A method and system for monitoring and early warning of the entire construction process of a tensioned timber arch and steel frame hybrid structure.

Abstract

This invention discloses a method and system for monitoring and early warning throughout the construction process of a tensioned timber arch steel frame hybrid structure, relating to the field of large-span building engineering technology. The method includes the following steps: acquiring material characteristic parameters of timber components, structural design parameters, and construction stage information. The material characteristic parameters of the timber components include longitudinal mechanical properties, transverse mechanical properties, mechanical property correction parameters under different moisture content gradients, and mechanical property correction parameters under different temperature gradients. These parameters are obtained using standard specimens of timber components from corresponding tree species. This invention solves the monitoring distortion and staged simulation deviations caused by anisotropy through timber component material testing and a cumulative benchmark model covering all construction stages. It establishes a hierarchical early warning and prediction mechanism to achieve accurate risk identification and trend prediction. Combined with edge computing and digital twin collaborative operation, it completes the closed-loop management of the entire process of data acquisition, early warning, and evolutionary prediction, providing a reliable solution for the intelligent management and control of complex hybrid structure construction.

Description

Technical Field

[0001] This invention relates to the field of large-span building engineering technology, and in particular to a method and system for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure. Background Technology

[0002] Large-span tensioned timber arch and steel frame hybrid roof structures typically include steel trusses, timber arches, cables, secondary beams, key connection nodes, and temporary support systems during construction. The construction process of this type of structure involves stages such as timber arch installation, steel truss assembly, facade steel frame installation, trolley disassembly, cable tensioning, and support unloading. Under different construction stages, the stress state of some components differs significantly from the final formed state.

[0003] Conventional construction monitoring methods often employ discrete point layout and manual inspection, which can obtain displacement or strain information of some components, but it is difficult to identify the coupled response between steel, wood, cables and temporary supports. Wood components are significantly affected by grain direction, moisture content and temperature, steel components are significantly affected by temperature effects and construction loads, and cables are significantly affected by tensioning sequence and anchorage status. If fixed thresholds are set only for a single material or a single component, it is easy to cause misjudgment or omission.

[0004] Furthermore, when multiple tensioned timber arch steel frame hybrid structures are installed one by one, construction deviations in the previous stage may accumulate in the later stage. Without dynamic comparison between the benchmark model of the construction stage and the real-time monitoring data on site, it is impossible to identify the trend of local over-limit component coupling abnormalities or overall imbalance evolution in a timely manner.

[0005] Therefore, a method and system for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure is provided to solve the problems mentioned above. Summary of the Invention

[0006] The technical problem to be solved by this invention is to provide a method and system for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure, addressing the issues of multi-material response differences, stress state changes during construction, difficulty in identifying cumulative errors, difficulty in monitoring and judging the impact of environmental disturbances, and difficulty in providing early warning of risk evolution.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure, comprising the following steps: S1. Obtain material property parameters, structural design parameters, and construction stage information of the wood components. The material property parameters of the wood components include mechanical properties along the grain, mechanical properties across the grain, mechanical property correction parameters under different moisture content gradients, and mechanical property correction parameters under different temperature gradients. The above parameters are obtained by conducting mechanical tests on standard specimens of wood components of the corresponding tree species under different stress directions, different moisture contents, and different temperature conditions. Material property specimens are made according to the wood component tree species, and the stress response, deformation response, and parameter variation relationship along the grain and across the grain under different moisture contents and different temperature conditions are obtained respectively. The parameter variation relationship is written into the material property database. S2. Based on the structural design parameters and construction stage information, establish a construction stage benchmark model including steel truss, wooden arch, cable, key nodes and sliding trolley support structure, and obtain the benchmark state data corresponding to each construction stage. S3. Based on the baseline state data, identify key monitoring nodes and key monitoring components, and generate a monitoring point layout scheme for steel components, wooden components, cables and sliding trolley support structures; S4. Collect on-site monitoring data according to the monitoring point layout plan, and align the on-site monitoring data according to the construction stage and collection time to obtain the measured status data; S5. Perform data filtering, environmental impact correction and multi-component coupling verification on the measured state data to obtain the construction coupling state vector composed of the corrected strain along the grain of the wooden component, the corrected strain across the grain of the wooden component, the corrected strain of the steel component, the corrected value of the node displacement, the corrected value of the component inclination angle, the corrected cable force of the cable, and the corrected stress and strain of the sliding trolley support structure. S6. Compare the construction coupling state vector with the baseline state data and graded early warning threshold of the corresponding construction stage to determine the deviation characteristics and risk level; S7. Based on the deviation characteristics and risk level described in S6, and combined with the deviation evolution patterns of historical multiple construction stages, deduce the full-path risk evolution trend from single-point local over-limit, abnormal coupling of related components to overall structural imbalance, and output corresponding graded early warning information and construction handling suggestions based on the risk level and the full-path risk evolution trend.

