CN112199745A - BIM-based template bent frame construction method and device - Google Patents
BIM-based template bent frame construction method and device Download PDFInfo
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- CN112199745A CN112199745A CN202010972022.XA CN202010972022A CN112199745A CN 112199745 A CN112199745 A CN 112199745A CN 202010972022 A CN202010972022 A CN 202010972022A CN 112199745 A CN112199745 A CN 112199745A
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
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- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
Abstract
The invention discloses a BIM-based template bent frame construction method, wherein the method comprises the following steps: obtaining first attribute information of a first template bent frame according to a BIM model; acquiring first image information and first parameter information of the second template bent, and acquiring second attribute information through a neural network model, wherein the second attribute information is actual attribute information of the second template bent; judging whether the second attribute information is the same as the first attribute information or not, and if the second attribute information is the same as the first attribute information, acquiring a first assembly instruction; and assembling construction is carried out on the second template bent frame according to the first assembling command team. The construction quality of the bent is greatly improved, the potential safety hazard of the frame body is reduced, the workload of secondary rectification in the later period is greatly reduced, and the cost and the construction period are saved.
Description
Technical Field
The invention relates to the field of bent frame construction methods, in particular to a template bent frame construction method and device based on BIM.
Background
In recent years, the construction quality of domestic template bent frames is not ideal as a whole, the template bent frames belong to a subsection project with high risk, if the construction quality of the template bent frames is not good, the deviation of the size, the positioning and the like of structural members can be caused, the quality of project entities is further influenced, and more importantly, the collapse of the template bent frames can be caused, and casualties, economic losses and severe social influences can be caused accordingly. In addition, the difficulty of the rectification of the template bent frame is high, if the template bent frame is not qualified at one time, a large amount of labor is consumed for the rectification at the later stage, and further the cost is increased and the construction period is delayed.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
the traditional construction method is lack of deepening before construction, or the deepening degree does not reach the requirements of site construction, and the phenomena of dislocation, loss and the like of all parts of the formwork bent are common due to the fact that process control and construction acceptance are not strict.
Disclosure of Invention
The embodiment of the application provides a template bent construction method and device based on BIM, the deepening before traditional construction method lacks the construction among the prior art has been solved, or the deepening degree does not reach the site operation requirement, the process management and control, the construction is checked and accepted not strictly, lead to the dislocation of each part of template bent, phenomenon such as disappearance is more general technical problem, the construction quality of bent has been realized having promoted by a wide margin, the potential safety hazard of support body has been reduced, and the work load of later stage secondary rectification has also been reduced by a wide margin, the technical effect of cost and time limit for a project has been saved.
The embodiment of the application provides a template bent frame construction method based on BIM, wherein the method comprises the following steps: obtaining first attribute information of a first template bent frame according to a BIM model; obtaining first image information of the second template bent; acquiring first parameter information of the second template bent, wherein the first parameter information is actual parameter information of the second template bent; obtaining second attribute information through a neural network model according to the first image information and the first parameter information, wherein the second attribute information is actual attribute information of the second template bent; judging whether the second attribute information is the same as the first attribute information or not, and obtaining a first judgment result; determining whether a first assembly instruction is obtained or not according to the first judgment result; and assembling construction is carried out on the second template bent frame according to the first assembling command team.
On the other hand, this application still provides a template framed bent construction equipment based on BIM, wherein, the device includes: a first obtaining unit, configured to obtain first attribute information of a first template bent according to a BIM model; a second obtaining unit configured to obtain first image information of the second template bent; a third obtaining unit, configured to obtain first parameter information of the second template bent, where the first parameter information is actual parameter information of the second template bent; a fourth obtaining unit, configured to obtain second attribute information through a neural network model according to the first image information and the first parameter information, where the second attribute information is actual attribute information of the second template bent; a first judging unit, configured to judge whether the second attribute information is the same as the first attribute information, and obtain a first judgment result; a fifth obtaining unit, configured to determine whether to obtain a first assembly instruction according to the first determination result; and the first assembling unit is used for assembling and constructing the second template bent according to the first assembling instruction.
