Large-span steel arch building monitoring and early warning method and system based on digital twinning

Abstract

The invention belongs to the technical field of steel arch building monitoring, particularly relates to a large-span steel arch building monitoring and early warning method and system based on digital twinning, and solves the technical problems that the structural state of a large-span steel arch building cannot be comprehensively and accurately mastered in real time, and early warning and monitoring cannot be comprehensively and timely performed. According to the method, the three-dimensional twinborn model is constructed through the BIM technology, and the sensor data is mapped, so that the real-time data of different nodes of the large-span steel arch building can be intuitively and comprehensively obtained in real time. Compared with a traditional monitoring mode, the building structure state can be visually analyzed on the basis, the monitoring accuracy and comprehensiveness are greatly improved, and a scientific and systematic analysis process is established; through identification of stress data distribution conditions under different working conditions and comparison with material allowable stress, a stress change rate preset value, a safety margin reserved safety margin and the like, whether the structure is abnormal or not can be accurately judged, and an early warning signal is generated in time.

Description

Technical Field

[0001] The present invention belongs to the technical field of steel arch building monitoring, and specifically relates to a monitoring and early warning method and system for long-span steel arch buildings based on digital twin. Background Art

[0002] With the wide application of long-span steel arch buildings in modern engineering, the structural safety monitoring thereof is of crucial importance. Due to its large span, complex structure, special stress system and other characteristics, the stress and deformation states of the long-span steel arch building structure change constantly under various working conditions such as daily use, wind load, snow load, and construction temporary load.

[0003] However, traditional monitoring methods are difficult to comprehensively, real-time and accurately grasp its structural state, and the development of BIM technology and sensor technology provides a new way to solve this problem. Through BIM technology, a three-dimensional twin model of the long-span steel arch building can be constructed, and sensors can collect building structure data in real time, providing rich data sources and more intuitive analysis means for building structure safety monitoring. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a monitoring and early warning method and system for long-span steel arch buildings based on digital twin, which solves the problems of being difficult to comprehensively, real-time and accurately grasp its structural state and being unable to conduct comprehensive and timely early warning monitoring.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A monitoring and early warning method for long-span steel arch buildings based on digital twin, comprising the following steps: Step1. Obtain a three-dimensional twin model of the long-span steel arch building through BIM technology, and at the same time obtain sensor data, and map the sensor data onto the three-dimensional twin model; Step2. Obtain the real-time data of different nodes of the long-span steel arch building according to the three-dimensional twin model, and identify the centralized distribution situation of the real-time data under different working conditions to generate a centralized distribution result and a non-centralized distribution result; Step3. Analyze the generated centralized distribution result, generate an early warning signal and a secondary analysis signal by comparing the allowable stress of the materials of the long-span steel arch building, and at the same time analyze the short-term stress change trend to process the secondary analysis signal to generate a normal monitoring signal and an early warning signal; Step4. Analyze the generated non-centralized result, screen out overloaded nodes, and at the same time calculate the deformation value corresponding to the overloaded nodes according to historical data, and comprehensively calculate to obtain the deformation mean value; Step 5. Analyze the relationship between the obtained deformation mean value and the load. At the same time, calculate the load capacity based on the current deformation value, and analyze the load capacity in combination with historical data to generate normal monitoring signals and warning signals.

[0006] As a further solution of the present invention, the specific manner in which the Step 2 generates the concentrated distribution result and the non-concentrated distribution result is as follows: Obtain all nodes and label them as i, where i = 1, 2, …, j, and j represents the number of nodes. Then, obtain the stress data Yi in the real-time data of node i, and identify the distribution of the stress data Yi under different working conditions to generate the concentrated distribution result and the non-concentrated distribution result.

[0007] As a further solution of the present invention, the specific manner in which the Step 3 analyzes the generated concentrated distribution result is as follows: Obtain the concentrated distribution result. At the same time, obtain the allowable stress of the materials of the long-span steel arch building, and compare the obtained real-time stress with the allowable stress of the materials. If the real-time stress is greater than the allowable stress of the materials, generate a warning signal; otherwise, generate a secondary analysis signal, and at the same time, analyze the secondary analysis signal to generate a margin analysis signal and a warning signal.

