) and the monitoring targets.

[0080] At the digital correlation level, this is key to achieving intelligent monitoring. After each sensor is installed on-site and its spatial coordinates are accurately measured, it must be assigned a unique digital identity in the BIM model. By binding the sensor's device ID, type, and installation coordinates one-to-one with specific components or monitoring points in the BIM model, a precise mapping relationship library from physical signals to the information model is established. This process simultaneously records the initial installation deviation, serving as the relative zero point for all subsequent displacement calculations. Thus, any real-time data stream collected by any sensor can be automatically and accurately attributed to the corresponding component in the BIM model, providing a structured and traceable data foundation for subsequent offset calculations, risk analysis, and visual early warning.

[0081] Therefore, by rationally setting up multi-source sensor clusters within the monitoring area corresponding to the construction structure, and focusing on key components or sensitive areas, comprehensive coverage and effective collection of real-time location information can be ensured. Simultaneously, establishing a clear mapping relationship between the multi-source sensors and the corresponding target components in the BIM model and recording this relationship within the BIM model allows for precise association of sensor data with components in the BIM model, greatly improving the accuracy and efficiency of data collection. This pre-planning and data association mechanism effectively avoids data misalignment, redundancy, or omissions, providing a solid data foundation for subsequent accurate offset calculation and evaluation based on the BIM model, thereby enhancing the reliability and practicality of the entire construction structure offset monitoring method.

[0082] Based on the first and second embodiments described above, a third embodiment of this application is proposed. Please refer to [link to third embodiment]. Figure 3 , Figure 3 This is a flowchart illustrating the third embodiment of the construction structure offset monitoring method utilizing BIM technology in this application.

[0083] As a refinement of step S20 in the first embodiment, in the third embodiment of this application, the content that is the same as or similar to that in the first embodiment can be referred to the above description, and will not be repeated hereafter. Based on this, the construction structure offset monitoring method of this application using BIM technology includes steps S21 to S24:

[0084] Step S21: In the mapping relationship table between the target component and the multi-source sensor corresponding to the BIM model, determine the target component corresponding to the monitoring data and obtain the preset standard coordinate information of the target component.

[0085] Here, in the mapping table between the target component corresponding to the BIM model and the multi-source sensor, the target component corresponding to the monitoring data is determined, and the preset standard coordinate information of the target component is obtained to ensure that the real-time monitoring data obtained from the sensor can be accurately associated with the specific target component in the BIM model, and the precise position information (standard coordinates) of the component in the design or initial state is obtained.

[0086] Specifically, a unique identifier can be pre-assigned to each component in the BIM model, and during sensor deployment, the sensors are bound to the identifiers of the monitored components, forming a mapping table. When sensor data is uploaded, the monitoring system can query the mapping table using the sensor identifiers to determine the corresponding component identifier and extract the standard coordinate information of that component from the BIM model. Alternatively, this can be achieved through a spatial matching algorithm. For example, since sensor data contains its own coordinates, the system can perform spatial matching based on the sensor coordinates and the geometric center or bounding box of the component in the BIM model to determine the corresponding target component and obtain the design coordinates of that component from the BIM model to obtain the corresponding standard coordinate information.

[0087] For example, by installing sensors in the components, data of the components can be obtained. The sensor numbers can be pre-bound to the BIM components, so that the installation position coordinates of the multi-source sensors correspond to the component ID. Through the binding, it can be determined which component's data is being collected by the current sensor.

[0088] Step S22: Calculate the corresponding cumulative offset distribution based on the standard coordinate information and real-time monitoring information of the target component.

[0089] Here, the cumulative offset distribution can be used to characterize the cumulative offset and statistical characteristics of a component over a period of time, and can be used to assess the stability and potential risks of component offset.

[0090] For example, the instantaneous offset vectors of the target component at multiple consecutive monitoring moments (the difference between real-time monitoring information and standard coordinate information) can be recorded. Then, statistical analysis can be performed on these instantaneous offset vectors, such as calculating their mean, variance, maximum value, minimum value, and frequency distribution of the offset direction, to form a cumulative offset distribution. Alternatively, time series analysis methods can be used, taking instantaneous offset data over a period of time as input, and calculating the distribution characteristics reflecting the cumulative effect of historical offsets, such as the cumulative probability distribution function or cumulative density function of the offset, through methods such as sliding window or exponential weighted averaging.

[0091] In some implementations, the step of calculating the corresponding cumulative offset distribution based on the standard coordinate information and real-time monitoring information of the target component includes: (1) Obtain multiple real-time monitoring data corresponding to the target component at multiple monitoring times.

[0092] Among them, acquiring multiple real-time monitoring data corresponding to the target component at multiple monitoring times can capture the changes in its position over time by continuously or periodically observing the target component at different time points.

