A monitoring and management method for the installation process of an assembled structure

Abstract

The present invention discloses a method for monitoring and managing the installation process of an assembled structure, and relates to the field of construction engineering technology. The method comprises: obtaining a first assembly connection node according to the assembly structure installation plan, performing geometric accuracy, tightness and load-bearing characteristic safety tests through an assembly sensor monitoring platform, obtaining corresponding data, collating and generating a monitoring report, judging whether the constraint conditions are met, and generating an early warning signal if they are not met. The technical problems of low accuracy and poor timeliness of assembly early warning of connection nodes of assembled structures in the prior art are solved, and by improving the accuracy and timeliness of assembly early warning of connection nodes of assembled structures, the quality and safety of assembled structures are guaranteed, and the technical effects of optimizing installation processes and project management are achieved.

Description

Technical Field

[0001] The present application relates to the field of construction engineering technology, and in particular to a method for monitoring and managing the installation process of an assembled structure. Background Art

[0002] In the installation scenario of prefabricated structures, the quality and safety issues of connection nodes are particularly prominent, and the contradiction between the accuracy and timeliness of node assembly warnings is relatively more prominent. Achieving accurate and timely assembly warnings has become a crucial link in ensuring the quality and safety of prefabricated structure installation. Traditional assembly warnings for prefabricated structure connection nodes are often one-sided and limited, relying only on limited detection methods or manual experience, and lacking an overall grasp of the node status. There is a lack of comprehensive and in-depth data monitoring and analysis, making it difficult to accurately assess the assembly status of the nodes. In terms of warnings, there are inaccuracies and delays, resulting in some potential problems not being discovered in time, and some false alarms causing waste of resources. The formulation of warning plans is relatively simple and rigid, and cannot cope well with the complex and changeable actual installation conditions of prefabricated structures.

[0003] In the current related technologies, there are technical problems such as low accuracy and poor timeliness of assembly warnings for connection nodes of prefabricated structures. Summary of the invention

[0004] The present application provides a method for monitoring and managing the installation process of an assembled structure. The method obtains a first assembly connection node by constructing according to the assembly structure installation plan, performs geometric accuracy, tightness and load-bearing characteristic safety tests through an assembly sensor monitoring platform, obtains corresponding data, and generates a monitoring report to determine whether the constraint conditions are met. If not, an early warning signal is generated. This achieves the technical effect of improving the accuracy and timeliness of assembly early warnings of assembly structure connection nodes, ensuring the quality and safety of the assembled structure, and optimizing the installation process and project management.

[0005] The present application provides a method for monitoring and managing the installation process of an assembled structure, comprising:

[0006] According to the prefabricated structure installation plan, construction is carried out to obtain a first assembly connection node; according to the assembly sensor monitoring platform, the first node assembly monitoring data corresponding to the first assembly connection node is retrieved, and the geometric accuracy analysis of the first assembly connection node is performed in combination with the assembly geometric accuracy detection space to obtain the first assembly connection geometric accuracy; based on the assembly sensor monitoring platform, in combination with the assembly connection tightness analytical model, the tightness detection of the first assembly connection node is performed to obtain the first assembly connection tightness; based on the multi-dimensional feature bearing safety weight, in combination with the prefabricated structure installation plan and the assembly sensor monitoring platform, the first assembly connection node is subjected to a bearing feature safety test to obtain the first assembly connection bearing safety; the first assembly connection geometric accuracy, the first assembly connection tightness and the first assembly connection bearing safety are sorted to generate a first node assembly monitoring report; it is determined whether the first node assembly monitoring report meets the predetermined assembly feature constraint conditions; if the first node assembly monitoring report does not meet the predetermined assembly feature constraint conditions, a first node assembly early warning signal is generated.

[0007] A method for monitoring and managing the installation process of prefabricated structures proposed in this application is to first obtain the first assembly connection node according to the prefabricated structure installation plan, perform geometric accuracy, tightness and load-bearing characteristic safety tests through the assembly sensor monitoring platform, obtain corresponding data, organize and generate a monitoring report, and determine whether the constraint conditions are met. If not, a warning signal is generated, thereby achieving the technical effect of improving the accuracy and timeliness of assembly warnings of prefabricated structure connection nodes, ensuring the quality and safety of prefabricated structures, and optimizing installation processes and project management. 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 system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately 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 flowchart of a method for monitoring and managing the installation process of an assembled structure provided in an embodiment of the present application;

[0010] Figure 2 A schematic diagram of a first assembly connection load-bearing safety degree generation process of a method for monitoring and managing the installation process of an assembled structure provided in an embodiment of the present application. 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, system, 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 method for monitoring and managing the installation process of an assembled structure, such as Figure 1 As shown, the method includes:

[0015] Step S100, construction is carried out according to the prefabricated structure installation scheme to obtain the first assembly connection node. Specifically, the construction process of the prefabricated structure installation scheme refers to the operation process of carrying out construction according to the established plan to obtain the first assembly connection node. Select the type of prefabricated structure required for construction, prepare various equipment and tools required for construction, clarify various construction parameters, such as the specifications of components, the order of installation, the method of connection, etc., carry out construction operations, and obtain relevant data of the first assembly connection node. The data of the first assembly connection node indicates the process of components gradually combining and connecting from a dispersed state in the early stage of construction, continuously advancing the construction progress, and obtaining data of subsequent assembly connection nodes. The data indicates the process of continuous improvement and stabilization of the structure in the subsequent stages of construction. The first assembly connection node includes any connection node of the prefabricated structure corresponding to the prefabricated structure installation scheme. For example, the first assembly connection node is a column-column connection node, a beam-column connection node, a wall panel connection node, etc.