[0008] As a further solution of the present invention, the specific manner in which the Step 3 analyzes the secondary analysis signal to generate a margin analysis signal and a warning signal is as follows: Obtain all stress parameters of the steel arch building within time t, and denote the obtained stress parameters as the stress data sequence y a , and at the same time, obtain the first-order forward difference of the stress data sequence at the a-th time point , and obtain the corresponding time interval , then substitute the two into the formula to calculate the stress change rate v a ; And so on, collect multiple groups of stress parameters within the time period t, and calculate the corresponding stress change rate v a , and at the same time, analyze the change situation of the stress change rate v a according to the collection order. Then, calculate the change difference of the stress change rate v a between adjacent periods, and calculate the mean value of all change differences to obtain the change mean value. At the same time, compare the change mean value with the preset value; If the change mean value is greater than the preset value, it indicates that there is an abnormality in the stress change of the corresponding steel arch building, and a warning signal is generated; otherwise, it indicates that the stress change of the corresponding steel arch building is normal, and a margin analysis signal is generated. At the same time, process the margin analysis signal to generate a normal monitoring signal and a warning signal.

[0009] As a further solution of the present invention, the specific manner of processing the margin analysis signal in Step3 to generate a normal monitoring signal and a warning signal is as follows: Calculate the safety margin of the structure according to the allowable stress of the material and the actual stress of the structure. At the same time, compare the obtained safety margin with the reserved safety margin. If the safety margin is greater than the reserved safety margin, it means that the safety margin can meet the corresponding production requirements, and a normal monitoring signal is generated; otherwise, it means that the safety margin cannot meet the corresponding production requirements, and a warning signal is generated.

[0010] As a further solution of the present invention, the specific manner of analyzing the generated non-concentrated result in Step4 is as follows: Obtain all nodes, and at the same time obtain the load corresponding to node i, and compare the load of node i with the preset load. Then screen the nodes corresponding to the node load greater than the preset load, and record them as overloaded nodes, and label them as a, and a = 1, 2,..., b, where b represents the number of overloaded nodes; Then obtain the historical data corresponding to the overloaded node a, obtain the number of overloading times corresponding to the overloaded node a according to the historical data, record it as Ca, and obtain the deformation value LCa corresponding to the number of overloading times Ca. By analogy, obtain the deformation values corresponding to all overloaded nodes a, then calculate the difference between the deformation values corresponding to adjacent two overloading times Ca, record it as Lc, and similarly calculate the deformation values of adjacent two times for all overloading times, and calculate the average value of all deformation differences, record it as the deformation average value.

[0011] As a further solution of the present invention, the specific manner of generating a normal monitoring signal and a warning signal in Step5 is as follows: Obtain all overloaded nodes a, and at the same time generate a pressure-bearing area with the two groups of overloaded nodes a at the farthest distance, and obtain the area A corresponding to the pressure-bearing area. According to Hooke's law formula , where is stress, E is the elastic modulus of the material, is strain, and at the same time, the external force F and the stress area A are known, then , strain , where is the change in length, that is, deformation, L is the original length, and further according to the formula is deformed to obtain , analyze the relationship between the load F and the deformation ; Substitute the deformation mean value into the formula to calculate the load value corresponding to the pressure-bearing area, then obtain the historical data, acquire the historical load condition corresponding to the pressure-bearing area, and determine whether the load value can meet the historical load condition. If it can meet, generate a secondary load analysis signal; otherwise, generate a warning signal. At the same time, analyze the secondary load analysis signal to generate a normal monitoring signal and a warning signal.

[0012] As a further solution of the present invention, the specific method for analyzing the secondary load analysis signal in Step 5 is as follows: Obtain the maximum historical load corresponding to the historical load condition, and compare the load value with the maximum historical load. If the load value is greater than the maximum historical load, generate a normal monitoring signal; otherwise, generate a warning signal.