[0093] Real-time monitoring data can be automatically collected by a multi-source sensor cluster at preset time intervals, such as data readings every few minutes or hours; or it can be collected based on specific events, such as intensive monitoring when construction loads change or environmental conditions fluctuate. This multi-moment data acquisition method provides a foundation for subsequent analysis of the dynamic behavior of components.

[0094] (2) Based on each real-time monitoring data and standard coordinate information, calculate the instantaneous offset vector of the target component at each monitoring time to obtain the instantaneous offset vector sequence of the target component at multiple monitoring times.

[0095] Based on each real-time monitoring data and standard coordinate information, the instantaneous offset vector of the target component at each monitoring time is calculated. The real-time position data obtained at each monitoring time can be compared with the preset standard coordinates in the BIM model to quantify the instantaneous displacement of the component at that time.

[0096] Here, the instantaneous offset vector is a physical quantity with direction and magnitude, which represents the deviation of a component from its designed position at a specific moment.

[0097] Specifically, the displacement vector can be obtained through simple subtraction of three-dimensional coordinates, or, in more complex scenarios, through coordinate transformation and geometric operations. After organizing and storing the instantaneous offset vectors calculated at different monitoring times in chronological order, an instantaneous offset vector sequence is formed. This sequence can reflect the continuous or discrete displacement history of the target component from the start of monitoring to the current moment. The sequence can be stored as an array, list, or timestamp data in a database.

[0098] (3) Calculate the cumulative offset distribution of the target component based on the instantaneous offset vector sequence.

[0099] Based on the instantaneous offset vector sequence, the cumulative offset distribution of the target component is calculated. This aims to comprehensively evaluate the overall offset of the component over a period of time based on the instantaneous offset vector sequence. The cumulative offset distribution is not simply a superposition of instantaneous offsets, but rather reveals the overall trend, range, and probability distribution of the component's offset through statistical analysis or mathematical processing of the entire sequence.

[0100] For example, after acquiring real-time monitoring data of the target component at multiple times, the acquired displacement values ​​of the component in different directions can be compared with the preset BIM coordinates. The difference between the coordinate information of two adjacent times in the calculated offset (ΔX, ΔY, ΔZ) at different times can be calculated to integrate them into an offset vector. After determining the calculated offsets at multiple adjacent time points, the corresponding offset sequence is obtained, which is used to determine the cumulative offset distribution of the target component.

[0101] Specifically, the cumulative offset distribution of the target component The calculation formula is as follows: in, This indicates the number of data points collected within the specified time period. Let t be the instantaneous offset vector at time t. Its energy distribution can be determined by averaging the deviation over a period of time (from the first time t=1 to time M). Let be the magnitude of the instantaneous offset vector at time t.

[0102] Step S23: Calculate the trend of the offset change of the target component based on the cumulative offset distribution of the target component.

[0103] The trend of offset change can be used to characterize whether the component offset tends to stabilize, continues to increase, or decreases, and can be used to predict future offset behavior and provide timely warnings. Specifically, regression analysis or trend line fitting can be performed on the changes of key statistics (such as mean and maximum value) in the cumulative offset distribution over time.

[0104] For example, methods such as linear regression, multinomial regression, or exponential smoothing can be used to extract the growth, decrease, or fluctuation trends of offset from historical cumulative offset data. Alternatively, the trend of offset changes can be determined by comparing the distribution characteristics of cumulative offset over different time periods (e.g., peak value, width, skewness, etc.).

[0105] For example, the trend of the offset change of the target component The calculation formula is as follows: in, Let be the instantaneous offset vector at time t. Let be the instantaneous offset vector at time t-1. for The length of the mold, The change at time t+1 relative to time t-1 This represents the slope of the curve fitted to the obtained change.

[0106] Step S24: Based on the product of the cumulative offset distribution and the offset change trend, the first offset evaluation index of the target component is obtained, which can be used to represent the degree of offset of the target component.

[0107] Among them, the first offset assessment index can be a more comprehensive and forward-looking offset assessment index, thus more accurately reflecting the offset risk of the component.

[0108] For example, the mean or maximum value of the cumulative offset distribution can be weighted and multiplied by the slope or growth rate of the trend line of the offset change trend. The weights can be set based on practical engineering experience or expert knowledge. Alternatively, a fusion function can be designed that takes the statistical characteristics of the cumulative offset distribution (e.g., mean, variance) and parameters of the offset change trend (e.g., slope, acceleration) as input, and outputs a first offset evaluation index through nonlinear combination or machine learning model.

[0109] For example, the first offset evaluation index of the i-th target component The calculation formula is as follows: in, Let i be the cumulative offset distribution of the i-th target component. This represents the trend of the offset change of the i-th target component.

