Fabricated building component quality monitoring method

Abstract

The invention discloses a prefabricated building component quality monitoring method, and relates to the technical field of buildings, and the method comprises the steps: interactively obtaining target building design data; obtaining a target building model; calling networking data according to the target building position to obtain multiple pieces of load environment information; obtaining a plurality of load condition models; m building areas identified by adopting the stage assembly task sequence are obtained; m component mass constraint libraries are obtained; and dynamically calling the M component quality constraint libraries according to the stage assembly task sequence to carry out quality monitoring in the production process of the assembly type building component. The technical problems that in existing building component quality monitoring, real-time monitoring is difficult to conduct at all assembly nodes, the quality problem is difficult to find in time, environment changes cannot be dynamically adapted, and then the real-time performance and accuracy of the result of building component quality monitoring are insufficient, and the environment adaptability is poor are solved. The technical effect of improving the accuracy, timeliness and construction flexibility of building component quality monitoring is achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to buildings, and in particular to a method for monitoring the quality of prefabricated building components. Background Art

[0002] Prefabricated buildings are a new type of construction method that completes construction through factory-produced building components and on-site assembly. That is, building components are produced in a modular or prefabricated manner in a factory or construction site, and then these components are transported to the construction site for assembly and installation, eventually forming a complete building structure. Compared with traditional construction, prefabricated buildings have the advantages of short construction period, friendly on-site working environment, stable quality and environmental protection. Prefabricated buildings have been increasingly widely used around the world. However, the quality control of building components to be produced in prefabricated buildings is still the main challenge faced, especially in different load conditions and complex building structures. How to ensure the quality of building components to be produced directly affects the safety and long-term stability of the building. Traditional building quality monitoring methods mostly focus on post-construction inspection and evaluation, especially when the building has been formed. This method is difficult to detect potential component defects or construction problems in a timely manner, and it is difficult to meet the requirements of modern efficient construction.

[0003] At present, there are technical problems in the quality monitoring technologies for prefabricated building components, such as difficulty in real-time monitoring at each assembly node to promptly discover quality problems and inability to dynamically adapt to environmental changes, which leads to insufficient real-time and accuracy of the results of building component quality monitoring and poor environmental adaptability. Summary of the invention

[0004] The present application solves the technical problems existing in the existing building component quality monitoring, such as the difficulty in real-time monitoring at each assembly node and timely discovery of quality problems, the inability to dynamically adapt to environmental changes, and the lack of real-time and precision of the building component quality monitoring results and poor environmental adaptability, by providing a method for monitoring the quality of prefabricated building components. The application achieves the technical effect of improving the accuracy, timeliness and construction flexibility of building component quality monitoring.

[0005] The present application provides a method for monitoring the quality of prefabricated building components, comprising: interactively obtaining target building design data of a proposed building, wherein the target building design data includes a building construction plan, component attribute information, a target building location, and a target building function; performing building structure digitization based on the component attribute information to obtain a target building model of the proposed building; performing networked data call according to the target building location to obtain multiple load environment information; using the multiple load environment information as dynamic constraints and the target building function as a steady-state constraint, performing mechanical behavior simulation on the target building model to obtain multiple load condition models; performing building blockization based on the building construction plan to obtain M building areas identified by a stage assembly task sequence; fitting the M building areas to the multiple load condition models to perform component mechanical property analysis to obtain M component quality constraint libraries; and dynamically calling the M component quality constraint libraries according to the stage assembly task sequence to perform quality monitoring of the prefabricated building component production process.

[0006] In a possible implementation, building structure digitization is performed based on the component attribute information to obtain the target building model of the proposed building, and the following processing is also performed: based on the component attribute information, H component geometric information and H component material properties of H types of building components to be produced are extracted; component modeling is performed using the H component geometric information, and a component model library is obtained by archiving the model, wherein the component model library includes H component models of H types of building components to be produced; component budgets are extracted based on the target building design data, and component models are batch copied in the component model library according to the component budget to obtain a spare component model set; component assembly relationships are extracted from the building construction plan, and the component assembly relationships are used as assembly constraints, and the spare component model set is used as component scheduling constraints, and building structure digitization is performed to obtain the target building model of the proposed building.

[0007] In a possible implementation, the building is segmented into blocks based on the building construction plan to obtain M building areas, and the following processing is performed: the building construction plan is disassembled to obtain M phased construction tasks, wherein the M phased construction tasks have M task execution sequence identifiers; the construction progress of the target building model is segmented into blocks based on the M phased construction tasks, and the segmentation results are sorted according to the M task execution sequence identifiers to obtain a phase assembly task sequence; the target building model is divided into the M building areas according to the phase assembly task sequence.

