Pressure monitoring method and device for steel cross beam assembly

Abstract

The invention discloses a pressure monitoring method and device for steel cross beam assembly, and relates to the technical field of structural engineering.The method comprises the steps that a steel cross beam assembly part comprising a cross beam body, a stand column side wall and the like is obtained, a nanoscale pressure sensor is connected to monitor the microscopic pressure of the steel cross beam assembly part in real time, and a pressure distribution diagram is synthesized; a flexible fabric material is adopted to be attached to a main body structure to obtain stress data, a sensing element connected with the top of a fixing part is used for monitoring pre-tightening force and stress distribution to obtain stress data, and a sensing element of an auxiliary supporting part is used for monitoring dynamic loads to obtain dynamic response data; overall pressure monitoring is carried out based on the data, and a bearing stability strategy is generated to ensure the assembly quality. The technical problem that existing steel cross beam assembly pressure monitoring is insufficient in precision, comprehensiveness and comprehensive analysis application is solved, and the technical effect of improving the steel cross beam assembly quality and the bearing performance and stability under various working conditions is achieved.

Description

Technical Field

[0001] The present application relates to the field of structural engineering technology, and in particular to a pressure monitoring method and device for steel beam assembly. Background Art

[0002] In the steel beam assembly scenario, the problem of ensuring assembly quality and stability is particularly prominent, and the contradiction between the demand for advanced, accurate and comprehensive monitoring technology is relatively more prominent. Effective assembly monitoring can better meet the safety needs of steel beams under different working conditions, which has become a crucial link in ensuring the quality of steel beam assembly. Traditional steel beam assembly monitoring technology is often extensive and one-sided, relying only on conventional pressure detection methods or local force analysis. It lacks overall monitoring of the steel beam assembly process and lacks in-depth analysis and utilization of multi-dimensional pressure data. It is difficult to comprehensively and accurately evaluate the pressure conditions of various components of the steel beam. In the comprehensive application of monitoring data, there are unreasonable situations, resulting in insufficient monitoring of some key parts and excessive monitoring of some non-key parts. The formulation of load-bearing stability strategies is relatively simple and fixed, and cannot cope well with the complex actual assembly of steel beams.

[0003] At present, relevant technologies still have technical problems in terms of accuracy, comprehensiveness and comprehensive analysis application of steel beam assembly pressure monitoring. Summary of the invention

[0004] The present application provides a pressure monitoring method and device for steel beam assembly, which obtains steel beam assembly parts including the beam body, column side walls, etc., connects nano-scale pressure sensors to monitor their microscopic pressure in real time and synthesizes a pressure distribution diagram; uses a flexible fabric material to fit the main structure to obtain force data, uses a sensor element on the top of the connecting and fixing component to monitor the preload and stress distribution to obtain stress data, and uses a sensor element on the auxiliary support component to monitor the dynamic load to obtain dynamic response data; based on the above data, the overall pressure is monitored and a load-bearing stability strategy is generated to ensure the assembly quality. By comprehensively and accurately monitoring the main structure assembly parts, connecting and fixing components, and auxiliary support components of the steel beam, and generating a load-bearing stability strategy based on the obtained multi-dimensional data, the technical effect of improving the assembly quality of the steel beam and the load-bearing performance and stability under various working conditions is achieved.

[0005] The present application provides a pressure monitoring method for steel beam assembly, comprising: Obtain steel beam assemblies, which include a beam body and column side walls corresponding to the main structure assembly part, and a bolt connection structure, an auxiliary fixing structure, and a shockproof isolation gasket corresponding to the connecting and fixing parts, and a connector, a limit plate, and a supporting mold frame corresponding to the auxiliary supporting parts; connect a nano-level pressure sensor to monitor the pressure of the steel beam assembly in real time during the steel beam assembly process, obtain pressure monitoring data, and synthesize a pressure distribution map; use a flexible fabric material with an integrated pressure sensing element, fit the flexible fabric material tightly to the surface of the main structure assembly part, perceive in real time and perform machine vision analysis to obtain the main structure assembly The pressure data corresponding to the parts are obtained; the change of the preload force is monitored by a pressure sensor installed on the top of the connecting and fixing component, the stress distribution of the connecting surface is monitored in real time, and the stress data corresponding to the connecting and fixing component is obtained; the dynamic load is monitored by a pressure sensor installed on the auxiliary support component, the dynamic load effect under actual working conditions is simulated, and the dynamic response data corresponding to the auxiliary support component are obtained; based on the pressure distribution diagram, combined with the force data corresponding to the assembly part of the main structure, the stress data corresponding to the connecting and fixing component, and the dynamic response data corresponding to the auxiliary support component, the overall pressure monitoring of the steel beam assembly process is carried out, and a load-bearing stability strategy is generated.

[0006] The present application also provides a pressure monitoring device for steel beam assembly, comprising: An accessory acquisition module, the accessory acquisition module is used to acquire steel beam assembly parts, the steel beam assembly parts include the beam body and column side walls corresponding to the main structure assembly part, and the bolt connection structure, auxiliary fixing structure, and shockproof isolation gasket corresponding to the connecting and fixing parts, and the connectors, limit plates, and support mold frames corresponding to the auxiliary support parts; a pressure distribution map synthesis module, the pressure distribution map synthesis module is used to connect the nano-level pressure sensor, and during the steel beam assembly process, the pressure of the steel beam assembly is monitored in real time, the pressure monitoring data is acquired, and the pressure distribution map is synthesized; a force data acquisition module, the force data acquisition module is used to use a flexible fabric material with an integrated pressure sensing element, tightly fit the flexible fabric material to the surface of the main structure assembly part, perceive in real time and perform machine vision analysis, and acquire the force data corresponding to the main structure assembly part. force data; a stress data acquisition module, the stress data acquisition module is used to monitor the change of the preload force by using a pressure sensor element installed on the top of the connecting and fixing component, monitor the stress distribution of the connecting surface in real time, and obtain the stress data corresponding to the connecting and fixing component; a dynamic response data acquisition module, the dynamic response data acquisition module is used to monitor the dynamic load by using a pressure sensor element installed on the auxiliary support component, simulate the dynamic load effect under actual working conditions, and obtain the dynamic response data corresponding to the auxiliary support component; a load-bearing stability strategy generation module, the load-bearing stability strategy generation module is used to perform overall pressure monitoring of the steel beam assembly process based on the pressure distribution diagram, combined with the force data corresponding to the assembly part of the main structure, the stress data corresponding to the connecting and fixing component, and the dynamic response data corresponding to the auxiliary support component, and generate a load-bearing stability strategy.

