BIM model dynamic update-driven real-time accurate early warning method and system for steel structure construction

Abstract

The invention relates to the field of building construction, and discloses a BIM model dynamic update-driven steel structure construction real-time accurate early warning method, which comprises the following steps: deploying a sensor array at a construction site for collecting various data of a steel structure, the various data including actual size, installation position, stress strain, temperature and humidity data; capturing various data of a construction area through a three-dimensional laser scanner and an image recognition technology; the invention also discloses a BIM model dynamic update-driven steel structure construction real-time accurate early warning system. The system comprises a data acquisition unit, a three-dimensional scanning unit, a data processing unit, a risk assessment unit, an early warning mechanism unit and a feedback correction unit. According to the method, the construction deviation is fed back in real time, the BIM model is dynamically updated, and risk assessment is performed by integrating multiple factors, so that the construction precision and safety are improved, the precise monitoring and management of the construction process are ensured, and manual errors and delayed response are avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of building construction, specifically a steel structure construction real-time precise early warning method and system driven by BIM model dynamic updating. BACKGROUND

[0002] In modern building construction, especially in large projects such as steel structure engineering, the control of construction quality and safety management is particularly important. In the construction process, any small deviation or risk can have a serious impact on the stability and safety of the structure. Traditional construction management often relies on manual inspection and periodic measurement, but this method cannot ensure timely detection and correction of potential problems.

[0003] In the prior art, building construction management generally uses BIM technology for design and planning. BIM models can provide detailed three-dimensional building information and provide some data support for construction management. By combining BIM models with on-site construction data, construction personnel can be provided with intuitive construction guidance and risk warnings. Some construction management platforms also collect on-site data through monitoring equipment and conduct simple risk analysis to identify potential problems in advance and provide recommendations for construction personnel.

[0004] However, the prior art has some limitations in practical application; first, although BIM technology provides detailed information in the design phase, many systems still lack real-time data updating functions, and actual deviations that occur during construction cannot be quickly fed back to the BIM model, resulting in construction personnel failing to adjust their work in a timely manner, increasing the accumulation of errors. Second, traditional risk assessment methods mostly rely on static data or a single evaluation index, lacking multi-factor dynamic evaluation, making it difficult to fully consider changes in stress, installation accuracy, and environmental factors during the construction process. Finally, the correction of construction deviations in the prior art usually relies on manual intervention, and the correction process is not quick and accurate enough, easily missing details, and unable to make real-time corrections, affecting construction progress and safety. SUMMARY

[0005] To overcome the shortcomings of the prior art, the present application provides a steel structure construction real-time precise early warning method and system driven by BIM model dynamic updating, which solves the problems of delayed correction of construction process deviations, lagging BIM model updates, and incomplete risk assessment in the prior art.

[0006] To achieve the above purpose, the present application realizes the following technical scheme: a steel structure construction real-time precise early warning method driven by BIM model dynamic updating, comprising the following steps: deploying a sensor array at the construction site to collect various data of the steel structure, the various data including actual dimensions, installation positions, stress and strain, temperature, and humidity data; Various data of the construction area are captured by a three-dimensional laser scanner and image recognition technology, and compared and analyzed with the BIM model; According to the captured data and three-dimensional scanning data, the BIM model is automatically updated to dynamically reflect the current construction state; based on risk assessment indexes specific to the construction state stage, risk assessment thresholds of different construction stages are set, and real-time construction risk assessment is performed through the dynamically updated BIM model, the risk assessment indexes including installation accuracy, stress condition and environmental impact parameters; When the real-time construction risk assessment value exceeds the set threshold, a warning mechanism is triggered, and real-time feedback is provided to the construction personnel and the risk area is identified; Through the real-time feedback of the warning information, the deviation in the construction process is corrected, and the BIM model is updated.

[0007] Preferably, the sensor array comprises: A stress-strain sensor for measuring the stress change of the steel structure member during construction and determining whether overload and abnormal stress condition occurs; A displacement sensor for monitoring the installation deviation of the steel structure member and comparing and analyzing with the design data in the BIM model; A temperature and humidity sensor for measuring the environmental parameters of the construction site and analyzing the influence of environmental factors on construction quality and structural stability in combination with the BIM model; A vibration sensor for detecting the vibration condition in the construction process and evaluating the influence of vibration on the stability of the steel structure in combination with the BIM model.

[0008] Preferably, the three-dimensional laser scanner and image recognition technology comprise: Three-dimensional laser scanning for generating point cloud data of the construction area and comparing with the BIM model to determine the installation accuracy; Image recognition technology based on deep learning algorithm for analyzing construction images, identifying component deviation and abnormal condition; fusion analysis, combining three-dimensional laser scanning and image recognition data, calculating the deviation between on-site construction and the BIM model, and providing adjustment suggestions.

[0009] Preferably, the dynamic updating of the BIM model comprises: Collecting data of the construction site and transmitting the data to the BIM model data processing system; Calculating the deviation of the data from the design parameters, and identifying installation errors, stress abnormalities and environmental impacts; Using adaptive adjustment algorithm to correct the BIM model, and optimizing the update strategy in combination with historical data; Providing construction adjustment suggestions and generating optimization schemes according to the corrected BIM model to guide the construction personnel to make adjustments.

[0010] Preferably, the risk assessment indicators include: Installation accuracy indicators for measuring the installation deviation of steel structure components, based on three-dimensional scanning data and sensor data to calculate the difference between actual position and design position; Stress condition indicators based on stress-strain sensor data analysis to judge the stress state of the component and whether there is an overload and structural deformation risk; Environmental impact parameters, through temperature and humidity sensors and vibration sensors to analyze the influence of external environment on steel structure construction quality and stability, and combined with BIM model to predict the hidden dangers caused by environmental factors; Dynamic weight adjustment mechanism, according to the construction stage and specific component type, dynamically adjust the weight of each risk assessment indicator to adapt to the risk judgment needs under different construction conditions.

