An intelligent management system and intelligent management method for prefabricated building construction

Abstract

The present application provides an intelligent management system and an intelligent management method for prefabricated building construction. First, a three-dimensional object group of a building information model of a prefabricated building is obtained; then, the assembly coordination degree and the assembly weight corresponding to each assembly object are determined; the three-dimensional object group of the building information model is classified according to the assembly coordination degree and the assembly weight corresponding to each assembly object, so as to obtain a plurality of assembly object levels; assembly is performed according to each assembly object in a first assembly object level, and the assembly adaptation entropy corresponding to each assembly object in the first assembly object level is determined according to an adaptability data group; the remaining assembly object levels are updated according to the assembly adaptation entropy corresponding to each assembly object in the first assembly object level, and segmented assembly is performed according to the remaining assembly object levels after the update. The present application performs segmented assembly according to the connection relationship between each assembly object in the prefabricated building, so as to avoid the potential safety hazard caused by excessive installation errors between assembly objects.

Description

Technical Field

[0001] The present application relates to the technical field of prefabricated buildings, and more specifically, to an intelligent management system and intelligent management method for prefabricated building construction. Background Art

[0002] With the rapid development of information technology, the construction industry is undergoing a profound transformation. Prefabricated buildings, as a new type of construction method, are gradually favored by the industry for their high efficiency and environmental protection. The construction management of residential prefabricated construction projects is a key link to ensure the smooth progress and high-quality completion of the project. With the rapid development and widespread application of prefabricated building technology, the importance of construction management has become increasingly prominent.

[0003] In the existing intelligent management methods for prefabricated building construction, the fault tolerance rate of the design and construction of prefabricated buildings is low. In actual projects, due to the adjustment of the project product positioning during the building design cycle, or the lag in the conditions for secondary in-depth design such as decoration and intelligence, the components designed in the early stage may not be able to fully meet the requirements of later installation or use. For example, the most important nodes and connections in structural design and construction, if design and construction errors occur, will lead to a decrease in the safety and reliability of the structure, and even safety hazards such as water seepage and leakage, durability and seismic resistance not meeting the requirements. Summary of the invention

[0004] The present application provides an intelligent management system and an intelligent management method for prefabricated building construction, so as to improve the connection stability between various component nodes when the prefabricated building structure is connected.

[0005] In a first aspect, the present application provides a method for intelligent management of prefabricated building construction, which can be executed by a network device, or by a chip configured in the network device, and the present application does not limit this.

[0006] Specifically, the method includes:

[0007] Obtain a three-dimensional object group of a building information model of a prefabricated building;

[0008] Determining the assembly coordination degree and assembly weight corresponding to each assembly object according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model;

[0009] Classifying the three-dimensional object group of the building information model according to the assembly coordination degree and the assembly weight corresponding to each assembly object to obtain a plurality of assembly object levels;

[0010] Performing assembly according to each assembly object in the first assembly object level, acquiring an adaptability data group in the assembly process, and determining assembly adaptability entropies corresponding to each assembly object in the first assembly object level according to the adaptability data group;

[0011] The remaining assembly object levels are updated according to the assembly adaptation entropies respectively corresponding to the respective assembly objects in the first assembly object level, and segmented assembly is performed according to the remaining assembly object levels after the update.

[0012] In combination with the first aspect, in some implementations of the first aspect, determining the assembly coordination degree and assembly weight corresponding to each assembly object according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model specifically includes:

[0013] Acquire the node connection relationship between each assembly object in the three-dimensional object group of the building information model;

[0014] Determine the assembly connection matrix according to the node connection relationship between each assembly object;

[0015] According to the assembly connection matrix, the assembly coordination degree and the assembly weight corresponding to each assembly object are determined.

[0016] In conjunction with the first aspect, in some implementations of the first aspect, assembling according to each assembly object in the first assembly object level specifically includes:

[0017] Obtaining assembly weights corresponding to each assembly object in the first assembly object level;

[0018] The respective assembly objects in the first assembly object level are assembled according to the assembly weights respectively corresponding to the respective assembly objects in the first assembly object level.