In another aspect, the present application further provides a BIM-based formwork racking construction apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1-7 when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
inputting the image information and the parameter information of the template bent into a first training model, so as to output the attribute category information of the template bent; the training model is a machine learning model, and the machine learning model can continuously learn through a large amount of data so as to continuously correct the model and finally obtain satisfactory experience to process other data; each group of training data in the plurality of groups comprises the image information, the parameter information and identification information for identifying the attribute category of the template shelving; through multiple times of training, accurate information of the attribute category of the template bent is obtained; the attribute type information of the template bent can be obtained through the image information and the parameter information, the construction quality of the bent is greatly improved, and the technical purpose of reducing potential safety hazards of a frame body is achieved.
The foregoing is a summary of the present disclosure, and embodiments of the present disclosure are described below to make the technical means of the present disclosure more clearly understood.
Drawings
Fig. 1 is a schematic flow chart of a formwork bent frame construction method based on BIM in an embodiment of the present application;
fig. 2 is a schematic flow chart illustrating a process of determining whether first warning information is obtained in a template bent frame construction method based on BIM according to an embodiment of the present disclosure;
fig. 3 is a schematic flowchart illustrating a first assembly instruction obtained in a template bent frame construction method based on BIM according to an embodiment of the present disclosure;
fig. 4 is a schematic flowchart illustrating a second assembly instruction obtained in a BIM-based formwork bent construction method according to an embodiment of the present disclosure;
FIG. 5 is a schematic flow chart illustrating more accurate training data obtained in a BIM-based template bent frame construction method according to an embodiment of the present disclosure;
fig. 6 is a schematic flowchart illustrating a third assembly instruction obtained in a template bent frame construction method based on BIM according to an embodiment of the present disclosure;
fig. 7 is a schematic flowchart illustrating a process of obtaining a first factory return instruction in a template bent frame construction method based on BIM according to an embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of a template bent frame construction device based on BIM according to an embodiment of the present disclosure;
fig. 9 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a first judging unit 15, a fifth obtaining unit 16, a first assembling unit 17, a fifth bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 306.
Detailed Description
The embodiment of the application provides a template bent construction method and device based on BIM, the deepening before traditional construction method lacks the construction among the prior art has been solved, or the deepening degree does not reach the site operation requirement, the process management and control, the construction is checked and accepted not strictly, lead to the dislocation of each part of template bent, phenomenon such as disappearance is more general technical problem, the construction quality of bent has been realized having promoted by a wide margin, the potential safety hazard of support body has been reduced, and the work load of later stage secondary rectification has also been reduced by a wide margin, the technical effect of cost and time limit for a project has been saved. Hereinafter, example embodiments of the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.
