Bridge construction state monitoring method and system based on BIM

Abstract

The invention provides a BIM-based bridge construction state monitoring method and system, and the method comprises the steps: firstly obtaining a physical monitoring data set collected by a plurality of monitoring nodes in real time in bridge construction, carrying out the dynamic data mapping of the physical monitoring data set and a pre-constructed BIM model, and generating a monitoring association data set; the BIM model is subjected to structural difference analysis based on the set, a structural difference index set of all construction units is obtained, then a construction state adjustment strategy set containing a construction parameter correction instruction and a construction resource allocation instruction is generated according to the structural difference index set, and finally the construction state adjustment strategy set is fed back to the construction control terminal. And a monitoring association data set of the BIM model is updated according to an execution result, so that real-time monitoring and dynamic adjustment of the construction state are realized, and the bridge construction quality and efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of building information models, and more particularly, to a method and system for monitoring the construction status of bridges based on BIM. Background Art

[0002] In the field of bridge engineering construction, accurate monitoring of the construction status is crucial for ensuring the quality of bridge construction, ensuring construction safety, and improving construction efficiency. In traditional bridge construction monitoring methods, construction workers mainly rely on manual inspections to monitor the bridge construction status. This method is not only inefficient but also greatly affected by human factors, making it difficult to ensure the accuracy and timeliness of the monitoring results. Manual inspections cannot achieve real-time monitoring, and it may not be possible to detect some sudden and subtle changes in a timely manner, easily leading to the accumulation of potential safety hazards.

[0003] With the development of related technologies, some automated monitoring devices have gradually been applied to bridge construction monitoring. These automated monitoring devices can collect some physical data, such as stress, displacement, etc. However, these monitoring data often exist in isolation and lack effective integration and analysis. It is difficult for construction workers to comprehensively and intuitively understand the actual status of the entire bridge construction from a large amount of scattered data, and thus it is impossible to make accurate decisions in a timely manner.

[0004] At the same time, most of the existing monitoring methods only simply monitor the construction status and record data, without effectively combining with the design model of the bridge. During the construction process, if there are situations that do not conform to the design scheme, it is very difficult to quickly analyze the problems and formulate corresponding adjustment strategies. Moreover, for the allocation of construction resources and the correction of construction parameters, there is a lack of scientific and systematic methods, and decisions are often made based on experience, resulting in low construction efficiency and serious resource waste. Summary of the Invention

[0005] In view of the above-mentioned problems, in combination with the first aspect of the present invention, embodiments of the present invention provide a method for monitoring the construction status of bridges based on BIM, the method comprising: Obtaining a set of physical monitoring data collected in real time by a plurality of monitoring nodes during the bridge construction process, and performing dynamic data mapping processing on the set of physical monitoring data and a pre-constructed BIM model to generate a set of monitoring associated data of the BIM model; Performing structural difference analysis processing on the BIM model based on the set of monitoring associated data to obtain a set of structural difference indicators for each construction unit in the BIM model; Generating a set of construction status adjustment strategies according to the set of structural difference indicators, the set of construction status adjustment strategies including construction parameter correction instructions and construction resource allocation instructions for the construction unit; Feed back the set of construction status adjustment strategies to the construction control terminal, and update the monitoring association data set of the BIM model based on the execution results of the construction control terminal.

[0006] In a possible implementation manner of the first aspect, the structural difference analysis and processing of the BIM model based on the monitoring association data set to obtain the set of structural difference indicators of each construction unit in the BIM model includes: Extract the actual geometric data set and the actual physical data set of the construction unit from the monitoring association data set, where the actual geometric data set includes the spatial coordinate data, dimension measurement data, and deformation monitoring data of the construction unit, and the actual physical data set includes the stress distribution data, load response data, and material property data of the construction unit; Call the predefined design geometric data set and design physical data set of the construction unit in the BIM model, where the design geometric data set includes the design coordinate data, design dimension data, and deformation allowable threshold of the construction unit, and the design physical data set includes the design stress range, design load standard, and material property standard of the construction unit; Perform item-by-item comparison processing on the actual geometric data set and the design geometric data set to generate the geometric difference indicator set of the construction unit, and the geometric difference indicator set includes the coordinate offset, dimension error value, and deformation overrun value; Perform dynamic matching processing on the actual physical data set and the design physical data set to generate the physical difference indicator set of the construction unit, and the physical difference indicator set includes the stress overrun ratio, load response deviation value, and material property deviation degree; Fuse the geometric difference indicator set and the physical difference indicator set to obtain the structural difference indicator set of the construction unit.

[0007] In a possible implementation manner of the first aspect, the item-by-item comparison processing of the actual geometric data set and the design geometric data set to generate the geometric difference indicator set of the construction unit includes: Extract the spatial coordinate data of the construction unit from the actual geometric data set, and perform three-dimensional coordinate offset calculation on the spatial coordinate data and the design coordinate data to obtain the coordinate offset; Extract the dimension measurement data from the actual geometric data set, and perform difference calculation on the dimension measurement data and the design dimension data to obtain the dimension error value; Extract the deformation monitoring data from the actual geometric data set, and perform interval comparison processing on the deformation monitoring data and the deformation allowable threshold to determine the deformation overrun value in the deformation monitoring data that exceeds the deformation allowable threshold; Perform standardized parameter space conversion processing on the coordinate offset, the dimension error value, and the deformation overrun value respectively to generate the geometric difference index set.

[0008] In a possible implementation manner of the first aspect, the dynamically matching the actual physical data set and the designed physical data set to generate the physical difference index set of the construction unit includes: Extract the stress distribution data from the actual physical data set, compare the maximum stress value in the stress distribution data with the designed stress range, and calculate the stress overrun ratio of the maximum stress value exceeding the designed stress range; Extract the load response data from the actual physical data set, and perform dynamic difference calculation on the load response data and the designed load standard to obtain the load response deviation value; Extract the material property data from the actual physical data set, and calculate the deviation degree of the material property data from the material property standard to obtain the material property deviation degree; Perform standardized parameter space conversion processing on the stress overrun ratio, the load response deviation value, and the material property deviation degree respectively to generate the physical difference index set.

[0009] In a possible implementation manner of the first aspect, the generating the construction state adjustment strategy set according to the structural difference index set includes: Extract the geometric difference index set and the physical difference index set from the structural difference index set, and input the geometric difference index set into a pre-trained construction parameter optimization model to generate a construction parameter correction instruction for the construction unit, where the construction parameter correction instruction includes construction equipment adjustment parameters, construction process optimization sequences, and construction accuracy calibration parameters; Input the physical difference index set into a predefined resource allocation rule library to match and obtain construction resource allocation instructions corresponding to the stress overrun ratio, the load response deviation value, and the material property deviation degree. The construction resource allocation instructions include material supplement types, support structure reinforcement plans, and construction progress adjustment strategies; Perform strategy integration processing on the construction parameter correction instruction and the construction resource allocation instruction to generate the construction state adjustment strategy set.

[0010] In a possible implementation manner of the first aspect, inputting the set of geometric difference indexes into a pre-trained construction parameter optimization model to generate a construction parameter correction instruction for the construction unit includes: Invoking the geometric error analysis module in the construction parameter optimization model, determining the position calibration parameter of the construction equipment based on the coordinate offset, and determining the processing precision adjustment parameter of the construction equipment based on the dimension error value; Invoking the deformation control module in the construction parameter optimization model, generating an optimized construction process sequence according to the deformation exceeding value, where the optimized construction process sequence includes the adjustment of the priority of construction steps, the correction of the construction interval time, and the addition scheme of the temporary support structure; Performing instruction encoding processing on the position calibration parameter, the processing precision adjustment parameter, and the optimized construction process sequence to generate the construction parameter correction instruction.

[0011] In a possible implementation manner of the first aspect, inputting the set of physical difference indexes into a predefined resource allocation rule library to match and obtain a construction resource allocation instruction corresponding to the stress exceeding ratio, the load response deviation value, and the material property deviation degree includes: Matching the material supplement type from the resource allocation rule library according to the stress exceeding ratio, where when the stress exceeding ratio exceeds the first threshold, matching the high-strength material supplement instruction, and when the stress exceeding ratio is lower than the first threshold, matching the local reinforcement material supplement instruction; Matching the support structure reinforcement scheme from the resource allocation rule library according to the load response deviation value, where when the load response deviation value is a positive deviation, matching the lateral support addition instruction, and when the load response deviation value is a negative deviation, matching the longitudinal support enhancement instruction; Matching the construction progress adjustment strategy from the resource allocation rule library according to the material property deviation degree, where when the material property deviation degree exceeds the second threshold, matching the construction progress delay instruction and associating the material re-inspection process, and when the material property deviation degree is lower than the second threshold, matching the construction progress segmented optimization instruction; Performing strategy encapsulation processing on the material supplement type, the support structure reinforcement scheme, and the construction progress adjustment strategy to generate the construction resource allocation instruction.