[0011] Preferably, the early warning mechanism includes: Risk identification and classification, according to the calculation results of the risk assessment unit, the construction risk is classified, and the response strategy of different risk levels is set; Real-time early warning push, when the risk value exceeds the set threshold, send early warning information to the intelligent terminal device of the construction personnel through wireless communication, and highlight the risk area in the BIM model; Multi-level early warning mode, including visual alarm, sound prompt and remote notification; Feedback mechanism, after receiving the early warning, the construction personnel can confirm the risk handling through the mobile terminal, and the adjusted data is returned to the BIM model, so that it is synchronized and updated to optimize the subsequent construction process.

[0012] Preferably, the data transmission includes: Multi-source data fusion transmission, through wireless network, optical fiber communication or industrial internet protocol, real-time transmission of sensor data, three-dimensional scanning data and image recognition data to BIM model data processing system; Edge computing and cloud computing collaborative processing, edge computing devices are deployed on the construction site to preliminarily filter and compress the data collected by sensors, and upload key data to the cloud BIM platform; Data encryption and permission management, using data encryption technology to ensure data transmission security, and setting data access range according to construction personnel permission level; Data synchronization update mechanism, when the construction site data is uploaded to the BIM model, the system automatically checks the data integrity, real-time updates the BIM model, and synchronously displays the latest construction status and adjustment suggestions on the construction personnel terminal device.

[0013] Preferably, the risk area includes: a structural installation deviation risk area, when the installation position deviation of the steel structure component exceeds the set threshold value, the system highlights the deviation area in the BIM model and provides correction suggestions; a stress anomaly risk area, when the stress and strain sensor detects that the steel structure component is overloaded, stress concentrated or deformed, the stress anomaly component is automatically identified, and the risk position is marked in the BIM model.

[0014] Preferably, the construction adjustment comprises: an automatic adjustment mechanism, based on the construction deviation information provided by the BIM model, automatically generates adjustment suggestions and guides the construction equipment to make accurate adjustments; manual intervention correction, construction personnel manually adjust the component installation mode through intelligent terminal and field measurement tool according to the provided construction deviation analysis and correction suggestions, and upload new construction data to the BIM model after adjustment, so that it remains dynamic consistent.

[0015] The application also provides a steel structure construction real-time precise early warning system driven by BIM model dynamic updating, comprising: a data acquisition unit, which acquires various data of the construction site through a sensor array, the various data including actual size, installation position, stress and strain, temperature and humidity data, and sends the acquired various data to a data processing unit, the sensor array including stress sensors, displacement sensors, temperature and humidity sensors and vibration sensors; a three-dimensional scanning unit connected with the data acquisition unit, for acquiring point cloud data of the construction area through a three-dimensional laser scanner, and combining with the various data of the data acquisition unit to form complete information of the construction site; a data processing unit connected with the data acquisition unit and the three-dimensional scanning unit respectively, for receiving and fusing the various data from the data acquisition unit and the point cloud data from the three-dimensional scanning unit, extracting image information of the site construction, comparing with the original data in the BIM model, calculating the construction error, and dynamically updating the BIM model; a risk assessment unit connected with the data processing unit, for performing risk analysis on the construction state based on the dynamically updated BIM model data and the specific risk assessment index of the construction stage, and performing early warning judgment according to the set risk threshold; a warning mechanism unit connected with the risk assessment unit, when the risk assessment unit detects that the real-time risk value exceeds the preset threshold, sends risk warning information to the terminal device of the construction personnel, highlights the risk area in the BIM model, and provides risk level information and suggested countermeasures; a feedback correction unit connected with the warning mechanism unit, adjusts the construction process and corrects the construction parameters according to the feedback information of the construction personnel, and returns the correction data to the data processing unit, so that the BIM model is updated synchronously.

[0016] The application provides a steel structure construction real-time precise early warning method and system driven by BIM model dynamic updating. 1、The application adopts a technical scheme based on BIM model dynamic updating and real-time risk assessment, and achieves the technical effects of precise construction risk monitoring and automatic deviation correction.

[0017] 2、The application adopts a technical scheme of combining real-time feedback early warning information with deviation correction in the construction process, and achieves the technical effects of efficient construction deviation correction and optimized construction quality.

[0018] 3、The application adopts a multi-dimensional risk assessment system including installation precision, stress state and environmental influence parameters for comprehensive evaluation, and achieves the technical effect of comprehensive construction risk identification.

[0019] 4、The application adopts a technical scheme of visualizing the corrected construction state through the BIM model, and achieves the technical effects of intuitive display of construction deviation correction effect and risk assessment results. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 is a method flowchart of the application; Figure 2 is a system construction schematic diagram of the application. DETAILED DESCRIPTION

[0021] With reference to the drawings of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work are within the scope of protection of the present application.

[0022] Please refer to the drawings of the present application Figure 1 The embodiments of the present application provide a steel structure construction real-time precise early warning method driven by BIM model dynamic update, which comprises the following steps: S1, deploying a sensor array at the construction site for collecting various data of the steel structure, the various data including actual size, installation position, stress and strain, temperature and humidity data; At the steel structure construction site, in order to improve the accuracy of data collection and ensure the construction quality, it is usually necessary to deploy a sensor array to monitor relevant parameters in real time. These parameters include but are not limited to actual size, installation position, stress and strain, temperature and humidity data. Generally, the layout of the sensor array needs to be closely combined with the construction process to ensure the comprehensiveness and accuracy of data collection, and to provide reliable basis for subsequent data analysis, structure health assessment, etc.