[0019] In combination with the first aspect, in some implementations of the first aspect, updating the remaining assembly object levels according to the assembly adaptation entropies respectively corresponding to the respective assembly objects in the first assembly object level specifically includes:

[0020] Obtain each assembly object in the remaining assembly object levels, and combine them to obtain an update object set;

[0021] Determine, according to the connection relationship between each assembly object in the first assembly level and the update object set, the coordination factor corresponding to each update object in the update object set;

[0022] Determine the secondary distribution matrix of the update object set according to the coordination factors corresponding to each update object and the assembly adaptation entropy corresponding to each assembly object;

[0023] The update object set is updated according to the secondary allocation matrix to obtain a plurality of updated assembly object levels.

[0024] In conjunction with the first aspect, in certain implementations of the first aspect, performing segmented assembly according to the remaining assembly object levels after the update specifically includes:

[0025] Assembling according to a first updated assembly object level in the remaining assembly object levels after the update, and determining the assembly adaptation entropies corresponding to the assembly objects in the first updated assembly object level respectively during the assembly process;

[0026] updating the remaining updated assembly object levels according to the assembly adaptation entropies respectively corresponding to the assembly objects in the first updated assembly object level;

[0027] Assembling is performed again according to the first updated assembly object level in the remaining assembly object levels after the update, and the above steps are repeated until all assembly objects have been assembled.

[0028] In combination with the first aspect, in some implementations of the first aspect, a K-means clustering method is used to perform two-dimensional clustering according to the assembly coordination degrees and assembly weights corresponding to each assembly object, thereby obtaining multiple assembly object levels.

[0029] In combination with the first aspect, in some implementations of the first aspect, the node connection relationship between the assembly objects includes a connection point, a connection type, and a connection object of each assembly object.

[0030] In a second aspect, the present application provides an intelligent management system for prefabricated building construction, the system comprising a construction control unit, the construction control unit comprising:

[0031] An acquisition module, used for acquiring a three-dimensional object group of a building information model of a prefabricated building;

[0032] A processing module, for determining the assembly coordination degree and assembly weight corresponding to each assembly object according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model;

[0033] The processing module is further used to classify the three-dimensional object group of the building information model according to the assembly coordination degree and assembly weight corresponding to each assembly object, so as to obtain a plurality of assembly object levels;

[0034] The processing module is further used to perform assembly according to each assembly object in the first assembly object level, obtain an adaptability data group in the assembly process, and determine the assembly adaptability entropy corresponding to each assembly object in the first assembly object level according to the adaptability data group;

[0035] The execution module is used to update the remaining assembly object levels according to the assembly adaptation entropy corresponding to each assembly object in the first assembly object level, and perform segmented assembly according to the remaining assembly object levels after the update.

[0036] In a third aspect, the present application provides a computer terminal device, which includes a memory and a processor, wherein the memory stores a code, and the processor is configured to obtain the code and execute the above-mentioned intelligent management method for prefabricated building construction.

[0037] In a fourth aspect, the present application provides a computer-readable storage medium, which stores at least one computer program, and the computer program is loaded and executed by a processor to implement the operations performed by the above-mentioned intelligent management method for prefabricated building construction.

[0038] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0039] In an intelligent management system and intelligent management method for prefabricated building construction provided by the present application, a three-dimensional object group of a building information model of a prefabricated building is first obtained; according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model, the assembly coordination degree and assembly weight corresponding to each assembly object are determined; wherein the assembly coordination degree represents the overall assembly difficulty of the assembly object when it is assembled with other assembly objects, and the assembly weight represents the importance of the assembly object in the prefabricated building. The assembly coordination degree and assembly weight corresponding to each assembly object are determined, so that the mutual relationship and influence between each component can be taken into account during the assembly process, ensuring that each node connection rationality and reliability; then, the three-dimensional object group of the building information model is classified according to the assembly coordination degree and assembly weight corresponding to each assembly object, and multiple assembly object levels are obtained, so that the most critical and complex assembly objects can be processed preferentially in the assembly process to ensure the connection quality of these key parts; assembly is performed according to each assembly object in the first assembly object level, and an adaptability data group in the assembly process is obtained, and the assembly adaptation entropy corresponding to the assembly objects in the first assembly object level is determined according to the adaptability data group; the remaining assembly object levels are updated according to the assembly adaptation entropy corresponding to each assembly object in the first assembly object level, and segmented assembly is performed according to the remaining assembly object levels after the update.