[0012] In a possible implementation manner of the first aspect, feeding back the set of construction state adjustment strategies to the construction control terminal and updating the monitoring association data set of the BIM model based on the execution result of the construction control terminal includes: Send the construction parameter correction instruction to the construction equipment control terminal, and collect the equipment status data set after the construction equipment control terminal executes the construction parameter correction instruction in real time; Send the construction resource allocation instruction to the resource scheduling terminal, and collect the resource distribution data set after the resource scheduling terminal executes the construction resource allocation instruction in real time; Perform dynamic fusion processing on the equipment status data set and the resource distribution data set to generate a post-execution monitoring data set; Perform incremental update processing on the post-execution monitoring data set and the monitoring association data set of the BIM model to obtain an updated monitoring association data set.

[0013] In a possible implementation manner of the first aspect, the performing dynamic fusion processing on the equipment status data set and the resource distribution data set to generate a post-execution monitoring data set includes: Extract the position calibration execution data, processing precision adjustment data, and construction process execution progress data of the construction equipment from the equipment status data set; Extract the material replenishment position data, support structure reinforcement status data, and construction progress adjustment node data from the resource distribution data set; Perform real-time comparison between the position calibration execution data and the design coordinate data of the BIM model to generate a position calibration feedback index; Perform correlation analysis on the processing precision adjustment data and the dimensional error value to generate a processing precision feedback index; Perform progress matching between the construction process execution progress data and the construction process optimization sequence to generate a process execution feedback index; Perform superposition processing on the material replenishment position data and the material distribution map of the BIM model to generate a material replenishment feedback index; Perform secondary verification on the support structure reinforcement status data and the design load standard to generate a support reinforcement feedback index; Perform dynamic alignment between the construction progress adjustment node data and the construction plan timeline of the BIM model to generate a progress adjustment feedback index; Integrate the position calibration feedback index, the processing precision feedback index, the process execution feedback index, the material replenishment feedback index, the support reinforcement feedback index, and the progress adjustment feedback index to generate the post-execution monitoring data set.

[0014] For example, in a possible implementation of the first aspect, the method of obtaining a set of physical monitoring data collected in real time by multiple monitoring nodes during bridge construction and performing dynamic data mapping processing on the set of physical monitoring data and a pre-constructed BIM model to generate a set of monitoring association data for the BIM model includes: Deploy multiple monitoring nodes at the bridge construction site, where each monitoring node includes a 3D laser scanner, a stress sensor, an inclination sensor, and a displacement meter; Collect a set of surface deformation data of the construction unit in real time through the 3D laser scanner, collect a set of real-time stress data of the construction unit through the stress sensor, collect a set of inclination angle data of the construction unit through the inclination sensor, and collect a set of displacement change data of the construction unit through the displacement meter; Perform timestamp alignment processing on the set of surface deformation data, the set of real-time stress data, the set of inclination angle data, and the set of displacement change data to generate the set of physical monitoring data; Perform spatial coordinate association mapping on each data item in the set of physical monitoring data and the design parameters of the corresponding construction unit in the BIM model to generate the set of monitoring association data, where the set of monitoring association data includes real-time monitoring data dynamically bound to the design coordinates, design stress, and design deformation threshold of the BIM model.

[0015] In another aspect, an embodiment of the present invention further provides a BIM-based bridge construction status monitoring system, including a processor and a machine-readable storage medium. The machine-readable storage medium is connected to the processor. The machine-readable storage medium is used to store programs, instructions, or codes, and the processor is used to execute the programs, instructions, or codes in the machine-readable storage medium to implement the above method.

[0016] Based on the above aspects, in the embodiments of the present invention, by performing dynamic data mapping processing on the set of physical monitoring data collected in real time by multiple monitoring nodes during the bridge construction process and a pre-constructed BIM model, the deep integration of the actual construction physical data and the virtual BIM model is achieved, which can timely and accurately reflect the actual situation during the construction process. Based on this monitoring association data set, structural difference analysis processing is performed on the BIM model, and the set of structural difference indicators for each construction unit is accurately obtained, which can effectively discover the deviation from the expected structure during the construction process. According to these sets of structural difference indicators, a set of construction status adjustment strategies is generated, including construction parameter correction instructions and construction resource allocation instructions. The construction status is optimized and adjusted from two key aspects of construction parameters and resource allocation to ensure that the construction process is more scientific and reasonable. The set of construction status adjustment strategies is fed back to the construction control terminal, and the monitoring association data set of the BIM model is updated according to the execution results, enabling the bridge construction to be optimized in real time and dynamically according to the actual situation, improving the construction quality and efficiency, reducing the construction risk, and reducing the construction cost, realizing the intelligent, precise and efficient management of the bridge construction process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic flowchart of the execution process of the BIM-based bridge construction status monitoring method provided by the embodiments of the present invention.

[0018] Figure 2 It is a schematic diagram of exemplary hardware and software components of the BIM-based bridge construction status monitoring system provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] The present invention will be specifically described below in conjunction with the accompanying drawings of the specification. Figure 1 It is a schematic flowchart of the BIM-based bridge construction status monitoring method provided by an embodiment of the present invention. The BIM-based bridge construction status monitoring method will be introduced in detail below.

[0020] Step S110: Obtain the set of physical monitoring data collected in real time by multiple monitoring nodes during the bridge construction process, and perform dynamic data mapping processing on the set of physical monitoring data and a pre-constructed BIM model to generate the monitoring association data set of the BIM model.

[0021] In the actual scenario of bridge construction status monitoring, in order to comprehensively and accurately obtain the information reflecting the bridge construction situation, a series of orderly operations are required. First, a plurality of monitoring nodes are reasonably deployed at key parts of the bridge construction site, and each monitoring node is equipped with a variety of data collection devices, which can monitor the status of the bridge construction unit from different aspects.

[0022] Step S111: Deploy multiple monitoring nodes at the bridge construction site. Each monitoring node includes a 3D laser scanner, a stress sensor, an inclination sensor, and a displacement meter.

[0023] At the bridge construction site, based on the structural characteristics, construction technology, and monitoring requirements of the bridge, the monitoring nodes are deployed scientifically and reasonably. For example, for large bridges, key areas such as piers and girders that bear loads and undergo deformations should be focused on deploying monitoring nodes. The entire bridge is divided into multiple construction units, and one or more monitoring nodes are set according to the size and complexity of each construction unit. Assuming the bridge is divided into n construction units, and each construction unit is set with an average of m monitoring nodes on average, then the total number of deployed monitoring nodes is n×m. The 3D laser scanner equipped in each monitoring node is used to obtain the surface geometric information of the construction unit, the stress sensor is used to monitor the stress condition borne by the construction unit, the inclination sensor is used to detect the change in the inclination angle of the construction unit, and the displacement meter is used to measure the displacement condition of the construction unit.

[0024] Step S112: Collect the surface deformation data set of the construction unit in real time through the 3D laser scanner, collect the real-time stress data set of the construction unit through the stress sensor, collect the inclination angle data set of the construction unit through the inclination sensor, and collect the displacement change data set of the construction unit through the displacement meter.

[0025] After the monitoring nodes are deployed, each device starts to collect data in real time. The 3D laser scanner scans the surface of the construction unit at a set time interval, and a set of three-dimensional coordinate data is obtained each time. Assuming the first scan is performed at time t1, and the three-dimensional coordinate set of the surface points obtained is P1 = {p11, p12,..., p1x}, where p1i represents the three-dimensional coordinates of the i-th point in the first scan; the second scan is performed at time t2, and the coordinate set obtained is P2 = {p21, p22,..., p2x}. By calculating the coordinate difference of the corresponding points, that is, di = p2i - p1i (i = 1, 2,..., x), the surface deformation data set D = {d1, d2,..., dx} can be obtained.

[0026] The stress sensor uses its internal sensitive element to sense the stress change borne by the construction unit in real time, and converts the stress signal into an electrical signal for output. Assuming the electrical signal data set collected by the stress sensor within a period of time is E = {e1, e2,..., ey}, through the pre-established stress-electrical signal conversion relationship function f(E), the electrical signal data can be converted into the real-time stress data set S = {s1, s2,..., sy}, where si = f(ei) (i = 1, 2,..., y).