[0016] Step S200, according to the assembly sensor monitoring platform, retrieve the first node assembly monitoring data corresponding to the first assembly connection node, and perform geometric accuracy analysis on the first assembly connection node in combination with the assembly geometric accuracy detection space to obtain the first assembly connection geometric accuracy. Specifically, the acquisition process of the first assembly connection geometric accuracy refers to the operation process of analyzing the first assembly connection node based on the assembly sensor monitoring platform and in combination with the assembly geometric accuracy detection space. Select the first assembly connection node to be analyzed, start the assembly sensor monitoring platform, set relevant instructions, and retrieve the first node assembly monitoring data corresponding to this node. These data cover the node's position, angle, size and other detailed information. Then, import the retrieved data into the assembly geometric accuracy detection space, which is specially designed for evaluating node geometric accuracy and has powerful computing and analysis capabilities. In this space, the system will compare and calculate the acquired data with the preset standard geometric accuracy parameters one by one. Through complex algorithms and models, the various geometric characteristics of the node are comprehensively considered, such as the length, width, height, angle deviation, etc. of the node. After careful and comprehensive analysis, we finally obtained a result that can accurately reflect the geometric accuracy of the first assembly connection node, namely the first assembly connection geometric accuracy. For example, in a prefabricated factory building construction project, for the connection node of a certain steel beam and a steel column, the actual installation data of the node was obtained through the assembly sensor monitoring platform, and then analyzed in the assembly geometric accuracy detection space. It was found that the angle of the node in the horizontal direction was accurate, but there was a slight deviation in the length in the vertical direction, thereby clarifying the geometric accuracy status of the node.

[0017] In a possible implementation, according to the assembly sensor monitoring platform, the first node assembly monitoring data corresponding to the first assembly connection node is retrieved, and the first assembly connection node is subjected to geometric accuracy analysis in combination with the assembly geometric accuracy detection space to obtain the first assembly connection geometric accuracy, and step S200 further includes step S210, wherein the first node assembly monitoring data includes first node assembly dimension monitoring data, first node assembly angle monitoring data, and first node assembly position monitoring data. Specifically, during the installation process of the prefabricated structure, detailed data about the first assembly connection node will be collected through various monitoring means and equipment, and the data is classified into different types, including data obtained from monitoring the node assembly dimension, such as the measured values ​​of the length, width, height, etc. of the component; monitoring data of the node assembly angle, such as the angle formed when two components are connected; and monitoring data of the node assembly position, such as the coordinate position of the node in the entire structure.

[0018] Step S220, the assembly geometry accuracy detection space includes the assembly dimension accuracy detection space, the assembly angle accuracy detection space and the assembly position accuracy detection space. Specifically, in order to accurately evaluate the geometric accuracy of the node, a special detection space is set up. The assembly dimension accuracy detection space is used to process and analyze the monitoring data related to the node size, and judge the accuracy level of the size through the preset standards and algorithms; the assembly angle accuracy detection space focuses on the evaluation of the node assembly angle data to determine whether the angle meets the design requirements; the assembly position accuracy detection space is responsible for evaluating the node position data to determine whether its position in the structure is accurate.

[0019] Step S230, based on the first node assembly dimension monitoring data, according to the assembly dimension accuracy detection space, obtain the first node assembly dimension accuracy. Specifically, the collected first node assembly dimension monitoring data is input into the assembly dimension accuracy detection space, and a specific calculation model and accuracy standard are set in the space, and the input data is compared and calculated with the standard. For example, if the standard stipulates that the dimension error cannot exceed a certain range, the deviation degree between the actual monitoring data and the standard is calculated, so as to obtain the accuracy value of the first node assembly dimension.

[0020] Step S240, based on the first node assembly angle monitoring data, according to the assembly angle accuracy detection space, obtain the first node assembly angle accuracy. Specifically, the first node assembly angle monitoring data is placed in the assembly angle accuracy detection space, and the space processes the input angle data according to the preset angle accuracy requirements and algorithms. By calculating the difference between the actual angle and the design angle, and according to the allowable angle deviation range, the accuracy value of the first node assembly angle is determined.

[0021] Step S250, based on the first node assembly position monitoring data, according to the assembly position accuracy detection space, obtain the first node assembly position accuracy. Specifically, the first node assembly position monitoring data is transferred to the assembly position accuracy detection space, and in the space, the accuracy result of the first node assembly position is obtained by comparing and calculating with the preset position accuracy standard, taking into account factors such as coordinate deviation and relative position relationship.

[0022] Step S260, based on the predetermined geometric accuracy detection weight, the first node assembly size accuracy, the first node assembly angle accuracy and the first node assembly position accuracy are weightedly calculated to generate the first assembly connection geometric accuracy. Specifically, the predetermined geometric accuracy detection weights for the node assembly size accuracy, angle accuracy and position accuracy are determined in advance, for example, the size accuracy weight is 0.3, the angle accuracy weight is 0.3, and the position accuracy weight is 0.4. Then, the first node assembly size accuracy, angle accuracy and position accuracy obtained previously are multiplied by their respective weights. Finally, the weighted results are added to obtain a comprehensive value, which is the first assembly connection geometric accuracy that can fully reflect the first assembly connection node geometric accuracy. For example, assuming that the first node assembly size accuracy is 90%, the angle accuracy is 85%, and the position accuracy is 95%, according to the above weight calculation: 0.3×90%+0.3×85%+0.4×95%=91%, then the first assembly connection geometric accuracy is 91%.

[0023] In a possible implementation, the assembly geometry accuracy detection space includes an assembly dimension accuracy detection space, an assembly angle accuracy detection space, and an assembly position accuracy detection space, and step S220 further includes step S221, loading an assembly dimension deviation sample set and an assembly dimension accuracy sample set. Specifically, a large amount of assembly dimension deviation sample data and assembly dimension accuracy sample data that have been pre-collected and sorted are read from a database or storage device, and the sample set includes actual measurement data under various conditions and corresponding accuracy standards.