[0040] The present application dynamically adjusts and updates the assembly strategies of the remaining assembly object levels according to the assembly adaptation entropy of each assembly object in the first assembly object level. Since the assembly adaptation entropy reflects the actual adaptation of each object in the assembly process, it can identify and correct potential assembly errors and connection problems. In addition, the present application adopts a segmented assembly method based on the connection relationship between each assembly object in the prefabricated building, which avoids the safety hazards caused by excessive installation errors between assembly objects and improves the connection stability between each component node. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is an exemplary flow chart of an intelligent management method for prefabricated building construction according to some embodiments of the present application;

[0042] Figure 2 is a schematic diagram of exemplary hardware and / or software of a construction control unit according to some embodiments of the present application;

[0043] Figure 3 It is a structural schematic diagram of a computer terminal device for implementing an intelligent management method for prefabricated building construction according to some embodiments of the present application. DETAILED DESCRIPTION

[0044] The present application first obtains a three-dimensional object group of a building information model of an assembled building; determines the assembly coordination degree and assembly weight corresponding to each assembly object according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model; classifies the three-dimensional object group of the building information model according to the assembly coordination degree and assembly weight corresponding to each assembly object, and obtains a plurality of assembly object levels; assembles according to each assembly object in the first assembly object level, obtains an adaptability data group in the assembly process, and determines the assembly adaptation entropy corresponding to each assembly object in the first assembly object level according to the adaptability data group; updates the remaining assembly object levels according to the assembly adaptation entropy corresponding to each assembly object in the first assembly object level, and performs segmented assembly according to the remaining assembly object levels after the update. The present application performs segmented assembly according to the connection relationship between each assembly object in the assembled building, avoids the safety hazard caused by excessive installation errors between assembly objects, and improves the connection stability between each component node.

[0045] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 , which is an exemplary flow chart of an intelligent management method for prefabricated building construction according to some embodiments of the present application. The intelligent management method 100 for prefabricated building construction mainly includes the following steps:

[0046] In step S101, a three-dimensional object group of a building information model of a prefabricated building is obtained.

[0047] It should be noted that Building Information Modeling (BIM) technology, as a digital modeling tool, is an emerging tool that uses three-dimensional graphics to assist in building construction. Its application in prefabricated building construction can not only improve construction efficiency, but also optimize design plans and reduce construction costs.

[0048] In some embodiments of the present application, the building information model three-dimensional object group is a collection of all prefabricated assembly component objects in the prefabricated building. For example, when the assembly of the building information model three-dimensional object group is a shear wall, the assembly component objects in the building information model three-dimensional object group are composed of prefabricated floor slabs, prefabricated shear walls, composite floor slabs, prefabricated stairs, prefabricated balconies, prefabricated air-conditioning panels, etc.

[0049] In specific implementation, Autodesk Revit and Graphisoft ArchiCAD may be used to create and manage a three-dimensional BIM model, thereby obtaining a three-dimensional object group of the building information model of the prefabricated building.

[0050] In step S102, the assembly coordination degree and assembly weight corresponding to each assembly object are determined according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model.

[0051] Optionally, in some embodiments, determining the assembly coordination degree and assembly weight corresponding to each assembly object according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model specifically includes:

[0052] Acquire the node connection relationship between each assembly object in the three-dimensional object group of the building information model;

[0053] Determine the assembly connection matrix according to the node connection relationship between each assembly object;

[0054] According to the assembly connection matrix, the assembly coordination degree and the assembly weight corresponding to each assembly object are determined.

[0055] In specific implementation, the node connection relationship between each assembly object includes the connection point of each assembly object, the connection type (such as welding, bolt connection, plug-in connection, etc.) and the connection object. In some embodiments, the connection attributes can be defined after determining the different connection types existing in the model, that is, considering factors such as connection strength, connection complexity and construction difficulty, and assigning corresponding assembly attribute values ​​to each connection type according to the weighting coefficient. Optionally, in some embodiments, the initial weighting coefficient of connection strength is 0.5, the initial weighting coefficient of connection complexity is 0.3, and the initial weighting coefficient of construction difficulty is 0.2. Then, for each connection type, according to the predetermined weighting coefficient, the connection attribute value is assigned to the connection attribute value. The performance of each attribute is evaluated by using defined standards or expert scoring methods, and the scores on each attribute are weighted and integrated according to the corresponding initial weighting coefficients to obtain the final assembly attribute value. The total assembly attribute value = (connection strength × strength weighting coefficient) + (connection complexity × complexity weighting coefficient) + (construction difficulty × difficulty weighting coefficient). Taking bolt connection as an example, its assembly attribute value = (4 × 0.5) + (2 × 0.3) + (3 × 0.2) = 2.0 + 0.6 + 0.6 = 3.2; the rows and columns of the matrix in the assembly connection matrix represent different assembly objects respectively, and the matrix elements represent the assembly attribute values ​​between two objects.