[0008] In a possible implementation, the multiple load environment information is used as dynamic constraints, the target building function is used as a steady-state constraint, mechanical behavior simulation is performed on the target building model to obtain multiple load condition models, and the following processing is performed: the H component models are serialized based on volume, and the limit component model with the smallest volume is extracted from the serialization result; 1 / 100 of the limit volume of the limit component model is set as the grid volume parameter; the grid unit shape is predefined, and the grid size is reversed according to the grid volume parameter to obtain the target grid; the target building model is imported into finite element analysis software, and after meshing processing is performed using the target grid, the material properties of the H component models in the target building model are defined using the H component material property mappings to obtain a building finite element model; the multiple load environment information is used as dynamic constraints, the target building function is used as a steady-state constraint, mechanical behavior simulation is performed on the building finite element model to obtain the multiple load condition models.

[0009] In a possible implementation, the multiple load environment information are used as dynamic constraints, the target building function is used as a steady-state constraint, and mechanical behavior simulation is performed on the building finite element model to obtain the multiple load condition models. The following processing is also performed: the multiple load environment information are combined and enumerated to obtain multiple groups of backup environment information; the multiple groups of backup environment information are traversed and screened by mutually exclusive weather states to obtain multiple groups of screened environment information; the extreme values ​​of overlapping environmental factors are retained for the multiple groups of screened environment information to obtain multiple fused environment information; the multiple load environment information are used as dynamic constraints, the target building function is used as a steady-state constraint, and load application and mechanical behavior simulation are performed on the building finite element model to obtain the multiple load condition models.

[0010] In a possible implementation, the M building areas are fitted to the multiple load condition models to perform component mechanical performance analysis, and M component mass constraint libraries are obtained. The following processing is also performed: the first building area is projected to the multiple load condition models to obtain multiple regional load models, wherein the first building area is any one of the M building areas; the component model structure of the first building area is extracted from the target building model to obtain a first group of component models, wherein the first group of component models includes N types of component models, and N is a positive integer less than or equal to H; N groups of first component load models are extracted from the first regional load model with the N types of component models as constraints, wherein the first regional load model is any one of the multiple regional load models; performance limit analysis is performed on the N groups of first component load models to obtain N component mass constraints; the N types of component models are associated with the N component mass constraints and stored as a first component mass constraint library; and by analogy, the M building areas are fitted to the multiple load condition models to perform component mechanical performance analysis, and the M component mass constraint libraries are obtained.

[0011] In a possible implementation, a performance limit analysis is performed on the N groups of first component load models to obtain N component quality constraints, and the following processing is also performed: predefine a key performance indicator set; extract performance indicators of the N groups of first component load models with the key performance indicator set as constraints to obtain N groups of component performance arrays; perform data fusion on the N groups of component performance arrays based on the same type of components to obtain N fused performance arrays; and retain the performance maximum of the N fused performance arrays to obtain the N component quality constraints.

[0012] In a possible implementation, the M component quality constraint libraries are dynamically called according to the stage assembly task sequence to perform quality monitoring of the prefabricated building component production process, and the following processing is also performed: based on the M task execution order identifiers, the initial stage construction tasks are sequentially called from the M stage construction tasks; the initial component quality constraint library is called from the M component quality constraint libraries according to the initial stage construction tasks; when the initial component quality constraint library is used to perform quality monitoring of the prefabricated building component production process, if the real-time building component does not satisfy the initial component quality constraint library, the real-time building component is used to traverse M-1 component quality constraint libraries to perform recycling analysis of the real-time building component.

[0013] The method for monitoring the quality of prefabricated building components proposed in this application is intended to interactively obtain the target building design data of the proposed building; perform building structure digitization to obtain the target building model; perform networked data calls according to the target building location to obtain multiple load environment information; perform mechanical behavior simulation to obtain multiple load condition models; obtain M building areas identified by stage assembly task sequences; perform component mechanical performance analysis to obtain M component quality constraint libraries; dynamically call M component quality constraint libraries according to the stage assembly task sequence to monitor the quality of the prefabricated building component production process. This solves the technical problems of the existing building component quality monitoring, such as the difficulty in real-time monitoring at each assembly node and timely discovery of quality problems, the inability to dynamically adapt to environmental changes, and the lack of real-time and accuracy of the building component quality monitoring results and poor environmental adaptability, and achieves the technical effect of improving the accuracy, timeliness and construction flexibility of building component quality monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] 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.

[0015] Figure 1 A schematic diagram of a process for monitoring the quality of prefabricated building components provided in an embodiment of the present application; Figure 2 A schematic diagram of a process for obtaining a target building model in a method for monitoring quality of prefabricated building components provided in an embodiment of the present application. DETAILED DESCRIPTION

[0016] 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.

[0017] 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.

[0018] 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.