[0013] The monitoring and warning system for long-span steel arch buildings based on digital twins includes a data acquisition module, a node analysis and identification module, a centralized situation analysis module, a non-centralized situation analysis module, and an information output module; The data acquisition module is used to obtain the real-time data of the long-span steel arch building according to the three-dimensional twin model, and at the same time transmit the real-time data to the node analysis and identification module; The node analysis and identification module is used to identify the distribution of different nodes of the long-span steel arch building under different working conditions according to the obtained real-time data, and generate a centralized distribution result and a non-centralized distribution result. At the same time, transmit the centralized distribution result to the centralized situation analysis module, and transmit the non-centralized distribution result to the non-centralized situation analysis module; The centralized situation analysis module is used to analyze the generated centralized distribution result, generate a warning signal and a secondary analysis signal by analyzing the magnitude of the allowable stress of the material and the real-time stress, then process the secondary analysis signal by analyzing the short-term trend of the real-time stress, analyze based on the calculated stress change rate, and generate a warning signal and a margin analysis signal. At the same time, calculate the magnitude of the safety margin and the reserved safety margin, generate a warning signal and a normal monitoring signal, and transmit the two to the information output module; The non-centralized situation analysis module is used to analyze the obtained non-centralized result, screen out the overloaded nodes based on the load of the nodes, calculate the deformation value of the overloaded nodes in combination with historical data, and calculate the deformation mean value at the same time. Then analyze the relationship between the deformation mean value and the load, calculate the corresponding load capacity based on the current deformation value, and analyze the load capacity in combination with historical data to generate a normal monitoring signal and a warning signal, and then transmit the two to the information output module; The information output module is used to display the obtained normal signal and warning signal to the corresponding operator.

[0014] Compared with the prior art, the present invention has the following beneficial effects: Through the BIM technology, the present invention constructs a three-dimensional twin model and maps sensor data, enabling intuitive, comprehensive, and real-time acquisition of real-time data of different nodes of a long-span steel arch building. Compared with traditional monitoring methods, visual analysis of the building structure state can be carried out based on this, greatly improving the accuracy and comprehensiveness of monitoring.

[0015] A scientific and systematic analysis process is established. By identifying the stress data distribution under different working conditions and comparing it with the allowable stress of materials, the preset value of stress change rate, and the reserved safety margin, etc., it can accurately judge whether the structure is abnormal and generate warning signals in a timely manner, greatly reducing the probability of misjudgment and missed judgment, and providing strong support for taking timely measures to ensure the safety of the building.

[0016] Combining real-time data and historical data, comprehensively analyze the safety margin and load capacity of the long-span steel arch building. By calculating the comparison between the safety margin and the reserved safety margin, analyzing the load relationship based on the mean deformation value, and combining the historical load situation to judge the load capacity, the safety and bearing capacity of the building structure can be evaluated more accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a diagram of the monitoring and warning method for a long-span steel arch building based on digital twin of the present invention; Figure 2 It is a schematic block diagram of the principle of the monitoring and warning system for a long-span steel arch building based on digital twin of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0019] Embodiment 1 Please refer to Figure 1 , the monitoring and warning method for a long-span steel arch building based on digital twin includes the following steps: Step1. Obtain the three-dimensional twin model of the long-span steel arch building through the BIM technology, and at the same time obtain sensor data and map the sensor data onto the three-dimensional twin model.

[0020] Step2. Obtain the real-time data of different nodes of the long-span steel arch building according to the three-dimensional twin model, and identify the centralized distribution situation of the real-time data under different working conditions to generate a centralized distribution result and a non-centralized distribution result.

[0021] Obtain all the nodes and label them as i, where i = 1, 2, …, j, and j represents the number of nodes. Then, obtain the stress data Yi in the real-time data of node i, and identify the distribution of the stress data Yi under different working conditions, generating a concentrated distribution result and a non-concentrated distribution result.

[0022] For example, in a long-span steel arch building, the working conditions can be divided into daily use (without special loads), wind load action, snow load action, construction temporary load action, etc. For each working condition, extract the stress data Yi of each node corresponding to the working condition. Taking the wind load working condition as an example, when the wind speed reaches the set monitoring threshold (such as 10 m / s), the system automatically identifies and enters the wind load working condition, and starts to record the stress data of all nodes under this working condition. Using statistical methods and data visualization techniques, identify the distribution of the stress data Yi under different working conditions, and the identification methods can include probability density function estimation, histogram analysis, etc. If most of the stress data is concentrated in a relatively small numerical interval and the degree of data dispersion is small, for example, more than 90% of the data is concentrated within the range of the stress mean ±10%, then it is determined as a concentrated distribution result; conversely, if the data is scattered in a large range, the data proportion in each numerical interval is relatively uniform, or there are multiple obvious data peaks, it is determined as a non-concentrated distribution result.