[0056] It should be noted that the assembly coordination degree represents the overall assembly difficulty of the assembly object when it is assembled with other assembly objects, and the assembly weight represents the importance of the assembly object in the prefabricated building. Optionally, in some embodiments, the correlation between each assembly object and other objects can be determined based on the assembly connection matrix, where the correlation can be defined as the sum of the assembly attribute values ​​between the assembly object and the other objects, and the assembly weight is the ratio between the number of assembly objects connected to the assembly object and the total number of objects in the three-dimensional object group of the building information model.

[0057] In step S103, the three-dimensional object group of the building information model is classified according to the assembly coordination degree and the assembly weight corresponding to each assembly object, so as to obtain a plurality of assembly object levels.

[0058] It should be noted that the assembly object level is a set of assembly objects, and the assembly objects in each assembly object level have the same object-level label. For example, the object-level labels of all assembly objects in the first assembly object level are 1. Optionally, in some embodiments, a K-means clustering method can be used to perform two-dimensional clustering according to the assembly coordination degree and assembly weight corresponding to each assembly object, thereby obtaining multiple assembly object levels.

[0059] Optionally, in some embodiments, the three-dimensional object group of the building information model is classified according to the assembly coordination degree and assembly weight corresponding to each assembly object, and the multiple assembly object levels are obtained, specifically including:

[0060] Obtain the assembly coordination degree corresponding to each assembly object; obtain the assembly weight corresponding to each assembly object;

[0061] According to the assembly coordination degree and assembly weight corresponding to each assembly object, each assembly object is transformed into a two-dimensional data space to obtain the two-dimensional data coordinate value corresponding to each assembly object.

[0062] According to the assembly coordination degree corresponding to each assembly object, the assembly balance degree and the assembly coordination mean value are determined;

[0063] Determine the number of classification clusters according to the assembly balance and the assembly coordination mean, and determine a plurality of initial two-dimensional cluster centers according to the number of classification clusters;

[0064] According to the two-dimensional data coordinate values ​​corresponding to each assembly object, each assembly object is classified into the nearest initial two-dimensional cluster center to obtain multiple assembly object levels.

[0065] In specific implementation, the assembly uniformity can be the standard deviation of the assembly coordination corresponding to each assembly object, the assembly coordination mean is the average value of the assembly coordination corresponding to each assembly object, the assembly uniformity and the assembly coordination mean are both distribution characteristics of the assembly coordination corresponding to each assembly object, and the number of classification clusters is determined according to the assembly balance and the assembly coordination mean, which can increase the accuracy of classifying the three-dimensional object group of the building information model. In some embodiments, the mapping value corresponding to the threshold interval where the product of the assembly balance and the assembly coordination mean is located can be determined, and the mapping value is the number of classification clusters. The number of the initial two-dimensional cluster centers is consistent with the number of classification clusters, and the initial two-dimensional cluster centers are uniformly generated in the two-dimensional data space where each assembly object is located. In some embodiments, the cluster center with the largest assembly weight (priority) and the smallest assembly coordination in the cluster center coordinates is taken as the first cluster center, and all assembly objects corresponding to the first cluster center are taken as the first assembly object level.

[0066] In step S104, assembly is performed according to each assembly object in the first assembly object level, an adaptability data group in the assembly process is acquired, and assembly adaptability entropies corresponding to each assembly object in the first assembly object level are determined according to the adaptability data group.

[0067] Optionally, in some embodiments, assembling according to each assembly object in the first assembly object level specifically includes:

[0068] Obtaining assembly weights corresponding to each assembly object in the first assembly object level;

[0069] According to the assembly weights respectively corresponding to the assembly objects in the first assembly object level, the assembly objects in the first assembly object level are assembled. In specific implementation, the assembly objects in the first assembly object level can be sorted and assembled from large to small according to the assembly weights respectively corresponding to the assembly objects, thereby ensuring that the assembly errors of the more important assembly objects are within a reasonable range.