[0019] The present application provides a method for monitoring the quality of prefabricated building components. Figure 1 As shown, the method includes: Step S100, interactively obtaining target building design data of the proposed building, wherein the target building design data includes a building construction plan, component attribute information, a target building location, and a target building function.

[0020] Preferably, the design data of the proposed building is obtained through design software (such as BIM system), database, etc., including construction plan, component attribute information, target building location and target building function. Specifically, the construction plan is a detailed plan and strategy on how to implement building construction, including construction steps, construction technology, construction schedule, construction methods and detailed description of required equipment. It is used to define the construction sequence and steps of the building at different stages to ensure the orderly construction process, and provide time nodes and technical parameter support for quality monitoring. For example, the construction plan may include assembly schedules for different areas, use plans for lifting equipment, etc.; component attribute information includes physical and structural information such as geometric dimensions, material types, strength grades, connection methods, manufacturing standards, etc. of the building components to be produced, and the responses of different component types to the environment and loads. The target building location refers to the specific geographical location of the proposed building, which is usually represented by coordinates or address information, and determines the environmental conditions in which the building is located, such as climate, geology, wind load, snow load, earthquake and other external influences, which are used to network and call local environmental load information, such as wind speed, precipitation, temperature, humidity, earthquake data, etc.; the target building function is a description of the purpose of the proposed building, which usually includes residential, office, commercial or industrial use. Buildings with different functions have different requirements for bearing capacity, thermal insulation, sound insulation, fire resistance, etc. The building function, as a steady-state constraint condition, directly affects the design of the building and the use of its components. For example, commercial buildings require stronger load-bearing capacity, while residential buildings may have higher requirements for thermal insulation and sound insulation.

[0021] Step S200: digitizing the building structure based on the component attribute information to obtain a target building model of the proposed building.

[0022] Further, such as Figure 2 As shown, step S200 also includes step S210, extracting H component geometry information and H component material properties of H kinds of building components to be produced based on the component attribute information; step S220, using the H component geometry information to perform component modeling, and obtaining a component model library by archiving the model, wherein the component model library includes H kinds of component models of H kinds of building components to be produced; step S230, extracting component budgets based on the target building design data, and batch copying component models in the component model library according to the component budget to obtain a spare component model set; step S240, extracting component assembly relationships from the building construction plan, and using the component assembly relationships as assembly constraints and the spare component model set as component scheduling constraints to perform building structure digitization to obtain the target building model of the proposed building.

[0023] Preferably, the building structure is digitally processed using the component attribute information (geometric shape, material properties, strength grade, connection method, etc. of each building component to be produced) to generate a virtual building model, that is, the actual building is converted into a digital model that can be used for analysis and simulation, and the target building model of the proposed building is obtained, reflecting the structure and component details of the building. Specifically, the component geometry information and component material information of H different types of building components to be produced are extracted from the component attribute information, wherein H is a positive integer, indicating that the construction project contains H different types of building components to be produced, such as beams, columns, wall panels, etc., and by analyzing these component attribute information, the geometric information such as shape and size of each component and the material properties of reinforced concrete, steel, wood, etc. are extracted; then, the extracted component geometry information is used for component modeling, that is, a three-dimensional model is generated for each building component to be produced, which not only shows the shape of the component, but also includes the material properties of the component, ensuring that mechanical analysis and assembly can be performed, and the generated multiple component models are stored in a database to form a component model library of the building components to be produced, and the component model library contains component models of H types of building components to be produced, which are used for analysis, simulation and assembly during the construction process.

[0024] Preferably, extracting the component budget based on the target building design data specifically refers to budgeting the usage of each building component to be produced based on the acquired target building design data, that is, calculating the number of H types of building components to be produced required in the entire construction project, and optimizing them in combination with the building construction plan to ensure cost control and the accuracy of component supply. According to the component budget, each building component to be produced is batch copied from the component model library according to the budget requirements, and multiple spare component models are generated to form a spare component model set to meet the component requirements of different construction stages and different areas, and can also cope with situations such as component damage and loss; then extracting the component assembly relationship from the building construction plan, the assembly relationship refers to how the components are combined into a complete building structure during the assembly process, and the details are as follows: It describes how components are connected to each other, the connection sequence, and the load-bearing requirements, for example, how columns are connected to beams, how wall panels are fixed to floors, etc.; finally, the component assembly relationship is used as the assembly constraint, and the spare component model set is used as the component scheduling constraint. Specifically, it refers to following the component assembly relationship and requirements (each component must be assembled in the order and manner required by the design, and there must be no structural imbalance or assembly errors) to ensure that the components are available at the appropriate time and place, that is, how to schedule (select and allocate) component models from the spare component model set to meet the assembly requirements in different time periods or construction stages, assemble and combine all spare component models in a correct way, and generate a complete digital building model, that is, the target building model of the proposed building, reflecting the final structure of the proposed building.