[0008] Preferably, the acquisition of material property parameters of wood components in step S1 specifically includes: making material property specimens according to the wood species, obtaining stress response, deformation response and parameter variation relationship in the direction along the grain and in the direction across the grain under different moisture contents and different temperatures, and writing the parameter variation relationship into the material property database.

[0009] Preferably, the establishment of the construction phase benchmark model in step S2 includes: Establish finite element models of the main truss, secondary beams, wooden arches, cables, connection nodes, and sliding trolley support structure; The assembly, tensioning, changes in temporary supports, disassembly of the sliding trolley, and unloading of supports are taken as boundary conditions for the construction phase. The stress, strain, displacement, tilt angle, and cable force of key nodes and key components at each construction stage are simulated cumulatively according to the construction sequence.

[0010] Preferably, the identification of key monitoring nodes and key monitoring components in step S3 specifically includes: calculating the stress sensitivity, deformation sensitivity and stage change range of each node and component under different construction stages based on the baseline state data, and identifying nodes and components that meet the sensitivity conditions or are located on the load transfer path as key monitoring nodes and key monitoring components. Specifically, the sensitivity conditions are as follows: in the construction calculation simulation, under various working conditions, if the absolute value of the stress change of a single node or component deviates from the design reference value by 5% or more, or the difference between the deformation value of the node or component and the reference deformation value reaches 3% or more of the reference deformation value, or the change in the stress state between two adjacent construction stages exceeds 10% of the total stress design value of the node or component, then it can be determined that it meets the sensitivity screening requirements and is included in the scope of key monitoring nodes and key monitoring components.

[0011] Preferably, the on-site monitoring data mentioned in step S4 includes the following data set: strain data of steel components, strain data of wood components along the grain, strain data of wood components across the grain, node displacement data, component tilt angle data, cable force data, ambient temperature data, ambient humidity data, wood moisture content data, and stress-strain data of the sliding trolley support structure.

[0012] Preferably, the environmental impact correction of the measured state data in step S5 specifically includes: correcting the strain along the grain of the wooden components, the strain across the grain of the wooden components, the strain of the steel components, and the cable tension based on the ambient temperature, ambient humidity, and wood moisture content, to obtain corrected monitoring data after eliminating environmental disturbances.

[0013] Preferably, the multi-component coupling verification in step S5 specifically includes: The consistency of the stress state of the wooden components along the grain and across the grain is verified. Couple the stress or deformation trends of steel components, wooden components, and cables for verification; The stress and strain changes of the sliding trolley support structure are compared with the corresponding truss monitoring data to verify the support relationship.

[0014] Preferably, the determination of deviation characteristics and risk level in step S6 specifically includes: Gradient thresholds are set according to the construction stage: 80% of the baseline state data for the corresponding construction stage is the safety state threshold, 90% is the dynamic anomaly threshold, 99% is the safety warning threshold, and 100% and above is the work stoppage warning threshold. The four thresholds are arranged in ascending order to form a continuously progressive interval division rule. Define the baseline state data as the upper limit of the design bearing capacity, and calculate the ratio of the current load effect value of the construction coupling state vector to the upper limit of the design bearing capacity; When the ratio is below 80%, it falls into the safe state range, and a safe state is output. When the ratio is in the 80%-90% range, it falls into the dynamic anomaly threshold range, and a dynamic anomaly prompt is output. When the ratio is in the range of 90%-99%, it falls into the safety warning threshold range, and a safety warning is output. When the ratio exceeds 100% and falls into the shutdown warning threshold range, a shutdown warning is output.

[0015] This invention also provides a monitoring system for the entire construction process of a tensioned timber arch steel frame hybrid structure, comprising: The material parameter acquisition module is used to acquire material property parameters, structural design parameters, and construction stage information for wooden components. The benchmark model building module is used to establish a benchmark model for each construction stage, including steel trusses, wooden arches, cables, key nodes, and sliding trolley support structures, and to obtain benchmark state data for each construction stage. The monitoring point layout module is used to identify key monitoring nodes and key monitoring components based on the baseline state data, and generate a monitoring point layout scheme for steel components, wooden components, cables and sliding trolley support structures; The on-site data acquisition module is used to collect on-site monitoring data according to the monitoring point layout plan, and to align the on-site monitoring data according to the construction stage and collection time to obtain the measured status data; The data processing module is used to perform data filtering, environmental impact correction, and multi-component coupling verification on the measured state data to obtain the construction coupling state vector; The risk assessment module is used to compare the construction coupling state vector with the baseline state data and graded early warning thresholds of the corresponding construction stage to determine the deviation characteristics and risk level. The early warning output module is used to deduce the risk evolution path of local over-limit, abnormal component coupling and overall imbalance based on the deviation characteristics and the risk level, and output the corresponding graded early warning information and construction treatment suggestions.