[0070] It should be noted that the adaptability data group is a set of adaptability data of each assembly object in the first assembly object level when assembling, and the adaptability data includes the following data:

[0071] Position error data: The error value between the expected position and the actual position of each assembly object.

[0072] Time consumption data: assembly time of each assembly object.

[0073] Resource consumption data: resource consumption index (such as manpower and materials) of each assembly object.

[0074] It should be noted that the assembly adaptation entropy is the degree of adaptability of the connection between the assembly object and the other assembly objects. In some embodiments, the adaptability data corresponding to each assembly object can be weightedly fused by setting corresponding position weights, time weights, and resource weights to obtain the assembly adaptation entropies corresponding to the assembly objects in the first assembly object level.

[0075] In step S105, the remaining assembly object levels are updated according to the assembly adaptation entropies respectively corresponding to the respective assembly objects in the first assembly object level, and segmented assembly is performed according to the remaining assembly object levels after the update.

[0076] Optionally, in some embodiments, updating the remaining assembly object levels according to the assembly adaptation entropy corresponding to each assembly object in the first assembly object level specifically includes:

[0077] Obtain each assembly object in the remaining assembly object levels, and combine them to obtain an update object set;

[0078] Determine, according to the connection relationship between each assembly object in the first assembly level and the update object set, the coordination factor corresponding to each update object in the update object set;

[0079] Determine the secondary distribution matrix of the update object set according to the coordination factors corresponding to each update object and the assembly adaptation entropy corresponding to each assembly object;

[0080] The update object set is updated according to the secondary allocation matrix to obtain a plurality of updated assembly object levels.

[0081] In a specific implementation, the coordination factor corresponding to the update object = the number of assembly objects connected to the update object / the total number of assembly objects in the first assembly object level, wherein the elements in the secondary allocation matrix represent the connection relationship and connection type between assembly objects, the rows of the matrix represent different assembly objects, the columns of the matrix represent different update objects, the matrix elements represent the allocation sub-coefficients between assembly objects and update objects, and the allocation sub-coefficients = the coordination factor corresponding to the update × the assembly adaptation entropy corresponding to the assembly object.

[0082] It should be noted that the allocation sub-coefficient reflects the connection reliability between the assembly object and the update object, and the allocation coefficient reflects the predicted value of the connection reliability of the update object based on the original building. Optionally, in some embodiments, the update object set is updated according to the secondary allocation matrix to obtain multiple updated assembly object levels, specifically including: taking the sum of all allocation sub-coefficients of the update object as the allocation coefficient of the update object, clustering according to the allocation sub-coefficients of all the updated objects, and obtaining multiple updated assembly object levels, wherein the order of the updated assembly object levels is based on the order of the allocation coefficients corresponding to the assembly object levels from large to small, that is, the assembly object level with the largest assembly object center among all the updated assembly object levels is taken as the first assembly object level, and the order of the remaining assembly object levels is the same, which will not be elaborated here.

[0083] Optionally, in some embodiments, performing segmented assembly according to the remaining assembly object levels after the update specifically includes:

[0084] Assembling according to a first updated assembly object level in the remaining assembly object levels after the update, and determining the assembly adaptation entropies corresponding to the assembly objects in the first updated assembly object level respectively during the assembly process;

[0085] updating the remaining updated assembly object levels according to the assembly adaptation entropies respectively corresponding to the assembly objects in the first updated assembly object level;

[0086] Assembling is performed again according to the first updated assembly object level in the remaining assembly object levels after the update, and the above steps are repeated until all assembly objects have been assembled.

[0087] Optionally, in some embodiments, assembling according to the first updated assembly object level in the remaining assembly object levels after the update specifically includes: sequentially assembling each updated object in the first updated assembly object level according to the order of assembly coefficients from large to small.

[0088] Optionally, in some embodiments, the process of updating the remaining updated assembly object levels according to the assembly adaptation entropies corresponding to the assembly objects in the first updated assembly object level can be implemented in the same manner as updating the remaining assembly object levels according to the assembly adaptation entropies corresponding to the respective assembly objects in the first updated assembly object level, which is not elaborated here.