[0110] This application establishes a foundation for subsequent offset calculations by associating real-time sensor data with target components in the BIM model and obtaining their standard coordinate information. Subsequently, the scheme moves beyond instantaneous offset calculations, comparing real-time monitoring data of the target component at multiple monitoring times with standard coordinate information to calculate a cumulative offset distribution reflecting its historical offset behavior. Based on this, the cumulative offset distribution is further analyzed to identify whether the offset is trending towards stability, continuous increase, or decrease. Finally, a comprehensive first offset evaluation index is obtained by multiplying and fusing the historical offset state of the component as reflected in the cumulative offset distribution with the future dynamics revealed by the offset change trend. This method ensures that the calculated first offset evaluation index not only includes the component's current offset but also incorporates considerations of its long-term behavior patterns and future development direction, significantly improving the comprehensiveness and foresight of the evaluation results. This provides more accurate and reliable input for subsequent corrections based on component importance and final monitoring and early warning, enabling the entire construction structure offset monitoring method to identify potential risks earlier and more accurately, improving the timeliness and effectiveness of early warnings.

[0111] Therefore, by introducing the calculation of the cumulative offset distribution and offset change trend of the target component, this application can overcome the limitations of relying solely on instantaneous offset data for evaluation. This method allows the first offset evaluation index to not only reflect the current offset state of the component, but also incorporate the statistical characteristics of its historical offset behavior and dynamic predictions of future offset development. Therefore, the obtained evaluation index is more comprehensive, accurate, and forward-looking, enabling earlier and more precise identification of potential structural offset risks. This provides a more reliable basis for subsequent component importance correction and monitoring and early warning, significantly improving the timeliness and effectiveness of construction structure offset monitoring.

[0112] Based on the first, second, and third embodiments of this application described above, a fourth embodiment of this application is proposed. Please refer to [link to previous document]. Figure 4 , Figure 4 This is a flowchart illustrating the fourth embodiment of the construction structure offset monitoring method utilizing BIM technology in this application.

[0113] As a refinement of step S30 in the first embodiment, in the fourth embodiment of this application, the content that is the same as or similar to that in the first embodiment can be referred to the above description, and will not be repeated hereafter. Based on this, the construction structure offset monitoring method of this application using BIM technology includes steps S31 to S32:

[0114] Step S31: Determine the economic impact value, rework probability, and stress condition of the target component.

[0115] The economic impact value refers to the quantifiable direct or indirect economic losses that may result when a target component shifts or malfunctions. The economic impact value can encompass repair costs, downtime losses, material waste, and penalties for project delays.

[0116] One approach is to estimate the potential economic impact by analyzing the material cost of the component, its installation complexity, and its location on the critical path throughout the project.

[0117] Another approach is to establish an economic loss model that comprehensively considers factors such as the cost of replacing components, the time of interruption in subsequent processes caused by component problems and their corresponding economic losses, as well as potential quality claims.

[0118] In addition, the rework probability of a target component refers to the likelihood that the component will need to be reworked during construction due to misalignment or other quality issues. The rework probability is an important indicator for measuring the construction risk of a component.

[0119] One approach is to determine the probability of rework based on factors such as the type of component, construction process, environmental conditions, and the historical performance of the construction team, through expert experience assessment or statistical analysis.

[0120] Another approach is to use machine learning models, inputting design parameters of the component, construction difficulty coefficient, environmental humidity / temperature, and other data, to predict the probability of rework for the component.

[0121] Furthermore, the stress condition of the target component refers to the mechanical state it experiences under design conditions or actual construction loads. The stress condition can include stress, strain, deformation, etc. The stress condition is usually extracted from the stress parameters and can be used to reflect the component's response to changes in external loads.

[0122] One approach is to estimate the stress level of a critical section by simplifying the mechanical model or structural mechanics calculations, based on the component's geometry, material properties, and external loads.

[0123] Another approach is to install strain sensors or displacement sensors on the components to monitor their actual stress or deformation during construction in real time, thereby obtaining their stress status.

[0124] In one specific implementation, the steps for determining the economic impact value of the target component include:

[0125] (1) Obtain historical data on the target component's deviation and rework during the historical construction process; the historical data includes the time spent on rework, the cost of rework, and the total number of reworks.

[0126] (2) Calculate the economic impact value of the target component based on the time spent on rework, the cost of rework, and the total number of reworks.

[0127] Here, detailed records can be collected and organized of target components in previous construction projects, where their position or shape deviated from the design requirements due to various reasons (such as design changes, construction errors, external environmental influences, etc.), thus requiring rework.

[0128] It's important to note that this historical data forms the basis for quantifying the economic impact of components, providing specific case information on past deviations that led to rework. This information is crucial for quantifying economic losses. This historical data can be obtained from documents such as Project Management Information Systems (PMIS), construction logs, engineering change records, and cost accounting reports. Some construction management software or BIM platforms integrate data logging functions, enabling them to automatically track and store this type of historical data.

