Building construction monitoring method and system based on FEA and BIM

Abstract

The invention discloses a building construction monitoring method and system based on FEA and BIM, and relates to the technical field of building construction monitoring, and the method comprises the steps: building a construction disturbance behavior model, achieving the time sequence modeling of a construction process and the generation of a dynamic excitation function, inputting the time sequence modeling and dynamic excitation function into a finite element simulation model, and obtaining the structural response index of each stage; a risk distribution diagram is generated in combination with the BIM, monitoring points are divided, an intelligent sensor network is further arranged to collect structural data, control suggestions are output through trend recognition and a feedback function and are visualized in the BIM, and dynamic closed-loop control of construction monitoring is achieved. The construction disturbance tolerance difference is combined, and the system can output feedback suggestion strength, guide the construction rhythm and load distribution adjustment, so that construction closed-loop control based on risk perception is realized, and the intelligent level and the risk pre-judgment capability of the construction monitoring system are improved.

Description

Technical Field

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

[0002] With the expansion of construction projects and the increasing complexity of structural systems, structural health monitoring (SHM) and building information modeling (BIM) have gradually become important supporting technologies for construction management and safety assurance. Traditional construction monitoring methods rely primarily on manually deployed sensors and static analysis models to observe physical quantities such as stress and displacement in key structural components. However, these methods are mostly post-event responses and lack dynamic coupling with actual construction behavior. In recent years, the application of finite element analysis (FEA) in building simulation has gradually deepened, allowing the mechanical response of structures during the construction phase to be numerically simulated in advance. At the same time, the development of intelligent sensing technology and 5G communications has also provided a technical foundation for the collection and processing of real-time monitoring data, providing a feasible path for digital and intelligent control during the construction process.

[0003] Although the existing monitoring system has initially acquired the capabilities of data collection and structural response assessment, there are still many technical bottlenecks in the actual construction process. First, existing methods fail to input construction behavior as a dynamic variable into the structural simulation model. Construction disturbances are mostly expressed in the form of simplified loads, which cannot reflect the time-varying, fluctuating and equipment cycle excitation characteristics in real working conditions, resulting in large errors in the structural response prediction results. Secondly, the layout of monitoring points still relies mainly on experience or standard templates, lacking intelligent layout control logic driven by simulation data, which can easily lead to blind spots in high-risk areas or waste of resources. At the same time, traditional systems are mostly based on single-point threshold over-limit alarms, lack continuous trend identification of structural health status, and cannot timely identify the evolution of potential risks. In addition, most current construction monitoring systems and BIM platforms are weakly integrated or have one-way visualization, which cannot achieve construction feedback control and decision-making recommendations based on structural evolution trends. In contrast, the present invention realizes closed-loop control of the entire process from construction behavior modeling to construction adjustment strategy push by constructing a five-in-one system architecture of construction disturbance modeling, structural response simulation, intelligent monitoring and control, trend identification and feedback optimization, effectively making up for the shortcomings of existing technologies in prediction accuracy, scientific monitoring and control, trend identification capabilities and BIM response feedback. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present application is that the existing building construction monitoring method has the problems of disturbance of construction behavior, direct analysis of single collection, insufficient accuracy of structure response prediction, lack of data-driven and risk coupling in monitoring point layout, and how to realize visual display and automatic feedback intervention suggestion of construction monitoring results in the BIM system.

[0006] To solve the above technical problems, the present application provides the following technical scheme: a building construction monitoring method based on FEA and BIM, comprising constructing a construction disturbance behavior model, time series modeling of each main working procedure in the construction plan, extracting disturbance types, operation time periods, equipment parameters, and excitation intensity, and establishing a dynamic disturbance input function associated with structural members. Based on the disturbance input function, a finite element analysis model coupled with the structural members is established, the response state of the structure at each stage is simulated, the multi-dimensional response indicators of the members under construction excitation are output, and the structure risk map and the monitoring point division map are generated in the building information model. According to the structure response intensity and spatial position, an intelligent sensor network is laid out, structure data under construction state is collected, a risk trend identification model and a feedback control function are constructed, control suggestions are output and visualized mapping to the BIM model.