[0025] Step S300, calling network data according to the target building location to obtain multiple load environment information.

[0026] Preferably, calling the networked data according to the target building location specifically refers to calling the external data source online to obtain the environment-related information of the location, especially the load data affecting the building components and structure, based on the geographical location of the proposed building. Specifically, calling the networked data refers to connecting to the external data source through the Internet to obtain real-time environmental data related to the building location. These environmental data may come from meteorological departments, engineering databases, geological surveys, building specification databases, etc., and then obtain multiple load environment information. Load environment information refers to various natural and man-made factors that exert loads or influences on the building structure, affecting the design of the building (such as having an important impact on the strength, stability and service life of the structure and components). Common load environment information includes wind load (the force exerted by wind on the surface of the building, obtained by calling meteorological data at the location of the building). Wind speed, wind direction and wind load distribution), snow load (the weight of snow on building structures, especially roofs and beams, obtain historical data on snowfall and snow load at the location from meteorological or engineering databases), earthquake load (vibration load on building foundations and structures caused by earthquakes, call the earthquake data source to obtain information such as earthquake activity, earthquake frequency, and magnitude at the building location), ground subsidence and foundation bearing capacity (changes in soil structure or groundwater flow, possible settlement of the foundation, call geological survey data to obtain the geological conditions of the building location, evaluate soil bearing capacity and potential foundation settlement risks), temperature changes and thermal loads (temperature changes can affect the expansion and contraction of building materials, especially under extreme climatic conditions, obtain historical temperature data for the location, as well as possible extreme high or low temperatures to evaluate the performance of building materials under thermal expansion and contraction conditions), etc.

[0027] Step S400, taking the multiple load environment information as dynamic constraints and the target building function as steady-state constraints, a mechanical behavior simulation is performed on the target building model to obtain multiple load condition models.

[0028] Furthermore, step S400 also includes serializing the H types of component models based on volume, and extracting the limit component model with the smallest volume from the serialization results; step S420, setting 1 / 100 of the limit volume of the limit component model as the grid volume parameter; step S430, predefining the grid unit shape, and performing grid size inversion according to the grid volume parameter to obtain the target grid; step S440, importing the target building model into finite element analysis software, and after meshing the target grid, using the H component material property mapping to define the material properties of the H types of component models in the target building model to obtain the building finite element model; step S450, using the multiple load environment information as dynamic constraints and the target building function as a steady-state constraint, performing mechanical behavior simulation on the building finite element model to obtain the multiple load condition models.

[0029] Preferably, volume serialization is to sort different component models in the building model according to their volumes. Specifically, the volumes of component models of H different types of prefabricated components (such as beams, columns, wall panels, etc.) are calculated and sorted to determine the geometric volume of each component. Then, from the volume serialization result, the component model with the smallest volume is extracted, which is called the extreme component model, indicating that the volume is the smallest among all component models and is used for setting subsequent meshing parameters, that is, the mesh size is defined by determining the minimum volume of the component to ensure that the meshing is fine enough to accurately simulate the mechanical behavior; then 1 / 100 of the extreme volume of the extreme component model is set as the mesh volume parameter, that is, the benchmark parameter for defining the mesh size to ensure that each mesh unit is small enough to accurately describe the mechanical properties of the component.

[0030] Preferably, in finite element analysis, the building model will be divided into small units (grids), each unit has a specific geometric shape. Commonly used grid unit shapes include tetrahedrons, hexahedrons (such as cubes, cuboids) and other irregular shapes. Different unit shapes are suitable for different types of components and structures. Then, the specific size of each grid unit is inferred through the grid volume parameter (1 / 100 of the limit component volume) to ensure that the grid division matches the complexity and details of the building model, thereby ensuring the accuracy of mechanical analysis; then the target building model is imported into professional finite element analysis software (such as ANSYS, ABAQUS, etc.), and the analysis software is used to simulate the mechanical response of the proposed building under different environmental load conditions, and then the determined grid unit shape and grid size parameters are used to analyze the target building. The building model is meshed, that is, the entire building model is divided into countless small units, each unit can independently calculate mechanical properties such as stress and strain, and then the mapping relationship between H component material properties and component models is used (each building component to be produced has its own unique material properties, such as strength, stiffness, density, elastic modulus, etc.) to configure the material properties of an unspecified number of component models in the target building model. Specifically, these material properties are mapped to the corresponding grid units in the finite element model. Each unit in the meshed building model will have corresponding material properties according to the component type to which it belongs, that is, the mechanical properties of each component of the building (such as walls, beams, columns, etc.) are accurately defined to ensure that the simulation results can truly reflect the mechanical behavior of the actual material and obtain the building finite element model.