[0007] The pressure monitoring method and device for steel beam assembly proposed in this application are intended to first obtain steel beam assembly parts including the beam body, column side walls, etc., connect nano-scale pressure sensors to monitor their microscopic pressure in real time and synthesize a pressure distribution diagram; use flexible fabric materials to fit the main structure to obtain force data, use the sensor elements on the top of the connecting and fixing parts to monitor the preload and stress distribution to obtain stress data, and use the sensor elements of the auxiliary support parts to monitor the dynamic load to obtain dynamic response data; based on the above data, the overall pressure is monitored and a load-bearing stability strategy is generated to ensure the assembly quality, and the main structure assembly parts, connecting and fixing parts, and auxiliary support parts of the steel beam are comprehensively and accurately monitored, and a load-bearing stability strategy is generated based on the obtained multi-dimensional data, thereby achieving the technical effect of improving the assembly quality of the steel beam and the load-bearing performance and stability under various working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the device according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0009] Figure 1 A schematic flow chart of a pressure monitoring method for steel beam assembly provided in an embodiment of the present application; Figure 2 A schematic structural diagram of a pressure monitoring device for steel beam assembly provided in an embodiment of the present application.

[0010] Explanation of the reference numerals: accessory acquisition module 10 , pressure distribution diagram synthesis module 20 , force data acquisition module 30 , stress data acquisition module 40 , dynamic response data acquisition module 50 , load-bearing stability strategy generation module 60 . DETAILED DESCRIPTION

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0012] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0013] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, device, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0014] The present application embodiment provides a pressure monitoring method for steel beam assembly, such as Figure 1 As shown, the method includes: Step S100, obtaining steel beam assemblies, the steel beam assemblies include the beam body and column side walls corresponding to the main structure assembly part, and the bolt connection structure, auxiliary fixing structure, and shockproof isolation gasket corresponding to the connection and fixing parts, and the plug-in parts, limit plates, and support formwork corresponding to the auxiliary support parts. Specifically, the content covered by the steel beam assemblies is clear and specific. The main structure assembly part corresponds to the beam body and the column side walls. The connection and fixing parts include bolt connection structures, auxiliary fixing structures, and shockproof isolation gaskets. The auxiliary support parts correspond to plug-in parts, limit plates, and support formwork. When obtaining, for the main structure assembly part, it is necessary to focus on the material characteristics, dimensional accuracy, and structural strength of the beam body, the verticality, surface flatness, and matching accuracy of the column side walls with the beam body. In terms of connection and fixing parts, the bolt specifications, thread quality, and tightening force parameters of the bolt connection structure must be accurately set, the material selection and processing technology of the auxiliary fixing structure must meet the connection strength requirements, and the material elasticity and durability of the shockproof isolation gasket must meet the expected standards. In the acquisition of auxiliary support components, the smoothness of plugging and unplugging, the matching accuracy and the load-bearing capacity of the connectors must be strictly inspected, the dimensional accuracy, installation position and limiting effect of the limit plate must be accurately controlled, and the structural stability and load-bearing capacity of the support formwork must meet the design requirements. In short, in the process of obtaining steel beam assemblies, the various performance indicators of each component must be carefully considered and strictly controlled to ensure that the quality and performance of the assembly meet the assembly requirements. For example, in a large-scale steel structure construction project, the project team worked closely with a professional steel structure manufacturer. The manufacturer produced the main beam body and column side walls according to high-precision standards, and conducted multiple rounds of tightening force tests on the bolted connection structure. When the project team received the assembly, they used advanced testing equipment for comprehensive testing and found that some limit plates had slight deviations in size. The manufacturer was immediately asked to adjust, ensuring the high quality and high performance of the assembly.

[0015] Step S200, connect the nano-level pressure sensor, and during the steel beam assembly process, monitor the pressure of the steel beam assembly in real time, obtain pressure monitoring data, and synthesize a pressure distribution map. Specifically, the operation of connecting the nano-level pressure sensor and monitoring the pressure of the steel beam assembly includes a series of key steps. First, determine the type of nano-level pressure sensor required, and its performance must meet high-precision requirements. Prepare before assembling the steel beam, and install the sensor according to the specification to the key points of the assembly, usually the parts where significant pressure changes or high pressure are expected. After the assembly starts, the sensor senses and collects subtle pressure change data in real time and transmits it to the data processing unit. The data processing unit uses algorithms and analysis tools to screen, organize and calculate the data, and integrates it into a pressure distribution map with the help of mathematical models and image generation technology. During the process, the working status of the sensor and data transmission must be continuously monitored. If there is an abnormality, measures must be taken to ensure uninterrupted monitoring and accurate data. For example, in a specific project, the sensor is installed in the connection between the beam and the column and the important support area, and the pressure data is successfully monitored during assembly and a pressure distribution map is generated.

[0016] Step S300, using a flexible fabric material with an integrated pressure sensor element, closely fitting the flexible fabric material to the surface of the main structure assembly part, real-time sensing and machine vision analysis are performed to obtain the force data corresponding to the main structure assembly part. Specifically, the operation of using a flexible fabric material with an integrated pressure sensor element to obtain the force data of the main structure assembly part includes a series of key processes. First, a specific flexible fabric material that meets the high-precision sensing requirements is selected, and preparations are made before the operation. The material is closely fitted to the surface of the main structure assembly part in a rigorous and fine manner to ensure that there is no gap or wrinkle between the fabric and the surface. When assembling the steel beam, the pressure sensor element of the flexible fabric material senses the pressure in real time and transmits the signal to the data analysis system. The system uses advanced machine vision analysis technology to process the signal, converts it into force data through algorithms and image recognition, and obtains the force condition of the main structure assembly part. During the process, the fabric fitting state and the performance of the sensor element need to be regularly checked and calibrated to ensure that the force data is accurate and reliable. For example, in a large steel beam assembly project, the fabric is successfully bonded and accurate force data is obtained, and the process is adjusted accordingly to ensure assembly quality and structural stability.