[0007] As a preferred scheme of the building construction monitoring method based on FEA and BIM according to the present application, wherein: the construction disturbance behavior model includes constructing a time-varying parameter model based on the time axis of the construction procedure, the equipment operation parameters and the structure action range, expressing the disturbance amplitude, frequency, phase delay, growth trend and attenuation process characteristics, simulating the disturbance behavior of concrete pumping, formwork removal, tower crane rotation, formwork striking, and establishing a data binding relationship with the target member in the three-dimensional building model as the dynamic input boundary of structure simulation.

[0008] As a preferred scheme of the building construction monitoring method based on FEA and BIM according to the present application, wherein: the establishment of the finite element analysis model coupled with the structural members includes using a multi-element mixed modeling method, inputting the construction disturbance function as the structure loading path, combining the member material properties and boundary constraint conditions, simulating the stress distribution and displacement evolution process of the member at each time step, outputting the response history data of the key member, and constructing the structure risk index system and the monitoring priority division basis.

[0009] As a preferred scheme of the building construction monitoring method based on FEA and BIM according to the present application, wherein: the generation of the structure risk map and the monitoring point division map includes normalizing the member response values in the simulation results, superimposing them into the BIM member level, and identifying the high-risk member cluster through a clustering algorithm.

[0010] The system automatically divides the candidate set of monitoring points among the component groups with high response gradient and concentrated distribution, and marks the recommended sensor types and installation locations according to the risk level to form a sensor layout map.

[0011] As a preferred solution of the FEA and BIM-based construction monitoring method described in the present invention, the deployment of the intelligent sensor network based on the structural response intensity and spatial position includes configuring sensors, the sensor types of which are optical fiber strain sensors, displacement meters, inclinometers, temperature and humidity sensors, and groundwater level monitoring modules, and configuring an edge control unit with communication function. The collected data is uploaded to the central platform via NB-IoT and synchronized and visualized in the BIM model in real time.

[0012] As a preferred solution of the FEA and BIM-based construction monitoring method described in the present invention, the risk trend identification model is constructed, which includes constructing a comprehensive trend indicator function including disturbance rate, strain change rate and environmental disturbance factor based on the structural state monitoring time series, identifying the trend of abnormal evolution behavior of the structure under the influence of construction disturbance through sliding window analysis and threshold judgment, and assigning risk level labels to abnormal components or areas.

[0013] As a preferred solution of the FEA and BIM-based construction monitoring method described in the present invention, the feedback control function includes constructing a nonlinear construction recommendation intensity function based on the deviation between the risk trend score and the construction disturbance tolerance, outputting intervention measures such as delaying work, reducing loads, increasing support or local suspension, and graphically marking the recommended intervention measures in the BIM platform and pushing them to the construction scheduling management system through the interface.

[0014] Another object of the present invention is to provide a construction monitoring system based on FEA and BIM, which can solve the problem that the current construction monitoring technology cannot accurately identify the potential evolution risks of the structure and can only rely on passive alarms with fixed thresholds through the constructed structural risk trend identification function.

[0015] As a preferred solution of the FEA and BIM-based construction monitoring system described in the present invention, it includes: a construction disturbance modeling module, a structural response simulation module, and an intelligent monitoring module.

[0016] The construction disturbance modeling module is used to build a construction disturbance behavior model, perform time series modeling on each major process in the construction plan, extract the disturbance type, operation period, equipment parameters, and excitation intensity, and establish a dynamic disturbance input function associated with the structural components.

[0017] The structural response simulation module is used to establish a finite element analysis model coupled with the structural components based on the disturbance input function, simulate the response state of the structure at each stage, output the multi-dimensional response index of the components under construction excitation, and generate a structural risk map and a monitoring point division map in the building information model.

[0018] The intelligent monitoring module is used to deploy an intelligent sensor network based on the structural response intensity and spatial position, collect structural data under construction status, and output control suggestions by constructing a risk trend identification model and feedback control function, and visually map them to the BIM model.

[0019] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a step of a construction monitoring method based on FEA and BIM.