[0031] Preferably, finally, multiple load environment information (such as wind load, snow load, earthquake load, etc.) is used as dynamic constraints, and the target building function (such as residential, commercial use) is used as a steady-state constraint to simulate the mechanical behavior of the building finite element model. Specifically, the environmental data of the building location is used as a dynamic input condition, and the fixed constraints on the design and load requirements of the building are proposed according to the function of the target building. After the mesh division and material property definition are completed, the entire building model is mechanically analyzed by finite element software, that is, the dynamic load information (such as wind, earthquake, temperature change) and the steady-state building function requirements (such as load-bearing, insulation, etc.) are combined to evaluate the mechanical performance of the building under these conditions, and the stress distribution, deformation and structural stability of the target building under different conditions are simulated. The simulation results under each load condition will generate a mechanical model, called a load condition model, which shows the mechanical performance of the building under different load conditions. The building model is simulated in detail by finite element analysis (FEA) to ensure the structural safety of the building under various load conditions. The mechanical behavior of the building can be accurately evaluated through volume serialization, mesh division, material property mapping and load simulation.

[0032] Step S450 further includes step S451, combining and enumerating the multiple load environment information to obtain multiple groups of backup environment information; step S452, traversing and filtering the multiple groups of backup environment information by mutually exclusive weather states to obtain multiple groups of filtered environment information; step S453, retaining the extreme values ​​of overlapping environmental factors for the multiple groups of filtered environment information to obtain multiple fused environment information; step S454, using the multiple load environment information as dynamic constraints and the target building function as a steady-state constraint, applying loads and simulating mechanical behaviors on the building finite element model to obtain the multiple load condition models.

[0033] Preferably, a plurality of different load environment information combinations are enumerated to generate different load combination scenarios, wherein enumeration refers to listing all possible load combinations, for example, a possible combination of wind load and snow load, or a combination of earthquake load and high temperature load, and multiple possible load scenarios are generated by combined enumeration, i.e., multiple sets of backup environment information, reflecting different complex environmental conditions that the building may face; under actual environmental conditions, certain weather conditions cannot occur at the same time (for example, strong wind and no wind are mutually exclusive states), and those load combinations that cannot occur at the same time are excluded by traversal and screening, specifically, all backup environment information is traversed, and weather or load combinations that meet the actual conditions are screened out, and unreasonable or mutually exclusive scenarios are deleted therefrom, for example, heavy snow and high temperature cannot exist at the same time, and such mutually exclusive weather states will be excluded, forming multiple sets of screened environment information, representing different external environmental conditions, which are more in line with the actual environmental load conditions.

[0034] Preferably, among the multiple screened environmental information, some environmental factors may overlap. In order to simplify the simulation and ensure the safety of the building under the worst conditions, the maximum values ​​of these overlapping environmental factors will be retained. For example, multiple wind speeds, precipitation, snowfall, etc. in the scene all retain the maximum values ​​as representative extreme conditions, ensuring that the building can withstand the load under the most demanding environmental conditions. By retaining extreme values ​​and simplifying overlapping factors, multiple fused environmental information is generated for load application and simulation of the finite element model; finally, multiple load environmental information is used as dynamic constraints and fixed conditions that the target building function must meet in the building (such as bearing capacity, earthquake resistance, wind resistance, etc.) are used as stable constraints. Dynamic constraints are applied to the finite element model of the building by applying multiple load conditions from fused environmental information, simulating the mechanical response of the building under these conditions, and evaluating the structural performance of the building under these loads, such as determining the stress distribution of the building under load and identifying high stress areas in the structure; evaluating the deformation of the building under load, including the displacement, bending or twisting of the building; predicting the possible damage or failure locations of the building under extreme load conditions, helping to identify the weak points of the building design; and finally generating multiple load condition models, each of which reflects the mechanical performance of the building under a specific load combination, which are used to analyze the safety, stability and bearing capacity of the building under different environmental conditions.

[0035] Step S500: Blocking the building based on the building construction plan to obtain M building areas marked by stage assembly task sequences.

[0036] Furthermore, step S500 further includes step S510, disassembling the building construction plan to obtain M phased construction tasks, wherein the M phased construction tasks have M task execution sequence identifiers; step S520, dividing the construction progress of the target building model into blocks based on the M phased construction tasks, and sorting the block results according to the M task execution sequence identifiers to obtain a phase assembly task sequence; step S530, dividing the target building model into the M building areas according to the phase assembly task sequence.