[0024] Step S222, constructing an assembly dimension accuracy detection coordinate system, wherein the assembly dimension accuracy detection coordinate system includes an assembly dimension deviation coordinate axis and an assembly dimension accuracy coordinate axis. Specifically, a coordinate system specifically used for analyzing assembly dimension accuracy is created, in which an assembly dimension deviation coordinate axis is set to indicate the degree of deviation between the actual measured dimension and the standard dimension; and an assembly dimension accuracy coordinate axis is set to reflect the level or degree of accuracy.

[0025] Step S223, based on the assembly dimension deviation sample set and the assembly dimension accuracy sample set, according to the assembly dimension accuracy detection coordinate system, construct the assembly dimension accuracy detection space. Specifically, using the data of the loaded assembly dimension deviation sample set and the assembly dimension accuracy sample set, according to the rules and definitions of the assembly dimension accuracy detection coordinate system, through mathematical modeling and calculation methods, a detection space that can accurately evaluate the assembly dimension accuracy is constructed, and the space can intuitively show the relationship between dimension deviation and accuracy.

[0026] Step S224, constructing the assembly angle accuracy detection space according to the assembly angle accuracy detection coordinate system. Specifically, similarly, based on the detection coordinate system specially designed for assembly angle accuracy, using corresponding algorithms and data processing methods, a detection space for evaluating assembly angle accuracy is constructed, and the space can clearly reflect the correspondence between angle deviation and angle accuracy.

[0027] Step S225, constructing the assembly position accuracy detection space according to the assembly position accuracy detection coordinate system. Specifically, according to the detection coordinate system set for the assembly position accuracy, using relevant data and calculation methods, constructing a detection space that can effectively evaluate the assembly position accuracy, so as to accurately measure the relationship between the deviation and accuracy of the assembly position.

[0028] Step S226, generating the assembly geometric accuracy detection space according to the assembly size accuracy detection space, the assembly angle accuracy detection space and the assembly position accuracy detection space. Specifically, the assembly size accuracy detection space, the assembly angle accuracy detection space and the assembly position accuracy detection space constructed separately above are integrated and comprehensively processed, and a comprehensive and integrated assembly geometric accuracy detection space is formed by integrating the detection spaces of these three aspects, so that the geometric accuracy of the assembled structure can be comprehensively and accurately evaluated and analyzed. For example, in the actual production of assembled building components, by collecting a large number of data samples of size deviation, angle deviation and position deviation and the corresponding accuracy standard samples, the detection spaces of each single dimension are constructed, and finally integrated into a complete assembly geometric accuracy detection space to ensure that the assembly accuracy of the components meets the design requirements.

[0029] In a possible implementation, based on the first node assembly dimension monitoring data and the assembly dimension accuracy detection space, the first node assembly dimension accuracy is obtained, and step S230 further includes step S231, based on the first assembly connection node, the dimension feature association of the prefabricated structure installation scheme is performed to determine the first node predetermined assembly dimension data. Specifically, focusing on the first assembly connection node, carefully studying the part of the prefabricated structure installation scheme related to the node, extracting the description and provisions of the dimension features therein, and through such association and analysis, clarifying the predetermined assembly dimension data that the node should achieve in an ideal state, which data is determined based on design requirements and specifications.

[0030] Step S232: Based on the predetermined assembly dimension data of the first node, deviation analysis is performed on the monitoring data of the assembly dimension of the first node to obtain deviation information of the assembly dimension of the first node. Specifically, the predetermined assembly dimension data of the first node that has been determined is used as a reference, and the assembly dimension data of the first node monitored in actual construction is compared and calculated therewith, and the difference between the actual dimension and the predetermined dimension is found through precise mathematical analysis, thereby obtaining deviation information of the assembly dimension of the first node, including the size and direction of the deviation, etc.

[0031] Step S233, input the first node assembly dimension deviation information into the assembly dimension accuracy detection space to generate the first node assembly dimension accuracy. Specifically, the obtained first node assembly dimension deviation information is input into a specially constructed assembly dimension accuracy detection space. The detection space contains a series of evaluation criteria and algorithms. Through calculation and processing in the space, the degree of deviation and the predetermined accuracy requirements are comprehensively considered, and finally a result that can accurately reflect the first node assembly dimension accuracy is generated. For example, in the construction of an assembled bridge, for the first assembly connection node between a pier and a beam body, first determine its predetermined length, width and other dimensional data according to the installation plan. Then, compare the actual monitored dimensional data to calculate the deviation value. These deviation values ​​are input into the assembly dimension accuracy detection space to determine whether the assembly dimension accuracy of the node meets the requirements.

[0032] Step S300, based on the assembly sensor monitoring platform, combined with the assembly connection tightness analytical model, the first assembly connection node is tested for tightness, and the first assembly connection tightness is obtained. Specifically, the acquisition process of the first assembly connection tightness refers to the operation process of performing tightness detection on the first assembly connection node based on the assembly sensor monitoring platform and combined with the assembly connection tightness analytical model. The assembly sensor monitoring platform is enabled, and this platform is equipped with a variety of sensing and data acquisition facilities, which can obtain relevant data of the first assembly connection node in construction in real time. At the same time, combined with a specially constructed assembly connection tightness analytical model, the model covers a series of parameters, calculation formulas and judgment criteria for tightness evaluation. The data such as torque and pressure collected by the platform are input into this model. The model processes and analyzes these data according to preset algorithms and rules. By comparing the actual data with the ideal tightness standard value in the model, various factors affecting the tightness are comprehensively considered, such as the material of the connector, the construction process, the environmental conditions, etc. After a complex calculation and evaluation process, we finally get a value that can accurately reflect the tightness of the first assembly connection node, that is, the first assembly connection tightness. For example, in the construction of an assembled concrete structure, for the first assembly connection node between the column and the beam, the assembly sensor monitoring platform collects the anchor bolt tightening torque data at the node connection. These data are imported into the tightness analysis model. The model comprehensively considers factors such as the specifications of the anchor bolts and the strength of the concrete, and calculates whether the tightness of the node meets the design requirements, thereby obtaining the first assembly connection tightness.