[0016] The field acquisition module includes a strain sensor, a displacement sensor, an inclination sensor, a cable force sensor, a temperature and humidity sensor, a moisture content sensor, a strain acquisition device, and a cloud transmission unit. The risk assessment module is connected to the digital twin model and the simulation analysis model, and is used to update the risk evolution path based on real-time monitoring data.

[0017] Compared with the prior art, the beneficial effects that this invention can achieve are: 1. This invention addresses the material anisotropy and multi-component collaborative stress characteristics of tensioned timber arch steel frame hybrid structures. Through targeted material property tests on timber components, it clarifies the material mechanical response laws under different grain directions, moisture contents, and temperature conditions. This provides accurate basic parameters for monitoring data correction and benchmark model construction, solving the problem of monitoring data distortion caused by the anisotropy of timber and providing a reusable reference for parameter selection in similar timber structure projects.

[0018] 2. The cumulative benchmark model constructed in this invention incorporates all elements of the sliding trolley support system, temporary load changes, and tensioning and unloading procedures into the simulation scope. It can realistically reflect the error accumulation and load redistribution effect during the installation of multiple trusses one by one. The obtained benchmark state data has a high degree of agreement with the actual measured trend on site. It not only provides an accurate reference for the state comparison of the entire construction process, but also effectively reduces the result deviation of traditional phased simulation, and provides reliable theoretical support for the optimization of construction schemes and the adjustment of procedures.

[0019] 3. The multi-dimensional data coupling verification mechanism established in this invention achieves cross-verification of monitoring data through three layers of logic: verification of the consistency of stress along and across the grain of wooden components, verification of the stress trend coupling of steel-wood-cable, and verification of the linkage between the superstructure and the sliding trolley support data. This enables accurate identification of different types of risks, such as anomalies in single components, abnormal load transfer paths, and abnormalities in temporary support systems, significantly improving the accuracy of risk identification and avoiding misjudgments and omissions caused by monitoring single parameters. This ensures that the stress is controllable throughout the entire construction process of ultra-large span hybrid structures.

[0020] 4. The hierarchical early warning and risk evolution prediction mechanism proposed in this invention sets gradient thresholds based on the characteristics of the construction stage and predicts the risk development path based on multi-period data trends. It can output targeted disposal suggestions according to the risk level, which not only realizes the early detection and early warning of construction risks, but also provides clear guidance for on-site decision-making. It effectively ensures the safe construction of ultra-large span hybrid structures and can provide important reference for the design, construction and monitoring of similar steel-wood hybrid structures in the future. It has significant engineering promotion value.

[0021] 5. This invention achieves closed-loop management of the entire process, including real-time data acquisition, rapid local early warning, and cloud-based evolution simulation, through the collaborative operation of on-site edge computing and cloud-based digital twin models. It can complete the dynamic assessment of structural status without extensive manual intervention, which not only improves monitoring efficiency and response speed but also reduces the manpower cost of on-site monitoring, providing a mature solution for the intelligent management and control of complex hybrid structure construction. Attached Figure Description

[0022] Figure 1 This is a schematic diagram illustrating the principle of the monitoring and early warning method for the entire construction process of the tensioned timber arch and steel frame hybrid structure in this invention. Figure 2 This is the data for the research and analysis of the properties of materials with different moisture contents in this invention; Figure 3 This is a basic model diagram for the building structure analysis in this invention; Figure 4 This is a structural analysis model diagram of the construction support system in this invention; Figure 5 Analysis and numbering of key strain nodes in the single-span large-span tensioned steel-wood hybrid structure of this invention; Figure 6 Analysis and numbering of key deformation nodes in the single-span large-span tensioned steel-wood hybrid structure of this invention; Figure 7 This is the AI ​​data comparison and analysis interface for monitoring points of the large-span tensioned steel-wood hybrid structure in this invention. Detailed Implementation

[0023] To make the technical means, creative features, and achieved objectives and effects of this invention easier to understand, the invention is further described below with reference to specific embodiments. However, the following embodiments are merely preferred embodiments of this invention and not all of them. Other embodiments obtained by those skilled in the art based on the embodiments described herein without creative effort are all within the protection scope of this invention. Unless otherwise specified, the experimental methods in the following embodiments are conventional methods, and the materials and reagents used in the following embodiments are commercially available unless otherwise specified.