[0020] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a construction monitoring method based on FEA and BIM.

[0021] Beneficial effects of the present invention: The construction monitoring method based on FEA and BIM provided by the present invention converts construction behavior parameters into dynamic disturbance functions by introducing a construction disturbance modeling mechanism, which is used as the input boundary conditions of the structural simulation, thereby significantly improving the authenticity and timing accuracy of the structural response simulation, and constructing a structural risk trend identification function. The function integrates the strain change rate, disturbance excitation fluctuations and environmental factors to achieve dynamic judgment of potential structural risks, and introduces a trend integration mechanism to avoid false alarms. Combined with the differences in construction disturbance tolerances, the system can output feedback suggestion intensity to guide the construction rhythm and load distribution adjustments, thereby realizing risk-awareness-based construction closed-loop control and improving the intelligence level and risk prediction capabilities of the construction monitoring system. The present invention achieves better results in terms of accuracy and monitoring closed loop. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0023] Figure 1 This is an overall flow chart of a construction monitoring method based on FEA and BIM provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0024] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0025] Example 1, reference Figure 1 , as one embodiment of the present invention, provides a construction monitoring method based on FEA and BIM, comprising: S1: Construct a construction disturbance behavior model, perform time series modeling on each major process in the construction plan, extract the disturbance type, operation period, equipment parameters, and excitation intensity, and establish a dynamic disturbance input function associated with the structural components.

[0026] It should be noted that before building the construction disturbance behavior model, data collection was first carried out at the construction site, including architectural design drawings and BIM structural models, the overall construction organization plan and detailed arrangement of each process, the operating frequency, load level, and cycle characteristics of construction equipment, concrete grade, steel type, soil properties, geological conditions, groundwater level, and hydro-meteorological parameters; Real-time sound and vibration data collection is performed simultaneously. Acoustic acquisition units (high-sensitivity MEMS microphones or acoustic array sensors) and distributed fiber optic sensors (Fiber Bragg Gratings (FBGs)) are deployed at the construction site to collect sound and vibration response signals from various processes (concrete pumping, crane operation, formwork tapping, and cutting). Spectral analysis of the acoustic wave data extracts characteristic fingerprints (dominant frequency, peak intensity, harmonic characteristics, and duration) for reverse identification of construction disturbance sources, improving the accuracy and real-time nature of disturbance identification. Distributed fiber optic sensors detect micro-vibration characteristics of structures under construction disturbances by observing changes in the internal reflection spectrum of the optical fiber, thus supplementing the limited spatial coverage of acoustic sensors.

[0027] Furthermore, a construction disturbance behavior model is constructed, and time series modeling of each major process in the construction plan is carried out, including building a time-varying parameter model based on the time axis of the construction process, equipment operating parameters and structural action range to express the disturbance amplitude, frequency, phase delay, growth trend and attenuation process characteristics, which is used to simulate the disturbance behavior of concrete pumping, formwork removal, tower crane rotation, and formwork impact, and establish a data binding relationship with the target component in the three-dimensional building model as the dynamic input boundary of the structural simulation.

[0028] It should be noted that, based on the available architectural design drawings and overall construction plan, we first modeled the key processes throughout the construction process, including but not limited to: excavation, support system construction, pile and foundation preparation, foundation pouring, formwork installation, floor structure erection, and unloading platform installation. These construction processes were discretized chronologically to form a time-labeled construction behavior sequence, thus constructing a construction behavior model with time evolution characteristics.

[0029] To achieve accurate spatial mapping between construction disturbances and structural components and reduce computational pressure, the construction-affected area is meshed. The meshing method is based on the geometric information of the building BIM model and uses the following method: The construction impact area is divided into four zones, with the center as the midpoint and divided in four directions: east, west, south and north. The four zones are calculated simultaneously, and the construction behavior sequence is disassembled into construction behavior nodes.

[0030] In this model, each construction behavior node contains the following parameters: construction start and end time, affected area, disturbance type (including load disturbance, vibration, and position movement), type of construction equipment used, and operation intensity level (quantized into levels 1 to 5), which are used for subsequent disturbance simulation.