[0033] In a possible implementation, based on the assembly sensor monitoring platform, in combination with the assembly connection tightness analytical model, the first assembly connection node is tested for tightness to obtain the first assembly connection tightness, and step S300 further includes step S310, according to the first assembly connection node, N detection points are set, where N is a positive integer greater than 1. Specifically, the first assembly connection node is carefully observed and analyzed, and the structural characteristics, stress conditions, and related design requirements of the node are considered. Based on comprehensive factors, it is determined that the number of detection points to be set is N, and N is determined based on actual conditions through scientific calculations and evaluations, and N is greater than 1, so as to ensure that the tightness of the node can be fully and accurately detected.

[0034] Step S320, activating the torque sensing module of the assembly sensing monitoring platform. Specifically, the torque sensing module, a key component in the assembly sensing monitoring platform, is a device specifically used to accurately measure the torque magnitude at the connection node. It has the characteristics of high precision and high sensitivity. After activation, it is ready to receive and process relevant data from the detection point.

[0035] Step S330, according to the torque sensing module and the assembly connection tightness analytical model, the N detection points are tested for tightness to obtain the detection tightness of the N points. Specifically, using the activated torque sensing module, combined with the assembly connection tightness analytical model, the previously set N detection points are tested one by one. When testing each point, the torque sensing module will measure the torque value at the node in real time and transmit the data to the analytical model. The analytical model will analyze and calculate the received data according to the preset algorithm and standard, so as to obtain the tightness value of each point. After testing the N points in sequence, the detection tightness of each of the N points is finally obtained.

[0036] Step S340, a centralized value calculation is performed based on the tightness detected at the N points to generate the first assembly connection tightness. Specifically, the centralized value calculation is performed on the obtained N point detection tightness, and a common centralized value calculation method is selected, such as average value calculation, that is, the N tightness values ​​are added and then divided by N. The result obtained is a comprehensive value that can represent the tightness of the entire first assembly connection node, that is, the first assembly connection tightness. Through the centralized value, a clear and accurate assessment of the overall tightness of the node can be made. For example, in the construction of an assembled bridge, for the first assembly connection node of an important pier and beam body, 8 detection points are set according to the complexity of the node and the key stress-bearing parts. After activating the torque sensing module, these 8 points are detected to obtain 8 tightness values. By calculating the average value of these 8 numbers, the first assembly connection tightness that can reflect the overall tightness of the node is generated. If this average value meets the tightness standard required by the project, the tightness of the node can be considered qualified; otherwise, the node needs further inspection and processing.

[0037] In a possible implementation, the N detection points are tested for tightness according to the torque sensing module and the assembly connection tightness analytical model to obtain the detection tightness of the N points, and step S330 further includes step S331, extracting the nth detection point according to the N detection points, where n is a positive integer, 0≤n≤N. Specifically, the determined N detection points are sorted out one by one, and the nth detection point is selected as the current detection object according to the sequence or specific rules, where n is a positive integer in the range of 0 to N, to ensure that the selected point is in the set of detection points.

[0038] Step S332: Based on the torque sensing module, the nth detection point is subjected to M times of tightness detection to obtain M detection tightening torques, where M is a positive integer greater than 1. Specifically, the torque sensing module is started to perform multiple tightness detections on the nth detection point, and M detections are performed to improve the accuracy and reliability of the detection results. Each detection will obtain a detection tightening torque value, and after M detections, M detection tightening torques are finally obtained.

[0039] Step S333: According to the nth expected tightening torque corresponding to the nth detection point, the M detected tightening torques are identified for deviations to obtain M tightening torque deviation information. Specifically, for the nth detection point, there is a preset expected tightening torque value, i.e., the nth expected tightening torque. The obtained M detected tightening torques are respectively compared with the expected tightening torque to calculate the deviation between them. Through the deviation calculation, M tightening torque deviation information is obtained, so as to understand the difference between the actual detection value and the expected value.

[0040] Step S334, input the M tightening torque deviation information into the assembly connection tightness analytical model to obtain M tightness detection coefficients. Specifically, the assembly connection tightness analytical model is a tool constructed based on a large amount of experimental data, theoretical analysis and mathematical modeling. By collecting a large amount of assembly connection tightness related data under different types, specifications and working conditions, including actual tightening torque, connection material characteristics, environmental conditions, etc., key features such as torque size, material strength, temperature, humidity, etc. are extracted from the collected data, and a suitable mathematical model such as linear regression, neural network, etc. is selected according to the data characteristics, and the training data is used to train and optimize the model, and the trained model is verified using the verification data set. The model is adjusted and improved according to the verification results. After multiple iterations and optimizations, a model that can accurately analyze the assembly connection tightness is determined, and the M tightening torque deviation information is input into this carefully constructed assembly connection tightness analytical model. The model will perform complex calculations and analysis based on the input deviation information, and output M tightness detection coefficients, which are used to further evaluate the tightness of the detection points.

[0041] Step S335, performing concentrated value calculation according to the M tightness detection coefficients, generating the nth point detection tightness, and adding the nth point detection tightness to the N point detection tightness. Specifically, the obtained M tightness detection coefficients are subjected to concentrated value calculation, such as calculating the average value or median, etc., and a comprehensive value representing the tightness of the nth detection point is generated through concentrated value calculation, that is, the nth point detection tightness, and the value is added to the set of the previously obtained N point detection tightness, so as to provide a data basis for the subsequent comprehensive evaluation of the tightness of the entire assembly connection node. For example, in the connection node detection of an assembled building structure, 5 (M=5) tightness tests are performed for the third detection point (n=3). The 5 tightening torques obtained by the detection are compared with the expected tightening torque to obtain deviation information, which is input into the assembly connection tightness analytical model that has been carefully constructed and trained to obtain 5 tightness detection coefficients. By calculating the average value of these five coefficients, the third point detection tightness is generated and added to the existing detection point tightness set.