[0027] The inclination sensor determines the inclination angle of the construction unit by detecting the components of the gravitational acceleration on different coordinate axes. At each sampling moment, the inclination sensor outputs an inclination angle value. Suppose z samplings are performed within a period of time, and the set of inclination angle data obtained is A = {a1, a2, ..., az}, where ai represents the inclination angle at the i-th sampling.

[0028] The displacement gauge obtains the displacement change of the construction unit by measuring the relative displacement between itself and the construction unit. Suppose the set of displacement data collected by the displacement gauge within a period of time is L = {l1, l2, ..., lw}, where li represents the displacement value at the i-th sampling moment.

[0029] Step S113: Perform timestamp alignment processing on the surface deformation data set, the real-time stress data set, the inclination angle data set, and the displacement change data set to generate the physical monitoring data set.

[0030] Since the data collection frequencies of the various devices may be different and the collection times may also vary, in order to ensure the consistency and accuracy of the data, it is necessary to perform timestamp alignment processing on the collected surface deformation data set, real-time stress data set, inclination angle data set, and displacement change data set. The specific approach is to use a unified time reference as a benchmark, sort the data in each data set in chronological order, and perform data matching at the same time points. For example, suppose the time series corresponding to the data in the surface deformation data set D is TD = {tD1, tD2, ..., tDx}, the time series corresponding to the data in the real-time stress data set S is TS = {tS1, tS2, ..., tSy}, the time series corresponding to the data in the inclination angle data set A is TA = {tA1, tA2, ..., tAz}, and the time series corresponding to the data in the displacement change data set L is TL = {tL1, tL2, ..., tLw}. By comparing these time series, the data at the same time points are found and combined together to form a new data set. If there is no corresponding data in a certain data set at a certain time point, interpolation or other appropriate methods can be used for supplementation. After the timestamp alignment processing, the generated physical monitoring data set M contains data on surface deformation, real-time stress, inclination angle, and displacement change at the same time point.

[0031] Step S114: Perform a spatial coordinate association mapping between each data item in the physical monitoring data set and the design parameters of the corresponding construction unit in the BIM model to generate the monitoring association data set, where the monitoring association data set includes real-time monitoring data dynamically bound to the design coordinates, design stress, and design deformation threshold of the BIM model.

[0032] After obtaining the physical monitoring data set, it is necessary to perform a spatial coordinate association mapping between each data item in it and the design parameters of the corresponding construction unit in the pre-constructed BIM model. The BIM model contains detailed design information of each construction unit of the bridge, such as design coordinates, design stress, design deformation threshold, etc. First, according to the spatial position of the construction unit corresponding to each data item in the physical monitoring data set, find the corresponding design parameters in the BIM model. For example, for a certain data item di in the surface deformation data set, through its corresponding three-dimensional coordinate information, find the design coordinates, design deformation threshold and other parameters of the construction unit corresponding to this coordinate position in the BIM model. Then, associate the data items in the physical monitoring data set with the corresponding design parameters to form a one-to-one correspondence. In this way, the monitoring association data set N is generated, and each data item in it is dynamically bound to parameters such as design coordinates, design stress, and design deformation threshold in the BIM model, which can reflect the difference between the actual state of the construction unit and the design requirements in real time.

[0033] Step S120: Based on the monitoring association data set, perform a structural difference analysis process on the BIM model to obtain a set of structural difference indicators for each construction unit in the BIM model.

[0034] After obtaining the monitoring association data set, it is necessary to further analyze it to find the differences between the actual state and the design state of each construction unit in the BIM model. By deeply mining and analyzing the monitoring association data set, the differences in geometry and physics of each construction unit can be quantified, providing a basis for formulating construction state adjustment strategies in the future.

[0035] Step S121: Extract the actual geometric data set and actual physical data set of the construction unit from the monitoring association data set, where the actual geometric data set includes the spatial coordinate data, dimension measurement data, and deformation monitoring data of the construction unit, and the actual physical data set includes the stress distribution data, load response data, and material property data of the construction unit.

[0036] In the monitored associated data set, it contains real-time monitoring data associated with the design parameters of the BIM model. For structural difference analysis, it is necessary to extract the actual geometric data set and the actual physical data set of the construction unit from it. The actual geometric data set reflects the spatial geometric characteristics of the construction unit. Among them, the spatial coordinate data can be obtained through processing the surface deformation data collected by a three-dimensional laser scanner, which represents the actual position of the construction unit in space; the dimension measurement data can be obtained through analysis and calculation of the three-dimensional laser scan data, which reflects the actual size of the construction unit; the deformation monitoring data directly comes from the surface deformation data collected by the three-dimensional laser scanner, reflecting the shape change of the construction unit. The actual physical data set reflects the physical performance characteristics of the construction unit. The stress distribution data is collected by stress sensors, which describes the stress distribution inside the construction unit; the load response data can be obtained through analysis of the load borne by the construction unit and corresponding data such as stress and displacement, which reflects the response of the construction unit under the action of the load; the material performance data can be obtained through testing and analysis of the materials used in the construction unit, which reflects the actual performance parameters of the materials.

[0037] Step S122: Call the predefined design geometric data set and design physical data set of the construction unit in the BIM model. Among them, the design geometric data set includes the design coordinate data, design dimension data and deformation allowable threshold of the construction unit, and the design physical data set includes the design stress range, design load standard and material performance standard of the construction unit.

[0038] When conducting structural difference analysis, it is necessary to compare the actual data with the design data. Therefore, it is necessary to call the predefined design geometric data set and design physical data set of the construction unit in the BIM model. The design geometric data set is the ideal geometric characteristics of the construction unit determined in the bridge design stage. Among them, the design coordinate data specifies the ideal position of the construction unit in space; the design dimension data clarifies the standard size of the construction unit; the deformation allowable threshold limits the maximum deformation range that the construction unit is allowed to occur under normal use conditions. The design physical data set is the ideal physical performance standard of the construction unit. The design stress range specifies the reasonable range of stress borne by the construction unit under normal working conditions; the design load standard clarifies the design load size that the construction unit should be able to bear; the material performance standard specifies the performance parameters that the materials used in the construction unit should possess.

[0039] Step S123: Perform item-by-item comparison processing on the actual geometric data set and the design geometric data set to generate the geometric difference index set of the construction unit. The geometric difference index set includes the coordinate offset, dimension error value and deformation overrun value.

[0040] To accurately evaluate the difference between the geometric state of the construction unit and the design requirements, it is necessary to compare item by item the actual geometric data set and the design geometric data set. The specific steps are as follows: Step S1231: Extract the spatial coordinate data of the construction unit from the actual geometric data set, and perform three-dimensional coordinate offset calculation on the spatial coordinate data and the design coordinate data to obtain the coordinate offset amount.

[0041] Extract the spatial coordinate data of the construction unit from the actual geometric data set and compare it with the design coordinate data. Assume that the actual spatial coordinate data is Pactual = {pactual1, pactual2,..., pactualn}, and the design coordinate data is Pdesign = {pdesign1, pdesign2,..., pdesignn}. By calculating the difference of the corresponding coordinate points, that is, Δpi = pactuali - pdesigni (i = 1, 2,..., n), the coordinate offset amount set ΔP = {Δp1, Δp2,..., Δpn} can be obtained.

[0042] Step S1232: Extract the dimension measurement data from the actual geometric data set, and perform difference calculation on the dimension measurement data and the design dimension data to obtain the dimension error value.

[0043] Extract the dimension measurement data from the actual geometric data set and compare it with the design dimension data. Assume that the actual dimension measurement data is Dactual = {dactual1, dactual2,..., dactualm}, and the design dimension data is Ddesign = {ddesign1, ddesign2,..., ddesignm}. By calculating the difference, that is, Δdi = dactuali - ddesigni (i = 1, 2,..., m), the dimension error value set ΔD = {Δd1, Δd2,..., Δdm} can be obtained.

[0044] Step S1233: Extract the deformation monitoring data from the actual geometric data set, and perform interval comparison processing on the deformation monitoring data and the deformation allowable threshold to determine the deformation overrun value in the deformation monitoring data that exceeds the deformation allowable threshold.

[0045] Extract deformation monitoring data from the actual geometric data set and compare it with the deformation allowable threshold. Suppose the deformation monitoring data is Factual = {factual1, factual2,..., factualk}, and the deformation allowable threshold is Fthreshold. For each deformation monitoring data item factuali, if factuali > Fthreshold, it is considered that the data item exceeds the deformation allowable threshold and is taken as the deformation overrun value. Through screening, the deformation overrun value set Fexceed = {fexceed1, fexceed2,..., fexceedl} is obtained, where l ≤ k.

[0046] Step S1234: Perform standardized parameter space conversion processing on the coordinate offset, the dimension error value, and the deformation overrun value respectively to generate the geometric difference index set.