[0023] Step 3: Analyze the generated concentrated distribution result, generate a warning signal and a secondary analysis signal by comparing the allowable stress of the materials of the long-span steel arch building, and at the same time analyze the short-term stress change trend to process the secondary analysis signal, generating a normal monitoring signal and a warning signal.

[0024] Obtain the concentrated distribution result, and at the same time obtain the allowable stress of the materials of the long-span steel arch building, and compare the obtained real-time stress with the allowable stress of the materials. The allowable stress of the materials is obtained from the material report of the corresponding steel structure. If the real-time stress is greater than the allowable stress of the materials, a warning signal is generated; otherwise, a secondary analysis signal is generated. For example, in the daily use working condition of a long-span steel arch building, through data analysis, it is found that the stress data of node numbers from 100 to 150 shows a concentrated distribution, and the numerical interval of the concentrated distribution stress is [80 MPa, 100 MPa]. For example, for Q345 steel, its allowable stress is usually taken as 215 MPa according to the design code under normal temperature and static load conditions. For another example, under a certain strong wind condition, the stress data of nodes 120 - 130 is concentrated in the range of [220 MPa, 240 MPa], while the allowable stress of the material is 215 MPa. In this case, the generated warning signal should clearly indicate these node numbers, the strong wind condition, the maximum real-time stress of 240 MPa, and the excess of the allowable stress by 25 MPa. In such a situation, a warning signal is generated. For example, under a snow load condition, the stress data of nodes 80 - 90 is concentrated in the range of [150 MPa, 170 MPa], which is less than the allowable stress of 215 MPa. In this case, a secondary analysis signal is generated.

[0025] Next, the generated secondary analysis signal is processed to obtain all the stress parameters of the steel arch building within time t, and the obtained stress parameters are denoted as the stress data sequence y. a , and at the same time, the first-order forward difference of the stress data sequence at the a-th time point is obtained. , and the corresponding time interval is obtained. , and then the two are substituted into the formula to calculate the stress change rate v. a ; By analogy, multiple groups of stress parameters within the time period t are collected, and the corresponding stress change rates v are calculated. a , and at the same time, the change situation of the stress change rate v a is analyzed according to the collection order. Then, the change difference of the stress change rate v a between adjacent cycles is calculated, and the mean value of all change differences is calculated to obtain the change mean value. At the same time, the change mean value is compared with a preset value, and the specific value of the preset value is set by the operator and is taken according to the properties of the material when setting. If the change mean value is greater than the preset value, it indicates that there is an abnormality in the stress change of the corresponding steel arch building, and a warning signal is generated; otherwise, it indicates that the stress change of the corresponding steel arch building is normal, and a margin analysis signal is generated. For example, for a long-span steel arch made of a certain specific type of steel, after evaluation, the preset value is determined to be 2.5 MPa / h. The calculated change mean value is strictly compared with the preset value. If the change mean value is greater than the preset value, such as in the above example where the change mean value is 3 MPa / h, which is greater than the preset value of 2.5 MPa / h, it indicates that the stress change of the corresponding steel arch building is in an abnormal state, and the system will immediately generate a warning signal to remind relevant personnel to conduct a comprehensive inspection and in-depth analysis of the steel arch structure; otherwise, if the change mean value is less than the preset value, it means that the stress change of the steel arch building is within the normal range, and the system generates a normal monitoring signal and continues to maintain the conventional monitoring frequency.

[0026] Meanwhile, for the generated margin analysis signal, calculate the safety margin of the structure based on the allowable stress of the material and the actual stress of the structure. The safety margin is the difference between the allowable stress and the actual stress. At the same time, compare the obtained safety margin with the reserved safety margin. The specific value of the reserved safety margin is set according to industry standards. If the safety margin is greater than the reserved safety margin, it means that the safety margin can meet the corresponding production requirements, and a normal monitoring signal is generated; otherwise, it means that the safety margin cannot meet the corresponding production requirements, and a warning signal is generated.

[0027] Step4. Analyze the generated non - concentrated results, screen out overloaded nodes, calculate the deformation value corresponding to the overloaded nodes according to historical data, and comprehensively calculate the average deformation value.