[0042] Step S400, based on the multi-dimensional feature bearing safety weight, combined with the prefabricated structure installation scheme and the assembly sensor monitoring platform, the first assembly connection node is subjected to a bearing feature safety test to obtain the first assembly connection bearing safety degree. Specifically, the acquisition process of the first assembly connection bearing safety degree refers to the operation process of carrying out a bearing feature safety test on the first assembly connection node based on the multi-dimensional feature bearing safety weight, combined with the prefabricated structure installation scheme and the assembly sensor monitoring platform. The multi-dimensional feature bearing safety weight is clarified. This weight is pre-set according to the prefabricated structure characteristics and relevant safety specifications, and is used to measure the importance of different bearing characteristics. The prefabricated structure installation scheme is obtained, which specifies the key contents such as the design details, construction process, material specifications, etc. of the structure in detail, and provides a basic reference framework for the bearing feature safety test. The assembly sensor monitoring platform is enabled. This platform is equipped with a variety of sensing and monitoring facilities, which can collect various types of data of the first assembly connection node in actual construction in real time, such as stress, strain, displacement, etc. Based on the data obtained by the above-mentioned installation scheme and monitoring platform, the bearing feature safety test is performed on the first assembly connection node from multiple dimensions. These dimensions include axial load, shear load, bending load and combined load. In the axial load test, the ability of the node to withstand pressure or tension along the structural axis is analyzed. For shear load, the performance of the node in resisting lateral shear force is evaluated. In the bending load test, the stability of the node under the action of bending force is considered. The combined load safety test comprehensively weighs the safety of the node when multiple stress conditions act simultaneously. Through the test and analysis of these different dimensions, the test results are compared with the corresponding safety standards and design requirements. Finally, according to the multi-dimensional characteristic load safety weight, the test results of each dimension are weighted. A value that can accurately reflect the load safety of the first assembly connection node is obtained, that is, the first assembly connection load safety degree. For example, in the construction of an assembled residential building, the first assembly connection node between a floor slab and a wall is tested for load characteristic safety. According to the installation plan and the data collected by the monitoring platform, after multi-dimensional analysis and weighted calculation, the first assembly connection load safety degree of the node is obtained, and then it is determined whether it meets the design and safety requirements.

[0043] In a possible implementation, based on the multi-dimensional feature bearing safety weight, the first assembly connection node is subjected to a bearing feature safety test in combination with the assembly structure installation scheme and the assembly sensor monitoring platform to obtain the first assembly connection bearing safety degree, such as Figure 2As shown, step S400 further includes step S410, performing an axial load safety test and analysis on the first assembly connection node according to the assembly structure installation plan and the assembly sensor monitoring platform to obtain a first axial load safety factor. Specifically, the assembly structure installation plan is obtained, which contains detailed information about the structural design, material specifications and construction requirements, and the assembly sensor monitoring platform is used to collect relevant data of the first assembly connection node in actual construction, such as stress conditions, deformation, etc. Based on the information and data, the axial load capacity of the node is deeply tested and analyzed, and the first axial load safety factor that can reflect the axial load safety of the node is obtained by comparing and calculating with the preset axial load safety standard.

[0044] Step S420, according to the prefabricated structure installation scheme and the assembly sensor monitoring platform, the first assembly connection node is subjected to shear load safety test analysis to obtain a first shear load safety factor. Specifically, with reference to the relevant provisions in the prefabricated structure installation scheme, and with the help of real-time data obtained by the assembly sensor monitoring platform, the shear load performance of the first assembly connection node is subjected to special test analysis, and various factors such as the structure of the node, the shear resistance of the material, etc. are comprehensively considered, and compared with the established shear load safety standard, the first shear load safety factor is calculated to evaluate the safety of the node in shear resistance.

[0045] Step S430, according to the prefabricated structure installation scheme and the assembly sensor monitoring platform, the first assembly connection node is subjected to a bending load safety test analysis to obtain a first bending load safety factor. Specifically, in the same manner, based on the prefabricated structure installation scheme and the data provided by the assembly sensor monitoring platform, a test analysis is carried out on the bending load capacity of the first assembly connection node, the structural form of the node, the bending strength of the material and other factors are analyzed, and the preset bending load safety standard is compared to obtain a first bending load safety factor, which is used to measure the safety of the node in terms of bending resistance.

[0046] Step S440, according to the prefabricated structure installation scheme and the assembly sensor monitoring platform, the first assembly connection node is subjected to a combined load-bearing safety test analysis to obtain a first combined load-bearing safety factor. Specifically, based on the prefabricated structure installation scheme and the data of the assembly sensor monitoring platform, a comprehensive test and analysis is performed on the combined load-bearing capacity of the first assembly connection node under the simultaneous action of multiple stress conditions, and the combined effects of multiple stresses such as axial, shear, and bending are comprehensively considered, and compared with the preset combined load-bearing safety standard, and the first combined load-bearing safety factor is calculated to evaluate the safety of the node under complex stress conditions.