[0047] To facilitate the comprehensive analysis and comparison of different types of geometric difference indicators, it is necessary to perform standardized parameter space conversion processing on the coordinate offset, the dimension error value, and the deformation overrun value respectively. Standardization processing can eliminate the dimensional differences between different indicators and make them on the same scale. Suppose the coordinate offset set is ΔP, the dimension error value set is ΔD, and the deformation overrun value set is Fexceed. Through the conventional standardized functions g1(ΔP), g2(ΔD), g3(Fexceed) of related technologies, perform standardized processing on them respectively to obtain the standardized coordinate offset set ΔP' = g1(ΔP), the standardized dimension error value set ΔD' = g2(ΔD), and the standardized deformation overrun value set Fexceed' = g3(Fexceed). Combine these standardized sets together to generate the geometric difference index set G = {ΔP', ΔD', Fexceed'}.

[0048] Step S124: Perform dynamic matching processing on the actual physical data set and the designed physical data set to generate the physical difference index set of the construction unit, and the physical difference index set includes the stress overrun ratio, the load response deviation value, and the material property deviation degree.

[0049] To evaluate the difference between the physical performance of the construction unit and the design requirements, it is necessary to perform dynamic matching processing on the actual physical data set and the designed physical data set. Specifically as follows: Step S1241: Extract the stress distribution data from the actual physical data set, compare the maximum stress value in the stress distribution data with the designed stress range, and calculate the stress overrun ratio of the maximum stress value exceeding the designed stress range.

[0050] Extract the stress distribution data from the actual physical data set and find the maximum stress value among them. Assume the stress distribution data is Sactual = {sactual1, sactual2,..., sactualp}, and the maximum stress value is smax = max(Sactual). The designed stress range is [Smin, Smax]. If smax > Smax, it is considered that the maximum stress value exceeds the designed stress range. By calculating the ratio of the stress value of the exceeded part to the upper limit of the designed stress range, that is, the stress overrun ratio Rstress = (smax - Smax) / Smax (when smax > Smax), when smax ≤ Smax, Rstress = 0.

[0051] Step S1242: Extract the load response data from the actual physical data set, and perform dynamic difference calculation on the load response data and the designed load standard to obtain the load response deviation value.

[0052] Extract the load response data from the actual physical data set and compare it with the designed load standard. Assume the load response data is Lactual = {lactual1, laactual2,..., laactualq}, and the designed load standard is Ldesign. By calculating the difference, that is, Δli = laactuali - Ldesign (i = 1, 2,..., q), the load response deviation value set ΔL = {Δl1, Δl2,..., Δlq} can be obtained.

[0053] Step S1243: Extract the material property data from the actual physical data set, and perform deviation calculation on the material property data and the material property standard to obtain the material property deviation.

[0054] Extract the material property data from the actual physical data set and compare it with the material property standard. Assume the material property data is Mactual = {mactual1, mactual2,..., mactualr}, and the material property standard is Mstandard. By calculating the absolute value of the difference between each material property data item and the material property standard and then taking the average value, that is, the material property deviation Rmaterial = (1 / r)×Σ|mactuali - Mstandard| (i = 1, 2,..., r).

[0055] Step S1244: Perform standardized parameter space conversion processing on the stress overrun ratio, the load response deviation value, and the material property deviation respectively to generate the physical difference index set.

[0056] To facilitate the comprehensive analysis and comparison of different types of physical difference indicators, it is necessary to perform standardized parameter space conversion processing on the stress overrun ratio, load response deviation value, and material property deviation degree respectively. Assume that the stress overrun ratio is Rstress, the set of load response deviation values is ΔL, and the material property deviation degree is Rmaterial. Through the conventional standardized functions h1(Rstress), h2(ΔL), and h3(Rmaterial) of related technologies, perform standardized processing on them respectively, and obtain the standardized stress overrun ratio Rstress' = h1(Rstress), the standardized set of load response deviation values ΔL' = h2(ΔL), and the standardized material property deviation degree Rmaterial' = h3(Rmaterial). Combine these standardized sets together to generate the physical difference indicator set P = {Rstress', ΔL', Rmaterial'}.

[0057] Step S125: Combine the geometric difference indicator set and the physical difference indicator set to obtain the structural difference indicator set of the construction unit.

[0058] To comprehensively reflect the structural difference situation of the construction unit, it is necessary to combine the geometric difference indicator set and the physical difference indicator set. The weighted splicing method can be used to assign different weights to the geometric difference indicator set and the physical difference indicator set respectively, and then splice them together. Assume that the geometric difference indicator set is G, the physical difference indicator set is P, the weight of the geometric difference indicator set is wG, the weight of the physical difference indicator set is wP, and wG + wP = 1. Through weighted splicing, obtain the structural difference indicator set C = (wG × G; wP × P), where ";" is the splicing operation.

[0059] Step S130: Generate a construction state adjustment strategy set according to the structural difference indicator set, and the construction state adjustment strategy set includes construction parameter correction instructions and construction resource allocation instructions for the construction unit.

[0060] After obtaining the structural difference indicator set of the construction unit, it is necessary to generate a corresponding construction state adjustment strategy set according to these difference indicators to ensure that the bridge construction can proceed smoothly according to the design requirements.

[0061] Step S131: Extract the geometric difference indicator set and the physical difference indicator set from the structural difference indicator set, and input the geometric difference indicator set into a pre-trained construction parameter optimization model to generate construction parameter correction instructions for the construction unit, where the construction parameter correction instructions include construction equipment adjustment parameters, construction process optimization sequences, and construction accuracy calibration parameters.

[0062] Separate the geometric difference index set and the physical difference index set from the structural difference index set. Input the geometric difference index set into a pre-trained construction parameter optimization model, which is trained with a large amount of historical construction data and corresponding optimal construction parameters. The construction parameter optimization model contains multiple modules inside and can generate corresponding construction parameter correction instructions according to the input geometric difference index. Specifically, the construction parameter optimization model includes a geometric error analysis module and a deformation control module.

[0063] Step S1311: Invoke the geometric error analysis module in the construction parameter optimization model, determine the position calibration parameters of the construction equipment based on the coordinate offset, and determine the processing precision adjustment parameters of the construction equipment based on the dimensional error value.

[0064] The geometric error analysis module will analyze and process the coordinate offset and dimensional error value in the input geometric difference index set. For the coordinate offset, the model will calculate the position adjustment amount of the construction equipment required to eliminate the coordinate offset, that is, the position calibration parameter, according to the preset algorithms and rules. For example, assuming that the coordinate offset is represented by the vector ΔP, the model will, according to the characteristics of the coordinate system and the operation mode of the construction equipment, obtain the distances that the construction equipment needs to move in each coordinate axis direction through a series of conversions and calculations, and these distance values constitute the position calibration parameter set Pcal = {pcalx, pcaly, pcalz}, where pcalx, pcaly, and pcalz respectively represent the position adjustment amounts in the x, y, and z axis directions.

[0065] For the dimensional error value, the geometric error analysis module will determine the processing precision adjustment parameters of the construction equipment according to the magnitude and direction of the dimensional error. If the dimensional error value is positive, it means that the actual size is larger than the designed size, and the model will calculate the adjustment amount required to reduce the processing precision of the construction equipment; if the dimensional error value is negative, it means that the actual size is smaller than the designed size, and the model will calculate the adjustment amount required to improve the processing precision of the construction equipment. Assuming that the dimensional error value set is ΔD, by analyzing and calculating each dimensional error value, the processing precision adjustment parameter set Aadj = {aadj1, aadj2,..., aadjm} is obtained, where aadji represents the processing precision adjustment amount corresponding to the i-th dimensional error value.

[0066] Step S1312: Invoke the deformation control module in the construction parameter optimization model, generate an optimized construction process sequence according to the deformation exceeding limit value, and the optimized construction process sequence includes the adjustment of the priority of construction steps, the correction of construction interval time, and the addition plan of temporary support structures.

[0067] The deformation control module generates an optimized construction process sequence based on the deformation exceedance values in the input set of geometric difference indicators. First, the module analyzes the causes and degrees of influence of deformation exceedance, and adjusts the priorities of construction steps according to this information. For example, if the implementation of a certain construction step may further exacerbate the deformation exceedance, the priority of this step will be lowered; conversely, if a step helps to improve the deformation situation, its priority will be raised.

[0068] Meanwhile, the deformation control module corrects the construction interval time according to the deformation exceedance value. If the deformation exceedance is relatively serious, it may be necessary to extend the interval time between some construction steps to allow the structure sufficient time for stress release and stabilization; if the deformation situation is relatively good, the construction interval time can be appropriately shortened to improve construction efficiency.