[0017] In a possible implementation, a flexible fabric material with an integrated pressure sensing element is used, the flexible fabric material is closely attached to the surface of the main structure assembly part, and real-time perception and machine vision analysis are performed to obtain the force data corresponding to the main structure assembly part. Step S300 further includes step S310, the flexible fabric material is tightly wrapped on the surface of the main structure assembly part, and the pure force data corresponding to the main structure assembly part is obtained. Specifically, a suitable flexible fabric material is selected to ensure that it has uniform texture, good ductility and sensing performance. Then, the fabric material is carefully and cautiously wrapped tightly, evenly and without wrinkles on the surface of the main structure assembly part. During the wrapping process, the stretching or twisting of the fabric material should be avoided to ensure that it is in a natural and undisturbed state. Through this careful wrapping operation, the pressure sensing element integrated in the fabric material can directly and purely sense the force borne by the main structure assembly part, thereby obtaining accurate and pure force data without additional interference.

[0018] Step S320, use an adhesive to tightly fit the flexible fabric material on the surface of the main structure assembly part, and obtain the disturbance force data corresponding to the main structure assembly part. Specifically, prepare an appropriate amount of adhesive with suitable performance, and evenly apply it on the surface of the main structure assembly part and the side where the flexible fabric material needs to be attached. Then, fit the flexible fabric material to the main structure with a certain pressure to ensure that the adhesive fully plays a role and the fabric material is tightly combined with the surface. However, due to the presence of the adhesive, it may have a slight effect on the sensing performance of the fabric material, so that the force data obtained includes the disturbance factor caused by the adhesive, forming disturbance force data.

[0019] Step S330, taking the pure force data and the disturbance force data as a control group, setting a first calibration processing channel, and the calibration processing channel is communicatively connected with the integrated sensor network formed by the flexible fabric material. Specifically, the pure force data and the disturbance force data obtained previously are sorted and classified, and they are set as two sets of data for mutual comparison. Then, a first calibration processing channel is specially set up for data calibration and processing. This channel establishes a stable communication connection with the integrated sensor network formed by the flexible fabric material through a specific communication protocol and interface. In this way, the pure force data and the disturbance force data from the sensor network can be received and processed in real time, providing strong support for subsequent data calibration, analysis and optimization.

[0020] In a possible implementation, the pure force data and the disturbed force data are used as a control group, and a first calibration processing channel is set. The calibration processing channel is communicatively connected to the integrated sensor network formed by the flexible fabric material. Step S330 further includes step S331, using the pure force data and the disturbed force data as a control group, predicting short-term trends, and initializing the fixed calibration mode. Specifically, the acquired pure force data and disturbed force data are combined together to form a control group. Then, data analysis and prediction techniques are used to predict the trends that this set of data may present in the short term. Based on the prediction results, the various parameters and settings of the fixed calibration mode are preliminarily determined and adjusted to complete the initialization configuration. For example, basic parameters such as the frequency and amplitude of the calibration are determined to adapt to the short-term variation of the data.

[0021] Step S332, based on the autoregressive integrated moving average model, analyze the potential disturbance changes caused by internal small disturbances, and initialize the configuration of the random calibration mode. Specifically, the autoregressive integrated moving average model, a powerful analysis tool, is first introduced. This model can deeply explore the inherent laws and dynamic characteristics in the data. The pure force data and the disturbed force data are input into the model, and the potential disturbance changes caused by those small internal disturbances are analyzed in detail. According to the analysis results of these changes, the relevant parameters and rules of the random calibration mode are initially set and arranged. For example, the trigger conditions of the random calibration, the range of the adjustment amplitude, etc. are determined to prepare for the effective operation of the subsequent random calibration mode.

[0022] In a possible implementation, based on the autoregressive integrated moving average model, the potential disturbance changes caused by the internal small disturbances are analyzed, and the random calibration mode is initialized and configured. Step S332 further includes step S3321, taking the pure force data and the disturbance force data as control groups, and quantifying the prediction accuracy through probability inference. , where the input feature X is the assembly parameter, and P is used to characterize the model parameter θ of the autoregressive integrated moving average model and the prediction accuracy of the i-th item under the input feature X. Specifically, firstly, the collected force data are classified and sorted, and the pure force data obtained by a specific method and the disturbed force data caused by certain factors are distinguished. In order to facilitate subsequent analysis and comparison, these two groups of data are managed as a control group. Each group of data is annotated and recorded in detail, including the time, location, and corresponding assembly parts of the data collection. At the same time, the input feature X is determined as the assembly parameter. The assembly parameter is the key factor affecting the stress condition, such as the tightening degree of the bolts, the splicing method of the parts, etc. Through precise measurement and recording methods, the accuracy and reliability of the assembly parameters are ensured. A preliminary statistical analysis is performed on the pure stress data and the disturbed stress data to understand the characteristics of their data distribution, such as the mean, variance, maximum value, minimum value, etc., which is helpful for the subsequent evaluation of the prediction accuracy and the configuration of the loss function. The structure and mechanism of the autoregressive integrated moving average model are clarified. The model can predict the stress condition based on the input assembly parameter X and the model parameter Θ through learning and analyzing historical data. Among them, the prediction accuracy , which indicates the prediction accuracy of the i-th force data under the given assembly parameter step X and model parameter Θ, through the function To quantify the prediction accuracy, It represents the variance between the model prediction value and the actual value. The smaller the variance, the higher the accuracy. The relationship between the model parameter Θ and the input feature X is analyzed. Through training and optimization of historical data, the model parameter Θ is adjusted so that the model can better adapt to different assembly parameters X, thereby improving the prediction accuracy.