[0089] In addition, in another aspect of the present application, in some embodiments, the present application provides an intelligent management system for prefabricated building construction, the system includes a construction control unit, reference Figure 2 , which is a schematic diagram of exemplary hardware and / or software of a construction control unit according to some embodiments of the present application, the construction control unit 200 includes: an acquisition module 201, a processing module 202 and an execution module 203, which are described as follows:

[0090] Acquisition module 201, in some specific embodiments of the present application, the acquisition module 201 is mainly used to acquire a three-dimensional object group of a building information model of a prefabricated building;

[0091] Processing module 202, in some specific embodiments of the present application, the processing module 202 is used to determine the assembly coordination degree and assembly weight corresponding to each assembly object according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model;

[0092] The processing module 202, in some specific embodiments of the present application, is further used to classify the three-dimensional object group of the building information model according to the assembly coordination degree and assembly weight corresponding to each assembly object, so as to obtain a plurality of assembly object levels;

[0093] The processing module 202 is further used in some specific embodiments of the present application to assemble according to each assembly object in the first assembly object level, obtain an adaptability data group in the assembly process, and determine the assembly adaptability entropy corresponding to each assembly object in the first assembly object level according to the adaptability data group;

[0094] Execution module 203, in some specific embodiments of the present application, the execution module 203 is mainly used to update the remaining assembly object levels according to the assembly adaptation entropy corresponding to each assembly object in the first assembly object level, and perform segmented assembly according to the remaining assembly object levels after the update.

[0095] The above describes in detail an example of an intelligent management system and intelligent management method for prefabricated building construction provided in an embodiment of the present application. It can be understood that in order to realize the above functions, the corresponding device includes a hardware structure and / or software module corresponding to executing each function.

[0096] Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed in this document, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function in the application is executed in hardware or in a computer software-driven hardware manner depends on the specific application and design constraints of the technical solution. Therefore, professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0097] In addition, the present application also provides a computer terminal device, which includes a memory and a processor, the memory stores a code, and the processor is configured to obtain the code and execute the above-mentioned intelligent management method for prefabricated building construction.

[0098] In some embodiments, reference Figure 3 , which is a schematic diagram of the structure of a computer terminal device using an intelligent management method for prefabricated building construction according to some embodiments of the present application. An intelligent management method for prefabricated building construction in the above embodiment can be Figure 3 The computer terminal device 300 shown in the figure is implemented, and the computer terminal device 300 includes at least one communication bus 301, a communication interface 302, a processor 303 and a memory 304.

[0099] Processor 303 can be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more processors for controlling the execution of an intelligent management method for prefabricated building construction in the present application.

[0100] The communication bus 301 may include a path for transmitting information between the above-mentioned components.

[0101] The memory 304 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including a compressed optical disc, a laser disc, an optical disc, a digital versatile disc, a Blu-ray disc, etc.), a magnetic disk or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 304 may exist independently and be connected to the processor 303 via the communication bus 301. The memory 304 may also be integrated with the processor 303.

[0102] The memory 304 is used to store the program code for executing the solution of the present application, and the execution is controlled by the processor 303. The processor 303 is used to execute the program code stored in the memory 304. The program code may include one or more software modules. The determination of the assembly adaptation entropy in the above embodiment can be implemented by the processor 303 and one or more software modules in the program code in the memory 304.

[0103] The communication interface 302 uses any transceiver or other device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0104] Optionally, the computer terminal device 300 may further include a power supply 305 for providing power to various devices or circuits in the real-time computer terminal device.

[0105] In a specific implementation, as an embodiment, a computer terminal device may include multiple processors, each of which may be a single-CPU processor or a multi-CPU processor. The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0106] The above-mentioned computer terminal device may be a general-purpose computer terminal device or a special-purpose computer terminal device. In a specific implementation, the computer terminal device may be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device or an embedded device. The embodiment of the present application does not limit the type of computer terminal device.

[0107] In addition, in other aspects of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores at least one computer program, and the computer program is loaded and executed by a processor to implement the operations performed by the above-mentioned intelligent management method for prefabricated building construction.