[0129] For example, the economic impact value of the target component The calculation formula is as follows: in, Indicates the first The length of time required for rework. Indicates the obtained first The cost of rework, where n is the number of times the target component has been reworked due to deviation during the historical construction process.

[0130] Specifically, the economic impact value of the target component It can be determined based on the time length of each of the n rework instances that occurred during the historical construction process. and the cost of rework The calculation shows that the time required for rework is [missing information]. and the cost of rework The calculation can be performed after normalization.

[0131] In one specific implementation, the step of determining the rework probability of the target component includes:

[0132] (1) Retrieve a set of historical cases with the same or similar offset from the historical construction database to obtain the target historical data.

[0133] The target historical data includes the total number of cases with the same or similar offset and the number of reworks.

[0134] Here, the historical construction database is a collection that stores a large amount of detailed information about past construction projects, which may include the type of different components, materials, construction environment, offset at different construction stages, whether rework has occurred, the specific reasons for rework, and the costs incurred by rework.

[0135] The retrieval process can utilize structured query language for precise matching, or employ machine learning algorithms to perform pattern recognition on historical data to find historical component instances that are closest to the current target component in terms of offset (e.g., offset magnitude, offset direction, offset type, etc.) or within a preset similarity range.

[0136] The degree of similarity or same offset can refer to the absolute value of the offset being within a certain range, or the angle between the direction of the offset vector and the direction of the offset vector of the target component being less than a certain threshold.

[0137] (2) Calculate the rework probability of the target component based on the total number of cases and the number of reworks.

[0138] The total number of cases refers to the total number of component instances that meet the same or similar offset criteria selected from the historical construction database during the above search process. The number of rework instances refers to the number of component instances among these selected historical cases that actually underwent rework operations such as correction, demolition, or reconstruction.

[0139] Specifically, the probability of rework for a target component can be calculated using frequency statistics, where the probability of rework is equal to the number of reworks divided by the total number of cases.

[0140] For example, the rework probability of the target component The specific calculation formula is as follows: Where N represents the number of identical histories obtained. This indicates the number of times rework occurred in the corresponding historical data.

[0141] In one specific implementation, the steps for determining the stress state of the target component include: (1) Based on the geometric and material properties of the target component in the BIM model, finite element analysis is performed on the target component and related structures.

[0142] Geometric attributes refer to the structural geometric data of the target component as defined in the BIM model, such as shape, size, cross-sectional features, and spatial location. For example, for a beam component, its geometric attributes may include length, width, and height; for a column component, its geometric attributes may include cross-sectional shape and size.

[0143] Material property information refers to the mechanical performance parameters of the materials used in the target component, such as elastic modulus, Poisson's ratio, yield strength, and compressive strength. The geometric and material property information of the target component can be stored and managed as inherent data of the component in the BIM model.

[0144] In practice, these parameters can be read directly through the application programming interface (API) of BIM software, or obtained by parsing the exported BIM model in an industry standard format.

[0145] It should be noted that finite element analysis (FEM) is a numerical calculation method that discretizes a complex continuum into a finite number of elements and solves for the overall structural mechanical response by analyzing these elements. In monitoring structural offset during construction, FEM is performed on the target component and its associated structures to simulate the stress, strain, and displacement distribution of the component under various loads. The associated structures here refer to surrounding components or structural parts that are directly or indirectly connected to the target component and mechanically interact with it. Performing correlation analysis allows for a more comprehensive consideration of the component's boundary conditions and interactions, thereby improving the accuracy of the analysis results.

[0146] Specifically, this can be achieved by importing the structural information from the BIM model into professional finite element analysis software (such as SAP2000, ETABS, ANSYS, etc.), or through the structural analysis module integrated into the BIM software.

[0147] (2) Extract the maximum stress value of the target component under the preset working conditions from the results of the finite element analysis to determine the stress condition of the target component.

[0148] Among them, the preset working conditions refer to various load combinations that may be encountered during construction, such as component self-weight, construction live load, wind load, seismic load, etc. These working conditions need to be set according to engineering design specifications and actual construction conditions.

[0149] The maximum stress value refers to the maximum response value of the target component under all preset working conditions, including stress, internal forces (such as axial force, shear force, and bending moment), or deformation. Extracting the maximum stress value is to identify the mechanical state of the component under the most unfavorable loading conditions, serving as a key indicator for assessing its mechanical sensitivity. Typically, finite element analysis software generates detailed analysis reports, from which users can filter or automatically extract these maximum values ​​using scripts. Determining the stress condition involves quantitatively describing the mechanical response state of the target component under various loads through the aforementioned finite element analysis and maximum stress value extraction. This includes, but is not limited to, the component's stress level, internal force magnitude, and deformation degree. This quantitative approach provides accurate mechanical sensitivity input for subsequent component importance calculations, making the assessment of component importance more objective and scientific.

[0150] Step S32: Calculate the component importance of the target component based on the economic impact value, rework probability, and stress conditions.