[0023] S3322, configure loss function , according to the loss function and the prediction accuracy, the autoregressive integrated moving average model is gradually converged in a sliding equilibrium manner, N is the number of samples in the control group, is the i-th pure force data of the control group, is the i-th disturbance force data of the control group, is the predicted force data for the i-th item, is a weight parameter for balancing the error terms corresponding to the pure force data and the perturbation force data. Specifically, the loss function is configured as .in, represents the sum of squares of the errors between pure force data and predicted force data, Represents the sum of squares of the errors between the disturbance force data and the predicted force data. By weighted summing these two parts of the error, the total loss function is obtained. The weight parameter Used to balance the error terms corresponding to pure force data and disturbed force data, and adjust according to actual conditions The value of can make the loss function focus more on pure data or perturbed data, or strike a balance between the two, and analyze the meaning and role of each item in the loss function Indicates pure force data With the model prediction value By minimizing the loss function, the predicted value of the model can be closer to the actual force data, thereby improving the accuracy of the model. N represents the number of samples in the control group, which plays a normalizing role in the loss function. By dividing the sum of squared errors by the number of samples N, the average error can be obtained, making the loss function more representative and comparable. is the i-th pure force data of the control group, is the i-th disturbance force data of the control group, To predict the force data for the i-th item, when calculating the loss function, it is necessary to traverse each sample in the control group, substitute its corresponding pure force data, perturbed force data and predicted force data into the loss function for calculation, and gradually converge the autoregressive integrated moving average model in a sliding equilibrium manner according to the loss function and the prediction accuracy. In each iteration process, the predicted force data is first calculated according to the current model parameter Θ , then, the pure force data , disturbance force data and predicted force data Substitute into the loss function In the process, the value of the loss function is calculated, and the direction and step size of the parameter update are determined according to the gradient of the loss function to the model parameter θ. , so that the loss function achieves a balance between pure force data and disturbed force data, achieves the effect of sliding equilibrium, and continuously monitors the value of the loss function. When the loss function gradually converges to a smaller threshold range, the iteration is stopped. The model parameter θ obtained at this time is the result after convergence. The model can better predict the force condition of the steel beam. In the process of model convergence, it is necessary to continuously evaluate the performance and accuracy of the model. The prediction accuracy can be calculated. , plot the loss function versus the number of iterations to evaluate the convergence of the model. If the model converges too slowly or overfitting occurs, you can adjust the model parameters, increase data samples, use regularization methods and other measures to optimize the model performance. Dynamically adjust the weight parameter λ according to actual conditions to adapt to different data distributions and prediction requirements.

[0024] Step S400, use the pressure sensor element installed on the top of the connecting and fixing component to monitor the change of the preload force, monitor the stress distribution of the connection surface in real time, and obtain the stress data corresponding to the connecting and fixing component. Specifically, the operation of using the pressure sensor element installed on the top of the connecting and fixing component to obtain stress data covers a series of key links, determining the type of adapted pressure sensor element, and its performance must meet the high-precision monitoring requirements for the change of preload force and stress distribution of the connecting and fixing component. Before the actual operation, make sufficient preparations and accurately install the pressure sensor element at the top position of the connecting and fixing component. This installation process is demanding, and it is imperative to ensure that the sensor element fits tightly to the surface of the component and that the position is accurate and without deviation, so as to ensure that the slightest changes in the preload force can be accurately sensed. When the steel beam assembly operation is carried out, the installed pressure sensor element is immediately put into operation. The pressure sensing element continuously captures any subtle changes in the preload force and quickly converts these changes into electrical signals to transmit to the data acquisition system. The pressure sensing element also monitors the stress distribution of the connection surface in real time. By sensitively sensing the stress differences at different positions, the stress condition of the connection surface is fully and meticulously grasped. After the data acquisition system receives the electrical signal from the pressure sensing element, it undergoes a series of fine processing and in-depth analysis, and finally successfully obtains the precise stress data corresponding to the connection and fixing components. For example, in a steel beam assembly project of a large steel structure building, technicians carefully selected highly sensitive pressure sensing elements and accurately installed them on the top of the connection components. During the assembly process, these sensing elements excellently monitor the changes in the preload force and the distribution of stress on the connection surface, providing key data support for ensuring the stability of the building structure.

[0025] In one possible implementation, a pressure sensing element installed on the top of the connecting and fixing component is used to monitor the change of the preload force, monitor the stress distribution of the connection surface in real time, and obtain the stress data corresponding to the connecting and fixing component. Step S400 further includes step S410, collecting the stress distribution data of the connection surface based on the connecting and fixing component, and obtaining the overall surface stress distribution data corresponding to the connecting and fixing component. Specifically, for the connecting and fixing component, special stress monitoring equipment and technology are used to comprehensively collect stress distribution data at various positions on the connection surface. These data cover the situation of the entire connection surface, including stress values ​​in different areas and directions. By comprehensively analyzing and processing these widely collected data, the overall surface stress distribution data corresponding to the connecting and fixing component can be obtained to fully understand the stress state of the connection surface.

[0026] Step S420, the pressure sensing element at the top of the connecting and fixing component monitors the change of the preload force and obtains the local surface stress distribution data corresponding to the connecting and fixing component. Specifically, a high-precision pressure sensing element is installed on the top of the connecting and fixing component. During assembly and use, these sensing elements focus on monitoring the change of the preload force. Due to the particularity of their position, the data obtained mainly reflects the surface stress distribution of the local area at the top of the connecting component. By analyzing and processing these local monitoring data, the local surface stress distribution data corresponding to the connecting and fixing component is obtained, which provides key local information for a deeper understanding of the stress characteristics of the connecting component.

[0027] Step S430, the overall surface stress distribution data and the local surface stress distribution data are used as a control group, and a second calibration processing channel is set. Specifically, the overall surface stress distribution data and the local surface stress distribution data obtained previously are combined as two sets of data for mutual comparison. Then, a mechanism or system called the second calibration processing channel is specially set up. This channel can compare, analyze and process the two sets of control data to find out the differences and correlations between the data, thereby calibrating and optimizing the monitoring system and improving the accuracy and reliability of stress monitoring.