[0031] According to the above parameters, define each type of construction disturbance behavior function , which is used to describe the dynamic excitation of structural components by this type of process in the time domain, and is expressed as:

[0032] in, For the The time disturbance intensity function caused by the construction process, is the initial amplitude of the disturbance, is the disturbance frequency, is the initial phase angle of the disturbance, is the stage perturbation growth activation coefficient, is the perturbation gradient intensity parameter, is the activation time of the disturbance phase, is the construction intensity growth slope parameter, is the disturbance peak time position control parameter, For time.

[0033] Perturbation functions are mapped to spatial component objects in the BIM model through component association. Each perturbation function is superimposed on the overall construction schedule model, forming a dynamic perturbation excitation sequence that changes over time. This sequence is input into the finite element modeling platform through an interface and serves as the boundary condition input for structural simulation. It also supports dynamic simulation of the construction plan and identification of perturbation excitation stages.

[0034] It should also be noted that, in the present invention, the structural construction generally includes types of beams, columns, shear walls, floor slabs, support system components, node transition areas, etc.

[0035] Furthermore, establishing a finite element analysis model coupled with structural components involves adopting a multi-unit hybrid modeling approach, inputting a construction disturbance function as the structural loading path, combining component material properties with boundary constraints, simulating the stress distribution and displacement evolution of components at each time step, and outputting historical response data of key components for constructing a structural risk indicator system and a basis for monitoring priority division. The key components are columns, beams, and shear walls.

[0036] It should be noted that after completing the construction behavior model and perturbation function, a finite element structural simulation model incorporating the aforementioned dynamic perturbation input was further constructed. This model analyzes the entire building structure system, encompassing the foundation pit support system, pile foundation system, subgrade, basement structure, upper load-bearing components (including beams, columns, and shear walls), and floor slab system. A hybrid element modeling approach was employed, with structural geometry and material parameters derived from design drawings and actual engineering data.

[0037] In the finite element modeling platform, a three-dimensional structural model is constructed based on the architectural design drawings, using shell elements to simulate floor slabs and walls, beam elements to simulate linear components, and solid elements to simulate foundations and node transition areas.

[0038] Input material parameters for various structural components, including elastic modulus, Poisson's ratio, yield limit, etc. of concrete, steel bars, soil, etc.

[0039] Fixed constraints are set at the bottom of the model, and construction disturbance load input is set at the top. The disturbance value comes from .

[0040] According to the construction behavior time series, the disturbance function is loaded stage by stage in a time stepping manner.

[0041] Select key locations of the structure as output nodes and extract their displacement, stress, strain, shear stress, lateral displacement and other structural response values. For each output node component, define its structural response, expressed as:

[0042] in, Indicates time When, The cumulative strain of a structural component under disturbance excitation, is the Young's modulus of the component, reflecting the difference in stiffness of different materials in response to disturbance rate. is the disturbance function corresponding to the component, the first-order derivative represents the disturbance velocity, and the second-order derivative represents the disturbance surge trend. is the risk amplification factor of the component structure type, It means traversing every moment from 0 to t, is the number of structural components, For is the unit of integration of the variable.

[0043] S2: Based on the perturbation function, a finite element analysis model coupled with the structural components is established to simulate the response state of the structure at each stage, output the multi-dimensional response index of the components under construction excitation, and generate a structural risk map and monitoring point division map in the building information model.

[0044] Furthermore, the generation of structural risk maps and monitoring point division maps includes normalizing the component response values ​​in the simulation results, superimposing them into the BIM component hierarchy, and identifying high-risk component clusters through clustering algorithms.

[0045] The system automatically divides the candidate set of monitoring points among the component groups with high response gradient and concentrated distribution, and marks the recommended sensor types and installation locations according to the risk level to form a sensor layout map.

[0046] It should be noted that after completing the structural finite element simulation, the present invention integrates the output structural response data with the three-dimensional BIM model to achieve visual management of the structural status and scientific layout of monitoring points. First, the response index data of each key structural component, including maximum strain, maximum lateral displacement, maximum shear stress, etc., is extracted and parameter binding relationships are established with the corresponding components in the BIM model. The structural response data is normalized to form a response heat matrix.