[0069] In addition, for relatively serious deformation exceedance situations, the deformation control module generates a scheme for adding temporary support structures. This scheme determines the type, quantity, and layout positions of temporary support structures according to the position, size, and direction of the deformation. For example, if the deformation in a certain area is mainly caused by excessive lateral force, it may be recommended to add lateral support structures; if the vertical deformation is excessive, it may be recommended to increase vertical support structures. The finally generated optimized construction process sequence Sopt = {sopt1, sopt2,..., soptn}, where sopti represents a specific optimization and adjustment item in the construction process, such as the adjustment of the priority of construction steps, the correction of construction interval time, or the specific content in the scheme for adding temporary support structures.

[0070] Step S1313: Perform instruction coding processing on the position calibration parameter, the machining accuracy adjustment parameter, and the optimized construction process sequence to generate the construction parameter correction instruction.

[0071] To facilitate the accurate understanding and execution by construction equipment and construction personnel, it is necessary to perform instruction coding processing on the position calibration parameter, the machining accuracy adjustment parameter, and the optimized construction process sequence. Instruction coding processing converts these parameters and sequences into the conventional coding formats in related technologies, and each code corresponds to a specific operation instruction. For example, for the set of position calibration parameters Pcal, each position adjustment amount is encoded into binary or decimal codes according to the set rules; similar coding processing is also performed on the set of machining accuracy adjustment parameters Aadj and the optimized construction process sequence Sopt. Finally, these codes are combined together to generate the construction parameter correction instruction Iparam, and this construction parameter correction instruction can be sent to the construction equipment control terminal and the operation terminal of construction personnel through the data transmission system.

[0072] Step S132: Input the set of physical difference indicators into a predefined resource allocation rule library, and match to obtain a construction resource allocation instruction corresponding to the stress overrun ratio, the load response deviation value, and the material property deviation degree. The construction resource allocation instruction includes a material replenishment type, a support structure reinforcement plan, and a construction progress adjustment strategy.

[0073] A large number of rules and strategies are stored in the predefined resource allocation rule library, which are formulated based on the experience of bridge construction and design requirements. Inputting the set of physical difference indicators into the resource allocation rule library can automatically match the corresponding construction resource allocation instructions according to the stress overrun ratio, the load response deviation value, and the material property deviation degree.

[0074] Step S1321: Match the material replenishment type from the resource allocation rule library according to the stress overrun ratio. Among them, when the stress overrun ratio exceeds the first threshold, match the high-strength material replenishment instruction; when the stress overrun ratio is lower than the first threshold, match the local reinforcement material replenishment instruction.

[0075] The first threshold is set in the resource allocation rule library for the stress overrun ratio. When the stress overrun ratio exceeds the first threshold, it indicates that the stress borne by the current structure exceeds the design allowable range by a large amount, and high-strength materials need to be replenished to improve the bearing capacity of the structure. At this time, the high-strength material replenishment instruction can be matched from the resource allocation rule library, and this high-strength material replenishment instruction will clarify the type, quantity, and specifications of the high-strength materials to be replenished. For example, the high-strength materials may be high-strength steel or high-performance concrete, etc.

[0076] When the stress overrun ratio is lower than the first threshold, it indicates that the stress overrun situation is relatively mild, and only local areas may need to be reinforced. At this time, the local reinforcement material replenishment instruction can be matched, and this reinforcement material replenishment instruction will specify the types of materials required for local reinforcement, such as reinforcement steel plates, carbon fiber cloth, etc., as well as the usage locations and quantities of these materials.

[0077] Step S1322: Match the support structure reinforcement plan from the resource allocation rule library according to the load response deviation value. Among them, when the load response deviation value is a positive deviation, match the transverse support addition instruction; when the load response deviation value is a negative deviation, match the longitudinal support enhancement instruction.

[0078] The load response deviation value reflects the difference between the response of the construction unit under the actual load and the design load standard. When the load response deviation value is a positive deviation, it indicates that the actual load response is greater than the design load standard, which may be caused by excessive lateral force. At this time, the resource allocation rule library will match the instruction to add lateral supports, and this instruction to add lateral supports will detail information such as the type, quantity, and layout position of the lateral support structure to be added to enhance the lateral bearing capacity of the structure.

[0079] When the load response deviation value is a negative deviation, it indicates that the actual load response is less than the design load standard, which may be a problem in the longitudinal force. At this time, the instruction to enhance the longitudinal supports can be matched, and this instruction to enhance the longitudinal supports will clarify the specific measures for enhancing the longitudinal support structure, such as increasing the quantity of longitudinal supports, replacing the longitudinal support material with a higher strength, etc.

[0080] Step S1323: Match the construction progress adjustment strategy from the resource allocation rule library according to the material property deviation degree. Among them, when the material property deviation degree exceeds the second threshold, match the construction progress delay instruction and associate it with the material re-inspection process. When the material property deviation degree is lower than the second threshold, match the construction progress segmented optimization instruction.

[0081] The resource allocation rule library sets a second threshold for the material property deviation degree. When the material property deviation degree exceeds the second threshold, it indicates that the actual performance of the material is quite different from the design standard, which may affect the construction quality and structural safety. At this time, the construction progress delay instruction can be matched and associated with the material re-inspection process. The construction progress delay instruction will require pausing or slowing down the current construction progress to have enough time to re-detect and evaluate the material. The material re-inspection process will clarify information such as the items, methods, and standards of the re-inspection.

[0082] When the material property deviation degree is lower than the second threshold, it indicates that although there are certain deviations in the material performance, they are still within the acceptable range. At this time, the construction progress segmented optimization instruction can be matched, and this construction progress segmented optimization instruction will adjust and optimize the construction progress in segments according to the actual situation of the material performance to improve the construction efficiency and quality.

[0083] Step S1324: Perform strategy encapsulation processing on the material supplement type, the support structure reinforcement plan, and the construction progress adjustment strategy to generate the construction resource allocation instruction.

[0084] To facilitate the allocation and management of construction resources, it is necessary to perform strategy encapsulation on the material replenishment type, the support structure reinforcement plan, and the construction progress adjustment strategy. The strategy encapsulation process will integrate this information into a unified instruction format, which contains detailed information on all aspects of construction resource allocation. For example, the specific contents of the material replenishment type, the support structure reinforcement plan, and the construction progress adjustment strategy will be encoded and combined to generate the construction resource allocation instruction Ires, which can be sent to the corresponding resource management department and construction team through the resource scheduling system.

[0085] Step S133: Perform strategy integration on the construction parameter correction instruction and the construction resource allocation instruction to generate the construction status adjustment strategy set.

[0086] To form a complete construction status adjustment plan, it is necessary to perform strategy integration on the construction parameter correction instruction and the construction resource allocation instruction. The strategy integration process will consider the mutual relationship and synergy between construction parameter correction and resource allocation to ensure the rationality and effectiveness of the adjustment strategy. For example, the correction of construction parameters may affect the resource requirements and allocation methods, and the resource allocation will also have an impact on the execution effect of construction parameters. Through the strategy integration process, the construction parameter correction instruction Iparam and the construction resource allocation instruction Ires are comprehensively analyzed and optimized to generate the construction status adjustment strategy set Sstrategy = {Iparam, Ires}, which contains comprehensive adjustment strategies for construction units.

[0087] Step S140: Feed back the construction status adjustment strategy set to the construction control terminal, and update the monitoring association data set of the BIM model based on the execution result of the construction control terminal.

[0088] After generating the construction status adjustment strategy set, it is necessary to feed it back to the construction control terminal so that construction personnel and equipment can make construction adjustments according to the strategy. At the same time, the monitoring association data set of the BIM model is updated based on the execution result of the construction control terminal to reflect the changes in the construction status in real time.

[0089] Step S141: Send the construction parameter correction instruction to the construction equipment control terminal, and collect the equipment status data set of the construction equipment control terminal after executing the construction parameter correction instruction in real time.

[0090] The construction parameter correction instruction Iparam is sent to the construction equipment control terminal through the data transmission system. The construction equipment control terminal will perform corresponding adjustment operations on the construction equipment according to the content in the instruction, such as adjusting the position of the equipment, the processing accuracy, and the construction process, etc. During the process of the construction equipment executing the instruction, the status data of the equipment will be collected in real time, including information such as the position of the equipment, the running speed, and the processing accuracy. For example, through the sensors installed on the equipment, the position coordinates of the equipment, the motor speed, the tool wear condition, etc. are obtained in real time. These collected data are sorted and summarized to generate the equipment status data set Ddevice = {ddevice1, ddevice2,..., ddevicen}, where ddevicei represents a certain status parameter of the equipment.