[0023] In the specific implementation, the deployment of the sensor array needs to be planned in combination with each stage of the steel structure construction. For example, in the steel member processing stage, size measurement sensors can be deployed at key positions to ensure processing accuracy; in the installation stage, three-dimensional positioning sensors and stress sensors are combined to obtain installation errors and actual stress state; in the long-term service stage, temperature and humidity sensors are used to monitor the influence of environmental changes on the structure.

[0024] As a possible implementation, the size measurement sensor can adopt a laser ranging sensor, an ultrasonic ranging sensor or a visual recognition sensor to measure the size according to the geometric characteristics of the steel member. Specifically, the laser ranging sensor is based on the triangulation principle, and its measurement accuracy can reach millimeter level, which can be used for size detection of key nodes; the ultrasonic ranging sensor is suitable for long-range distance measurement, and has strong anti-interference ability especially in complex environment; the visual recognition sensor can extract the boundary features of the steel member through image processing algorithm to realize high-precision size detection.

[0025] In one possible implementation, the detection of the installation position can be achieved by combining an inertial measurement unit (IMU) and a laser positioning system to provide high-precision position information. The inertial measurement unit includes an accelerometer and a gyroscope, and the accuracy of the position information is improved through Kalman filtering algorithm for error correction. The laser positioning system can be based on LiDAR technology, and a high-precision three-dimensional model can be established by scanning the point cloud data of the construction site, so as to realize the accurate matching of the installation position of the component.

[0026] In terms of stress and strain monitoring, in some embodiments, the sensor array can use fiber Bragg grating (FBG) sensors, piezoelectric sensors, or resistance strain gauges for stress and strain measurement. Specifically, the fiber Bragg grating sensor can achieve micro-strain measurement based on Bragg wavelength change, and is suitable for long-term health monitoring; the piezoelectric sensor can be used for dynamic stress monitoring, and has high sensitivity especially in a vibration environment; the resistance strain gauge measures resistance change based on a Wheatstone bridge, and can achieve high-precision static stress monitoring.

[0027] In terms of environmental parameter collection, temperature and humidity data can be monitored by a distributed temperature and humidity sensor. Generally, the temperature sensor can be selected from a thermocouple, a thermistor, or an infrared thermometer. The thermocouple is based on the thermoelectric effect and is suitable for high-temperature environments; the thermistor has high sensitivity and can be used for fine temperature measurement; the infrared thermometer can be used for non-contact measurement and is suitable for special scenarios. The humidity sensor can be selected from a capacitive, impedance, or optical humidity sensor, among which the capacitive humidity sensor has a fast response speed and is suitable for dynamic humidity change monitoring.

[0028] As an option, the data acquisition system can combine wireless transmission technologies such as ZigBee, LoRa, or 5G communication to ensure remote transmission and real-time analysis of data. Specifically, the ZigBee protocol is suitable for short-distance data transmission, the LoRa technology can achieve long-distance low-power communication, and the 5G network can provide high-bandwidth, low-latency data transmission capabilities to meet the remote monitoring needs of complex construction sites.

[0029] In the formula part, let the strain value of a certain measuring point be ε, the stress value be σ, and the elastic modulus of the steel material be E, then the stress-strain relationship is: σ = E·ε; wherein: σ is the actual stress of the steel structure component, the unit is Pascal (Pa); ε is the strain value of the measuring point, which is a dimensionless parameter; E is the elastic modulus of the steel material, the unit is Pascal (Pa).

[0030] In addition, in the temperature compensation calculation, the correction can be made based on the thermal expansion coefficient α: ε T = α·ΔT; wherein: ε T εadd is the additional strain due to temperature change; α is the thermal expansion coefficient of the material in K -1 ; ΔΤ is the temperature change in Kelvin (K).

[0031] S2, capturing various data of the construction area by a three-dimensional laser scanner and image recognition technology, and comparing and analyzing the data with the BIM model; Real-time capturing of the actual state information of the steel structure on the construction site and comparing and analyzing the data with the BIM model data are important steps to ensure the installation quality and construction precision of the steel structure. Generally, the steel structure construction site environment is complex, the types of components are various, and there are certain deviations in the size, position and shape of the components, and the influence of environmental factors on data acquisition cannot be ignored. Therefore, in order to realize high-precision and comprehensive data acquisition and real-time checking combined with the accurate design data of the BIM model, a three-dimensional laser scanner and image recognition technology are introduced in the present application as a data capturing means. This technical route is organically connected with the aforementioned sensor array arrangement, component size measurement, stress and strain monitoring and other links to form a complete construction quality monitoring and data feedback closed loop, thereby forming an effective whole-process dynamic control system.

[0032] In the present embodiment, the three-dimensional laser scanner is used to quickly capture the spatial point cloud data of the construction site in a large range to form a high-precision point cloud model. Generally, the three-dimensional laser scanner can be selected from a scanning device based on the time-of-flight (TOF) principle or a scanning device based on the phase comparison principle, wherein the TOF type scanner is suitable for large-scale and high-speed scanning, and the phase comparison type scanner is suitable for high-precision and short-distance scanning.

[0033] In some embodiments, the three-dimensional laser scanner is arranged at a high place or other position with good view in the construction area, and combined with multi-station scanning and inter-station point cloud splicing technology, a complete point cloud model of the construction area is formed. Specifically, the point cloud splicing can use the ICP (Iterative Closest Point) algorithm or a splicing algorithm based on feature points to gradually improve the splicing accuracy.

[0034] In one possible implementation, after the point cloud data is preprocessed, noise filtering is first performed to filter out environmental stray points. Subsequently, based on the geometric characteristics of the components, independent point cloud subsets of each component are extracted. Generally, the point cloud segmentation can use a region growing-based segmentation method or a plane fitting-based segmentation method, the former is suitable for regular components, and the latter is suitable for large planar components.