[0151] Calculating the importance of a target component based on stress conditions, rework probability, and economic impact involves comprehensively evaluating the aforementioned multi-dimensional information to quantify the component's criticality and potential risks within the overall construction structure. This approach integrates the component's structural safety, construction quality risks, and economic risks.

[0152] One approach is to use a weighted summation method, assigning different weights to the normalized stress conditions, rework probability, and economic impact value, and then performing a linear combination to obtain the component importance.

[0153] Another approach is to construct a multi-criteria decision analysis model, such as the Analytic Hierarchy Process (AHP) or fuzzy comprehensive evaluation method, using the above information as evaluation indicators, determining the weight of each indicator through expert scoring or data-driven methods, and finally calculating the importance of the component.

[0154] For example, the component importance of the target component The calculation formula is as follows: in, The economic impact value of the target component. Let be the probability of rework for the target component. This describes the stress state of the target component.

[0155] In one implementation, the component importance of the target component is determined. Then, the importance of the target component can be determined. The second offset evaluation index of the target component is calculated using the following formula: here, ,here, The first offset evaluation metric, The second offset evaluation metric is the component importance based on the target component. The offset evaluation index after correction of the first offset evaluation index.

[0156] In the above embodiments, the accuracy and reliability of monitoring structural offsets are improved by finely determining the importance of target components. Specifically, firstly, by determining the economic impact value of the target component, the potential economic losses caused by a problem with the component are quantified, providing an economic dimension for risk assessment. Secondly, by determining the rework probability of the target component, the likelihood of quality problems occurring during construction is assessed, reflecting the inherent risks of the construction process. Thirdly, by determining the stress state of the target component, the mechanical criticality of the component in the structural system is revealed, i.e., its impact on the overall stability of the structure. Subsequently, these multi-dimensional information, namely stress state, rework probability, and economic impact value, are comprehensively calculated to obtain a comprehensive and objective component importance. This multi-dimensional and comprehensive assessment method allows the component importance to more accurately reflect the actual risk level of the component. When this meticulously calculated component importance is used to correct the first offset assessment index, it can more effectively identify components that are highly important but have small offsets, or components that have large offsets but relatively low importance. This avoids misjudgments that may be caused by a single physical offset index, thus enabling the final generated second offset assessment index to more accurately reflect the comprehensive risk of the component and providing a more solid foundation for subsequent monitoring and early warning.

[0157] Therefore, the aforementioned monitoring scheme proposes a more comprehensive and accurate method for assessing the importance of components. This method not only considers the physical and mechanical properties of the components but also incorporates economic and quality risks during construction, making component importance no longer a single-dimensional assessment. Based on this multi-dimensional and comprehensive assessment, the criticality and potential risks of target components within the entire construction structure can be more accurately reflected. When the first offset assessment index is corrected using this component importance, it can effectively avoid misjudgments of risk that might arise from focusing solely on physical offset. For example, a component with a small offset but a significant economic impact or extremely high mechanical sensitivity can be assigned a higher risk weight, thus ensuring that monitoring and early warning information can more accurately target those components that truly require attention. This significantly improves the accuracy of early warnings and the scientific basis of decision-making in construction structure offset monitoring.

[0158] Based on the first to fourth embodiments of this application described above, a fifth embodiment of this application is proposed. Please refer to [link to previous document]. Figure 5 , Figure 5 This is a flowchart illustrating the fifth embodiment of the construction structure offset monitoring method utilizing BIM technology in this application.

[0159] As an extension of step S40 in the first embodiment, in the fifth embodiment of this application, the content that is the same as or similar to that in the first embodiment can be referred to the above description and will not be repeated hereafter. Based on this, the construction structure offset monitoring method of this application using BIM technology includes steps S41 to S42:

[0160] Step S41: For a group of interconnected components consisting of multiple mechanically related components in the construction structure, calculate the linkage risk value of the interconnected component group.

[0161] In structural construction, multiple components are directly or indirectly mechanically connected, and their forces, deformations, or displacements affect each other. For example, in frame structures, beams and columns, and slabs and beams on the same floor are typically closely mechanically linked. Identifying these interconnected component groups can be achieved by analyzing the structural topology, connection methods, and load transfer paths of the components in the BIM model. Alternatively, it can be determined based on predefined structural type rules or the expertise of structural engineers.

[0162] It should be noted that the probability or severity of systemic risk in a group of related components can be quantified by calculating the linkage risk value. This risk value comprehensively considers the offset of each component within the group and their mutual influence.

[0163] One approach is to perform a weighted calculation based on the second offset evaluation index of each component in the associated component group, combined with the mechanical connection strength or influence factor between components.