[0028] Obtain all nodes, and at the same time obtain the load corresponding to node i, and compare the load of node i with the preset load. The specific value of the preset load is set by the operator. Then screen out the nodes whose node load is greater than the preset load, and record them as overloaded nodes, and label them as a, where a = 1, 2,..., b, and b represents the number of overloaded nodes. Then obtain the historical data corresponding to the overloaded node a, obtain the number of overload times Ca corresponding to the overloaded node a according to the historical data, and obtain the deformation value LCa corresponding to the number of overload times Ca. Here, the deformation amount is the single - time deformation amount. By analogy, obtain the deformation values corresponding to all overloaded nodes a. Then calculate the difference between the deformation values corresponding to adjacent two numbers of overload times Ca, and record it as Lc. Similarly, calculate the deformation values of adjacent two numbers of all overload times, and calculate the average value of all deformation amount differences, and record it as the average deformation value.

[0029] Step5. Analyze the relationship between the obtained average deformation value and the load. At the same time, calculate the load - bearing capacity based on the current deformation value, and analyze the load - bearing capacity in combination with historical data to generate normal monitoring signals and warning signals.

[0030] Obtain all overloaded nodes a, and at the same time generate a pressure - bearing area with the two groups of overloaded nodes a at the farthest distance. The generated pressure - bearing area includes all overloaded nodes, and obtain the area A corresponding to the pressure - bearing area. According to Hooke's law formula , where is stress, E is the elastic modulus of the material, is strain. At the same time, given the external force F and the force - bearing area A, then , strain , where is the change in length, that is, deformation, L is the original length, and further according to the formula deform to get , and analyze the relationship between the load F and the deformation . Substitute the deformation mean value into the formula to calculate the load value corresponding to the pressure-bearing area, then obtain historical data, acquire the historical load conditions corresponding to the pressure-bearing area, and determine whether the load value can meet the historical load conditions. If it can be met, a secondary load analysis signal is generated; otherwise, a warning signal is generated. And being able to meet here means that the currently calculated load value can meet all the historical load conditions in the historical data. If any group is not satisfied, a non-satisfaction signal is generated. Process the generated secondary load analysis signal, obtain the maximum historical load in the historical load conditions, and compare the load value with the maximum historical load. If the load value is greater than the maximum historical load, a normal monitoring signal is generated; otherwise, a warning signal is generated.

[0031] Embodiment 2 The large-span steel arch building monitoring and warning system based on digital twin includes: a data acquisition module, a node analysis and identification module, a centralized situation analysis module, a non-centralized situation analysis module, and an information output module, and in combination Figure 2 It can be known that there is a one-way electrical connection between the above functional modules.

[0032] The data acquisition module is used to obtain the real-time data of the large-span steel arch building according to the three-dimensional twin model, and at the same time transmit the real-time data to the node analysis and identification module; The node analysis and identification module is used to identify the distribution of different nodes of the large-span steel arch building under different working conditions according to the obtained real-time data, and generate a centralized distribution result and a non-centralized distribution result. At the same time, transmit the centralized distribution result to the centralized situation analysis module, and transmit the non-centralized distribution result to the non-centralized situation analysis module. And the specific processing method is the same as the processing process of Step2 in Embodiment 1; The centralized situation analysis module is used to analyze the generated centralized distribution result, generate a warning signal and a secondary analysis signal by analyzing the magnitude of the allowable stress of the material and the real-time stress, then process the secondary analysis signal by analyzing the short-term trend of the real-time stress, analyze based on the calculated stress change rate, and generate a warning signal and a margin analysis signal. At the same time, calculate the magnitude of the safety margin and the reserved safety margin, generate a warning signal and a normal monitoring signal, and transmit the two to the information output module. And the specific processing method is the same as the processing process of Step3 in Embodiment 1; The non - centralized situation analysis module is used to analyze the obtained non - centralized results, screen out overloaded nodes based on the load of nodes, calculate the deformation value of overloaded nodes in combination with historical data, and calculate the average deformation value at the same time. The specific processing method is the same as the processing process of Step 4 in Embodiment 1. Then, analyze the relationship between the average deformation value and the load, calculate the corresponding load capacity based on the current deformation value, and analyze the load capacity in combination with historical data to generate normal monitoring signals and warning signals, and then transmit the two to the information output module. The specific processing method is the same as the processing process of Step 5 in Embodiment 1; The information output module is used to display the obtained normal signals and warning signals to the corresponding operators.