[0024] Example: Example 1: This example proposes a method for monitoring and early warning throughout the construction process of a tensioned timber arch steel frame hybrid structure. The specific implementation process is as follows: First, the material property parameters, structural design parameters, and construction stage information of the wood components are obtained. The material property parameters of the wood components include mechanical properties along the grain, mechanical properties across the grain, mechanical property correction parameters under different moisture content gradients, and mechanical property correction parameters under different temperature gradients. The above parameters are obtained by conducting mechanical tests on standard wood component specimens of the corresponding tree species under different stress directions, different moisture contents, and different temperature conditions. Material property specimens are made according to the wood component tree species, and the stress response, deformation response, and parameter variation relationship along the grain and across the grain under different moisture contents and different temperature conditions are obtained respectively. The parameter variation relationship is then written into the material property database.

[0025] Based on the structural design drawings and construction organization plan, a finite element model was established, including the main truss, secondary beams, wooden arches, cables, connection nodes, and sliding trolley support structure. Assembly, tensioning, temporary support changes, sliding trolley disassembly, and support unloading were used as boundary conditions for each construction stage. An incremental simulation method was adopted, using the structural state of the previous construction stage as the initial condition for the next construction stage. New components, construction loads, tension forces, and support release conditions were applied stage by stage to obtain the stress, strain, displacement, tilt angle, and cable force reference state data of key nodes and components in each construction stage.

[0026] Based on the baseline state data, the stress sensitivity, deformation sensitivity, and stage change range of each node and component are calculated. The nodes and components in the connection area between the steel truss and the wooden arch, the cable anchorage area, the temporary support force transmission area, and the mid-span large deformation area are identified as key monitoring objects. A monitoring point layout plan is generated, with 8 strain measurement points and 7 deformation measurement points set up for each truss. The 20 steel-wood trusses are set up one by one. At the same time, stress and strain measurement points are set up at the key stress positions of the lower sliding trolley support structure.

[0027] Various sensors were installed according to the deployment plan to collect data on steel component strain, wood component strain along the grain, wood component strain across the grain, node displacement, component tilt angle, cable force, ambient temperature, ambient humidity, wood moisture content, and stress-strain data of the sliding trolley support structure. The collected raw data were then corrected with timestamps, identified as missing data, and subjected to abnormal jumps and filtering. The data were then assigned to the corresponding construction stage based on the construction procedure code to form actual measurement status data.

[0028] To address the anisotropy of timber components and the impact of environmental disturbances, environmental impact corrections and multi-component coupling verifications were performed on the measured state data. Specifically, the longitudinal / transverse strain of timber components was corrected based on ambient temperature, humidity, and timber moisture content; the strain of steel components and cable forces were corrected based on temperature effects; and the displacement data was normalized based on the changes in the measurement point reference. In sequence, the consistency of longitudinal and transverse stress states of timber components, the coupling verification of stress-deformation trends of steel-timber-cable, and the verification of the data support relationship between the sliding trolley support structure and the upper truss were carried out to obtain the construction coupling state vector.

[0029] The construction coupling state vector is compared with the baseline state data and graded early warning thresholds of the corresponding construction stage to determine the deviation characteristics and risk level. When the deviation falls into the safe state threshold range, it is judged as a normal construction state. When it falls into the dynamic abnormal threshold range, a data retest prompt is triggered. When it falls into the safety early warning threshold range, a risk inspection prompt is triggered. When it falls into the work stoppage early warning threshold range, a construction suspension command is triggered. Among them, each threshold is based on the baseline status data of the construction stage. Below 80% is a safe state, 80-90% is the dynamic abnormal threshold range, 90-99% is the safety warning threshold, and 100% and above is the work stoppage threshold. Based on the deviation change trend over multiple consecutive periods, the risk evolution path is deduced. If it is a single point short-term anomaly, local reinforcement suggestions are output. If it is a multi-point linked anomaly, suggestions for adjusting the tensioning sequence and temporarily suspending unloading are output, so as to achieve accurate early warning and dynamic control of the entire construction process.