[0047] Within the 3D BIM environment, a risk heat map layer was constructed to display component response indicators as hotspots. Colors were mapped to numerical levels, with red, orange, yellow, and blue corresponding to four levels. To further identify high-risk clusters, a cluster analysis method was introduced to spatially cluster component response values. Using the K-means clustering algorithm, high-response areas in the heat map were divided into several cluster centers, and the maximum response point in each cluster center was extracted as a candidate monitoring point location.

[0048] The final monitoring point division results are as follows: Level 1 risk area: The response value is lower than the first level or is located in an area where group operations exist. It is necessary to deploy multi-sensor combination monitoring and all-weather data collection.

[0049] Secondary risk area: The response value is lower than the second level and higher than the first level, or it is an area with concentrated mechanical operations. Displacement and stress sensors are deployed and periodic data feedback is implemented.

[0050] Level 3 risk area: The response value is higher than the second level, but there are historical accident records, and data is collected through inspections.

[0051] Level 4 risk area: The response value is higher than the second level, there is no historical accident record, personnel are self-controlled, and data is collected by inspection.

[0052] The candidate coordinates of each monitoring point, the name of the component where it is located, the response index, and the recommended sensor type are recorded in the monitoring database and displayed synchronously in the BIM model to facilitate subsequent installation personnel to deploy and execute.

[0053] Furthermore, the intelligent sensor network is deployed according to the structural response intensity and spatial position, including the configuration of sensors. The sensor types include optical fiber strain sensors, displacement meters, inclinometers, temperature and humidity sensors, and groundwater level monitoring modules, and an edge control unit with communication function. The collected data is uploaded to the central platform through NB-IoT and synchronized and visualized in the BIM model in real time.

[0054] It should be noted that after the monitoring points are delineated, a structural intelligent monitoring system will be constructed, encompassing a variety of sensor types and deployment methods. The monitoring system design is based on a modular principle, with deployment based on risk levels to ensure monitoring coverage and data accuracy, while minimizing redundant deployments.

[0055] The system sampling frequency is dynamically adjusted according to the risk level: level 1 area ≥10Hz, level 2 area ≥2Hz, and level 3 area is activated on demand.

[0056] After sensor data is uploaded, it enters the structural monitoring database through the data center, where it is used by the subsequent trend identification module. Simultaneously, all monitoring data is mapped in real time on the BIM platform. Each sensor node corresponds to a visual marker in the 3D model. Clicking on it displays its current status data, sampling curve, alarm level, and historical data trajectory.

[0057] Realize high-density, high-precision, partitioned intelligent monitoring of the entire structural construction process, and provide basic support for data-driven intelligent identification and feedback mechanisms.

[0058] S3: Deploy an intelligent sensor network based on the structural response intensity and spatial position to collect structural data under construction. By building a risk trend identification model and feedback control function, control recommendations are output and visually mapped to the BIM model.

[0059] Furthermore, the construction of a risk trend identification model includes constructing a comprehensive trend indicator function based on the structural status monitoring time series, which includes the disturbance rate, strain change rate and environmental disturbance factor. Through sliding window analysis and threshold judgment, the trend of abnormal evolution behavior of the structure under the influence of construction disturbance is identified, and risk level labels are assigned to abnormal components or areas.

[0060] It should be noted that after the structural monitoring system is deployed and operating stably, the present invention constructs a structural response trend analysis model and an abnormal evolution identification mechanism by performing time series processing on the multi-dimensional monitoring data collected by sensors. Monitoring data includes, but is not limited to, structural strain, component displacement, joint angle changes, disturbance excitation levels, construction progress status, and environmental parameters.

[0061] The sliding time window analysis method is used to extract the characteristics of the key indicators such as the rate of change, fluctuation amplitude, and nonlinear mutation in each time interval, and a structural risk trend index function is constructed to quantify the changing trend of the current structural state, which is expressed as:

[0062] in, For the Monitoring points at time Structural risk trend index, is the sliding analysis time window, is the measured strain-time function, is the perturbation function, is the environmental factor response function, is the weighted coefficient of each item, and the sum of the three weighted coefficients is 1. The value range is [0.5,0.8], The value range is [0.15,0.4], The value range is [0.5,0.15].