[0047] Step S450, weighted calculation is performed on the first axial bearing safety factor, the first shear bearing safety factor, the first bending bearing safety factor and the first combined bearing safety factor according to the multi-dimensional characteristic bearing safety weight, so as to generate the first assembly connection bearing safety degree. Specifically, the multi-dimensional characteristic bearing safety weight is predetermined, and the weight reflects the relative importance of axial bearing, shear bearing, bending bearing and combined bearing in the overall bearing safety. The first axial bearing safety factor, the first shear bearing safety factor, the first bending bearing safety factor and the first combined bearing safety factor obtained above are multiplied by the corresponding weights respectively, and the weighted values ​​are added together to obtain a comprehensive value through weighted calculation, that is, to generate the first assembly connection bearing safety degree that can fully reflect the bearing safety of the first assembly connection node. For example, in a construction project of an assembled bridge, for a certain key assembly connection node, the axial, shear, bending and combined bearing safety test analysis is performed in sequence according to the above steps to obtain the corresponding safety factor. Assume that in the multi-dimensional characteristic bearing safety weight, the axial bearing weight is 0.3, the shear bearing weight is 0.2, the bending bearing weight is 0.3, and the combined bearing weight is 0.2. The safety factors are: the first axial bearing safety factor is 0.8, the first shear bearing safety factor is 0.7, the first bending bearing safety factor is 0.9, and the first combined bearing safety factor is 0.8. The weighted calculation is: 0.3×0.8+0.2×0.7+0.3×0.9+0.2×0.8=0.81, and the final first assembly connection bearing safety is 0.81, thus making a comprehensive evaluation of the bearing safety of the node.

[0048] In a possible implementation, an axial load safety test analysis is performed on the first assembly connection node according to the assembly structure installation scheme and the assembly sensor monitoring platform to obtain a first axial load safety factor, and step S410 further includes step S411, extracting the first expected axial load corresponding to the first assembly connection node according to the assembly structure installation scheme. Specifically, the assembly structure installation scheme is studied, and the scheme includes detailed design information, material properties, and expected stress conditions of the structure. Through the description and calculation of the first assembly connection node in the scheme, the axial force value that the node should be able to withstand under ideal conditions, that is, the first expected axial load, is extracted.

[0049] Step S412, based on the first expected axial bearing capacity, the first assembly connection node is tested for axial bearing capacity according to the assembly sensor monitoring platform to obtain a first test axial bearing capacity. Specifically, with the first expected axial bearing capacity as a reference, the axial force that the first assembly connection node can actually withstand is tested using the relevant equipment and technology of the assembly sensor monitoring platform. During the test, the platform will collect various data in real time, such as the deformation of the node, stress distribution, etc., and after analysis and calculation, the actual axial bearing capacity value, i.e., the first test axial bearing capacity, is obtained.

[0050] Step S413: input the first expected axial bearing capacity and the first tested axial bearing capacity into Q pre-constructed axial bearing safety assessment models to obtain Q axial bearing safety assessment coefficients, where Q is a positive integer greater than 1. Specifically, Q axial load safety assessment models are pre-constructed, and a large amount of historical data related to axial load is collected, including expected axial load capacity and actual tested axial load capacity under different structural types, materials, connection methods, etc. Features that have a significant impact on the axial load safety assessment, such as material strength, node structure, stress conditions, etc., are selected from the collected data. According to the data characteristics and assessment requirements, a suitable mathematical model, such as a linear regression model, a neural network model, etc., is selected, and the selected model is trained using the collected data. By continuously adjusting the parameters of the model, the model can be accurately output according to the input expected axial load capacity and the tested axial load capacity. The model is verified using a part of the data that is not involved in the training, and the model is optimized and improved according to the verification results to ensure the accuracy and reliability of the model. The first expected axial load capacity and the first tested axial load capacity are input into the Q pre-constructed axial load safety assessment models. Each model will process the input data according to its internal algorithm and parameters, and output an axial load safety assessment coefficient respectively, thereby obtaining Q different axial load safety assessment coefficients.

[0051] Step S414, performing a proportion calculation based on the Q evaluation accuracy parameters corresponding to the Q axial load-bearing safety evaluation models, and generating Q evaluation incentive weight coefficients. Specifically, for the Q axial load-bearing safety evaluation models, each model has a corresponding evaluation accuracy parameter, which reflects the quantitative index of the accuracy of the model in the previous evaluation. According to the evaluation accuracy parameters, according to a certain proportion calculation method, such as according to the proportion of the accuracy parameters or based on a certain weighting algorithm, a corresponding evaluation incentive weight coefficient is generated for each model, and finally Q evaluation incentive weight coefficients are obtained.

[0052] Step S415, weighted calculation is performed on the Q axial load-bearing safety assessment coefficients according to the Q assessment incentive weight coefficients to generate the first axial load-bearing safety coefficient. Specifically, the Q assessment incentive weight coefficients obtained above are respectively multiplied by the corresponding Q axial load-bearing safety assessment coefficients, the products are added, and a comprehensive value is obtained by weighted calculation. This value is the first axial load-bearing safety coefficient that can accurately reflect the axial load-bearing safety of the first assembly connection node. For example, in the construction of an assembled building frame, for the first assembly connection node of a beam-column connection, the above steps are followed. Assuming that three axial load-bearing safety assessment models are constructed, three assessment coefficients are obtained respectively, and three weight coefficients are generated by calculation, and finally the first axial load-bearing safety coefficient is obtained by weighted calculation, so as to make an accurate assessment of the axial load-bearing safety of the node.