[0030] Example 2, the specific details of the environmental impact correction for strain in wooden components are as follows: First, temperature and humidity sensors and wood moisture content sensors are deployed on-site to collect real-time data on ambient temperature, ambient humidity, and the actual moisture content of the wooden components at the monitoring points. The measured strain of the wooden components is then corrected based on parameters obtained from material property tests to eliminate monitoring biases caused by environmental disturbances. The specific calculation formula is as follows: ; In the formula, The corrected actual stress and strain of the wooden component reflects the true strain value of the wooden component caused by the structural load and is the core input parameter for subsequent risk assessment. The measured strain of the wooden component is collected in real time by strain sensors. It is directly collected by strain sensors installed at key stress locations of the wooden component and includes stress strain and additional strain caused by environmental factors. The temperature strain coefficient of the wooden component is obtained by strain testing of unloaded specimens under different temperature conditions in material property tests, reflecting the additional strain value of the wooden component caused by a unit temperature change. To monitor the difference between the ambient temperature and the material test reference temperature, the temperature data collected in real time by the on-site temperature and humidity sensor is subtracted from the test reference temperature to reflect the deviation between the current temperature and the reference conditions. The moisture content strain coefficient of the wooden component is obtained by strain testing of unloaded specimens under different moisture content conditions in material property tests. It reflects the additional strain value of the wooden component caused by the unit change in moisture content. To monitor the difference between the current wood moisture content and the material test reference moisture content, the difference is obtained by subtracting the test reference moisture content from the wood moisture content data collected in real time by the on-site moisture content sensor, reflecting the deviation between the current moisture content and the reference conditions.

[0031] After the correction is completed, multi-dimensional coupling verification is carried out: the ratio of the corrected strain along the grain to the corrected strain across the grain of the wooden component should be within the threshold range of the strain ratio along the grain and across the grain. This threshold is derived based on the anisotropic mechanical properties of the bent wooden component and is determined by combining the material mechanics test results of the corresponding tree species and the numerical statistical results of the structural finite element simulation analysis. If it exceeds the threshold, it is judged as abnormal strain data. Method for determining the longitudinal and transverse strain ratio threshold: This threshold is determined by combining the longitudinal and transverse elastic modulus ratios obtained from the material mechanics test of the corresponding tree species with the statistical results of the finite element simulation of the corresponding bending member. In conventional engineering scenarios, the threshold value ranges from 12 to 18. Different tree species can be adapted and adjusted according to the measured mechanical parameters.

[0032] Method for determining the threshold of steel-wood-cable coupling correlation coefficient: The threshold is obtained by simulating the force transmission path during the entire construction stage of the structural design phase. The minimum correlation coefficient of the force changes of steel, wood and cable under each working condition is selected as the base value, and then reduced by 10% as the final judgment threshold. In conventional engineering scenarios, the threshold is not lower than 0.7, taking into account the requirements of anomaly identification sensitivity and false alarm rate control.

[0033] Method for determining the threshold of the coupling correlation coefficient between the trolley and the structure: The threshold is determined by the design force transmission efficiency of the sliding support system and the stiffness matching characteristics of the superstructure. In conventional engineering scenarios, the threshold value is not less than 0.8. The threshold value can be flexibly adjusted according to the structural form of the temporary support to adapt to the support verification requirements under different spans and load conditions.

[0034] The correlation coefficients of the changing trends of the corrected strain of the wooden components, the strain of the steel components, and the cable force during the same construction stage should not be less than the threshold of the steel-wood-cable coupling correlation coefficient. This threshold is determined based on the simulation analysis results of the force transmission path during the structural design stage. It is necessary to take into account both the sensitivity of anomaly identification and the control requirements of false alarm rate. If the requirements are not met, it is judged as an anomaly in the force transmission path, so as to ensure the matching of the stress state of each component.

[0035] For the sliding trolley support structure, its stress and strain monitoring data are compared with the deformation monitoring data of the corresponding upper truss. The correlation coefficient between the stress change of the trolley support and the displacement change of the corresponding position of the upper truss should not be less than the trolley-structure coupling correlation coefficient threshold. This threshold is determined jointly based on the design force transmission efficiency of the sliding support system and the stiffness matching characteristics of the upper structure. The threshold can be adjusted according to the structural form of the temporary support. If the correlation coefficient is lower than the threshold or the data trend deviates, a temporary support check prompt is immediately triggered to verify the rationality of the force transmission path of the support system and avoid abnormal stress on the upper structure.