[0028] Step S500, using the pressure sensing element installed on the auxiliary support component to monitor the dynamic load, simulate the dynamic load effect under the actual working condition, and obtain the dynamic response data corresponding to the auxiliary support component. Specifically, the operation of obtaining the dynamic response data using the pressure sensing element installed on the auxiliary support component includes a series of key steps. First, the auxiliary support component to be monitored is clearly defined, and the appropriate type of pressure sensing element is carefully selected, and its performance must meet the high-precision monitoring requirements for the dynamic load. Before the formal operation, sufficient preparations are made to accurately and firmly install the pressure sensing element at a specific position of the auxiliary support component. This installation process requires extremely strict requirements. It must ensure that the connection between the sensing element and the component is tight and stable, and the position is accurate to ensure that the dynamic load can be accurately monitored. When the relevant monitoring work is started, the installed pressure sensing element is immediately put into operation. They continuously monitor the dynamic load acting on the auxiliary support component in real time, accurately capture the changes in key parameters such as the size, direction, and frequency of the load, and use professional simulation software or experimental equipment to simulate various dynamic load situations that may occur under actual working conditions. For example, by simulating the vibration load on the structure caused by the operation of large machinery, or the impact load on the structure caused by severe weather conditions, through the real-time monitoring of the pressure sensor element and the coordinated work of the simulation equipment, a series of response data of the auxiliary support components under different dynamic loads can be comprehensively obtained, such as displacement, strain value, acceleration, etc. These data together constitute the precise dynamic response data corresponding to the auxiliary support components. For example, in a construction monitoring project of a large steel structure building, technicians installed high-performance pressure sensor elements on the auxiliary support components, and successfully obtained detailed and accurate dynamic response data by simulating the dynamic loads under actual working conditions, which provided a key basis for the safety assessment and optimal design of the building structure.

[0029] In a possible implementation, the dynamic load is monitored by using a pressure sensor installed on the auxiliary support component to simulate the dynamic load effect under actual working conditions, and the dynamic response data corresponding to the auxiliary support component is obtained. Step S500 further includes step S510, based on the auxiliary support component, collecting the pressure change data under different dynamic load conditions, and obtaining the dynamic pressure distribution data corresponding to the connecting and fixing component. Specifically, for the auxiliary support component, a comprehensive data acquisition system is established, and under various dynamic load conditions, such as different vibration frequencies, different impact forces, etc., high-precision pressure sensors are used to collect pressure change data in real time, and data from different conditions are sorted and analyzed, so as to obtain the dynamic pressure distribution data corresponding to the connecting and fixing component, so as to clearly understand the distribution of pressure under different dynamic loads.

[0030] Step S520, based on the auxiliary support component, the dynamic load under the actual working condition is simulated under the current load condition to obtain the simulated pressure distribution data corresponding to the connecting and fixing component. Specifically, based on the auxiliary support component, under the current load condition, advanced simulation technology and software are used to accurately simulate various complex dynamic load conditions that may occur in the actual working condition, and through in-depth analysis of the simulation results, the simulated pressure distribution data corresponding to the connecting and fixing component is obtained to provide a reference for subsequent comparison and calibration.

[0031] Step S530, the dynamic pressure distribution data and the simulated pressure distribution data are used as a control group, and a third calibration processing channel is set up. Specifically, the previously acquired dynamic pressure distribution data and simulated pressure distribution data are integrated into a pair of control groups, and a third calibration processing channel is specially set up. This channel can perform detailed comparison, analysis and processing on these two sets of data. By finding out the differences and similarities between the two, the monitoring and simulation systems are calibrated and optimized, thereby improving the accuracy and reliability of the data. For example, in a monitoring project of a bridge structure, the above operation is performed on the auxiliary support components, and the relevant data is successfully obtained and the design and maintenance plan of the bridge structure is optimized through the calibration processing channel.

[0032] Step S600, based on the pressure distribution diagram, combined with the force data corresponding to the assembly part of the main structure, the stress data corresponding to the connecting and fixing parts, and the dynamic response data corresponding to the auxiliary support parts, the overall pressure monitoring of the steel beam assembly process is carried out, and a load-bearing stability strategy is generated. Specifically, the operation of carrying out the overall pressure monitoring of the steel beam assembly process and generating a load-bearing stability strategy based on the pressure distribution diagram and combined with the force data corresponding to the assembly part of the main structure, the stress data corresponding to the connecting and fixing parts, and the dynamic response data corresponding to the auxiliary support parts includes a series of key processes. First, a detailed pressure distribution diagram is obtained to present the pressure distribution status of the steel beam assembly, and then the above-mentioned various types of data are integrated, and an in-depth and comprehensive analysis is carried out to grasp the mechanical state. In the analysis, the factors affecting the assembly pressure of the steel beam, such as material properties, assembly process, and external environment, are comprehensively considered, and a comprehensive assessment is made to monitor the pressure changes in all directions.

[0033] In a possible implementation, based on the pressure distribution diagram, combined with the force data corresponding to the main structure assembly part, the stress data corresponding to the connecting and fixing parts, and the dynamic response data corresponding to the auxiliary support parts, the overall pressure monitoring of the steel beam assembly process is performed, and a load-bearing stability strategy is generated. Step S600 further includes step S610, based on the surface pretreatment process corresponding to the main structure assembly part, the surface roughness is extracted. Specifically, the surface pretreatment process used in the main structure assembly part is clarified, including operations such as grinding, polishing, and sandblasting, and a special roughness measuring instrument or equipment is used to measure the pretreated surface according to relevant measurement standards and methods. A numerical value that can accurately reflect the degree of surface roughness, that is, the surface roughness, is extracted from the measurement results.

[0034] Step S620, based on the preload torque verification algorithm corresponding to the connection and fixing component, extract the preload force data. Specifically, for the connection and fixing component, determine the corresponding preload torque verification algorithm, which is usually established based on mechanical principles and component characteristics, and use relevant measurement tools and techniques to operate according to the requirements of the verification algorithm to obtain the actual measurement value of the preload torque. The measured value of the preload torque is converted into preload force data through the algorithm, and the accurate preload force value is extracted from it.