[0053] Step S500, sort out the geometric accuracy of the first assembly connection, the tightness of the first assembly connection and the bearing safety of the first assembly connection, and generate a first node assembly monitoring report. Specifically, the generation process of the first node assembly monitoring report refers to the operation process of sorting out the geometric accuracy of the first assembly connection, the tightness of the first assembly connection and the bearing safety of the first assembly connection. Obtain the detailed data and evaluation results of the geometric accuracy of the first assembly connection, the tightness of the first assembly connection and the bearing safety of the first assembly connection that have been obtained. For the geometric accuracy of the first assembly connection, trace back the data and analysis results of the dimensional accuracy, angle accuracy and position accuracy involved in its acquisition process. For the tightness of the first assembly connection, sort out the tightening torque data, deviation information and the tightness detection coefficient finally obtained at each detection point in the tightness detection. As for the bearing safety of the first assembly connection, summarize the safety test data of different dimensions such as axial load, shear load, bending load and combined load and the calculated safety factor. Then, these data and results are sorted and classified according to a specific format and logic. The specific indicators and values ​​of geometric accuracy, tightness and load-bearing safety can be listed separately, and the corresponding explanations and interpretations can be attached. Then, based on the sorted data and information, write the main body of the first node assembly monitoring report. In the text, describe the detection methods, results and analysis of each aspect in detail, covering whether the relevant standards and requirements are met, as well as the existing problems and improvement suggestions. At the same time, in order to make the report clearer and more intuitive, charts can be used to display key data and trends, such as using bar charts to present the values ​​of various accuracies, and using line charts to show the changes in the load-bearing safety factor. Finally, the entire report is reviewed and proofread to ensure the accuracy of the data, the logical coherence and the standardization of the language. After the review is correct, the first node assembly monitoring report is formally generated. For example, in the monitoring of the first assembly connection node of an assembled plant, the node length and angle deviation data of the geometric accuracy, the tightening torque values ​​of each point in the tightness, and the axial, shear and other safety factors in the load-bearing safety are sorted out. According to the above steps, a detailed monitoring report is generated to provide strong support for subsequent construction and quality assessment.

[0054] Step S600, determine whether the first node assembly monitoring report meets the predetermined assembly feature constraint conditions. Specifically, the predetermined assembly feature constraint conditions include assembly connection geometric accuracy constraint, assembly connection tightness constraint and assembly connection load-bearing safety constraint. For assembly connection geometric accuracy constraint, it is necessary to clarify the limited range of dimensional accuracy, angular accuracy, position accuracy, etc.; assembly connection tightness constraint needs to clearly define the tightening torque value range, tightness qualification standard coefficient, etc.; assembly connection load-bearing safety constraint needs to accurately set the safety factor thresholds of axial load, shear load, bending load and combined load. Then, the first node assembly monitoring report is deeply analyzed. In terms of assembly connection geometric accuracy, the measured data such as dimensional accuracy in the report is compared with the geometric accuracy constraint range; in terms of assembly connection tightness, the tightening torque detection value and the tightness coefficient in the report are compared with the tightness constraint standard; in terms of assembly connection load-bearing safety, the relevant safety factor in the report is compared with the load-bearing safety constraint threshold. If all the data are within the constraints, the report is deemed to meet the conditions. Otherwise, as long as one of the data exceeds the constraints, such as in prefabricated bridge projects, the dimensional accuracy error exceeds the limit, the tightness coefficient is lower than the specified value, or the safety factor does not meet the standard, the report is deemed to not meet the predetermined assembly feature constraints.

[0055] Step S700, if the first node assembly monitoring report does not meet the predetermined assembly feature constraint condition, generate the first node assembly warning signal. Specifically, when it is determined that the first node assembly monitoring report does not meet the predetermined assembly feature constraint condition, the system will immediately start the warning signal generation process. The system will classify according to the specific constraint condition category that is not met, such as the geometric accuracy of the assembly connection that does not meet the standard is marked as a geometric accuracy related category, the tightness that does not meet the standard is marked as a tightness related category, and the insufficient load-bearing safety is marked as a load-bearing safety related category. Then extract the specific data and parameters that do not meet the constraint conditions, such as the deviation value in terms of geometric accuracy, the value below the standard in terms of tightness, and the value below the threshold in terms of load-bearing safety. Then construct the warning signal content according to the preset rules and format, including the type of unsatisfied conditions, deviation data, possible risk impact, etc. After the construction is completed, select a suitable transmission method, such as transmitting to the monitoring terminal, notifying the responsible person by SMS or email, etc., to ensure accurate and timely transmission, so that relevant personnel can take measures.

[0056] The embodiment of the present application adopts a method of obtaining a first assembly connection node according to the installation plan of the prefabricated structure, performing geometric accuracy, tightness and load-bearing characteristic safety tests through an assembly sensor monitoring platform, obtaining corresponding data, compiling and generating a monitoring report, and judging whether the constraint conditions are met. If not met, a warning signal is generated, thereby achieving the technical effect of improving the accuracy and timeliness of the assembly warning of the prefabricated structure connection node, ensuring the quality and safety of the prefabricated structure, and optimizing the installation process and project management.

[0057] 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 method for monitoring and managing the installation process of an assembled structure, characterized in that: The method comprises: Perform construction according to the prefabricated structure installation plan to obtain a first assembly connection node; According to the assembly sensor monitoring platform, the first node assembly monitoring data corresponding to the first assembly connection node is retrieved, and the geometric accuracy analysis of the first assembly connection node is performed in combination with the assembly geometric accuracy detection space to obtain the first assembly connection geometric accuracy; Based on the assembly sensor monitoring platform, in combination with the assembly connection tightness analytical model, a tightness detection is performed on the first assembly connection node to obtain the first assembly connection tightness; Based on the multi-dimensional characteristic bearing safety weight, in combination with the assembly structure installation scheme and the assembly sensor monitoring platform, a bearing characteristic safety test is performed on the first assembly connection node to obtain the bearing safety degree of the first assembly connection; Arrange the geometric accuracy of the first assembly connection, the tightness of the first assembly connection, and the load-bearing safety of the first assembly connection to generate a first node assembly monitoring report; Determining whether the first node assembly monitoring report satisfies a predetermined assembly feature constraint condition; If the first node assembly monitoring report does not satisfy the predetermined assembly feature constraint condition, generating a first node assembly warning signal; According to the assembly sensor monitoring platform, the first node assembly monitoring data corresponding to the first assembly connection node is retrieved, and the geometric accuracy analysis of the first assembly connection node is performed in combination with the assembly geometric accuracy detection space to obtain the first assembly connection geometric accuracy, including: The first node assembly monitoring data includes first node assembly dimension monitoring data, first node assembly angle monitoring data and first node assembly position monitoring data; The assembly geometry accuracy detection space includes an assembly size accuracy detection space, an assembly angle accuracy detection space and an assembly position accuracy detection space; Based on the first node assembly dimension monitoring data, and according to the assembly dimension accuracy detection space, obtaining the first node assembly dimension accuracy; Based on the first node assembly angle monitoring data, and according to the assembly angle accuracy detection space, obtaining the first node assembly angle accuracy; Based on the first node assembly position monitoring data, and according to the assembly position accuracy detection space, obtaining the first node assembly position accuracy; Performing weighted calculation on the first node assembly size accuracy, the first node assembly angle accuracy and the first node assembly position accuracy based on a predetermined geometric accuracy detection weight to generate the first assembly connection geometric accuracy; Based on the first node assembly dimension monitoring data and according to the assembly dimension accuracy detection space, obtaining the first node assembly dimension accuracy includes: Associating the dimension features of the assembly structure installation scheme based on the first assembly connection node to determine the predetermined assembly dimension data of the first node; Performing deviation analysis on the first node assembly dimension monitoring data based on the first node predetermined assembly dimension data to obtain first node assembly dimension deviation information; The first node assembly dimension deviation information is input into the assembly dimension accuracy detection space to generate the first node assembly dimension accuracy.