[0036] Example 3: The specific method for dynamically determining the construction risk level of a tensioned timber arch steel frame hybrid structure is as follows: First, for different construction stages, the graded early warning thresholds for each monitoring parameter are determined by combining design allowable values, baseline state data, and material test results. In each acquisition cycle, the system obtains the measured values ​​of each parameter in the construction coupled state vector, calculates the deviation of each parameter relative to the baseline state, and determines the current construction risk level based on the importance of the parameters. The specific calculation formula is as follows: ; In the formula, The comprehensive construction risk coefficient is used to quantify the degree of deviation between the current structural state and the baseline state, and is the core indicator for determining the risk level. The corrected measured strain of the component was obtained by collecting data from a strain sensor and then corrected for environmental conditions. The reference strain value of the component during the corresponding construction stage is obtained by simulation calculation from the reference model during the construction stage; The safe allowable threshold for component strain is calculated from the material strength design value specified in the structural design documents. The measured displacement values ​​of key nodes are obtained in real time by displacement sensors deployed at the node locations; The reference displacement values ​​of the nodes corresponding to the construction stage are obtained by simulation calculation from the reference model of the construction stage; The safe allowable threshold for nodal displacement is determined by the allowable deformation value specified in the structural design documents; The measured cable force value is obtained in real time by a cable force sensor. The reference cable force value for the lower cable during the construction phase is obtained from the simulation calculation of the reference model during the construction phase; The safe allowable threshold for cable force is determined by the cable design bearing capacity and tension control requirements.

[0037] Furthermore, when the comprehensive construction risk coefficient R is less than the safety status threshold, the system is determined to be in a safe state and outputs a normal construction prompt. When the comprehensive construction risk coefficient R is greater than or equal to the safety status threshold and less than the dynamic anomaly threshold, it is determined to be a dynamic anomaly state, and the system outputs data retesting and encrypted monitoring prompts. When the comprehensive construction risk coefficient R is greater than or equal to the dynamic anomaly threshold and less than the safety warning threshold, it is determined to be a safety warning state, and the system outputs a prompt to suspend the current process and carry out on-site inspection and model verification. When the comprehensive construction risk coefficient R is greater than or equal to the safety warning threshold, the system is determined to be in a work stoppage warning state, and the system outputs a handling suggestion to immediately stop construction and investigate the risk source.

[0038] The system continuously collects the risk coefficient change trend over multiple periods and inputs it into the risk evolution and deduction module. If the risk coefficient continues to rise and the deviation of multiple parameters increases synchronously, it is determined that there is a risk of abnormal component coupling or even overall imbalance. The system automatically pushes out special treatment plans to provide data support for construction decisions.

[0039] In Example 4, the present invention also provides a monitoring and early warning system for the entire construction process of a tensioned timber arch steel frame hybrid structure. The system is divided into a two-level architecture: an on-site edge computing layer and a cloud platform layer. The edge computing layer is deployed in the main control room of the construction site, connects to all on-site acquisition devices, and is responsible for real-time data acquisition, preliminary filtering, local threshold judgment and audible and visual alarms. When the monitoring data reaches the safety early warning threshold, the edge computing layer can directly trigger the on-site alarm device without waiting for cloud instructions, thereby improving the emergency response speed.

[0040] The cloud platform layer deploys a benchmark model management module, a historical data storage module, a risk evolution simulation module, and an early warning output module. It receives all monitoring data uploaded from the edge computing layer, interacts with the measured data and the benchmark model in the construction phase in real time, dynamically updates the structural simulation model based on digital twin technology, and combines continuous monitoring data to deduce the risk development path. The system is also connected to the construction progress management system, which automatically switches the baseline status data and early warning thresholds of the corresponding stage according to the current construction process, so as to realize the dynamic matching between monitoring logic and construction progress.

[0041] During construction, on-site management personnel can view the change curves and risk status of various monitoring parameters in real time through a mobile APP. When an early warning is triggered, the system automatically pushes the warning information and handling suggestions to the corresponding responsible person. All warning events and handling results are recorded in the system database and can be used as reference data for subsequent construction of similar structures.

[0042] Through the collaborative operation of edge computing and cloud computing, real-time perception, precise analysis, rapid response, and closed-loop management of the entire construction process are achieved, effectively reducing the construction safety risks of large-span tensioned timber arch steel frame hybrid structures.