[0108] In summary, in an intelligent management system and intelligent management method for prefabricated building construction disclosed in an embodiment of the present application, first, a three-dimensional object group of a building information model of a prefabricated building is obtained; according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model, the assembly coordination degree and assembly weight corresponding to each assembly object are determined; the three-dimensional object group of the building information model is classified according to the assembly coordination degree and assembly weight corresponding to each assembly object, so as to obtain multiple assembly object levels; according to each assembly object in the first assembly object level, assembly is performed to obtain an adaptability data group in the assembly process, and according to the adaptability data group, the assembly adaptation entropy corresponding to each assembly object in the first assembly object level is determined; according to the assembly adaptation entropy corresponding to each assembly object in the first assembly object level, the remaining assembly object levels are updated, and segmented assembly is performed according to the remaining assembly object levels after the update. The present application performs segmented assembly according to the connection relationship between each assembly object in the prefabricated building, thereby improving the connection stability between each component node.

[0109] The above is only an embodiment of the present application, and the common knowledge such as the specific technical scheme or characteristics in the scheme is not described in detail here. It should be pointed out that for those skilled in the art, without departing from the technical scheme of the present application, several modifications and improvements can be made, which should also be regarded as the scope of protection of the present application, and these will not affect the effect of the implementation of the present application and the practicality of the patent.

[0110] The scope of protection claimed by this application shall be based on the content of its claims. The specific implementation methods and other records in the specification can be used to interpret the content of the claims. Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is also intended to include these modifications and variations.

Claims

1. An intelligent management method for prefabricated building construction, characterized in that: include: Obtain a three-dimensional object group of a building information model of a prefabricated building; Determining the assembly coordination degree and assembly weight corresponding to each assembly object according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model; Classifying the three-dimensional object group of the building information model according to the assembly coordination degree and the assembly weight corresponding to each assembly object to obtain a plurality of assembly object levels; Assembling each assembly object in the first assembly object level, acquiring an adaptability data group in the assembly process, and determining assembly adaptability entropies corresponding to each assembly object in the first assembly object level according to the adaptability data group; updating the remaining assembly object levels according to the assembly adaptation entropies respectively corresponding to the respective assembly objects in the first assembly object level, and performing segmented assembly according to the remaining assembly object levels after the update; Updating the remaining assembly object levels according to the assembly adaptation entropies corresponding to the respective assembly objects in the first assembly object level specifically includes: Obtain each assembly object in the remaining assembly object levels, and combine them to obtain an update object set; Determine, according to the connection relationship between each assembly object in the first assembly object level and the update object set, the coordination factor corresponding to each update object in the update object set; Determine the secondary distribution matrix of the update object set according to the coordination factors corresponding to each update object and the assembly adaptation entropy corresponding to each assembly object; updating the update object set according to the secondary allocation matrix to obtain a plurality of updated assembly object levels; The assembly coordination degree represents the overall assembly difficulty of the assembly object when it is assembled with other assembly objects, and the assembly weight represents the importance of the assembly object in the prefabricated building; The adaptability data group is a set of adaptability data of each assembly object in the first assembly object level when being assembled, and the adaptability data includes the following data: Position error data: the error value between the expected position and the actual position of each assembly object; Time consumption data: assembly time of each assembly object; Resource consumption data: resource consumption index of each assembly object; The assembly adaptation entropy is the degree of adaptability of the connection between the assembly object and other assembly objects. By setting corresponding position weights, time weights and resource weights, the adaptability data corresponding to each assembly object is weighted and fused to obtain the assembly adaptation entropies corresponding to the assembly objects in the first assembly object level. The coordination factor corresponding to the update object = the number of assembly objects connected to the update object / the total number of assembly objects in the first assembly object level, wherein the rows of the secondary allocation matrix represent different assembly objects, the columns of the matrix represent different update objects, the matrix elements represent allocation sub-coefficients between assembly objects and update objects, and the allocation sub-coefficients = the coordination factor corresponding to the update object × the assembly adaptation entropy corresponding to the assembly object.

2. The method according to claim 1, characterized in that Determining the assembly coordination degree and assembly weight corresponding to each assembly object according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model specifically includes: Acquire the node connection relationship between each assembly object in the three-dimensional object group of the building information model; Determine the assembly connection matrix according to the node connection relationship between each assembly object; According to the assembly connection matrix, the assembly coordination degree and the assembly weight corresponding to each assembly object are determined.