[0063] Identify whether the trend anomaly is persistent and construct a cumulative trend anomaly integral value function, which is expressed as:

[0064] in, For the Point risk identification threshold, Z is the indicator function, indicating that at the start time To the current moment The cumulative time that the risk trend index exceeds the risk identification threshold.

[0065] This is used to determine whether the structural trend index has entered a potentially abnormal evolutionary state. Based on the high percentile of historical monitoring data, 80% of the high percentile of historical monitoring data is used as the judgment standard for key components or early stages of a project to identify potential hazards in advance.

[0066] If both are satisfied, , and at the same time, if a sudden change in acoustic energy and a rise or fall rate of the vibration signal exceed 5 με / s (a commonly used reference warning value in optical fiber engineering monitoring), the system will determine that there is an abnormal trend in structural evolution at the monitoring point and trigger the next feedback control mechanism. The minimum cumulative duration.

[0067] The sudden change of sound energy is not used as the sole basis for judgment, which can avoid erroneous judgments caused by environmental factors or human interference.

[0068] Furthermore, the feedback control function includes constructing a nonlinear construction recommendation intensity function based on the deviation between the risk trend score and the construction disturbance tolerance, outputting intervention measures such as delaying work, reducing loads, increasing supports or local suspension, and graphically marking the recommended intervention measures in the BIM platform and pushing them to the construction scheduling management system through the interface.

[0069] It should be noted that after the system identifies an abnormal structural evolution trend, the present invention constructs a feedback control suggestion generation model based on the coupling of structural response trends and construction disturbances to guide actual construction rhythm adjustments and operational optimization. Feedback suggestions are output as quantifiable parameters and integrated into the construction management system or scheduling platform through an interface, implementing a closed-loop mechanism of early warning, control, confirmation, and execution.

[0070] The build control recommendation strength is expressed as:

[0071] in, For the Construction control suggestion intensity at monitoring points, is the current risk trend index, The current disturbance level is dynamically read by the construction scheduling system. The perturbation intensity allowed by the simulation is calculated and recorded in advance by the structural finite element simulation system. is the stability coefficient, and its value range is [0.05,0.2]. Activates the slope factor for feedback.

[0072] Example 2 is the second embodiment of the present invention, which is different from the previous embodiment in that: If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0073] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0074] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or processing it in another suitable manner as necessary, and then storing it in a computer memory.

[0075] It should be understood that various components of the present invention may be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods may be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, it may be implemented using a combination of any of the following technologies known in the art: discrete logic circuits having logic gate circuits for implementing logic functions on data signals, application-specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0076] Example 3 is the third embodiment of the present invention. This embodiment provides a system for a construction monitoring method based on FEA and BIM, including a construction disturbance modeling module, a structural response simulation module, and an intelligent monitoring module.

[0077] The construction disturbance modeling module is used to build a construction disturbance behavior model, perform time series modeling on the major processes in the construction plan, extract disturbance types, operation periods, equipment parameters, and excitation intensity, and establish a dynamic disturbance input function associated with the structural components. The structural response simulation module is used to establish a finite element analysis model coupled with the structural components based on the disturbance function, simulate the response state of the structure at each stage, output the multi-dimensional response index of the components under construction excitation, and generate a structural risk map and monitoring point division map in the building information model. The intelligent monitoring module is used to deploy an intelligent sensor network based on the structural response intensity and spatial location, collect structural data under construction, and output control suggestions by constructing a risk trend identification model and feedback control function, and visually map them to the BIM model.