[0043] Furthermore, the design principle of setting environmental humidity and wood moisture content as parallel monitoring variables in this scheme is as follows: Large-span construction sites may involve open-air installations, temporary protective disturbances, etc. The moisture content of wooden components is not only affected by long-term environmental humidity but also by temporary water accumulation, localized covering layers, and differences in ventilation in different areas. Environmental humidity alone cannot accurately characterize the actual moisture content of a single wooden component. Therefore, it is necessary to collect and coordinately correct both types of data in parallel: First, based on the constitutive correlation model of environmental humidity and wood moisture content, the real-time collected wood moisture content data is validated for rationality, eliminating moisture content jumps caused by sensor anomalies; then, the time lag error of wood moisture content is corrected by combining environmental humidity; finally, the validated data from both types are substituted into the wood component strain correction formula to eliminate correction bias caused by monitoring a single variable and avoid monitoring distortion caused by relying solely on environmental humidity to estimate moisture content.

[0044] exist Figure 2 (a), (b), (c), and (d) in the figure correspond to the load-deformation curves of four experimental groups with moisture contents of 8%, 10%, 12%, and 14%, respectively. Each experimental group contains experimental components numbered 1 to 8. The names of the experimental components SL8, SL10, SL12, and SL14 correspond to the four experimental groups with different moisture contents. The horizontal axis represents the deformation in mm, and the vertical axis represents the load in kN.

[0045] exist Figure 5 In this context, S represents strain, and S-1 to S-8 correspond to the numbers of different strain critical nodes.

[0046] exist Figure 6 In this context, D represents displacement, and D-1 to D-8 correspond to the numbers of different displacement critical nodes.

[0047] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0048] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for monitoring and early warning throughout the construction process of a tensioned timber arch and steel frame hybrid structure, characterized in that, It includes the following steps: S1. Obtain material property parameters, structural design parameters, and construction stage information of the wood components. The material property parameters of the wood components include mechanical properties along the grain, mechanical properties across the grain, mechanical property correction parameters under different moisture content gradients, and mechanical property correction parameters under different temperature gradients. The above parameters are obtained by conducting mechanical tests on standard specimens of wood components of the corresponding tree species under different stress directions, different moisture contents, and different temperature conditions. Material property specimens are made according to the wood component tree species, and the stress response, deformation response, and parameter variation relationship along the grain and across the grain under different moisture contents and different temperature conditions are obtained respectively. The parameter variation relationship is written into the material property database. S2. Based on the structural design parameters and construction stage information, establish a construction stage benchmark model including steel truss, wooden arch, cable, key nodes and sliding trolley support structure, and obtain the benchmark state data corresponding to each construction stage. S3. Based on the baseline state data, identify key monitoring nodes and key monitoring components, and generate a monitoring point layout scheme for steel components, wooden components, cables and sliding trolley support structures; S4. Collect on-site monitoring data according to the monitoring point layout plan, and align the on-site monitoring data according to the construction stage and collection time to obtain the measured status data; S5. Perform data filtering, environmental impact correction and multi-component coupling verification on the measured state data to obtain the construction coupling state vector composed of the corrected strain along the grain of the wooden component, the corrected strain across the grain of the wooden component, the corrected strain of the steel component, the corrected value of the node displacement, the corrected value of the component inclination angle, the corrected cable force of the cable, and the corrected stress and strain of the sliding trolley support structure. S6. Compare the construction coupling state vector with the baseline state data and graded early warning threshold of the corresponding construction stage to determine the deviation characteristics and risk level; S7. Based on the deviation characteristics and risk level described in S6, and combined with the deviation evolution patterns of historical multiple construction stages, deduce the full-path risk evolution trend from single-point local over-limit, abnormal coupling of related components to overall structural imbalance, and output corresponding graded early warning information and construction handling suggestions based on the risk level and the full-path risk evolution trend.

2. The method for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure according to claim 1, characterized in that, The specific steps in step S1 for obtaining the material property parameters of the wood components include: preparing material property specimens based on the wood species, obtaining the stress response, deformation response, and parameter variation relationships in the direction along and across the grain under different moisture contents and temperatures, and writing the parameter variation relationships into the material property database.

3. The method for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure according to claim 1, characterized in that, The S2 step involves establishing a benchmark model for the construction phase, including: Establish finite element models of the main truss, secondary beams, wooden arches, cables, connection nodes, and sliding trolley support structure; The assembly, tensioning, changes in temporary supports, disassembly of the sliding trolley, and unloading of supports are taken as boundary conditions for the construction phase. The stress, strain, displacement, tilt angle, and cable force of key nodes and key components at each construction stage are simulated cumulatively according to the construction sequence.