2. The method according to claim 1, characterized in that The steps of constructing the assembly geometric accuracy detection space include: Loading assembly dimension deviation sample set and assembly dimension accuracy sample set; Constructing an assembly dimension accuracy detection coordinate system, wherein the assembly dimension accuracy detection coordinate system includes an assembly dimension deviation coordinate axis and an assembly dimension accuracy coordinate axis; Based on the assembly dimension deviation sample set and the assembly dimension accuracy sample set, and according to the assembly dimension accuracy detection coordinate system, constructing the assembly dimension accuracy detection space; Constructing the assembly angle accuracy detection space according to the assembly angle accuracy detection coordinate system; Constructing the assembly position accuracy detection space according to the assembly position accuracy detection coordinate system; The assembly geometry accuracy detection space is generated according to the assembly size accuracy detection space, the assembly angle accuracy detection space and the assembly position accuracy detection space.

3. The method according to claim 1, characterized in that Based on the assembly sensor monitoring platform, in combination with the assembly connection tightness analytical model, the first assembly connection node is tested for tightness to obtain the first assembly connection tightness, including: According to the first assembly connection node, N detection points are set, where N is a positive integer greater than 1; activating a torque sensing module of the assembly sensing monitoring platform; According to the torque sensing module and the assembly connection tightness analytical model, the tightness of the N detection points is detected to obtain the detection tightness of the N points; A concentrated value calculation is performed based on the tightness detected at the N points to generate the first assembly connection tightness.

4. The method according to claim 3, characterized in that According to the torque sensing module and the assembly connection tightness analytical model, the tightness of the N detection points is detected to obtain the detection tightness of the N points, including: According to the N detection points, extract the nth detection point, where n is a positive integer, 0≤n≤N; Based on the torque sensing module, perform M times of tightness detection on the nth detection point to obtain M detection tightening torques, where M is a positive integer greater than 1; According to the nth expected tightening torque corresponding to the nth detection point, deviation identification is performed on the M detected tightening torques to obtain M tightening torque deviation information; Inputting the M tightening torque deviation information into the assembly connection tightness analytical model to obtain M tightness detection coefficients; A concentrated value calculation is performed based on the M tightness detection coefficients to generate an n-th point detection tightness, and the n-th point detection tightness is added to the N-point detection tightness.

5. The method according to claim 1, characterized in that Based on the multi-dimensional characteristic bearing safety weight, the bearing characteristic safety test is performed on the first assembly connection node in combination with the assembly structure installation scheme and the assembly sensor monitoring platform to obtain the first assembly connection bearing safety degree, including: Performing an axial load safety test analysis on the first assembly connection node according to the assembly structure installation scheme and the assembly sensor monitoring platform to obtain a first axial load safety factor; Performing a shear bearing safety test analysis on the first assembly connection node according to the assembly structure installation scheme and the assembly sensor monitoring platform to obtain a first shear bearing safety factor; Performing a bending load safety test analysis on the first assembly connection node according to the assembly structure installation scheme and the assembly sensor monitoring platform to obtain a first bending load safety factor; Performing a combined load-bearing safety test analysis on the first assembly connection node according to the assembly structure installation scheme and the assembly sensor monitoring platform to obtain a first combined load-bearing safety factor; The first axial bearing safety factor, the first shear bearing safety factor, the first bending bearing safety factor and the first combined bearing safety factor are weightedly calculated according to the multi-dimensional characteristic bearing safety weight to generate the first assembly connection bearing safety degree.

6. The method according to claim 5, characterized in that According to the assembly structure installation scheme and the assembly sensor monitoring platform, an axial load safety test analysis is performed on the first assembly connection node to obtain a first axial load safety factor, including: According to the assembly structure installation scheme, extracting a first expected axial bearing capacity corresponding to the first assembly connection node; Based on the first expected axial bearing capacity, performing an axial bearing capacity test on the first assembly connection node according to the assembly sensor monitoring platform to obtain a first test axial bearing capacity; Inputting the first expected axial bearing capacity and the first tested axial bearing capacity into Q pre-constructed axial bearing safety assessment models to obtain Q axial bearing safety assessment coefficients, where Q is a positive integer greater than 1; Performing a proportion calculation according to the Q assessment accuracy parameters corresponding to the Q axial load safety assessment models to generate Q assessment incentive weight coefficients; The Q axial load-bearing safety assessment coefficients are weightedly calculated according to the Q assessment incentive weight coefficients to generate the first axial load-bearing safety factor.

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