[0037] Preferably, building blockization refers to dividing the entire construction project into multiple construction areas, and carrying out construction management in stages and areas, so as to more effectively arrange resources and personnel and improve construction efficiency. Each construction area can represent a part of the building, such as foundation, wall, floor, etc. Each construction area will be associated with a specific construction task and identify its assembly task sequence. The task sequence identifier defines the order in which each area needs to be assembled during the construction process. Specifically, the complex construction plan is disassembled into M smaller phased construction task units, each task represents a construction stage, such as foundation preparation, steel bar installation, concrete pouring, structure assembly, etc. Each phased task is independent and executed in a certain order, and each construction task has a The unique execution sequence identifier is used to determine its position in the entire construction progress and ensure that each construction task can be carried out in the correct time sequence; then based on the M phased construction tasks obtained by disassembly, the entire building model is divided into blocks according to the construction progress, and the work in different construction phases is divided into smaller and manageable units to facilitate the construction of multiple areas at the same time, thereby improving the efficiency of overall progress control and resource allocation; these blocks are then sorted according to the task execution sequence identifier to obtain the phase assembly task sequence, that is, the construction sequence list of each building block; finally, according to the generated phase assembly task sequence, the target building model is divided into M building areas, each area corresponds to a part of the construction process, and the construction tasks of each area will be executed in the planned order.

[0038] Step S600: Fit the M building areas to the multiple load condition models to perform component mechanical performance analysis to obtain M component mass constraint libraries.

[0039] Further, step S600 also includes step S610, projecting the first building area to the multiple load condition models to obtain multiple regional load models, wherein the first building area is any one of the M building areas; step S620, extracting the component model composition of the first building area from the target building model to obtain a first group of component models, wherein the first group of component models includes N types of component models, and N is a positive integer less than or equal to H; step S630, extracting N groups of first component load models from the first regional load model with the N types of component models as constraints, wherein the first regional load model is any one of the multiple regional load models; step S640, performing performance limit analysis on the N groups of first component load models to obtain N component mass constraints; step S650, associating the N types of component models with the N component mass constraints and storing them as a first component mass constraint library; step S660, and so on, fitting the M building areas to the multiple load condition models to perform component mechanical performance analysis to obtain the M component mass constraint library.

[0040] Preferably, M building areas are fitted with corresponding load models, and the mechanical properties of components in each area under different load conditions are analyzed to obtain the performance of components in each area under various load conditions, such as stress, strain, deformation, etc., and generate corresponding M component mass constraint libraries. Specifically, the first building area (such as a foundation, a certain floor or a wall) is mapped to multiple load condition models generated previously, and the performance of the area under different load conditions is analyzed, such as the effect of wind, earthquake or snow load on the components in the area, to obtain multiple regional load models to show the stress state of the building area under different loads, wherein the first building area is any one of the M building areas; each building area contains multiple building components to be produced, and these components have different types, sizes and materials. Multiple specific component models of the area are extracted from the target building model to form a first group of component models, representing N types of components in the first area, N can be less than or equal to H types (the total number of component types of the entire building), including beams, columns, walls, etc.

[0041] Preferably, according to the N component models in the first region, their force constraint conditions under load conditions (such as the maximum load and deformation limit that each component can withstand, etc.) are defined, and the specific performance of each component under different load conditions is extracted from the generated regional load model to form N groups of first component load models, which represent the stress state and mechanical properties of each component under different environmental conditions; then, a performance limit analysis is performed on the N groups of first component load models, that is, a limit analysis is performed on the load model of each component to evaluate the maximum stress, strain, deformation and other limit values ​​that the component can withstand under different load conditions, to ensure that each component will not fail when exceeding its design limit, and to generate N quality constraint standards, including indicators such as strength and stiffness of the component under various load conditions. Ensure that the components can operate safely under extreme environments; then associate the N analyzed component models with their corresponding quality constraints (i.e., their performance limits and quality standards) and store them as the first component quality constraint library, which contains the quality control standards of all components in the first area. Similarly, fit the M building areas to multiple load condition models for component mechanical performance analysis. Specifically, through the same process, fit other building areas (such as the second and third areas) to different load condition models for mechanical performance analysis, and generate corresponding component quality constraint libraries. Finally, component quality constraint libraries for M areas are generated. Each library contains the quality standards and performance limits of the components in the area under different environmental loads, ensuring the safety and stability of the components in each building area under different environmental conditions.

[0042] Step S640 further includes step S641, predefining a key performance indicator set; step S642, extracting performance indicators of the N groups of first component load models based on the key performance indicator set as a constraint to obtain N groups of component performance arrays; step S643, fusing data of the N groups of component performance arrays based on the same type of components to obtain N fused performance arrays; step S644, retaining the performance maximum of the N fused performance arrays to obtain the N component quality constraints.