Summary of the application
In recent years, the construction quality of domestic template bent frames is not ideal as a whole, the template bent frames belong to a subsection project with high risk, if the construction quality of the template bent frames is not good, the deviation of the size, the positioning and the like of structural members can be caused, the quality of project entities is further influenced, and more importantly, the collapse of the template bent frames can be caused, and casualties, economic losses and severe social influences can be caused accordingly. However, the prior art also has the technical problems that the traditional construction method is lack of deepening before construction, or the deepening degree does not meet the requirements of site construction, and the phenomena of dislocation, deficiency and the like of all parts of the formwork bent are common due to the strictness of process control and construction acceptance inspection, and the like.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides a template bent frame construction method based on BIM, wherein the method comprises the following steps: obtaining first attribute information of a first template bent frame according to a BIM model; obtaining first image information of the second template bent; acquiring first parameter information of the second template bent, wherein the first parameter information is actual parameter information of the second template bent; obtaining second attribute information through a neural network model according to the first image information and the first parameter information, wherein the second attribute information is actual attribute information of the second template bent; judging whether the second attribute information is the same as the first attribute information or not, and obtaining a first judgment result; determining whether a first assembly instruction is obtained or not according to the first judgment result; and assembling construction is carried out on the second template bent frame according to the first assembling command team.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, an embodiment of the present application provides a formwork bent construction method based on BIM, where the method includes:
step S100: obtaining first attribute information of a first template bent frame according to a BIM model;
specifically, the core of the BIM is to provide a complete building engineering information base consistent with the actual situation for a virtual building engineering three-dimensional model by establishing the model and utilizing a digital technology. According to special construction schemes such as design drawings, standard rules and template engineering of buildings, BIM modeling software is used for building a BIM model, and a primary model of a first template bent is obtained, wherein the primary model comprises a template main body, primary and secondary ridges, vertical rods, base plates, horizontal rods and sweeping rods of the template main body, and further comprises a scissor support and a holding column. The first attribute information of the first template bent comprises the specifications and the quantity and the fixed condition of embedded parts and reserved holes, the information of whether the position of a positioning point is accurate, whether the support is firm, whether the template is flat and vertical and the like, and the first attribute information is obtained by inputting the image information of the first template bent and the parameter information of the first template bent in the BIM model into the neural network model. By obtaining the first attribute information, a foundation is laid for subsequently ensuring construction quality, reducing potential safety hazards and the like.
Step S200: obtaining first image information of the second template bent;
specifically, the second template bent frame is an adjacent template bent frame assembled with the first template bent frame, a plane and a section layout of the template bent frame are obtained through the built BIM model, and the first image information of the second template bent frame comprises a model diagram, a plane diagram and an erection positioning diagram of the second template bent frame. And a foundation is laid for subsequent assembly with the first template bent frame by obtaining the first image information of the second template bent frame.
Step S300: acquiring first parameter information of the second template bent, wherein the first parameter information is actual parameter information of the second template bent;
particularly, the first parameter information of the second template bent is the data parameter information such as the vertical and horizontal distance of the vertical rod, the ground clearance of the floor sweeping rod, the step pitch of the horizontal rod, the width, the step pitch and the included angle of the horizontal cross brace, the width, the distance and the inclined angle of the vertical cross brace, the position of the butt joint of the bent rods, the position and the lap length of the lap joint of the bent rods, which are accurately reflected through the template bent model, and is used for the erection and the positioning of the second template bent. And a foundation is laid for improving the construction quality of the bent frame.
Step S400: obtaining second attribute information through a neural network model according to the first image information and the first parameter information, wherein the second attribute information is actual attribute information of the second template bent;
specifically, the neural network model is a machine learning model, and the machine learning model can continuously learn through a large amount of data, further continuously correct the model, and finally obtain satisfactory experience to process other data. The process by which the neural network model is trained with training data is essentially a supervised learning process. And outputting the second attribute information by the machine learning model through the obtained first image information and the first parameter information, and then continuously adjusting the data of the machine learning model until the machine learning model reaches the expected accuracy rate, and then performing supervised learning on the next group of data. The machine learning model is continuously corrected and optimized through training data, the accuracy of the machine learning model for processing the data is improved through the process of supervised learning, and accurate second attribute information is obtained. The second attribute information comprises the specifications and the quantity and the fixed condition of the embedded parts and the reserved holes of the second template bent, the position of the positioning point is accurate, the support is firm, and the template is flat and vertical. Through obtaining second attribute information has realized promoting the construction quality of framed bent by a wide margin, has reduced the technological effect of the potential safety hazard of support body.
Step S500: judging whether the second attribute information is the same as the first attribute information or not, and obtaining a first judgment result;
specifically, by judging whether the second attribute information is the same as the first attribute information, it can be determined whether the positions of the reserved holes of the first template bent and the second template bent correspond to each other, whether the number and the specification are the same, whether the positions of positioning installation correspond to each other, whether the support is firm, and the like. Through judging, the construction quality of the bent frame is greatly improved, the potential safety hazard of the frame body is reduced, the workload of secondary rectification in the later period is greatly reduced, and the cost and the construction period are saved.