[0035] In this embodiment, image recognition technology is used to capture image data of the construction site in real time to supplement the details that are difficult to capture accurately in the point cloud data, such as component surface numbers, installation marks, and weld seam shapes. Generally, image recognition can use a multispectral camera or a high-resolution industrial camera to obtain image data, and combine image enhancement, image segmentation, and feature extraction algorithms to identify the marking information and surface defect information of the components.

[0036] In one possible implementation, the image recognition process includes the following steps: first, image preprocessing, including grayscale, denoising, and enhancement; then, target region segmentation based on morphological algorithms and edge detection algorithms; and finally, target recognition and defect classification based on deep learning models such as U-Net or YOLO.

[0037] After the above data acquisition is completed, in this embodiment, both the three-dimensional point cloud data and the image recognition data need to be compared and analyzed with the BIM model. Generally, the comparison of the three-dimensional geometric data of the BIM model and the point cloud data can be based on component center line matching, surface shape comparison, or overall envelope error analysis.

[0038] As an option, the center line matching can be based on the spatial deviation calculation between the component design center line and the point cloud fitting center line, and the deviation calculation formula is as follows: Wherein: Δd is the center line deviation distance, in millimeters (mm); x1, y1, z1 are the coordinates of the center line point in the BIM model; x2, y2, z2 are the coordinates of the corresponding point of the point cloud fitting center line.

[0039] Specifically, the surface shape comparison can be based on the point-by-point distance calculation between the surface mesh of the BIM model and the component surface of the point cloud, and the distance calculation formula is as follows: Wherein: D i is the distance from the point cloud point p i to the nearest point on the surface of the BIM model; p i is a sampling point in the point cloud; p j is a sampling point on the surface of the BIM model; ||.|| represents the Euclidean distance calculation, and min represents the minimum value operation; p j ∈BIM represents p j is a sampling point on the surface of the BIM model, which belongs to the sampling point set in the BIM model.

[0040] In a possible implementation, the overall envelope error analysis can calculate the three-dimensional envelope volume deviation based on the component minimum bounding box (MBB) comparison. The envelope volume deviation calculation formula is as follows: ΔV=V BM -V PointCloud ; Wherein: ΔV is the envelope volume deviation, with the unit of cubic millimeter (mm 3 );V BM is the envelope volume of the BIM model component; V PointCloud is the envelope volume of the point cloud component.

[0041] In a possible implementation, the comparison between the image recognition data and the BIM model data can be based on the component number and identification comparison. Specifically, the preset component number in the BIM model is compared with the number text in the image recognition result through OCR, and the number matching rate is calculated. The number matching rate calculation formula is as follows: Wherein: R is the number matching rate, with the unit of percentage (%); N match is the number of consistent numbers between the image recognition and the BIM number; N total is the total number of numbers in the BIM model.

[0042] Generally, if the number matching rate is lower than the preset threshold, it is considered that there is a risk of missing or wrong component installation number, which needs to be further manually reviewed.

[0043] As an option, the comparison between the image recognition data and the BIM model data can also include the weld form comparison. Specifically, the preset weld position and type information in the BIM model is compared with the weld form information extracted by the image recognition through contour comparison and size comparison. The weld contour comparison can be based on the Fourier descriptor algorithm or the morphological contour matching algorithm; the weld size comparison can be based on the one-by-one comparison of the weld width and depth measurement data.

[0044] The results of the above comparison analysis can be comprehensively analyzed with the size, position and stress and strain data obtained by the sensor array to form a comprehensive quality evaluation and deviation tracing mechanism of the construction site.

[0045] S3, automatically update the BIM model according to the captured data and the three-dimensional scanning data, so that it dynamically reflects the current construction state; Dynamic updating of BIM model is an important link to ensure consistency between construction process and design planning. Generally, there are inevitable errors in the construction process, such as component size deviation, installation position error, and welding seam shape difference. In order to ensure the construction quality and realize the accurate feedback of the construction state, the BIM model needs to be dynamically updated based on the captured field data and three-dimensional scanning data, so as to reflect the current construction state. This process not only needs to analyze the construction deviation in real time, but also needs to combine the geometric, topological and attribute information of the BIM model for intelligent adjustment, and form a closed-loop management with subsequent construction monitoring, quality evaluation and other links.

[0046] In this embodiment, the dynamic updating of the BIM model relies on the point cloud data of the construction site obtained by the three-dimensional laser scanner, and combines the component identification and size information extracted by the image recognition technology to adjust the model in real time. Generally, the point cloud data can be aligned with the BIM model through the ICP (Iterative Closest Point) algorithm to determine the spatial position and attitude deviation of the component. Specifically, let the component center point coordinates of the BIM model be (x B ,y B ,z B ), and the component center point coordinates fitted by the point cloud be (x P ,y P ,z P ), then the position deviation calculation formula is as follows: Wherein: Δd is the center line deviation distance, unit: millimeter (mm); x B ,y B ,z B is the component center point coordinate of the BIM model; x P ,y P ,z P is the component center point coordinate fitted by the point cloud.

[0047] In some embodiments, the topological structure of the BIM model also needs to be adjusted according to the scanning data to reflect the latest state of the construction site. Generally, the topological structure updating can be based on the component connection relationship adjustment algorithm, and the spatial changes of the connection nodes are calculated by comparing the relative positions of the components in the point cloud data. Let the BIM coordinates of a connection node be (X B ,Y B ,Z B )(X P ,Y P ,Z P ), and the corresponding connection point coordinates in the scanning data be: wherein: AL is the spatial deviation of the connecting node, in millimeters (mm); X B Y B Z B are the coordinates of the connecting node in the BIM model; X P Y P Z P are the coordinates of the connecting node fitted from the point cloud data.