[0043] Preferably, key performance indicators are predefined according to building specifications, design requirements and environmental conditions, including key parameters for evaluating component performance, including stress (internal force borne by a component under different load conditions), strain (deformation of a component under load), deformation (displacement or deformation of a component under a specific load), stiffness (ability of a component to resist deformation), strength (maximum load that a component can withstand), fatigue limit (fatigue strength that a component can withstand under repeated loads), etc.; then, using the key performance indicator set as a constraint condition, performance data corresponding to the key performance indicator set is extracted from each component load model. For example, under wind load, performance indicators such as stress, strain, and deformation of each component are extracted to form N groups of component performance arrays, each performance array representing the specific performance of a component under different load conditions. For example, the stress and strain data of a component under wind load and seismic load will be organized into an array.

[0044] Preferably, if there are multiple groups of components of the same type (e.g., multiple identical beams or multiple identical wall panels) in the first region, which have similar mechanical performances under different environmental loads, the performance arrays of these components of the same type are data-fused, that is, the performance data of the same components are combined together to eliminate redundant data, and the performance under different environments is merged and averaged. The performance of all the same components is integrated to generate N fused performance arrays, each array representing the comprehensive performance of the type of components under all environmental loads; under different environmental load conditions, certain performance indicators (such as stress, deformation) will reach limit values, and the performance limit value (maximum stress, maximum deformation, etc.) of each component is extracted from the fused performance array to ensure that the component can still operate safely under the worst design conditions, and the quality constraint of each component is generated by retaining the maximum value to ensure that the component can maintain structural stability and safety under different environmental loads, wherein the quality constraint defines the performance upper limit of the component under various loads, and finally N component quality constraints are obtained, and the N component quality constraints correspond to the quality control standards of all components in the first region to ensure that their mechanical properties under all load conditions meet the requirements.

[0045] Step S700: dynamically calling the M component quality constraint libraries according to the stage assembly task sequence to perform quality monitoring of the production process of prefabricated building components.

[0046] Furthermore, step S700 also includes step S710, calling the initial phase construction task from the M phase construction tasks in sequence based on the M task execution sequence identifiers; step S720, calling the initial component quality constraint library from the M component quality constraint libraries according to the initial phase construction task; step S730, when using the initial component quality constraint library to monitor the quality of the prefabricated building component production process, if the real-time building component does not satisfy the initial component quality constraint library, then using the real-time building component to traverse M-1 component quality constraint libraries to perform recycling analysis on the real-time building component.

[0047] Preferably, based on the stage assembly task sequence (determining the task execution order of each stage in the construction process), the component quality constraint library corresponding to each construction stage is dynamically called. During the component production process, the quality of each component is monitored to ensure that it meets the predefined quality constraints. Specifically, based on M task execution sequence identifiers, the first stage construction task is called from the M stage construction tasks according to the construction progress, that is, the initial stage construction task, which represents the starting point of the entire construction process, and all subsequent construction tasks depend on the correct execution of this stage; each stage construction task corresponds to a set of component production and assembly quality requirements. After calling the initial stage construction task, the quality constraint library related to the initial stage is called from the M component quality constraint library, that is, the initial component Quality constraint library; during the production process of prefabricated building components, each component is monitored in real time to ensure that they meet the standards defined in the initial component quality constraint library (including component size, strength, material properties, etc.). If a component does not meet the requirements in the initial component quality constraint library during the production process, it will not be discarded immediately. Instead, through recycling analysis, the remaining M-1 component quality constraint libraries (i.e., quality standards for other construction stages) are traversed to determine whether the component can meet the requirements of other stages in subsequent construction tasks, thereby minimizing waste. For example, if a component fails in the initial construction stage but still meets the quality standards of other stages, it will be reallocated to other construction tasks for continued use, thereby improving component utilization and optimizing production and construction efficiency.

[0048] 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 the quality of assembled building components, characterized in that: The method comprises: Interactively obtaining target building design data of the proposed building, wherein the target building design data includes a building construction plan, component attribute information, a target building location, and a target building function; Perform building structure digitization based on the component attribute information to obtain a target building model of the proposed building; Calling network data according to the target building location to obtain multiple load environment information; Taking the multiple load environment information as dynamic constraints and the target building function as steady-state constraints, mechanical behavior simulation is performed on the target building model to obtain multiple load condition models; Based on the building construction plan, the building is divided into blocks to obtain M building areas marked by a stage assembly task sequence; Fitting the M building areas to the multiple load condition models to perform component mechanical performance analysis to obtain M component mass constraint libraries; The M component quality constraint libraries are dynamically called according to the stage assembly task sequence to perform quality monitoring of the production process of prefabricated building components.