[0164] Another approach is to construct a probabilistic model to assess the risk of interconnected components by analyzing the probability of each component's offset and the probability of their mutual influence. The interconnected risk value is then compared to a preset interconnected threshold, which serves as a benchmark for determining whether a group of related components is in a dangerous state. This threshold can be set based on structural design codes, safety standards, or historical engineering experience. For example, different interconnected thresholds can be set according to the safety requirements of specific structural types or construction stages.

[0165] In some implementations, a method for calculating the linkage risk value and issuing early warnings for a group of mechanically related components in a construction structure is proposed. However, in practical applications, how to accurately and comprehensively assess the linkage risk of a group of mechanically related components, especially how to quantify the mutual influence between different components and their contribution to the overall risk, is a technical problem that needs to be solved. If the calculation method for the linkage risk value is not precise enough, it may lead to the failure to detect potential structural risks in a timely manner or to generate unnecessary false alarms, affecting construction safety and efficiency. Based on this, the steps for calculating the linkage risk value of a group of mechanically related components in a construction structure include:

[0166] (1) Based on the finite element analysis results of the BIM model, determine the mechanical connection weights between different components in the associated component group.

[0167] Among them, the mechanical connection weight aims to quantify the tightness or influence of mechanical coupling between different components in a group of associated components. That is, when a component is offset, its adjacent components with higher mechanical connection weights are more affected.

[0168] As one implementation method, structural mechanics analysis can be performed on the BIM model to simulate how the displacement or stress change of one component is transmitted and affects other components under specific load or deformation conditions, thereby calculating the stiffness ratio, stress transmission coefficient or deformation compatibility coefficient between components to quantify the weights.

[0169] As another approach, the mechanical connection strength can be evaluated by analyzing the connection type (such as rigid connection, hinged connection, elastic connection) and the number and geometric dimensions of the connection points between components in the finite element model, combined with material properties, and then converted into weights.

[0170] (2) Based on historical construction data, determine the probability of co-occurrence of problems among different components in the associated component group, and the probability of problems existing individually in each component in the associated component group.

[0171] Among them, the probability of co-occurrence of problems and the probability of individual problems are used to quantify the statistical patterns of problems occurring in components during historical construction. In particular, when a component has a problem, other related components may also have problems, as well as the possibility of a component having a problem independently. This helps to assess the associated risks at the empirical level.

[0172] For example, by mining historical construction project databases, we can statistically analyze the frequency of simultaneous occurrences of problems such as displacement, deformation, or rework in two or more components within a group of related components under similar construction conditions, thereby calculating the co-occurrence probability of the problem. Simultaneously, we can also statistically analyze the frequency of individual problems occurring in each component.

[0173] As another approach, machine learning methods, such as Bayesian networks or association rule mining, can be used to analyze the dependencies between component problems in historical data, thereby predicting the probability of problem co-occurrence and the probability of each component having a problem individually.

[0174] (3) Calculate the correlation influence factors between different components in the related component group.

[0175] Among them, the correlation influence factor is an indicator that comprehensively considers factors such as mechanical connection weight and the co-occurrence probability of historical problems to quantify the degree of mutual influence between components. The correlation influence factor can be used to reflect the comprehensive possibility and intensity of the influence of the offset or problem of one component on other related components.

[0176] Specifically, the correlation influence factor can be obtained by weighted averaging or product of mechanical connection weight and problem co-occurrence probability. For example, the mechanical connection weight can be used as the basis, and then the problem co-occurrence probability can be used for correction to reflect actual construction experience.

[0177] As another approach, a multi-factor evaluation model can be constructed, taking mechanical connection weights, problem co-occurrence probability, and other relevant factors (e.g., geometric location of components, construction sequence, etc.) as inputs, and calculating the comprehensive correlation influence factors through an expert system or fuzzy comprehensive evaluation method.

[0178] (4) Based on the associated impact factors and the second offset evaluation index of the associated components, the linkage risk value of the associated component group is calculated.

[0179] Among them, the linkage risk value is a quantitative indicator of the overall risk of the associated component group. The linkage risk value can combine the degree of mutual influence between components and the offset risk of each component itself, and is used to determine whether the entire associated component group is in a dangerous state and trigger regional early warning.

[0180] For example, the linkage risk value can be obtained by weighted summation or matrix operation of the second offset evaluation index of each component in the associated component group and the correlation influence factors between them.

[0181] Specifically, the second offset evaluation index of each component can be multiplied by its correlation influence factor on other components, and then the influence of all components can be summed.

[0182] As another implementation method, network analysis can also be used, treating the group of related components as a network, with components as nodes and related influence factors as edge weights. Then, by combining the second offset evaluation index of each component, the linkage risk value of the entire network can be calculated through a network risk propagation model.

[0183] For example, calculating the correlation influence factor between different components in a group of related components can be done by calculating the correlation influence factor between two adjacent components in the group of related components. The formula is as follows: in, To determine the mechanical connection weights between different components in a group of related components based on the results of finite element analysis, This represents the probability that both components have a problem. Indicates the obtained first The probability of a problem occurring in a component. Indicates the obtained first +1 probability of having a problem.