[0048] In one possible implementation, the geometric information adjustment of the BIM model can be processed in combination with a parametric modeling method. Generally, parametric modeling can use B-Rep (Boundary Representation) or NURBS (Non-Uniform Rational B-Spline) surface representation to automatically correct the geometric information of the component. For example, if there is a deviation in the component surface fitted from the point cloud, the surface least squares fitting method can be used to adjust it to make the fitted surface optimally match the original BIM model. Its error function can be expressed as: wherein: E is the elastic modulus of the steel material; p i is the sampling point in the point cloud; S(u i ,v i ) is the corresponding point on the NURBS surface. n is the number of sampling points in the point cloud, i.e., the total number of points involved in error calculation; i is an index variable used to traverse all sampling points in the point cloud.

[0049] In one possible implementation, the attribute information of the BIM model also needs to be dynamically adjusted to reflect the construction progress and material change. Generally, the material properties, installation status, and other information of the component can be updated in combination with RFID tags or image recognition results. For example, if a component is replaced with a new material due to on-site adjustment, the material attribute field in the BIM database can be automatically updated to ensure consistency in subsequent construction management.

[0050] As an option, the updated data of the BIM model can be synchronized to the cloud construction management system to realize remote monitoring and construction coordination. Generally, data synchronization can use MQTT, HTTP, or WebSocket protocols to ensure the real-time and integrity of the data. Specifically, the MQTT protocol is suitable for low-bandwidth environments, the HTTP protocol is suitable for batch data synchronization, and the WebSocket protocol is suitable for high-frequency data update scenarios.

[0051] S4, based on the risk assessment index specific to the construction state stage, set the risk assessment threshold of different construction stages, and through the dynamic updating of the BIM model, the construction risk is evaluated in real time, and the risk assessment index includes installation accuracy, stress condition and environmental influence parameter; The risk assessment of the construction process is crucial to ensure the safety of the steel structure. Generally, there may be installation accuracy deviation, abnormal stress state and environmental factor change and other risks during the construction process. If these risks are not identified in time, it may lead to structural safety hazards. Therefore, in order to ensure the construction quality and reduce the risk, the present application sets the risk assessment threshold of different construction stages based on the risk assessment index specific to the construction state stage, and relies on the dynamic updating of the BIM model to evaluate the construction risk in real time. This scheme closely links with the aforementioned three-dimensional scanning data capture, BIM model dynamic updating and other technical modules, and realizes intelligent monitoring and risk control of the whole construction process.

[0052] In this embodiment, the construction stage is divided according to the steel structure installation process, including the component hoisting stage, the positioning and fixing stage and the structure stress adjustment stage. Generally, the construction risk of each stage has different evaluation indexes and corresponding thresholds, and different risk evaluation standards need to be set.

[0053] In some embodiments, installation accuracy is the core parameter of construction quality evaluation. Generally, installation accuracy can be quantified by the spatial deviation of components, including horizontal deviation, vertical deviation and angle deviation. Specifically, let the theoretical installation position coordinates of the component be (x T ,y T ,z T ), and the actual installation position coordinates be (x A ,y A ,z A ), then the horizontal and vertical deviation is calculated as follows: δ x =|x T -x A |,δ y =|y T -y A |,δ z =|z T -z A |; Wherein: δ x , δ y , δ z are the horizontal, longitudinal and vertical deviations of the component, respectively, with the unit of millimeter (mm); (x T ,y T ,z T ) is the theoretical installation coordinate provided by the BIM model; (x A ,y Az A ) are the coordinates measured in actual installation.

[0054] In one possible implementation, if the above deviation exceeds the threshold set in the construction phase, the system triggers a risk alert and marks the abnormal component in the BIM model, prompting the construction personnel to make adjustments.

[0055] In this embodiment, the stress condition is another important indicator for risk assessment. Generally, the stress state in the construction phase needs to be calculated in combination with the structure analysis module of the BIM model to determine whether the structure stress is within the safe range. Specifically, the stress state of the component can be evaluated by parameters such as internal stress, node reaction force, and support reaction force. Let the axial stress of the component be σ, and its calculation formula is as follows: Wherein: σ is the actual stress of the steel structure component, the unit is Pascal (Pa); F is the axial force acting on the component, the unit is Newton (N); A is the cross-sectional area of the component, the unit is square meter (m 2 ).

[0056] In some embodiments, the stress state of the component can be simulated by the finite element analysis method, and the safety factor of the component is calculated in combination with the actual monitoring stress data. Generally, the safety factor SF can be defined as: Wherein: SF is the safety factor, dimensionless; σ y is the yield stress of the component material; σ is the actual stress of the steel structure component.

[0057] As an option, if the safety factor is lower than the preset threshold, the system identifies the component in the BIM model and prompts the construction personnel to take reinforcement measures, such as increasing support or adjusting the stress path.

[0058] In this embodiment, the environmental impact parameter is also an important factor for construction risk assessment. Generally, the environmental impact parameters include temperature, humidity, and wind speed, which have an impact on construction accuracy and stress state. Specifically, temperature changes may cause thermal expansion of the component, resulting in size changes, which need to be calculated for temperature compensation. Let the thermal expansion length change ΔL T of the component due to temperature change be calculated as follows: ΔL T = αL0ΔT; Wherein: ΔL T is the length change of the component caused by temperature change, the unit is millimeter (mm); α is the thermal expansion coefficient of the material, the unit is K -1 ; L0 is the initial length of the component, the unit is millimeter (mm); ΔT is the temperature change, the unit is Kelvin (K).

[0059] In one possible implementation, the temperature and humidity of the construction site can be collected by distributed sensors and transmitted to the BIM model in real time to dynamically adjust the component size error compensation parameters.