Step S600: determining whether a first assembly instruction is obtained or not according to the first judgment result;
specifically, according to the first determination result, if the second attribute information of the second template bent is the same as the first attribute information of the first template bent, it is indicated that the first and second template bent can be correctly assembled, and a first assembly instruction is obtained for prompting the assembly of the second template bent. The method has the advantages of greatly reducing the workload of secondary rectification in the later period and saving the cost and the construction period.
Step S700: and assembling construction is carried out on the second template bent frame according to the first assembling command team.
Specifically, if the first assembly result is obtained by the first determination, the first assembly instruction is executed, and the second template bent and the first template bent are assembled according to the predetermined parameter information of the second template bent. The technical purpose of standard construction and reduction of potential safety hazards of the frame body is achieved.
As shown in fig. 2, in order to determine whether to obtain the first warning information, step S500 in the embodiment of the present application further includes:
step S501 a: if the first judgment result is that the second attribute information is different from the first attribute information, first mark information is obtained;
step S502 a: marking and storing the second template bent frame according to the first marking information;
step S503 a: and obtaining first early warning information according to the first mark information, wherein the first early warning information is used for reminding the second template bent frame of forbidding assembly construction.
Specifically, if the first judgment result shows that the second attribute information is different from the first attribute information, the second template bent is not up to standard in positioning or installation specification, and the first template bent cannot be matched with the first template bent, the first marking information is obtained and used for marking and storing the second template bent, and first early warning information is obtained and used for reminding the second template bent of not up to standard and forbidding assembly construction. Through right the attribute of second template framed bent compares the judgement, has reached the construction quality that has promoted the framed bent by a wide margin, has reduced the potential safety hazard of support body to also reduce the work load that the later stage secondary was rectified and improved by a wide margin, saved the technical effect of cost and time limit for a project.
As shown in fig. 3, in order to obtain the first assembly instruction, step S500 in this embodiment further includes:
step S501 b: if the first judgment result is that the second attribute information is the same as the first attribute information, a first assembly instruction is obtained;
step S502 b: and assembling the second template bent frame according to the first assembling instruction.
Specifically, if the second attribute information is the same as the first attribute information, it represents that the second template bent can be correctly assembled with the first template bent, a first assembly instruction is obtained, and then the second template bent is assembled according to the first assembly instruction. By obtaining the first assembly instruction, the technical purpose of improving the standardization of assembly construction is achieved.
As shown in fig. 4, in order to obtain the second assembly instruction, step S100 in this embodiment further includes:
step S101: obtaining a third template bent frame;
step S102: according to the third attribute information of the third template bent;
step S103: judging whether the third attribute information is the same as the first attribute information;
step S104: if the third attribute information is the same as the first attribute information, obtaining a second assembly instruction;
step S105: and assembling and constructing the third template bent frame according to the second assembling instruction.
Specifically, image information and parameter information of the third template bent are obtained based on a BIM technology, third attribute information of the third template bent, including embedded parts of the third template bent, specification number and fixing conditions of reserved holes, information of whether a positioning point is accurate or not, whether support is firm or not, whether a template is flat or vertical or not, and the like, is obtained through comparison with the first attribute information, and if the third attribute information is the same as the first attribute information, a second assembly instruction is obtained to remind that the third template bent can be assembled correctly with the second template bent. The assembling construction is carried out through the modes, the 3D laser scanning technology is applied to check and accept the template bent after all the construction is finished, the point cloud model generated by scanning through the 3D laser scanner is compared with the BIM model, and problems are found and organized and rectified through the comparison of the models. The construction quality of the bent is greatly improved, the potential safety hazard of the frame body is reduced, the workload of secondary rectification in the later period is greatly reduced, and the cost and the construction period are saved.