[0184] After determining the correlation influence factors between two adjacent components, multiple different correlation influence factors between adjacent components can be obtained. Furthermore, a cumulative correlation impact factor analysis is performed based on the cumulative correlation impact factors of multiple components. Here, the linkage risk value corresponding to multiple adjacent factors can be calculated. Specifically, the cumulative linked risk values ​​corresponding to multiple adjacent factors The specific calculation formula is as follows: in, This refers to the cumulative impact factor among (i to a) determined based on multiple and adjacent related impact factors calculated above. The second offset evaluation index is for the a-th target component of the cumulative plurality.

[0185] here, ,here, The first offset evaluation index for the a-th target component. The second offset evaluation metric for the a-th target component is, i.e., the component importance based on the target component. The offset evaluation index after correction of the first offset evaluation index.

[0186] Step S42: Compare the linkage risk value with the preset linkage threshold. When the linkage risk value exceeds the linkage threshold, generate regional linkage early warning information.

[0187] The linkage threshold can also be dynamically adjusted, for example, adaptively adjusted based on real-time monitoring data or environmental conditions. When the linkage risk value exceeds the linkage threshold, a regional linkage early warning information is generated, which can promptly notify relevant personnel, indicating that a certain group of related components has a systemic risk and requires intervention measures.

[0188] Early warning information can include the risk level, the affected component groups, and recommended inspection or remedial measures, and can be sent to project managers or construction teams through various means such as BIM platforms, SMS, and email. Furthermore, early warning information can trigger automated responses, such as initiating more intensive monitoring, adjusting construction plans, or restricting work in the relevant areas.

[0189] This application's solution, building upon the offset monitoring and risk assessment of individual components, further introduces a mechanism for comprehensive risk assessment of interconnected component groups within a construction structure. First, the system identifies mechanically interconnected component groups within the construction structure, where components influence each other in terms of stress or deformation. Then, for these interconnected component groups, the system calculates a linkage risk value. This linkage risk value is not simply an arithmetic of the individual offset risks of each component within the group, but rather takes into account factors such as the mechanical connection weights between components, the probability of problem co-occurrence, and correlation influence factors, thus more accurately reflecting the systemic risk of the entire component group. By comparing the calculated linkage risk value with a preset linkage threshold, if the linkage risk value exceeds the threshold, it indicates a potential systemic risk in the interconnected component group, at which point the system immediately generates a regional linkage early warning. This mechanism allows the monitoring system to move from risk assessment of local components to risk assessment of the entire structural system, effectively compensating for systemic risks that may be overlooked by focusing only on individual components, thereby providing a more comprehensive and in-depth guarantee of construction safety.

[0190] Therefore, by introducing a holistic risk assessment of interconnected component groups consisting of multiple mechanically related members in the construction structure, this method effectively addresses the problem that focusing solely on the offset of a single component might overlook systemic risks. By calculating the linkage risk value of the interconnected component group and comparing it with a linkage threshold, this method can promptly identify and warn of potential structural problems caused by the synergistic effects of multiple components, preventing overall structural instability or failure due to the accumulation of localized issues. This elevates the monitoring of construction structure offsets from the level of a single component to the level of the entire structural system, significantly improving the safety early warning capabilities and risk management level during construction. This allows for earlier intervention measures, reducing construction risks and potential economic losses.

[0191] Furthermore, this application also proposes a construction structure offset monitoring system 60 utilizing BIM technology, please refer to... Figure 6 , Figure 6 This is a structural diagram of a construction structure offset monitoring system utilizing BIM technology. Specifically, the construction structure offset monitoring system utilizing BIM technology includes: the monitoring system comprising a BIM model and a multi-source sensor cluster, and:

[0192] The acquisition module 61 is used to acquire real-time location information of multiple different components in the construction structure through a multi-source sensor cluster to obtain real-time monitoring data;

[0193] The calculation module 62 is used to calculate the first offset evaluation index of the target component based on the real-time monitoring data and the preset coordinates corresponding to the components in the BIM model; wherein the target component is any component in the construction structure, and the first offset evaluation index is obtained by fusing the cumulative offset distribution and offset change trend of different components.

[0194] The acquisition module 63 is used to acquire the component importance of the target component; wherein the component importance is determined based on the mechanical properties, historical rework data and economic impact information of the target component;

[0195] Correction module 64 is used to correct the first offset evaluation index of the target component based on the component importance score to obtain a second offset evaluation index;

[0196] The determination module 65 is used to compare the second offset evaluation index with a preset offset threshold to determine the monitoring and early warning information.