[0035] Step S630, connect the laser alignment instrument corresponding to the auxiliary support component to extract the installation deviation data, the laser alignment instrument is used to monitor the verticality and flatness of the auxiliary support component. Specifically, connect and set the laser alignment instrument to the auxiliary support component. Start the laser alignment instrument so that the laser beam it emits can accurately irradiate the auxiliary support component. By receiving and analyzing the reflected signal of the laser, the laser alignment instrument can monitor the verticality and flatness of the auxiliary support component. From the data obtained by the instrument, extract the specific value that can reflect the installation deviation, that is, the installation deviation data.

[0036] Step S640, through the surface roughness, preload data, and installation deviation data, the force data corresponding to the main structure assembly part, the stress data corresponding to the connecting and fixing parts, and the dynamic response data corresponding to the auxiliary support parts are corrected as a whole. Specifically, the surface roughness, preload data, and installation deviation data extracted previously are comprehensively compared and analyzed with the force data corresponding to the main structure assembly part, the stress data corresponding to the connecting and fixing parts, and the dynamic response data corresponding to the auxiliary support parts. According to the actual situation reflected by these additional data, the original force, stress, and dynamic response data are adjusted and corrected. Through correction, these data can more accurately reflect the real mechanical state of the steel beam assembly. For example, in a specific steel beam assembly project, the data are accurately extracted and corrected according to the above steps, which effectively improves the accuracy of the data and provides a reliable basis for the evaluation and optimization of assembly quality.

[0037] The embodiment of the present application adopts the method of obtaining steel beam assembly parts including the beam body, column side walls, etc., connecting nano-scale pressure sensors to monitor the microscopic pressure in real time and synthesize the pressure distribution diagram; using flexible fabric materials to fit the main structure to obtain force data, using the sensor elements on the top of the connecting and fixing parts to monitor the preload and stress distribution to obtain stress data, and using the sensor elements of the auxiliary support parts to monitor the dynamic load to obtain dynamic response data; based on the above data, the overall pressure is monitored and a load-bearing stability strategy is generated to ensure the assembly quality, thereby achieving the technical effect of improving the assembly quality of the steel beam and the load-bearing performance and stability under various working conditions by comprehensively and accurately monitoring the main structure assembly parts, connecting and fixing parts, and auxiliary supporting parts of the steel beam, and generating a load-bearing stability strategy based on the obtained multi-dimensional data.

[0038] In the above, refer to Figure 1 The pressure monitoring method for steel beam assembly according to an embodiment of the present invention is described in detail. Figure 2 A pressure monitoring device for steel beam assembly according to an embodiment of the present invention is described.

[0039] The pressure monitoring device for steel beam assembly according to the embodiment of the present invention is used to solve the technical problems of the existing steel beam assembly pressure monitoring in terms of accuracy, comprehensiveness and comprehensive analysis application. By comprehensively and accurately monitoring the main structure assembly parts, connecting and fixing parts, and auxiliary support parts of the steel beam, and generating a load-bearing stability strategy based on the acquired multi-dimensional data, the technical effect of improving the steel beam assembly quality and the load-bearing performance and stability under various working conditions is achieved. The pressure monitoring device for steel beam assembly includes: an accessory acquisition module 10, a pressure distribution diagram synthesis module 20, a force data acquisition module 30, a stress data acquisition module 40, a dynamic response data acquisition module 50, and a load-bearing stability strategy generation module 60.

[0040] The accessory acquisition module 10 is used to acquire steel beam assembly parts, which include the beam body and column side walls corresponding to the main structure assembly part, and the bolt connection structure, auxiliary fixing structure, and shockproof isolation gasket corresponding to the connection and fixing parts, and the connector, limit plate, and support formwork corresponding to the auxiliary support parts; The pressure distribution diagram synthesis module 20 is used to connect the nano-level pressure sensor, monitor the pressure of the steel beam assembly in real time during the steel beam assembly process, obtain pressure monitoring data, and synthesize the pressure distribution diagram; The force data acquisition module 30 is used to use a flexible fabric material with an integrated pressure sensor element, closely fit the flexible fabric material to the surface of the main structure assembly part, sense in real time and perform machine vision analysis to obtain the force data corresponding to the main structure assembly part; The stress data acquisition module 40 is used to monitor the change of the preload force by using a pressure sensor element installed on the top of the connection fixing component, monitor the stress distribution of the connection surface in real time, and obtain the stress data corresponding to the connection fixing component; The dynamic response data acquisition module 50 is used to monitor the dynamic load by using the pressure sensor element installed on the auxiliary support component, simulate the dynamic load effect under the actual working condition, and acquire the dynamic response data corresponding to the auxiliary support component; The load-bearing stability strategy generation module 60 is used to perform overall pressure monitoring of the steel beam assembly process and generate a load-bearing stability strategy based on the pressure distribution diagram, combined with the force data corresponding to the main structure assembly part, the stress data corresponding to the connecting and fixing components, and the dynamic response data corresponding to the auxiliary support components.

[0041] The specific configuration of the force data acquisition module 30 will be described in detail below. As described above, a flexible fabric material with an integrated pressure sensor element is used, the flexible fabric material is tightly attached to the surface of the main structure assembly part, and real-time perception and machine vision analysis are performed to obtain the force data corresponding to the main structure assembly part. The force data acquisition module 30 further includes: a pure force data acquisition unit, the pure force data acquisition unit is used to tightly wrap the flexible fabric material on the surface of the main structure assembly part to obtain the pure force data corresponding to the main structure assembly part; A disturbance force data acquisition unit, the disturbance force data acquisition unit is used to use an adhesive to tightly fit the flexible fabric material to the surface of the main structure assembly part, and acquire disturbance force data corresponding to the main structure assembly part; A communication connection unit is used to use the pure force data and the disturbance force data as a control group, set a first calibration processing channel, and the calibration processing channel is communicatively connected to the integrated sensor network formed by the flexible fabric material.