2. The method for monitoring the quality of prefabricated building components according to claim 1, characterized in that: Digitalizing the building structure based on the component attribute information to obtain a target building model of the proposed building, the method comprising: Extracting H component geometric information and H component material properties of H types of building components to be produced based on the component property information; Using the H component geometric information to perform component modeling, and obtaining a component model library by archiving the model, wherein the component model library includes H component models of H building components to be produced; Extracting component budget based on the target building design data, and performing batch copying of component models in the component model library according to the component budget to obtain a spare component model set; Component assembly relations are extracted from the building construction plan, and the component assembly relations are used as assembly constraints, and the spare component model set is used as component scheduling constraints to perform building structure digitization and obtain a target building model of the proposed building.

3. The method for monitoring the quality of prefabricated building components according to claim 1, characterized in that: Based on the building construction plan, building blocks are formed to obtain M building areas. The method includes: Disassembling the building construction plan to obtain M phased construction tasks, wherein the M phased construction tasks have M task execution sequence identifiers; Divide the target building model into blocks based on the M phased construction tasks, and sort the block results according to the M task execution sequence identifiers to obtain a phased assembly task sequence; The target building model is divided into the M building areas according to the stage assembly task sequence.

4. The method for monitoring the quality of prefabricated building components according to claim 2, characterized in that: Taking the multiple load environment information as dynamic constraints and the target building function as steady-state constraints, mechanical behavior simulation is performed on the target building model to obtain multiple load condition models, the method includes: Serialize the H component models based on volume, and extract the limit component model with the smallest volume from the serialization results; Setting 1 / 100 of the limit volume of the limit component model as a grid volume parameter; Predefine the grid unit shape, and perform grid size inversion according to the grid volume parameter to obtain the target grid; The target building model is imported into finite element analysis software, and after meshing is performed using the target mesh, the material properties of H component models in the target building model are defined using the H component material property mappings to obtain a building finite element model; Taking the multiple load environment information as dynamic constraints and the target building function as steady-state constraints, mechanical behavior simulation is performed on the building finite element model to obtain the multiple load condition models.

5. The method for monitoring the quality of prefabricated building components according to claim 4, characterized in that: Taking the multiple load environment information as dynamic constraints and the target building function as steady-state constraints, mechanical behavior simulation is performed on the building finite element model to obtain the multiple load condition models, the method comprising: Combining and enumerating the plurality of load environment information to obtain a plurality of sets of backup environment information; Perform mutually exclusive weather state traversal screening on the multiple sets of backup environmental information to obtain multiple sets of screened environmental information; The extreme values ​​of overlapping environmental factors are retained for multiple sets of screening environmental information to obtain multiple fused environmental information; Taking the multiple load environment information as dynamic constraints and the target building function as steady-state constraints, load application and mechanical behavior simulation are performed on the building finite element model to obtain the multiple load condition models.

6. The method for monitoring the quality of prefabricated building components according to claim 5, characterized in that: The M building areas are fitted to the multiple load condition models to perform component mechanical performance analysis to obtain M component mass constraint libraries, the method comprising: Projecting a first building area onto the multiple load condition models to obtain multiple regional load models, wherein the first building area is any one of the M building areas; Extracting a component model of the first building area from the target building model to obtain a first group of component models, wherein the first group of component models includes N types of component models, where N is a positive integer less than or equal to H; Extracting and obtaining N groups of first component load models from a first regional load model with the N component models as constraints, wherein the first regional load model is any one of the multiple regional load models; Performing performance limit analysis on the N groups of first component load models to obtain N component mass constraints; The N component models are associated with the N component mass constraints and stored as a first component mass constraint library; By analogy, the M building areas are fitted to the multiple load condition models to perform component mechanical performance analysis, and the M component mass constraint libraries are obtained.

7. The method for monitoring the quality of prefabricated building components according to claim 6, characterized in that: Performing performance limit analysis on the N groups of first component load models to obtain N component mass constraints, the method comprising: Predefined set of key performance indicators; Extracting performance indicators of the N groups of first component load models with the key performance indicator set as a constraint to obtain N groups of component performance arrays; Based on the same kind of components, data fusion is performed on the N groups of component performance arrays to obtain N fused performance arrays; The performance maximum is retained for the N fusion performance arrays to obtain the N component quality constraints.

8. The method for monitoring the quality of prefabricated building components according to claim 3, characterized in that: The M component quality constraint libraries are dynamically called according to the stage assembly task sequence to perform quality monitoring of the production process of prefabricated building components, and the method includes: Based on the M task execution sequence identifiers, calling the initial phased construction task from the M phased construction tasks in sequence; Calling an initial component quality constraint library from the M component quality constraint libraries according to the initial phased construction tasks; When the initial component quality constraint library is used to monitor the quality of the production process of prefabricated building components, if the real-time building components do not meet the initial component quality constraint library, the real-time building components are used to traverse M-1 component quality constraint libraries to perform recycling analysis on the real-time building components.

Images