[0060] Generally, wind speed is an important factor affecting the installation of high-altitude components. Let the wind speed be V w , the wind load F w acting on the component is calculated as follows: Where: F w is the wind load, in Newton (N); C d is the wind resistance coefficient, dimensionless; A is the cross-sectional area of the component, in square meters (m 2 ); ρ is the air density, in kilograms per cubic meter (kg / m 3 ); is the wind speed, in meters per second (m / s).

[0061] As an option, if the wind speed exceeds the safety threshold during the construction phase, the system marks the high-risk area in the BIM model and suggests suspending work until the environmental conditions meet the construction requirements.

[0062] In some embodiments, the risk assessment results can be synchronized to a remote monitoring platform to enable real-time monitoring and decision support for construction managers. Generally, data synchronization can use wireless communication technology such as 5G or LoRa to ensure the stability of data transmission.

[0063] S5, when the real-time construction risk assessment value exceeds the set threshold, triggering the early warning mechanism, real-time feedback to the construction personnel and identifying the risk area; Risk assessment of the construction site is an important link to ensure construction safety and quality control. Generally, there are many uncontrollable factors during construction, such as changes in construction environment, equipment failure or construction personnel error, which may increase the risk of construction. Therefore, in order to identify and respond to these risks in a timely manner, the present application monitors various risks during construction through a real-time risk assessment mechanism. Once the risk assessment value exceeds the set threshold, the system will automatically trigger the early warning mechanism, timely feedback to the construction personnel and identify the high-risk area, so as to ensure the construction safety.

[0064] In this embodiment, the risk assessment value is mainly based on the evaluation indicators discussed earlier, including installation accuracy, stress condition, and environmental impact parameters, etc. When the real-time construction risk assessment value exceeds the set threshold, the system will start the early warning mechanism and provide real-time feedback. Generally, the calculation process of the risk assessment value is based on the dynamically updated BIM model, combined with real-time data feedback, to assess the safety of the current construction state. The set risk threshold is determined by the safety requirements of different construction stages, usually set through historical data analysis and engineering experience.

[0065] In some embodiments, when the real-time risk assessment value exceeds the set threshold, the system first compares and judges the risk value. Specifically, let the real-time assessment value be R current , and the set threshold be R threshold , if: R current >R threshold ; the early warning mechanism is triggered. At this time, the system generates an early warning report indicating the specific risk type and risk area, and timely transmits it to the terminal device of the construction personnel, such as a mobile phone or tablet. Generally, the risk assessment value includes the weighted average of various indicators, such as installation accuracy, stress condition, and environmental impact. As an option, the weighted coefficient of installation accuracy is α1, the weighted coefficient of stress condition is α2, and the weighted coefficient of environmental impact is α3, then the overall risk assessment value calculation formula is: R current = α1 × R precision + α2 × R stress + α3 × R environment ; where: R current is the real-time calculated construction risk assessment value; R precision is the installation accuracy assessment value; R stress is the stress condition assessment value; R environment is the environmental impact assessment value; α1, α2, α3 are the weight coefficients of each indicator.

[0066] Specifically, when the real-time risk assessment value exceeds the set threshold, the system identifies the risk area through the BIM model. Generally, the risk area will be displayed in different colors or symbols in the BIM model, making it easy for construction personnel to intuitively identify high-risk areas. As an option, the identification of risk areas can be based on risk types. For example, installation accuracy problems may be identified as red, stress abnormalities may be identified as orange, and environmental factors may be identified as yellow. The system will automatically select the most appropriate identification method based on the specific conditions of the construction site.

[0067] In one possible implementation, the system can also automatically push relevant corrective action suggestions. For example, when an abnormal stress value exceeds a set threshold, the system not only identifies the area with excessive stress but also recommends reinforcement measures, such as adding supports or adjusting construction methods. Typically, these corrective actions are automatically generated based on construction processes and safety standards. For changes in environmental factors, such as excessive wind speed or abnormal temperature, the system will also automatically recommend suspending high-risk operations until environmental conditions return to normal.

[0068] Alternatively, the early warning mechanism can be triggered not only within localized risks at the construction site but also encompasses a systematic risk assessment throughout the entire construction process. Once construction risk exceeds a set threshold, the system conducts a multi-dimensional global assessment, analyzing the risk profile at each construction stage. This comprehensive analysis allows construction managers to proactively identify potential risk trends and make timely adjustments to the construction plan, effectively mitigating overall risk.

[0069] In some embodiments, warning information can also be delivered to construction personnel via various communication methods. For example, text messages, emails, instant messages, and other methods can be used to provide feedback, ensuring timely delivery and response. Generally, the choice of communication method can be dynamically adjusted based on on-site construction conditions and the equipment available to construction personnel, ensuring that warning information is delivered without delay.

[0070] S6. Correct deviations in the construction process and update the BIM model through real-time feedback of early warning information.

[0071] The implementation of a real-time early warning mechanism aims to promptly detect deviations during the construction process and implement effective corrective measures. This process relies closely on the aforementioned construction risk assessment system. Real-time early warning feedback enables a rapid response to errors and discrepancies that arise during construction. Generally, when the real-time construction risk assessment exceeds a set threshold, the system automatically triggers an early warning and provides feedback to construction personnel. At this point, construction personnel adjust the construction process based on the early warning information, effectively correcting any deviations. The corrected data is then updated in real time into the BIM model, ensuring that the model is consistent with the actual construction status.

[0072] In this embodiment, through the real-time feedback of warning information, construction personnel can take corresponding adjustment measures according to the specific risk type. For example, if a deviation in installation accuracy is detected during the construction process, the warning information will indicate the deviation location and magnitude, and provide specific correction suggestions. In general, the deviation in installation accuracy can be calculated by comparing the BIM model with the real-time measurement data. If the set accuracy threshold is δ threshold , while the actual measured deviation is δ actual , then when: δ actual >δ threshold ; The system triggers an early warning and feeds back to the construction personnel. Specifically, the construction personnel can make adjustments on site according to the early warning information to ensure that the installation precision meets the design requirements.