4. The method for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure according to claim 1, characterized in that, The identification of key monitoring nodes and key monitoring components in step S3 specifically includes: calculating the stress sensitivity, deformation sensitivity and stage change range of each node and component under different construction stages based on the baseline state data, and identifying nodes and components that meet the sensitivity conditions or are located on the load transfer path as key monitoring nodes and key monitoring components. Specifically, the sensitivity conditions are as follows: in the construction calculation simulation, under various working conditions, if the absolute value of the stress change of a single node or component deviates from the design reference value by 5% or more, or the difference between the deformation value of the node or component and the reference deformation value reaches 3% or more of the reference deformation value, or the change in the stress state between two adjacent construction stages exceeds 10% of the total stress design value of the node or component, then it can be determined that it meets the sensitivity screening requirements and is included in the scope of key monitoring nodes and key monitoring components.

5. The method for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure according to claim 1, characterized in that, The on-site monitoring data mentioned in step S4 includes the following data sets: strain data of steel components, strain data of wood components along the grain, strain data of wood components across the grain, node displacement data, component tilt angle data, cable force data, ambient temperature data, ambient humidity data, wood moisture content data, and stress-strain data of the sliding trolley support structure.

6. The method for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure according to claim 1, characterized in that, The environmental impact correction in step S5 specifically includes: based on the ambient temperature data, ambient humidity data, and measured moisture content data of wood collected on site, correcting the strain along the grain of wood components, the strain across the grain of wood components, the strain of steel components, and the cable tension to obtain corrected monitoring data after eliminating environmental disturbances.

7. The method for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure according to claim 1, characterized in that, The multi-component coupling verification in step S5 specifically includes: The consistency of the stress state of the wooden components along the grain and across the grain is verified. Couple the stress or deformation trends of steel components, wooden components, and cables for verification; The stress and strain changes of the sliding trolley support structure are compared with the corresponding truss monitoring data to verify the support relationship.

8. The method for monitoring and early warning of the entire construction process of a tensioned timber arch steel frame hybrid structure according to claim 1, characterized in that, The determination of deviation characteristics and risk level in step S6 specifically includes: Gradient thresholds are set according to the construction stage: 80% of the baseline state data for the corresponding construction stage is the safety state threshold, 90% is the dynamic anomaly threshold, 99% is the safety warning threshold, and 100% and above is the work stoppage warning threshold. The four thresholds are arranged in ascending order to form a continuously progressive interval division rule. Define the baseline state data as the upper limit of the design bearing capacity, and calculate the ratio of the current load effect value of the construction coupling state vector to the upper limit of the design bearing capacity; When the ratio is below 80%, it falls into the safe state range, and a safe state is output. When the ratio is in the 80%-90% range, it falls into the dynamic anomaly threshold range, and a dynamic anomaly prompt is output. When the ratio is in the range of 90%-99%, it falls into the safety warning threshold range, and a safety warning is output. When the ratio exceeds 100% and falls into the shutdown warning threshold range, a shutdown warning is output.

9. A monitoring system for the entire construction process of a tensioned timber arch and steel frame hybrid structure, based on the monitoring and early warning method for the entire construction process of a tensioned timber arch and steel frame hybrid structure as described in any one of claims 1-8, characterized in that, include: The material parameter acquisition module acquires material property parameters, structural design parameters, and construction stage information for wooden components. The benchmark model construction module establishes a benchmark model for each construction stage, including steel trusses, wooden arches, cables, key nodes, and sliding trolley support structures, and obtains benchmark state data corresponding to each construction stage. The monitoring point deployment module identifies key monitoring nodes and key monitoring components based on the baseline state data, and generates a monitoring point deployment scheme for steel components, wooden components, cables, and sliding trolley support structures. The on-site data acquisition module collects on-site monitoring data according to the monitoring point layout plan, and aligns the on-site monitoring data according to the construction stage and acquisition time to obtain measured status data; The data processing module performs data filtering, environmental impact correction, and multi-component coupling verification on the measured state data to obtain the construction coupling state vector; The risk assessment module compares the construction coupling state vector with the baseline state data and graded early warning thresholds of the corresponding construction stage to determine the deviation characteristics and risk level. The early warning output module deduces the risk evolution path of local over-limit, abnormal component coupling, and overall imbalance based on the deviation characteristics and risk level, and outputs corresponding graded early warning information and construction handling suggestions.

10. The monitoring system for the entire construction process of a tensioned timber arch and steel frame hybrid structure according to claim 9, characterized in that, The field acquisition module includes a strain sensor, a displacement sensor, an inclination sensor, a cable force sensor, a temperature and humidity sensor, a moisture content sensor, a strain acquisition device, and a cloud transmission unit. The risk assessment module is connected to the digital twin model and the simulation analysis model, and is used to update the risk evolution path based on real-time monitoring data.

Images