3. The method according to claim 1, characterized in that Assembling each assembly object in the first assembly object level specifically includes: Obtaining assembly weights corresponding to each assembly object in the first assembly object level; The respective assembly objects in the first assembly object level are assembled according to the assembly weights respectively corresponding to the respective assembly objects in the first assembly object level.

4. The method according to claim 1, characterized in that The segmented assembly according to the remaining assembly object level after the update specifically includes: Assembling according to a first updated assembly object level in the remaining assembly object levels after the update, and determining the assembly adaptation entropies corresponding to the assembly objects in the first updated assembly object level respectively during the assembly process; updating the remaining updated assembly object levels according to the assembly adaptation entropies respectively corresponding to the assembly objects in the first updated assembly object level; Assembling is performed again according to the first updated assembly object level in the remaining assembly object levels after the update, and the above steps are repeated until all assembly objects have been assembled.

5. The method according to claim 1, characterized in that The K-means clustering method is used to perform two-dimensional clustering according to the assembly coordination degree and assembly weight corresponding to each assembly object, thereby obtaining multiple assembly object levels.

6. The method according to claim 1, characterized in that The node connection relationship between each assembly object includes the connection point, connection type and connection object of each assembly object.

7. An intelligent management system for prefabricated building construction, the system includes a construction control unit, characterized in that: The construction control unit comprises: An acquisition module, used for acquiring a three-dimensional object group of a building information model of a prefabricated building; A processing module, for determining the assembly coordination degree and assembly weight corresponding to each assembly object according to the node connection relationship between each assembly object in the three-dimensional object group of the building information model; The processing module is further used to classify the three-dimensional object group of the building information model according to the assembly coordination degree and assembly weight corresponding to each assembly object, so as to obtain a plurality of assembly object levels; The processing module is further used to assemble each assembly object in the first assembly object level, obtain an adaptability data group in the assembly process, and determine the assembly adaptability entropy corresponding to each assembly object in the first assembly object level according to the adaptability data group; An execution module, used for updating the remaining assembly object levels according to the assembly adaptation entropies respectively corresponding to the respective assembly objects in the first assembly object level, and performing segmented assembly according to the remaining assembly object levels after the update; Updating the remaining assembly object levels according to the assembly adaptation entropies corresponding to the respective assembly objects in the first assembly object level specifically includes: Obtain each assembly object in the remaining assembly object levels, and combine them to obtain an update object set; Determine, according to the connection relationship between each assembly object in the first assembly object level and the update object set, the coordination factor corresponding to each update object in the update object set; Determine the secondary distribution matrix of the update object set according to the coordination factors corresponding to each update object and the assembly adaptation entropy corresponding to each assembly object; updating the update object set according to the secondary allocation matrix to obtain a plurality of updated assembly object levels; The assembly coordination degree represents the overall assembly difficulty of the assembly object when it is assembled with other assembly objects, and the assembly weight represents the importance of the assembly object in the prefabricated building; The adaptability data group is a set of adaptability data of each assembly object in the first assembly object level when being assembled, and the adaptability data includes the following data: Position error data: the error value between the expected position and the actual position of each assembly object; Time consumption data: assembly time of each assembly object; Resource consumption data: resource consumption index of each assembly object; The assembly adaptation entropy is the degree of adaptability of the connection between the assembly object and other assembly objects. By setting corresponding position weights, time weights and resource weights, the adaptability data corresponding to each assembly object is weighted and fused to obtain the assembly adaptation entropies corresponding to the assembly objects in the first assembly object level. The coordination factor corresponding to the update object = the number of assembly objects connected to the update object / the total number of assembly objects in the first assembly object level, wherein the rows of the secondary allocation matrix represent different assembly objects, the columns of the matrix represent different update objects, the matrix elements represent allocation sub-coefficients between assembly objects and update objects, and the allocation sub-coefficients = the coordination factor corresponding to the update object × the assembly adaptation entropy corresponding to the assembly object.

8. A computer terminal device, characterized in that: The computer terminal device includes a memory and a processor, the memory stores codes, and the processor is configured to obtain the codes and execute an intelligent management method for prefabricated building construction as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing at least one computer program, characterized in that: The computer program is loaded and executed by a processor to implement the operations performed by the intelligent management method for prefabricated building construction as described in any one of claims 1 to 6.

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