[0042] Wherein, the communication connection unit is used to use the pure force data and the disturbance force data as a control group, set up a first calibration processing channel, and the calibration processing channel is communicatively connected to the integrated sensor network formed by the flexible fabric material. The communication connection unit further includes: an initialization configuration subunit, the initialization configuration subunit is used to use the pure force data and the disturbance force data as a control group, predict short-term trends, and initialize the fixed calibration mode; a disturbance change analysis subunit, the disturbance change analysis subunit is used to analyze the potential disturbance changes caused by internal small disturbances based on the autoregressive integrated moving average model, and initialize the random calibration mode.

[0043] The disturbance change analysis subunit is used to analyze the potential disturbance changes caused by internal small disturbances based on the autoregressive integrated moving average model, and initialize the random calibration mode. The disturbance change analysis subunit further includes: a probability inference microunit, which is used to use the pure force data and the disturbance force data as a control group, and quantify the prediction accuracy through probability inference. , where the input feature X is the assembly parameter, P is used to characterize the model parameter θ of the autoregressive integrated moving average model and the prediction accuracy of the i-th item under the input feature X; a convergence training unit, which is used to configure the loss function , according to the loss function and the prediction accuracy, the autoregressive integrated moving average model is gradually converged in a sliding equilibrium manner, N is the number of samples in the control group, is the i-th pure force data of the control group, is the i-th disturbance force data of the control group, is the predicted force data for the i-th item, It is a weight parameter for balancing the error terms corresponding to the pure force data and the disturbance force data.

[0044] The specific configuration of the stress data acquisition module 40 will be described in detail below. As described above, a pressure sensing element installed on the top of the connecting and fixing component is used to monitor the change of the preload force, monitor the stress distribution of the connection surface in real time, and obtain the stress data corresponding to the connecting and fixing component. The stress data acquisition module 40 further includes: an overall surface stress distribution data acquisition unit, which is used to collect the connection surface stress distribution data based on the connecting and fixing component and obtain the overall surface stress distribution data corresponding to the connecting and fixing component; a local surface stress distribution data acquisition unit, which is used to monitor the change of the preload force at the pressure sensing element on the top of the connecting and fixing component and obtain the local surface stress distribution data corresponding to the connecting and fixing component; a second calibration processing channel setting unit, which is used to use the overall surface stress distribution data and the local surface stress distribution data as a control group to set a second calibration processing channel.

[0045] The specific configuration of the dynamic response data acquisition module 50 will be described in detail below. As described above, the dynamic load is monitored by using the pressure sensing element installed in the auxiliary support component to simulate the dynamic load effect under the actual working condition, and the dynamic response data corresponding to the auxiliary support component is obtained. The dynamic response data acquisition module 50 further includes: a dynamic pressure distribution data unit, which is used to collect pressure change data under different dynamic load conditions based on the auxiliary support component, and obtain the dynamic pressure distribution data corresponding to the connecting and fixing component; a simulated pressure distribution data acquisition unit, which is used to obtain the simulated pressure distribution data corresponding to the connecting and fixing component based on the auxiliary support component and simulate the dynamic load effect under the actual working condition under the current load condition; a third calibration processing channel setting unit, which is used to use the dynamic pressure distribution data and the simulated pressure distribution data as a control group to set a third calibration processing channel.

[0046] The specific configuration of the load-bearing stability strategy generation module 60 will be described in detail below. As described above, based on the pressure distribution diagram, combined with the force data corresponding to the main structure assembly part, the stress data corresponding to the connecting and fixing parts, and the dynamic response data corresponding to the auxiliary support parts, the pressure of the steel beam assembly process is monitored as a whole, and a load-bearing stability strategy is generated. The load-bearing stability strategy generation module 60 further includes: a surface roughness extraction unit, the surface roughness extraction unit is used to extract surface roughness based on the surface pretreatment process corresponding to the main structure assembly part; a preload data extraction unit, the preload data extraction unit is used to extract preload data based on the preload torque verification algorithm corresponding to the connecting and fixing parts; an installation deviation data extraction unit, the installation deviation data extraction unit is used to connect the laser alignment instrument corresponding to the auxiliary support part to extract installation deviation data, and the laser alignment instrument is used to monitor the verticality and flatness of the auxiliary support part; an overall correction unit, the overall correction unit is used to perform overall correction on the force data corresponding to the main structure assembly part, the stress data corresponding to the connecting and fixing parts, and the dynamic response data corresponding to the auxiliary support parts through the surface roughness, preload data, and installation deviation data.

[0047] The pressure monitoring device for steel beam assembly provided in the embodiment of the present invention can execute the pressure monitoring method for steel beam assembly provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0048] Although the present application makes various references to certain modules in the device according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0049] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A pressure monitoring method for steel beam assembly, characterized in that: The method comprises: Obtain steel beam assemblies, which include a beam body and column side walls corresponding to the main structure assembly part, and a bolt connection structure, an auxiliary fixing structure, and a shockproof isolation gasket corresponding to the connecting and fixing parts, and a connector, a limit plate, and a supporting formwork corresponding to the auxiliary supporting parts; Connecting a nano-scale pressure sensor to monitor the pressure of the steel beam assembly in real time during the steel beam assembly process, obtain pressure monitoring data, and synthesize a pressure distribution diagram; A flexible fabric material with an integrated pressure sensor element is used to closely fit the flexible fabric material to the surface of the main structure assembly part, and real-time sensing and machine vision analysis are performed to obtain the force data corresponding to the main structure assembly part; A pressure sensing element installed on the top of the connecting and fixing component is used to monitor the change of the preload force, monitor the stress distribution of the connecting surface in real time, and obtain the stress data corresponding to the connecting and fixing component; Using a pressure sensor installed on the auxiliary support component to monitor the dynamic load, simulate the dynamic load effect under actual working conditions, and obtain dynamic response data corresponding to the auxiliary support component; Based on the pressure distribution diagram, combined with the force data corresponding to the main structure assembly parts, the stress data corresponding to the connecting and fixing components, and the dynamic response data corresponding to the auxiliary support components, the overall pressure monitoring of the steel beam assembly process is carried out, and a load-bearing stability strategy is generated.