[0197] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for monitoring the offset of a construction structure using BIM technology, characterized in that, The method is applied to a construction structure offset monitoring system, the monitoring system including a BIM model and a multi-source sensor cluster, and the method includes: By using a multi-source sensor cluster, real-time location information of multiple different components in the construction structure is collected to obtain real-time monitoring data; Based on the real-time monitoring data and the preset coordinates corresponding to the components in the BIM model, a first offset evaluation index for the target component is calculated; wherein, the target component is any component in the construction structure, and the first offset evaluation index is obtained by fusing the cumulative offset distribution and offset change trend of different components; Obtain the component importance of the target component; wherein the component importance is determined based on the mechanical properties, historical rework data and economic impact information of the target component; The first offset evaluation index of the target component is corrected based on the component importance score to obtain the second offset evaluation index. The second offset evaluation index is compared with a preset offset threshold to determine the monitoring and early warning information.

2. The method for monitoring the offset of construction structures using BIM technology according to claim 1, characterized in that, Before the step of acquiring real-time monitoring data by collecting real-time location information of multiple different components in the construction structure through a multi-source sensor cluster, the method further includes: The multi-source sensor cluster is set up within the monitoring area corresponding to the construction structure; wherein, at least one multi-source sensor is set up for each key component or sensitive area in the construction structure. The mapping relationship between the multi-source sensors and the corresponding target components in the construction structure is written into the BIM model to record the mapping relationship between the target components and the corresponding multi-source sensors in the BIM model.

3. The method for monitoring the offset of construction structures using BIM technology according to claim 1, characterized in that, The step of inputting the real-time monitoring data into BIM and calculating the first offset evaluation index of the target component in the construction structure includes: In the mapping table between the target component and the multi-source sensor corresponding to the BIM model, the target component corresponding to the monitoring data is determined, and the preset standard coordinate information of the target component is obtained; Based on the standard coordinate information and real-time monitoring information of the target component, the corresponding cumulative offset distribution is calculated; Based on the cumulative offset distribution of the target component, calculate the trend of offset change of the target component; The first offset evaluation index of the target component is obtained by multiplying the cumulative offset distribution with the offset change trend.

4. The method for monitoring the offset of construction structures using BIM technology according to claim 3, characterized in that, The step of calculating the corresponding cumulative offset distribution based on the standard coordinate information and real-time monitoring information of the target component includes: Acquire multiple real-time monitoring data corresponding to the target component at multiple monitoring times; Based on each of the real-time monitoring data and the standard coordinate information, the instantaneous offset vector of the target component at each monitoring time is calculated to obtain a sequence of instantaneous offset vectors of the target component at multiple monitoring times; The cumulative offset distribution of the target component is calculated based on the instantaneous offset vector sequence.

5. The method for monitoring structural offset using BIM technology according to claim 1, characterized in that, The step of obtaining the component importance of the target component includes: Determine the economic impact value, rework probability, and stress condition of the target component; Based on the economic impact value, the rework probability, and the stress condition, the component importance of the target component is calculated.

6. The method for monitoring the offset of construction structures using BIM technology according to claim 5, characterized in that, The step of determining the economic impact value of the target component includes: Obtain historical data on the target component's displacement and rework during historical construction; wherein, the historical data includes the time spent on rework, the cost incurred by rework, and the total number of reworks; The economic impact value of the target component is calculated based on the time spent on rework, the cost of rework, and the total number of reworks.

7. The method for monitoring the offset of construction structures using BIM technology according to claim 5, characterized in that, The step of determining the rework probability of the target component includes: From the historical construction database, retrieve a set of historical cases with the same or similar degree of offset as the target component to obtain the target historical data; wherein, the target historical data includes the total number of cases with the same or similar degree of offset and the number of times rework occurred; Based on the total number of cases and the number of reworks, the rework probability of the target component is calculated.

8. The method for monitoring the offset of construction structures using BIM technology according to claim 5, characterized in that, The steps for determining the stress state of the target component include: Based on the geometric and material properties of the target component in the BIM model, finite element analysis is performed on the target component and its associated structures. From the results of the finite element analysis, the maximum stress value of the target component under the preset working conditions is extracted to determine the stress condition of the target component.

9. The method for monitoring the offset of a construction structure using BIM technology according to any one of claims 1 to 8, characterized in that, After the step of correcting the first offset evaluation index of the target component based on the component importance score to obtain the second offset evaluation index, the construction structure offset monitoring method using BIM technology further includes: For a group of interconnected components consisting of multiple mechanically related components in the construction structure, calculate the linkage risk value of the interconnected component group. The linkage risk value is compared with a preset linkage threshold. When the linkage risk value exceeds the linkage threshold, a regional linkage early warning information is generated.

10. A construction structure offset monitoring system utilizing BIM technology, characterized in that, include: Memory and processor; The memory is connected to the processor; The memory is used to store program instructions; The processor is configured to implement the construction structure offset monitoring method using BIM technology as described in any one of claims 1-9 when program instructions are executed.

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