[0033] For some data in the above formula, only their numerical values are taken for calculation, and the parameter units are not substituted for calculation. At the same time, the content not described in detail in this specification belongs to the prior art well - known to those skilled in the art.

[0034] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A monitoring and early warning method for long-span steel arch buildings based on digital twins, characterized in that It includes the following steps: Step 1: Obtain the three-dimensional twin model of the long-span steel arch building through BIM technology, and at the same time obtain the sensor data and map the sensor data onto the three-dimensional twin model; Step 2: Obtain the real-time data of different nodes of the long-span steel arch building according to the three-dimensional twin model, and identify the concentration distribution of the real-time data under different working conditions to generate the concentrated distribution result and the non-concentrated distribution result; Step 3: Analyze the generated concentrated distribution result, generate a warning signal and a secondary analysis signal by comparing the allowable stress of the materials of the long-span steel arch building, and at the same time analyze the short-term stress change trend to process the secondary analysis signal to generate a normal monitoring signal and a warning signal; Step 4: Analyze the generated non-concentrated result, screen out the overloaded nodes, calculate the deformation value corresponding to the overloaded nodes according to the historical data, and comprehensively calculate the average deformation value; Step 5: Analyze the relationship between the obtained average deformation value and the load, calculate the load capacity based on the current deformation value, and analyze the load capacity in combination with the historical data to generate a normal monitoring signal and a warning signal.

2. The monitoring and early warning method for long-span steel arch buildings based on digital twins according to claim 1, wherein The specific method for Step 2 to generate the concentrated distribution result and the non-concentrated distribution result is as follows: Obtain all the nodes and label them as i, and i = 1, 2,..., j, where j represents the number of nodes. Then obtain the stress data Yi in the real-time data of node i, and identify the distribution of the stress data Yi under different working conditions to generate the concentrated distribution result and the non-concentrated distribution result.

3. The monitoring and early warning method for long-span steel arch buildings based on digital twins according to claim 1, characterized in that, The specific method for Step 3 to analyze the generated concentrated distribution result is as follows: Obtain the concentrated distribution result, and at the same time obtain the allowable stress of the materials of the long-span steel arch building, and compare the obtained real-time stress with the allowable stress of the materials. If the real-time stress is greater than the allowable stress of the materials, generate a warning signal; On the contrary, generate a secondary analysis signal, and at the same time analyze the secondary analysis signal to generate a margin analysis signal and a warning signal.

4. The monitoring and early warning method for long-span steel arch buildings based on digital twins according to claim 3, wherein, The specific method for Step 3 to analyze the secondary analysis signal to generate a margin analysis signal and a warning signal is as follows: Obtain all stress parameters of the steel arch structure within time t, and denote the obtained stress parameters as the stress data sequence y a , and at the same time obtain the first-order forward difference of the stress data sequence at the a-th time point , and obtain the corresponding time interval , then substitute the two into the formula to calculate the stress change rate v a ; By analogy, multiple groups of stress parameters within the time period t are collected, and the corresponding stress change rate v is calculated. a , and at the same time, according to the collection order, the change of the stress change rate v a is analyzed. Then, the change difference of the stress change rate v a between adjacent cycles is calculated, and the mean value of all change differences is calculated to obtain the change mean value. At the same time, the change mean value is compared with the preset value; If the change average value is greater than the preset value, it indicates that there is an abnormality in the stress change of the corresponding steel arch building, and a warning signal is generated; on the contrary, it indicates that the stress change of the corresponding steel arch building is normal, and a margin analysis signal is generated. At the same time, the margin analysis signal is processed to generate a normal monitoring signal and a warning signal.

5. The monitoring and early warning method for long-span steel arch buildings based on digital twins according to claim 4, characterized in that, The specific method for Step 3 to process the margin analysis signal to generate a normal monitoring signal and a warning signal is as follows: Calculate the safety margin of the structure according to the allowable stress of the material and the actual stress of the structure, and at the same time compare the obtained safety margin with the reserved safety margin. If the safety margin is greater than the reserved safety margin, it indicates that the safety margin can meet the corresponding production requirements, and a normal monitoring signal is generated; on the contrary, it indicates that the safety margin cannot meet the corresponding production requirements, and a warning signal is generated.