2. The pressure monitoring method for steel beam assembly according to claim 1, characterized in that: Based on the pressure distribution diagram, combined with the force data corresponding to the main structure assembly part, the stress data corresponding to the connecting and fixing components, and the dynamic response data corresponding to the auxiliary support components, the overall pressure monitoring of the steel beam assembly process is performed, and the method includes: Extracting surface roughness based on the surface pretreatment process corresponding to the assembly part of the main structure; Extracting preload force data based on a preload torque verification algorithm corresponding to the connecting and fixing component; Connecting the laser alignment instrument corresponding to the auxiliary support component to extract installation deviation data, wherein the laser alignment instrument is used to monitor the verticality and flatness of the auxiliary support component; The force data corresponding to the assembly part of the main structure, the stress data corresponding to the connecting and fixing components, and the dynamic response data corresponding to the auxiliary supporting components are corrected as a whole through the surface roughness, preload force data, and installation deviation data.

3. The pressure monitoring method for steel beam assembly according to claim 2, characterized in that: A flexible fabric material with an integrated pressure sensing element is used to closely fit the flexible fabric material to the surface of the main structure assembly part, and real-time sensing and machine vision analysis are performed to obtain force data corresponding to the main structure assembly part. The method includes: Wrapping the flexible fabric material tightly on the surface of the main structure assembly part to obtain pure force data corresponding to the main structure assembly part; Using an adhesive to tightly adhere the flexible fabric material to the surface of the main structure assembly part, and obtaining disturbance force data corresponding to the main structure assembly part; The pure force data and the disturbance force data are used as a control group, and a first calibration processing channel is set. The calibration processing channel is communicatively connected with the integrated sensor network formed by the flexible fabric material.

4. The pressure monitoring method for steel beam assembly according to claim 3, characterized in that: The pure force data and the disturbed force data are used as a control group, and a first calibration processing channel is set. The method includes: The pure force data and the disturbed force data are used as a control group to predict short-term trends and initialize the fixed calibration mode; Based on the autoregressive integrated moving average model, the potential disturbance changes caused by small internal disturbances are analyzed, and the random calibration mode is initialized and configured.

5. The pressure monitoring method for steel beam assembly according to claim 4, characterized in that: Based on the autoregressive integrated moving average model, the potential disturbance changes caused by the internal small disturbance are analyzed, and the random calibration mode is initialized and configured. The method includes: The pure force data and the disturbed force data are used as control groups, and the prediction accuracy is quantified through probability inference. , where the input feature X is the assembly parameter, and P is used to characterize the model parameter θ of the autoregressive integrated moving average model and the prediction accuracy of the i-th item under the input feature X; Configuring the loss function , according to the loss function and the prediction accuracy, the autoregressive integrated moving average model is gradually converged in a sliding equilibrium manner, N is the number of samples in the control group, is the i-th pure force data of the control group, is the i-th disturbance force data of the control group, is the predicted force data for the i-th item, It is a weight parameter for balancing the error terms corresponding to the pure force data and the disturbance force data.

6. The pressure monitoring method for steel beam assembly according to claim 3, characterized in that: A pressure sensing element installed on the top of the connecting and fixing component is used to monitor the change of the preload force, monitor the stress distribution of the connecting surface in real time, and obtain the stress data corresponding to the connecting and fixing component. The method includes: Based on the connecting and fixing component, connecting surface stress distribution data is collected to obtain overall surface stress distribution data corresponding to the connecting and fixing component; A pressure sensing element at the top of the connecting and fixing component monitors the change of the preload force and obtains the local surface stress distribution data corresponding to the connecting and fixing component; The overall surface stress distribution data and the local surface stress distribution data are used as a control group, and a second calibration processing channel is set.

7. The pressure monitoring method for steel beam assembly according to claim 3, characterized in that: The method comprises: monitoring the dynamic load by using a pressure sensor element installed on the auxiliary support component, simulating the dynamic load effect under actual working conditions, and obtaining the dynamic response data corresponding to the auxiliary support component. Based on the auxiliary support component, collecting pressure change data under different dynamic load conditions, and obtaining dynamic pressure distribution data corresponding to the connecting and fixing component; Based on the auxiliary support component, the dynamic load effect under the actual working condition is simulated under the current load condition to obtain the simulated pressure distribution data corresponding to the connecting and fixing component; The dynamic pressure distribution data and the simulated pressure distribution data are used as a control group, and a third calibration processing channel is set.

8. A pressure monitoring device for steel beam assembly, characterized in that: The device is used to implement the pressure monitoring method for steel beam assembly according to any one of claims 1 to 7, and the device comprises: An accessory acquisition module, the accessory acquisition module is used to acquire steel beam assembly parts, the steel beam assembly parts include a beam body and a column side wall corresponding to the main structure assembly part, and a bolt connection structure, an auxiliary fixing structure, and a shockproof isolation gasket corresponding to the connection and fixing parts, and a connector, a limit plate, and a support formwork corresponding to the auxiliary support parts; A pressure distribution diagram synthesis module, wherein the pressure distribution diagram synthesis module is used to connect to a nano-level pressure sensor, monitor the pressure of the steel beam assembly in real time during the steel beam assembly process, obtain pressure monitoring data, and synthesize a pressure distribution diagram; A force data acquisition module, wherein the force data acquisition module is used to use a flexible fabric material with an integrated pressure sensor element, closely fit the flexible fabric material to the surface of the main structure assembly part, sense in real time and perform machine vision analysis to acquire force data corresponding to the main structure assembly part; A stress data acquisition module, wherein the stress data acquisition module is used to monitor the change of the preload force by using a pressure sensor element installed on the top of the connecting and fixing component, monitor the stress distribution of the connecting surface in real time, and obtain the stress data corresponding to the connecting and fixing component; A dynamic response data acquisition module, which is used to monitor the dynamic load by using a pressure sensor element installed on the auxiliary support component, simulate the dynamic load effect under actual working conditions, and acquire the dynamic response data corresponding to the auxiliary support component; A load-bearing stability strategy generation module is used to perform overall pressure monitoring of the steel beam assembly process and generate a load-bearing stability strategy based on the pressure distribution diagram, combined with the force data corresponding to the main structure assembly part, the stress data corresponding to the connecting and fixing parts, and the dynamic response data corresponding to the auxiliary support parts.

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