[0091] Step S142: Send the construction resource allocation instruction to the resource scheduling terminal, and collect the resource distribution data set after the resource scheduling terminal executes the construction resource allocation instruction in real time.

[0092] The construction resource allocation instruction Ires is sent to the resource scheduling terminal. The resource scheduling terminal will allocate and manage the construction resources according to the content in the instruction, such as replenishing materials, strengthening the support structure, and adjusting the construction progress, etc. During the process of the resource scheduling terminal executing the instruction, the distribution data of the resources will be collected in real time, including information such as the storage location of the materials, the installation status of the support structure, and the completion status of the construction progress. For example, the storage quantity and location information of the materials are obtained through the inventory management system, the reinforcement status data of the support structure are obtained through the on-site monitoring equipment, and the actual completion status of the construction progress is obtained through the progress management system. These collected data are sorted and summarized to generate the resource distribution data set Dresource = {dresource1, dresource2,..., dresourcem}, where dresourcei represents a certain distribution parameter of the resources.

[0093] Step S143: Perform dynamic fusion processing on the equipment status data set and the resource distribution data set to generate the post-execution monitoring data set.

[0094] In order to comprehensively understand the execution effect of the construction status adjustment strategy, it is necessary to perform dynamic fusion processing on the equipment status data set and the resource distribution data set. Specifically as follows: Step S1431: Extract the position calibration execution data, processing accuracy adjustment data, and construction process execution progress data of the construction equipment from the equipment status data set.

[0095] Filter out the data related to the position calibration, machining precision adjustment, and construction process execution progress of the construction equipment from the device status data set Ddevice. For example, through the data filtering algorithm, extract the actual moving distance and direction data of the equipment during the position calibration process as the position calibration execution data; extract the actual machining error data after the machining precision adjustment of the equipment as the machining precision adjustment data; extract the actual completion time and progress percentage data of the construction process as the construction process execution progress data. Combine these extracted data into the position calibration execution data set Dcal = {dcal1, dcal2,..., dcalp}, the machining precision adjustment data set Dadj = {dadj1, dadj2,..., dadjq}, and the construction process execution progress data set Dproc = {dproc1, dproc2,..., dprocr}.

[0096] Step S1432: Extract the material replenishment position data, support structure reinforcement status data, and construction progress adjustment node data from the resource distribution data set.

[0097] Filter out the data related to the material replenishment position, support structure reinforcement status, and construction progress adjustment node from the resource distribution data set Dresource. For example, through the data filtering algorithm, extract the actual storage position and quantity data of the replenishment materials as the material replenishment position data; extract the actual bearing capacity and stability data after the support structure reinforcement as the support structure reinforcement status data; extract the actual start time and end time data after the construction progress adjustment as the construction progress adjustment node data. Combine these extracted data into the material replenishment position data set Dmat = {dmat1, dmat2,..., dmats}, the support structure reinforcement status data set Dsup = {dsup1, dsup2,..., dsupt}, and the construction progress adjustment node data set Dtime = {dtime1, dtime2,..., dtimeu}.

[0098] Step S1433: Compare the position calibration execution data with the design coordinate data of the BIM model in real time to generate a position calibration feedback index.

[0099] Compare and analyze the position calibration execution data set Dcal with the design coordinate data in the BIM model. By calculating the difference between the position calibration execution data and the design coordinate data, evaluate the execution effect of the position calibration. For example, for each position calibration execution data item dcali, calculate its coordinate difference Δdi = dcali - pdesigni (where pdesigni is the corresponding point in the design coordinate data) with the corresponding point in the design coordinate data. Statistically analyze these differences to generate a position calibration feedback index Fcal, which can reflect the accuracy and deviation degree of the position calibration.

[0100] Step S1434: Perform correlation analysis on the machining precision adjustment data and the dimensional error value to generate a machining precision feedback index.

[0101] Perform correlation analysis on the machining precision adjustment data set Dadj and the dimensional error value set ΔD calculated previously. By comparing the relationship between the data after machining precision adjustment and the dimensional error value, evaluate the effect of the machining precision adjustment. For example, calculate the correlation coefficient between the data after machining precision adjustment and the dimensional error value, or calculate the reduction ratio of the dimensional error after machining precision adjustment, etc. According to these analysis results, generate a machining precision feedback index Fadj, which can reflect the effectiveness and improvement degree of the machining precision adjustment.

[0102] Step S1435: Match the construction process execution progress data with the construction process optimization sequence to generate a process execution feedback index.

[0103] Perform progress matching analysis on the construction process execution progress data set Dproc and the construction process optimization sequence Sopt. Compare the actual execution progress of the construction process with the progress requirements specified in the optimization sequence to evaluate the execution effect of the construction process. For example, calculate the difference between the actual completion time and the time node specified in the optimization sequence, or calculate the difference between the actual completion progress and the progress percentage specified in the optimization sequence, etc. According to these analysis results, generate a process execution feedback index Fproc, which can reflect the timeliness and accuracy of the construction process execution.

[0104] Step S1436: Overlay the material replenishment position data with the material distribution map of the BIM model to generate a material replenishment feedback index.

[0105] Overlay the material replenishment position data set Dmat with the material distribution map in the BIM model. By comparing the actual positions of material replenishment with the positions specified in the material distribution map, evaluate the accuracy and rationality of material replenishment. For example, calculate the distance difference between the material replenishment position and the corresponding position in the material distribution map, or count the coincidence degree between the material replenishment position and the position specified in the material distribution map. According to these analysis results, generate the material replenishment feedback index Fmat, which can reflect the effect and quality of material replenishment.

[0106] Step S1437: Perform a secondary verification on the support structure reinforcement status data and the design load standard to generate a support reinforcement feedback index.

[0107] Perform a secondary verification on the support structure reinforcement status data set Dsup and the design load standard in the BIM model. Evaluate the effect of support structure reinforcement by analyzing whether the actual bearing capacity and stability of the support structure after reinforcement meet the requirements of the design load standard. For example, calculate the ratio of the actual bearing capacity of the support structure after reinforcement to the design load standard, or evaluate the deformation of the support structure under the action of the design load. According to these analysis results, generate the support reinforcement feedback index Fsup, which can reflect the effectiveness and safety of support structure reinforcement.

[0108] Step S1438: Dynamically align the construction progress adjustment node data with the construction plan timeline of the BIM model to generate a progress adjustment feedback index.

[0109] Perform a dynamic alignment analysis on the construction progress adjustment node data set Dtime and the construction plan timeline in the BIM model. Compare the actual time nodes after construction progress adjustment with the time nodes specified in the construction plan timeline to evaluate the effect of construction progress adjustment. For example, calculate the time difference between the actual time node and the planned time node, or count the coincidence degree between the actual time node and the planned time node. According to these analysis results, generate the progress adjustment feedback index Ftime, which can reflect the rationality and effectiveness of construction progress adjustment.

[0110] Step S1439: Integrate the position calibration feedback index, the processing accuracy feedback index, the process execution feedback index, the material replenishment feedback index, the support reinforcement feedback index, and the progress adjustment feedback index to generate the post-execution monitoring data set.

[0111] Integrate the data of the position calibration feedback index Fcal, the processing accuracy feedback index Fadj, the process execution feedback index Fproc, the material replenishment feedback index Fmat, the support reinforcement feedback index Fsup, and the schedule adjustment feedback index Ftime. The weighted splicing method can be used to assign different weights to each feedback index and then splice them together. Suppose the weight of the position calibration feedback index is wcal, the weight of the processing accuracy feedback index is wadj, the weight of the process execution feedback index is wproc, the weight of the material replenishment feedback index is wmat, the weight of the support reinforcement feedback index is wsup, and the weight of the schedule adjustment feedback index is wtime, and wcal + wadj + wproc + wmat + wsup + wtime = 1. Through weighted splicing, the post - execution monitoring data set Dpost = (wcal×Fcal; wadj×Fadj; wproc×Fproc; wmat×Fmat; wsup×Fsup; wtime×Ftime) is obtained.

[0112] Step S144: Perform incremental update processing on the post - execution monitoring data set and the monitoring association data set of the BIM model to obtain an updated monitoring association data set.

[0113] After obtaining the post - execution monitoring data set, it is necessary to perform incremental update processing on it and the existing monitoring association data set of the BIM model to ensure that the BIM model can accurately reflect the latest state of bridge construction in real time. Incremental update processing means only updating the changed data part instead of replacing the entire monitoring association data set, which can improve the efficiency of data update and reduce the workload of data processing.