[0073] As an option, the deviation correction is updated to the BIM model through real-time data. For example, the corrected component installation position coordinates are set as (x new ,y new ,z new ), at this time, the system automatically updates the coordinate information of the component in the BIM model to ensure that the model reflects the latest construction state. Generally, the updated BIM model is rechecked to ensure that the corrected coordinates are consistent with the connection relationship of the surrounding components, thereby avoiding introducing new deviations.

[0074] In some embodiments, the correction of the deviation is not only the coordinate update, but also the correction of the stress state. Generally, the stress state deviation can be compared with the finite element analysis (FEA) result to determine whether the component is within the normal stress range. If the stress deviation exceeds the set threshold, the system will propose a reinforcement or adjustment scheme according to the calculation result. Suppose the theoretical stress of the component is F theory , and the actual measured stress is F actual , if: F actual >F theory ; a reinforcement suggestion will be triggered, and the system will feed back to the construction personnel and update the corrected stress distribution according to the BIM model to adjust the related support or stress transmission path.

[0075] Specifically, the information after the construction deviation correction is also fed back to the overall construction management platform to ensure that other departments and management personnel can timely understand the construction progress and adjustment. In one possible implementation, the construction management platform can receive the corrected BIM model data in real time through the cloud synchronization function, and perform data analysis to further optimize the construction scheme, identify possible risks in advance, and ensure the coordination of various indicators in the construction process.

[0076] As an option, the BIM model after the deviation correction can be displayed through a visualization tool, so that the construction personnel and management personnel can intuitively see the difference between the construction state and the model and make targeted adjustments. For example, by using virtual reality (VR) technology, construction personnel can view the corrected construction state in a virtual environment to further confirm the adjustment effect and reduce uncertainty in actual construction.

[0077] The BIM model dynamic updating driven steel structure construction real-time accurate early warning system described below can be correspondingly referred to the BIM model dynamic updating driven steel structure construction real-time accurate early warning method described above.

[0078] Please refer to the attached Figure 2 The application also provides a BIM model dynamic updating driven steel structure construction real-time accurate early warning system, comprising: A data acquisition unit acquires various data of the construction site through a sensor array, the various data including actual size, installation position, stress and strain, temperature and humidity data, and sends the acquired various data to a data processing unit, the sensor array including a stress sensor, a displacement sensor, a temperature and humidity sensor and a vibration sensor; A three-dimensional scanning unit connected with the data acquisition unit is used to obtain point cloud data of the construction area through a three-dimensional laser scanner, and combines with the various data of the data acquisition unit to form complete information of the construction site; A data processing unit connected with the data acquisition unit and the three-dimensional scanning unit is used to receive and fuse the various data from the data acquisition unit and the point cloud data from the three-dimensional scanning unit, extract image information of the site construction, compare the original data in the BIM model, calculate the construction error, and dynamically update the BIM model; A risk assessment unit connected with the data processing unit is used to perform risk analysis on the construction state based on the dynamically updated BIM model data and the risk assessment index specific to the construction stage, and perform early warning judgment according to the set risk threshold; an early warning mechanism unit connected with the risk assessment unit sends risk early warning information to the terminal device of the construction personnel when the risk assessment unit detects that the real-time risk value exceeds the preset threshold, highlights the risk area in the BIM model, and provides risk level information and suggested countermeasures; A feedback correction unit connected with the early warning mechanism unit adjusts the construction process and corrects the construction parameters according to the feedback information of the construction personnel, and returns the correction data to the data processing unit to synchronize the BIM model update.

[0079] The system of the embodiment can be used to execute the method embodiments, and the principles and technical effects are similar, which will not be repeated here.

[0080] Although the embodiments of the application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the application, and the scope of the application is defined by the appended claims and their equivalents.

Claims

1. A real-time and accurate early warning method for steel structure construction driven by dynamic updating of BIM models, characterized by: The following steps are involved: Deploy a sensor array at the construction site to collect various data about the steel structure, including actual size, installation location, stress and strain, temperature, and humidity data; Capture various data of the construction area through 3D laser scanners and image recognition technology, and compare and analyze them with the BIM model; Automatically update the BIM model based on captured data and 3D scanning data to dynamically reflect the current construction status; Based on specific risk assessment indicators at the construction stage, risk assessment thresholds are set for different construction stages, and construction risks are assessed in real time through a dynamically updated BIM model. The risk assessment indicators include installation accuracy, stress conditions, and environmental impact parameters. When the real-time construction risk assessment value exceeds the set threshold, the early warning mechanism is triggered, and real-time feedback is provided to construction personnel and risk areas are identified; Through real-time feedback of early warning information, deviations in the construction process can be corrected and the BIM model can be updated.

2. The real-time and accurate early warning method for steel structure construction driven by dynamic update of BIM model according to claim 1 is characterized in that: The sensor array comprises: Stress and strain sensors are used to measure the stress changes of steel structure components during construction and to determine whether overload and abnormal stress conditions occur; Displacement sensors are used to monitor the installation offset of steel structure components and compare and analyze them with the design data in the BIM model; Temperature and humidity sensors are used to measure environmental parameters at the construction site and analyze the impact of environmental factors on construction quality and structural stability in combination with BIM models; Vibration sensors are used to detect vibrations during construction and, combined with BIM models, to assess the impact of vibrations on the stability of steel structures.

3. The real-time and accurate early warning method for steel structure construction driven by dynamic update of BIM model according to claim 1 is characterized in that: The three-dimensional laser scanner and image recognition technology include: 3D laser scanning is used to generate point cloud data of the construction area and compare it with the BIM model to determine installation accuracy; Image recognition technology, based on deep learning algorithms, analyzes construction images to identify component deviations and anomalies; Fusion analysis combines 3D laser scanning and image recognition data to calculate the deviation between on-site construction and the BIM model and provide adjustment suggestions.