6. The monitoring and early warning method for long-span steel arch buildings based on digital twins according to claim 1, characterized in that, The specific method for Step 4 to analyze the generated non-concentrated result is as follows: Obtain all nodes, and at the same time obtain the load corresponding to node i. Compare the load of node i with the preset load, and then filter out the nodes whose node load is greater than the preset load, and record them as overloaded nodes, and label them as a, where a = 1, 2, …, b, and b represents the number of overloaded nodes; Then obtain the historical data corresponding to the overloaded node a, obtain the overloading times corresponding to the overloaded node a according to the historical data, record it as Ca, and obtain the deformation value LCa corresponding to the overloading times Ca. By analogy, obtain the deformation values corresponding to all overloaded nodes a. Then calculate the difference between the deformation values corresponding to adjacent two overloading times Ca, and record it as Lc. Similarly, calculate the deformation values of adjacent two times for all overloading times, and calculate the average value of all deformation differences, and record it as the deformation average value.

7. The monitoring and early warning method for long-span steel arch buildings based on digital twins according to claim 1, characterized in that, The specific way for Step 5 to generate normal monitoring signals and warning signals is as follows: Obtain all overloaded nodes a, generate a pressure-bearing area with the two groups of overloaded nodes a at the farthest distance, and obtain the corresponding area A of the pressure-bearing area. According to Hooke's law formula , where is stress, E is the elastic modulus of the material, is strain. At the same time, the external force F and the stress area A are known, then , strain , where is the change in length, that is, deformation, L is the original length, and further according to the formula is deformed to obtain , and the relationship between the load F and the deformation is analyzed; Substitute the deformation average value into the formula to calculate the load value corresponding to the pressure-bearing area. Then obtain the historical data, obtain the historical load condition corresponding to the pressure-bearing area, and judge whether the load value can meet the historical load condition. If it can be met, generate a load secondary analysis signal; otherwise, generate a warning signal, and at the same time analyze the load secondary analysis signal to generate normal monitoring signals and warning signals.

8. The monitoring and early warning method for long-span steel arch buildings based on digital twins according to claim 7, characterized in that, The specific way for Step 5 to analyze the load secondary analysis signal is as follows: Obtain the maximum historical load corresponding to the historical load condition, and compare the load value with the maximum historical load. If the load value is greater than the maximum historical load, generate a normal monitoring signal; otherwise, generate a warning signal.

9. A monitoring and early warning system for long-span steel arch buildings based on digital twins, which is used to execute the monitoring and early warning method for long-span steel arch buildings based on digital twins according to any one of claims 1-8, characterized in that, It includes a data acquisition module, a node analysis and identification module, a centralized situation analysis module, a non-centralized situation analysis module, and an information output module; The data acquisition module is used to obtain the real-time data of the long-span steel arch building according to the three-dimensional twin model, and at the same time transmit the real-time data to the node analysis and identification module; The node analysis and identification module is used to identify the distribution of different nodes of the long-span steel arch building under different working conditions according to the obtained real-time data, and generate a centralized distribution result and a non-centralized distribution result. At the same time, transmit the centralized distribution result to the centralized situation analysis module, and transmit the non-centralized distribution result to the non-centralized situation analysis module; The centralized situation analysis module is used to analyze the generated centralized distribution result, generate warning signals and secondary analysis signals by analyzing the magnitude of the allowable stress of the material and the real-time stress, and then process the secondary analysis signal by analyzing the short-term trend of the real-time stress, analyze based on the calculated stress change rate, and generate warning signals and margin analysis signals. At the same time, calculate the magnitude of the safety margin and the reserved safety margin, generate warning signals and normal monitoring signals, and transmit the two to the information output module; The non - centralized situation analysis module is used to analyze the obtained non - centralized results, screen out overloaded nodes based on the load of nodes, calculate the deformation value of the overloaded nodes in combination with historical data, and at the same time calculate the average deformation value. Then, analyze the relationship between the average deformation value and the load, calculate the corresponding load capacity based on the current deformation value, and analyze the load capacity in combination with historical data to generate normal monitoring signals and warning signals, and then transmit the two to the information output module; The information output module is used to display the obtained normal signals and warning signals to the corresponding operators.

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