As shown in fig. 5, in order to obtain more accurate training data, step S400 in the embodiment of the present application further includes:
step S401: inputting the first image information and the first parameter information into a first training model, wherein the first training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets includes: the first image information, the first parameter information and identification information for identifying the attribute category of the template bent;
step S402: obtaining first output information of the first training model, wherein the first output information includes second attribute information of the second template bent.
Specifically, the identification information for identifying the attribute category of the template shelving is specifically the attribute information of the template shelving which is accurate. The training model is a machine learning model, and the machine learning model can continuously learn through a large amount of data, further continuously correct the model, and finally obtain satisfactory experience to process other data.
Further, the machine model is obtained by training a plurality of sets of training data, and the process of training the neural network model by the training data is essentially a process of supervised learning. Each set of training data in the plurality of sets of training data comprises: the first image information, the first parameter information and identification information for identifying the attribute category of the template bent; under the condition of obtaining the first image information and the first parameter information, the machine learning model outputs the template shelving attribute category information, the template shelving attribute category information output by the machine learning model is verified through the identified template shelving attribute category information, if the output template shelving attribute category information is consistent with the identified template shelving attribute category information, the data supervised learning is finished, and then the next group of data supervised learning is carried out; and if the output template bent attribute category information is inconsistent with the identified template bent attribute category information, adjusting the machine learning model by the machine learning model, and performing supervised learning on the next group of data until the machine learning model reaches the expected accuracy. The machine learning model is continuously corrected and optimized through training data, the accuracy of the machine learning model for processing the data is improved through the process of supervised learning, accurate template bent attribute category information is further obtained, and the technical aims of accurately estimating the assembly safety degree and reducing the potential safety hazard of a frame body are achieved.
As shown in fig. 6, in order to obtain the third assembly instruction, step S502a in this embodiment of the present application further includes:
step S502a 1: obtaining the model information of the second template bent frame;
step S502a 2: judging whether the second template bent is qualified or not according to whether the second attribute information corresponds to the model information or not;
step S502a 3: if the second attribute information corresponds to the model information, determining that the second template bent is qualified, and obtaining a third assembly instruction;
step S502a 4: and rearranging the assembling position of the second template information according to the third assembling instruction.
Specifically, the model information of the second template bent is obtained, including obtaining the material usage condition of the second template bent corresponding to the model, the specification and number of each component, holes, the positioning condition and the like, by comparing the model information of the second bent with the second attribute information output by the neural network model, if the second attribute information corresponds to the second model information, the second template bent is qualified, and the standard is met, the second template bent is not matched with the first template bent attribute information because the model is different and is not damaged, and then the third assembly instruction is obtained for assembling the second template bent with the template bent matched with other models. By obtaining the third assembly instruction, the technical effects of greatly reducing the workload of secondary rectification in the later period and saving the cost and the construction period are achieved.
As shown in fig. 7, in order to obtain the first factory return instruction, step S502a2 in this embodiment of the present application further includes:
step S502a 21: if the second attribute information does not correspond to the model information, determining that the second template bent is unqualified, and obtaining a first factory return instruction;
step S502a 22: and according to the first factory return instruction, performing factory return processing on the second template bent.
Specifically, if the second attribute information does not correspond to the model information, the quality of the second template bent is unqualified, that is, the reason why the second template bent does not correspond to the first template bent attribute information is the quality defect of the second template bent, and at this time, the first factory return instruction is obtained and used for performing factory return processing on the second template bent. By obtaining the first factory return instruction, the technical effects of greatly reducing the workload of secondary rectification in the later period and saving the cost and the construction period are achieved.
Further, in the embodiment of the present application, after the template bent model is established and optimized by using the BIM software, the template bent material statistical table and the template bent member configuration table may be generated on the basis of the template bent model. According to the material usage amount summarized in the template bent material statistical table, a purchase or lease plan of the template bent material is made, and the material is processed in advance according to a template bent member configuration table. By adopting the method, the purchase or lease plan of the template bent frame material is accurately and reasonably made before construction, and the steel pipe to be cut is industrially cut in advance, so that the cost is effectively saved, the actual requirements on the site can be met to the maximum extent, and the technical effect of reducing the workload of site cutting to the maximum extent is realized.