[0078] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A construction monitoring method based on FEA and BIM, characterized in that: include: Construct a construction disturbance behavior model, model the time series of each major process in the construction plan, extract the disturbance type, operation period, equipment parameters, and excitation intensity, and establish a dynamic disturbance input function associated with the structural components; Based on the disturbance input function, a finite element analysis model coupled with the structural components is established to simulate the response state of the structure at each stage, output multi-dimensional response indicators of the components under construction excitation, and generate a structural risk map and a monitoring point division map in the building information model; An intelligent sensor network is deployed based on the structural response intensity and spatial position to collect structural data under construction. By building a risk trend identification model and feedback control function, control recommendations are output and visually mapped to the BIM model.

2. The construction monitoring method based on FEA and BIM according to claim 1, characterized in that: The construction disturbance behavior model is constructed to perform time series modeling on the main processes in the construction plan, including constructing a time-varying parameter model based on the time axis of the construction process, equipment operating parameters and structural action range, expressing the disturbance amplitude, frequency, phase delay, growth trend and attenuation process characteristics, which is used to simulate the disturbance behavior of concrete pumping, formwork removal, tower crane rotation, and formwork impact, and establish a data binding relationship with the target component in the three-dimensional building model as the dynamic input boundary of the structural simulation.

3. The construction monitoring method based on FEA and BIM according to claim 2, characterized in that: The establishment of a finite element analysis model coupled with structural components includes adopting a multi-unit hybrid modeling method, inputting a construction disturbance function as a structural loading path, combining component material properties and boundary constraints, simulating the stress distribution and displacement evolution process of the components at each time step, and outputting response history data of key components.

4. The construction monitoring method based on FEA and BIM according to claim 3, characterized in that: Generating the structural risk map and monitoring point division map includes normalizing component response values ​​in the simulation results, superimposing them into the BIM component hierarchy, and identifying high-risk component clusters through a clustering algorithm; The system automatically divides the candidate set of monitoring points among the component groups with high response gradient and concentrated distribution, and marks the recommended sensor types and installation locations according to the risk level to form a sensor layout map.

5. The construction monitoring method based on FEA and BIM according to claim 4, characterized in that: The deployment of the intelligent sensor network based on the structural response intensity and spatial position includes configuring sensors, the sensor types of which are optical fiber strain sensors, displacement meters, inclinometers, temperature and humidity sensors, and groundwater level monitoring modules, and configuring an edge control unit with communication function. The collected data is uploaded to the central platform via NB-IoT and synchronized and visualized in the BIM model in real time.

6. The construction monitoring method based on FEA and BIM according to claim 5, characterized in that: The risk trend identification model is constructed by constructing a comprehensive trend indicator function including disturbance rate, strain change rate and environmental disturbance factor based on the structural state monitoring time series. Through sliding window analysis and threshold judgment, the trend of abnormal evolution behavior of the structure under the influence of construction disturbance is identified, and risk level labels are assigned to abnormal components and areas.

7. The construction monitoring method based on FEA and BIM according to claim 6, characterized in that: The feedback control function includes constructing a nonlinear construction recommendation intensity function based on the deviation between the risk trend score and the construction disturbance tolerance, outputting intervention measures such as delaying work, reducing loads, increasing supports, and local suspension, and graphically annotating the recommended intervention measures in the BIM platform and pushing them to the construction scheduling management system through an interface.

8. A system using the FEA and BIM-based construction monitoring method according to any one of claims 1 to 7, characterized in that: Including construction disturbance modeling module, structural response simulation module, and intelligent monitoring module; The construction disturbance modeling module is used to build a construction disturbance behavior model, perform time series modeling on each major process in the construction plan, extract the disturbance type, operation period, equipment parameters, and excitation intensity, and establish a dynamic disturbance input function associated with the structural components; The structural response simulation module is used to establish a finite element analysis model coupled with the structural components based on the disturbance input function, simulate the response state of the structure at each stage, output multi-dimensional response indicators of the components under construction excitation, and generate a structural risk map and a monitoring point division map in the building information model; The intelligent monitoring module is used to deploy an intelligent sensor network based on the structural response intensity and spatial position, collect structural data under construction status, and output control suggestions by constructing a risk trend identification model and feedback control function, and visually map them to the BIM model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the construction monitoring method based on FEA and BIM are implemented as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the construction monitoring method based on FEA and BIM are implemented as described in any one of claims 1 to 7.

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