[0114] First, it is necessary to check the consistency of the data structure and data type between the post - execution monitoring data set and the monitoring association data set of the BIM model. Ensure that the data items in the two data sets have the same meaning and format so that data comparison and update can be accurately carried out. For example, if the position calibration feedback index in the post - execution monitoring data set is represented in the form of coordinate differences, then the corresponding position data in the monitoring association data set of the BIM model should also be able to be effectively compared and updated with it.

[0115] Next, perform a data comparison operation. Each data item in the post-execution monitoring data set is compared one by one with the corresponding data item in the monitoring associated data set of the BIM model. The purpose of the comparison is to identify data items that have changed, which may be caused by the execution of the construction status adjustment strategy. For example, by comparing the position calibration feedback index in the post-execution monitoring data set with the construction unit position data in the BIM model, it is determined whether the position has changed; by comparing the processing accuracy feedback index with the dimension-related data in the model, it is determined whether the processing accuracy has been adjusted, etc.

[0116] For the data changes found during the comparison process, corresponding update operations are performed. The update operations will be processed differently according to the specific type and change situation of the data. For example, if it is numerical data such as stress value, displacement value, etc., the old value in the monitoring associated data set of the BIM model is directly replaced with the new value in the post-execution monitoring data set; if it is status data such as the completion status of the construction process, the reinforcement status of the support structure, etc., it is updated according to the new status information.

[0117] During the update process, the relevance and consistency of the data also need to be considered. There may be interrelated relationships between certain data items. For example, the change in the position of a construction unit may affect the stress distribution and load response of its surrounding units. Therefore, when updating a data item, the associated data items need to be adjusted and updated accordingly to ensure the consistency and accuracy of the entire monitoring associated data set.

[0118] At the same time, in order to facilitate the traceability and management of the data update process, detailed information about each update needs to be recorded, including the update time, the updated data item, the reason for the update, etc. These recorded information can be stored in a special data log for subsequent query and analysis.

[0119] After the above incremental update process, an updated monitoring associated data set is obtained. This new monitoring associated data set contains the latest status information of the bridge construction after the execution of the construction status adjustment strategy, providing an accurate data basis for subsequent further structural difference analysis and construction status adjustment.

[0120] To sum up, the entire BIM-based bridge construction status monitoring method forms a closed-loop monitoring and adjustment system through a series of orderly steps, from data collection, analysis to strategy generation and feedback update. By continuously obtaining real-time data, analyzing structural differences, generating adjustment strategies and updating monitoring data, problems existing in the bridge construction process can be timely discovered and effective measures can be taken for adjustment to ensure that the bridge construction can proceed smoothly according to the design requirements, improving the construction quality and safety.

[0121] In addition, regarding the construction and training of the pre-trained construction parameter optimization model, its necessary modules, levels, and connection relationships are as follows: The construction parameter optimization model mainly includes an input layer, a geometric error analysis module, a deformation control module, and an output layer. The input layer is responsible for receiving the set of geometric difference indicators and passing them to the subsequent processing modules. The geometric error analysis module and the deformation control module are the core processing parts of the model. They respectively analyze and process different types of geometric difference indicators to generate corresponding construction parameter correction information. The output layer then integrates these correction information and outputs them as construction parameter correction instructions.

[0122] In terms of levels, the input layer is directly connected to the geometric error analysis module and the deformation control module, and passes the input data to these two modules respectively. There may be certain information interaction between the geometric error analysis module and the deformation control module to ensure the rationality and consistency of the generated construction parameter correction information. Finally, the output results of these two modules are aggregated to the output layer, and the output layer generates the final instructions.

[0123] The specific steps for training this construction parameter optimization model are as follows: Step S210: Collect training sample data. The training sample data is historical bridge construction data, including geometric difference indicator data and corresponding optimal construction parameter data during the construction process. These data can come from multiple different bridge construction projects to ensure the diversity and representativeness of the data.

[0124] Step S220: Clean and sort the training sample data, removing the noise data and outliers therein. At the same time, perform standardization processing on the training sample data to unify different types of geometric difference indicators and construction parameter data into the same scale range, so that the model can better learn and process these data.

[0125] Step S230: Retrieve the model architecture and initial parameters of this construction parameter optimization model, and initialize the construction parameter optimization model. The selection of the model architecture of this construction parameter optimization model needs to be reasonably designed according to the characteristics of the data and the requirements of the task to ensure that this construction parameter optimization model can effectively process the input data and generate accurate output results.

[0126] Step S240: Divide the preprocessed training sample data into a training set and a validation set, and use the training set to train the construction parameter optimization model. During the training process, by continuously adjusting the parameters of the construction parameter optimization model, the error between the output result of the construction parameter optimization model and the actual optimal construction parameter data is minimized. Optimization algorithms such as gradient descent can be used to update the parameters of the model.

[0127] Step S250: Use the validation set to evaluate the trained construction parameter optimization model, evaluate the performance and accuracy of the model. The evaluation metrics can include error rate, accuracy, etc. If the performance of the construction parameter optimization model does not meet the requirements, return to Step S230, adjust the architecture or parameters of the model, and retrain.

[0128] Step S260: When the performance of the construction parameter optimization model reaches a satisfactory level, deploy it to the actual bridge construction status monitoring system for real-time generation of construction parameter correction instructions.

[0129] Throughout the process, for data collection involved, especially the collection of physical monitoring data sets, attention should be paid to the protection of privacy-sensitive data. Since the main data collected in this scenario is the physical state data of bridge construction units, it generally does not involve sensitive information such as personal privacy. However, if some device identification information or other potential sensitive data may be involved in the data collection process, encryption technology needs to be used to encrypt this data. For example, use a symmetric encryption algorithm to encrypt the data, and only authorized devices and personnel can decrypt and access this data. At the same time, during the data transmission process, use a secure transmission protocol, such as the SSL / TLS protocol, to ensure the security of data transmission and prevent data from being stolen or tampered with. In terms of data storage, store the data on a secure server and set strict access control permissions, and only personnel with corresponding permissions can access and process this data. Through these technical means, the security of privacy-sensitive data can be effectively protected and data leakage can be prevented.

[0130] Figure 2 FIG. shows a schematic diagram of exemplary hardware and software components of a BIM-based bridge construction status monitoring system 100 that can implement the idea of the present application provided by some embodiments of the present application. For example, the processor 120 can be used on the BIM-based bridge construction status monitoring system 100 and is used to execute the functions in the present application.

[0131] The BIM-based bridge construction status monitoring system 100 can be a general-purpose server or a special-purpose server, both of which can be used to implement the BIM-based bridge construction status monitoring method of the present application. Although only one server is shown in the present application, for convenience, the functions described in the present application can be implemented in a distributed manner on multiple similar platforms to balance the processing load.

[0132] For example, the BIM-based bridge construction status monitoring system 100 may include a network port 110 connected to a network, one or more processors 120 for executing program instructions, a communication bus 130, and different forms of storage media 140, such as disks, ROM, or RAM, or any combination thereof. Exemplarily, the BIM-based bridge construction status monitoring system 100 may further include program instructions stored in ROM, RAM, or other types of non-transitory storage media, or any combination thereof. The methods of the present application can be implemented according to these program instructions. The BIM-based bridge construction status monitoring system 100 further includes an I / O interface 150 between the computer and other input / output devices.

[0133] For ease of explanation, only one processor is described in the BIM-based bridge construction status monitoring system 100. However, it should be noted that the BIM-based bridge construction status monitoring system 100 in the present application may further include multiple processors. Therefore, the steps executed by one processor described in the present application may also be jointly executed or separately executed by multiple processors. For example, if the processor of the BIM-based bridge construction status monitoring system 100 executes step A and step B, it should be understood that step A and step B may also be jointly executed by two different processors or separately executed in one processor. For example, the first processor executes step A, the second processor executes step B, or the first processor and the second processor jointly execute steps A and B.

[0134] In addition, an embodiment of the present invention further provides a readable storage medium, in which computer-executable instructions are preset. When the processor executes the computer-executable instructions, the above-mentioned BIM-based bridge construction status monitoring method is implemented.

[0135] It should be noted that, in order to simplify the presentation of the disclosure of the present invention and thus help the understanding of one or more embodiments of the invention, in the foregoing description of the embodiments of the present invention, sometimes multiple features are merged into one embodiment, drawing, or description thereof.

Claims

1. A BIM-based bridge construction status monitoring method, characterized in that, The method includes: Obtaining a set of physical monitoring data collected in real time by multiple monitoring nodes during the bridge construction process, and performing dynamic data mapping processing on the set of physical monitoring data and a pre-constructed BIM model to generate a set of monitoring associated data of the BIM model; Performing structural difference analysis processing on the BIM model based on the set of monitoring associated data to obtain a set of structural difference indicators for each construction unit in the BIM model; Generating a set of construction state adjustment strategies according to the set of structural difference indicators, where the set of construction state adjustment strategies includes construction parameter correction instructions and construction resource allocation instructions for the construction unit; Feeding back the set of construction state adjustment strategies to the construction control terminal, and updating the set of monitoring associated data of the BIM model based on the execution result of the construction control terminal.