To sum up, the template bent frame construction method based on the BIM provided by the embodiment of the application has the following technical effects:
1. inputting the image information and the parameter information of the template bent into a first training model, so as to output the attribute category information of the template bent; the training model is a machine learning model, and the machine learning model can continuously learn through a large amount of data so as to continuously correct the model and finally obtain satisfactory experience to process other data; each group of training data in the plurality of groups comprises the image information, the parameter information and identification information for identifying the attribute category of the template shelving; through multiple times of training, accurate information of the attribute category of the template bent is obtained; the attribute type information of the template bent can be obtained through the image information and the parameter information, the construction quality of the bent is greatly improved, and the technical purpose of reducing potential safety hazards of a frame body is achieved.
2. Because the mode that the virtual building engineering three-dimensional model is established based on the BIM model is adopted to obtain the image information and the parameter information of the template bent frame, and then the assembly construction is carried out in a mode of matching through the obtained attribute information, the technical purposes of greatly improving the construction quality of the bent frame and reducing the potential safety hazard of the frame body are realized, the 3D laser scanning technology is applied to check and accept the template bent frame after the construction is finished, and the guarantee is further provided for the construction quality and the safety performance of the template bent frame.
Example two
Based on the same inventive concept as the template bent frame construction method based on the BIM in the previous embodiment, the invention also provides a template bent frame construction device based on the BIM, as shown in FIG. 8, the device comprises:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain first attribute information of a first template bent according to a BIM model;
a second obtaining unit 12, wherein the second obtaining unit 12 is configured to obtain first image information of the second template bent;
a third obtaining unit 13, where the third obtaining unit 13 is configured to obtain first parameter information of the second template bent, where the first parameter information is actual parameter information of the second template bent;
a fourth obtaining unit 14, where the fourth obtaining unit 14 is configured to obtain second attribute information through a neural network model according to the first image information and the first parameter information, where the second attribute information is actual attribute information of the second template bent;
a first judging unit 15, where the first judging unit 15 is configured to judge whether the second attribute information is the same as the first attribute information, and obtain a first judgment result;
a fifth obtaining unit 16, where the fifth obtaining unit 16 is configured to determine whether to obtain a first assembly instruction according to the first determination result;
and the first assembling unit 17, wherein the first assembling unit 17 is used for assembling the second formwork bent according to the first assembling instruction.
Further, the apparatus further comprises:
a sixth obtaining unit, configured to obtain first label information if the first determination result is that the second attribute information is different from the first attribute information;
the first storage unit is used for marking and storing the second template bent frame according to the first marking information;
and the seventh obtaining unit is used for obtaining first early warning information according to the first marking information, and the first early warning information is used for reminding the second template bent frame to forbid assembling construction.
Further, the apparatus further comprises:
an eighth obtaining unit, configured to obtain a first assembly instruction if the first determination result indicates that the second attribute information is the same as the first attribute information;
and the second assembling unit is used for assembling and constructing the second template bent frame according to the first assembling instruction.
Further, the apparatus further comprises:
a ninth obtaining unit for obtaining a third template bent;
a tenth obtaining unit configured to obtain third attribute information of the third template bent;
a second judging unit configured to judge whether the third attribute information is the same as the first attribute information;
an eleventh obtaining unit configured to obtain a second assembly instruction if the third attribute information is the same as the first attribute information;
and the third assembling unit is used for assembling and constructing the third template bent frame according to the second assembling instruction.