4. The real-time and accurate early warning method for steel structure construction driven by dynamic update of BIM model according to claim 1 is characterized in that: The dynamic update of the BIM model includes: Collect data from the construction site and transmit the data to the BIM model data processing system; Calculate the deviation between data and design parameters and identify installation errors, abnormal stress and environmental influences; Adopt adaptive adjustment algorithms to modify BIM models and optimize update strategies based on historical data; Provide construction adjustment suggestions based on the revised BIM model, generate optimization plans, and guide construction personnel to make adjustments.

5. The real-time and accurate early warning method for steel structure construction driven by dynamic update of BIM model according to claim 1 is characterized in that: The risk assessment indicators include: Installation accuracy index, used to measure the installation deviation of steel structure components, and calculates the difference between the actual position and the designed position based on 3D scanning data and sensor data; Stress condition indicators: Analyze the stress state of components based on data from stress and strain sensors to determine whether there is a risk of overload and structural deformation; Environmental impact parameters: Use temperature, humidity, and vibration sensors to analyze the impact of the external environment on the construction quality and stability of steel structures, and combine BIM models to predict hidden dangers caused by environmental factors; The dynamic weight adjustment mechanism dynamically adjusts the weights of various risk assessment indicators according to the construction stage and specific component type to adapt to the risk judgment needs under different construction conditions.

6. The real-time and accurate early warning method for steel structure construction driven by dynamic update of BIM model according to claim 1 is characterized in that: The early warning mechanism includes: Risk identification and classification: Based on the calculation results of the risk assessment unit, construction risks are classified and response strategies for different risk levels are set; Real-time warning push: when the risk value exceeds the set threshold, the warning information is sent to the construction workers' smart terminal devices via wireless communication, and the risk area is highlighted in the BIM model; Multi-level early warning methods, including visual alarm, sound prompt and remote notification; Feedback mechanism: after receiving an early warning, construction personnel can confirm the risk handling status through mobile terminals and send the adjusted data back to the BIM model for synchronous update to optimize the subsequent construction process.

7. The real-time and accurate early warning method for steel structure construction driven by dynamic update of BIM model according to claim 4 is characterized in that: The data transmission includes: Multi-source data fusion transmission: sensor data, 3D scanning data, and image recognition data are transmitted to the BIM model data processing system in real time via wireless networks, fiber optic communications, or industrial Internet protocols; Edge computing and cloud computing work together to deploy edge computing equipment at the construction site to preliminarily screen and compress the data collected by sensors, while uploading key data to the cloud BIM platform; Data encryption and authority management: data encryption technology is used to ensure data transmission security, and data access scope is set according to the authority level of construction personnel; Data synchronization and update mechanism: when the construction site data is uploaded to the BIM model, the system automatically verifies the data integrity, updates the BIM model in real time, and simultaneously displays the latest construction status and adjustment suggestions on the construction personnel's terminal devices.

8. The real-time and accurate early warning method for steel structure construction driven by dynamic update of BIM model according to claim 6 is characterized in that: The risk areas include: Structural installation deviation risk area: When the installation position deviation of steel structure components exceeds the set threshold, the system highlights the deviation area in the BIM model and provides correction suggestions; Abnormal stress risk areas: When the stress and strain sensor detects that the steel structure components are overloaded, stressed or deformed, it automatically identifies the abnormal stress components and marks the risk location in the BIM model.

9. The real-time and accurate early warning method for steel structure construction driven by dynamic update of BIM model according to claim 6 is characterized in that: The construction adjustments include: Automatic adjustment mechanism, based on the construction deviation information provided by the BIM model, automatically generates adjustment suggestions and guides construction equipment to make precise adjustments; Manual intervention correction: Construction personnel manually adjust the component installation method through smart terminals and on-site measurement tools based on the provided construction deviation analysis and correction suggestions, and upload the new construction data to the BIM model after adjustment to keep it dynamically consistent.

10. A real-time and accurate early warning system for steel structure construction driven by dynamic updating of a BIM model, a real-time and accurate early warning method for steel structure construction driven by dynamic updating of a BIM model according to any one of claims 1 to 9, characterized in that: include: A data acquisition unit collects various data from the construction site through a sensor array, including actual size, installation position, stress and strain, temperature and humidity data, and sends the collected data to a data processing unit. The sensor array includes stress sensors, displacement sensors, temperature and humidity sensors, and vibration sensors; The 3D scanning unit is connected to the data acquisition unit and is used to obtain point cloud data of the construction area through a 3D laser scanner and combine it with various data from the data acquisition unit to form complete information of the construction site; The data processing unit is connected to the data acquisition unit and the 3D scanning unit respectively, and is used to receive and fuse various data from the data acquisition unit and the point cloud data from the 3D scanning unit, and at the same time extract image information of the on-site construction, compare it with the original data in the BIM model, calculate the construction error, and dynamically update the BIM model; The risk assessment unit is connected to the data processing unit and is used to perform risk analysis on the construction status based on the dynamically updated BIM model data and the risk assessment indicators specific to the construction stage, and to make early warning judgments based on the set risk thresholds; The early warning mechanism unit is connected to the risk assessment unit. When the risk assessment unit detects that the real-time risk value exceeds the preset threshold, it sends a risk warning message to the terminal device of the construction personnel, highlights the risk area in the BIM model, and provides risk level information and recommended response measures; The feedback correction unit is connected to the early warning mechanism unit. It adjusts the construction process and corrects the construction parameters according to the feedback information of the construction personnel, and returns the corrected data to the data processing unit to synchronize the update of the BIM model.

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