2. The BIM-based bridge construction status monitoring method according to claim 1, characterized in that, The performing structural difference analysis processing on the BIM model based on the set of monitoring associated data to obtain a set of structural difference indicators for each construction unit in the BIM model includes: Extracting a set of actual geometric data and a set of actual physical data of the construction unit from the set of monitoring associated data, where the set of actual geometric data includes spatial coordinate data, dimension measurement data and deformation monitoring data of the construction unit, and the set of actual physical data includes stress distribution data, load response data and material property data of the construction unit; Invoking a set of designed geometric data and a set of designed physical data of the construction unit predefined in the BIM model, where the set of designed geometric data includes designed coordinate data, designed dimension data and deformation allowable threshold of the construction unit, and the set of designed physical data includes designed stress range, designed load standard and material property standard of the construction unit; Performing item-by-item comparison processing on the set of actual geometric data and the set of designed geometric data to generate a set of geometric difference indicators of the construction unit, where the set of geometric difference indicators includes coordinate offset, dimension error value and deformation overrun value; Performing dynamic matching processing on the set of actual physical data and the set of designed physical data to generate a set of physical difference indicators of the construction unit, where the set of physical difference indicators includes stress overrun ratio, load response deviation value and material property deviation degree; Performing fusion processing on the set of geometric difference indicators and the set of physical difference indicators to obtain a set of structural difference indicators of the construction unit.

3. The BIM-based bridge construction status monitoring method according to claim 2, characterized in that, The performing item-by-item comparison processing on the set of actual geometric data and the set of designed geometric data to generate a set of geometric difference indicators of the construction unit includes: Extracting the spatial coordinate data of the construction unit from the set of actual geometric data, and performing three-dimensional coordinate offset calculation on the spatial coordinate data and the designed coordinate data to obtain the coordinate offset; Extracting the dimension measurement data from the set of actual geometric data, and performing difference calculation on the dimension measurement data and the designed dimension data to obtain the dimension error value; Extract the deformation monitoring data from the actual geometric data set, and perform interval comparison processing on the deformation monitoring data and the deformation allowable threshold to determine the deformation overrun value in the deformation monitoring data that exceeds the deformation allowable threshold; Perform standardized parameter space conversion processing on the coordinate offset, the dimension error value, and the deformation overrun value respectively to generate the geometric difference index set.

4. The BIM-based bridge construction status monitoring method according to claim 2, characterized in that, The dynamic matching process of the actual physical data set and the designed physical data set to generate the physical difference index set of the construction unit includes: Extract the stress distribution data from the actual physical data set, compare the maximum stress value in the stress distribution data with the designed stress range, and calculate the stress overrun ratio of the maximum stress value exceeding the designed stress range; Extract the load response data from the actual physical data set, and perform dynamic difference calculation on the load response data and the designed load standard to obtain the load response deviation value; Extract the material property data from the actual physical data set, and calculate the deviation degree of the material property data and the material property standard to obtain the material property deviation degree; Perform standardized parameter space conversion processing on the stress overrun ratio, the load response deviation value, and the material property deviation degree respectively to generate the physical difference index set.

5. The BIM-based bridge construction status monitoring method according to claim 2, characterized in that, Generating a construction state adjustment strategy set according to the structural difference index set includes: Extract the geometric difference index set and the physical difference index set from the structural difference index set, and input the geometric difference index set into a pre-trained construction parameter optimization model to generate construction parameter correction instructions for the construction unit, where the construction parameter correction instructions include construction equipment adjustment parameters, construction process optimization sequences, and construction accuracy calibration parameters; Input the physical difference index set into a predefined resource allocation rule library, and match to obtain construction resource allocation instructions corresponding to the stress overrun ratio, the load response deviation value, and the material property deviation degree. The construction resource allocation instructions include material supplement types, support structure reinforcement plans, and construction progress adjustment strategies; Perform strategy integration processing on the construction parameter correction instructions and the construction resource allocation instructions to generate the construction state adjustment strategy set.

6. The BIM-based bridge construction status monitoring method according to claim 5, characterized in that, Inputting the geometric difference index set into a pre-trained construction parameter optimization model to generate construction parameter correction instructions for the construction unit includes: Call the geometric error analysis module in the construction parameter optimization model, determine the position calibration parameters of the construction equipment based on the coordinate offset, and determine the processing accuracy adjustment parameters of the construction equipment based on the dimension error value; Call the deformation control module in the construction parameter optimization model, and generate a construction process optimization sequence according to the deformation overrun value. The construction process optimization sequence includes the adjustment of the priority of construction steps, the correction of construction interval time, and the addition plan of temporary support structures; Perform instruction coding processing on the position calibration parameter, the processing precision adjustment parameter, and the construction process optimization sequence to generate the construction parameter correction instruction.

7. The BIM-based bridge construction status monitoring method according to claim 5, characterized in that,Inputting the set of physical difference indicators into a predefined resource allocation rule library, and matching to obtain a construction resource allocation instruction corresponding to the stress overrun ratio, the load response deviation value, and the material property deviation degree, includes: Matching the material supplement type from the resource allocation rule library according to the stress overrun ratio. Among them, when the stress overrun ratio exceeds the first threshold, match the high-strength material supplement instruction; when the stress overrun ratio is lower than the first threshold, match the local reinforcement material supplement instruction; Matching the support structure reinforcement plan from the resource allocation rule library according to the load response deviation value. Among them, when the load response deviation value is a positive deviation, match the lateral support addition instruction; when the load response deviation value is a negative deviation, match the longitudinal support enhancement instruction; Matching the construction progress adjustment strategy from the resource allocation rule library according to the material property deviation degree. Among them, when the material property deviation degree exceeds the second threshold, match the construction progress delay instruction and associate the material re-inspection process; when the material property deviation degree is lower than the second threshold, match the construction progress segmented optimization instruction; Perform strategy encapsulation processing on the material supplement type, the support structure reinforcement plan, and the construction progress adjustment strategy to generate the construction resource allocation instruction.

8. The BIM-based bridge construction status monitoring method according to claim 5, wherein, Feedback the set of construction state adjustment strategies to the construction control terminal, and update the monitoring correlation data set of the BIM model based on the execution result of the construction control terminal, includes: Send the construction parameter correction instruction to the construction equipment control terminal, and collect the equipment state data set after the construction equipment control terminal executes the construction parameter correction instruction in real time; Send the construction resource allocation instruction to the resource scheduling terminal, and collect the resource distribution data set after the resource scheduling terminal executes the construction resource allocation instruction in real time; Perform dynamic fusion processing on the equipment state data set and the resource distribution data set to generate the post-execution monitoring data set; Perform incremental update processing on the post-execution monitoring data set and the monitoring correlation data set of the BIM model to obtain the updated monitoring correlation data set.

9. The BIM-based bridge construction status monitoring method according to claim 8, wherein, The performing dynamic fusion processing on the equipment state data set and the resource distribution data set to generate the post-execution monitoring data set, includes: Extract the position calibration execution data, the processing precision adjustment data, and the construction process execution progress data of the construction equipment from the equipment state data set; Extract the material supplement position data, the support structure reinforcement state data, and the construction progress adjustment node data from the resource distribution data set; Perform real-time comparison between the position calibration execution data and the design coordinate data of the BIM model to generate a position calibration feedback index; Perform correlation analysis on the processing precision adjustment data and the dimensional error value to generate a processing precision feedback index; Match the progress of the construction process execution data with the optimized sequence of the construction process to generate a process execution feedback index; Overlay the material replenishment position data with the material distribution map of the BIM model to generate a material replenishment feedback index; Perform a secondary verification on the support structure reinforcement status data with the design load standard to generate a support reinforcement feedback index; Dynamically align the construction progress adjustment node data with the construction plan timeline of the BIM model to generate a progress adjustment feedback index; Integrate the position calibration feedback index, the processing accuracy feedback index, the process execution feedback index, the material replenishment feedback index, the support reinforcement feedback index, and the progress adjustment feedback index to generate the post-execution monitoring data set.

10. A BIM-based bridge construction status monitoring system, wherein, It includes a processor and a memory. The memory is connected to the processor. The memory is used to store programs, instructions or codes, and the processor is used to execute the programs, instructions or codes in the memory to implement the BIM-based bridge construction status monitoring method according to any one of claims 1-9 above.

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