Further, the apparatus further comprises:
a first input unit, configured to input the first image information and the first parameter information into a first training model, where the first training model is obtained by training multiple sets of training data, and each set of training data in the multiple sets includes: the first image information, the first parameter information and identification information for identifying the attribute category of the template bent;
a twelfth obtaining unit, configured to obtain first output information of the first training model, where the first output information includes second attribute information of the second template bent.
Further, the apparatus further comprises:
a thirteenth obtaining unit configured to obtain model information of the second template bent;
a third judging unit, configured to judge whether the second template bent is qualified according to whether the second attribute information corresponds to the model information;
a fourteenth obtaining unit, configured to determine that the second template bent is qualified if the second attribute information corresponds to the model information, and obtain a third assembly instruction;
a first correcting unit for rearranging the fitting position of the second template information according to the third fitting instruction.
Further, the apparatus further comprises:
a fifteenth obtaining unit, configured to determine that the second template bent is unqualified if the second attribute information does not correspond to the model information, and obtain a first factory return instruction;
and the first processing unit is used for carrying out factory return processing on the second template bent frame according to the first factory return instruction.
Exemplary electronic device
The electronic apparatus of the embodiment of the present application is described below with reference to fig. 9.
Fig. 9 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the template bent construction method based on the BIM in the foregoing embodiments, the present invention further provides a template bent construction device based on the BIM, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of any one of the foregoing template bent construction methods based on the BIM.
Where in fig. 9 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 306 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. A BIM-based formwork bent construction method, wherein the method comprises the following steps:
obtaining first attribute information of a first template bent frame according to a BIM model;
obtaining first image information of the second template bent;
acquiring first parameter information of the second template bent, wherein the first parameter information is actual parameter information of the second template bent;
obtaining second attribute information through a neural network model according to the first image information and the first parameter information, wherein the second attribute information is actual attribute information of the second template bent;
judging whether the second attribute information is the same as the first attribute information or not, and obtaining a first judgment result;
determining whether a first assembly instruction is obtained or not according to the first judgment result;
and assembling the second template bent frame according to the first assembling instruction.
2. The method of claim 1, wherein the method comprises:
if the first judgment result is that the second attribute information is different from the first attribute information, first mark information is obtained;
marking and storing the second template bent frame according to the first marking information;
and obtaining first early warning information according to the first mark information, wherein the first early warning information is used for reminding the second template bent frame of forbidding assembly construction.
3. The method of claim 1, wherein the method comprises:
if the first judgment result is that the second attribute information is the same as the first attribute information, a first assembly instruction is obtained;
and assembling the second template bent frame according to the first assembling instruction.
4. The method of claim 2, wherein the method comprises:
obtaining a third template bent frame;
according to the third attribute information of the third template bent;
judging whether the third attribute information is the same as the first attribute information;
if the third attribute information is the same as the first attribute information, obtaining a second assembly instruction;
and assembling and constructing the third template bent frame according to the second assembling instruction.
5. The method of claim 1, wherein the obtaining second attribute information from the first image information and the first parameter information via a neural network model comprises:
inputting the first image information and the first parameter information into a first training model, wherein the first training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets includes: the first image information, the first parameter information and identification information for identifying the attribute category of the template bent;
obtaining first output information of the first training model, wherein the first output information includes second attribute information of the second template bent.
6. The method of claim 2, wherein the method comprises:
obtaining the model information of the second template bent frame;
judging whether the second template bent is qualified or not according to whether the second attribute information corresponds to the model information or not;
if the second attribute information corresponds to the model information, determining that the second template bent is qualified, and obtaining a third assembly instruction;
and rearranging the assembling position of the second template information according to the third assembling instruction.
7. The method of claim 6, wherein the method comprises:
if the second attribute information does not correspond to the model information, determining that the second template bent is unqualified, and obtaining a first factory return instruction;
and according to the first factory return instruction, performing factory return processing on the second template bent.
8. A BIM-based formwork bent construction apparatus, wherein the apparatus comprises:
a first obtaining unit, configured to obtain first attribute information of a first template bent according to a BIM model;
a second obtaining unit configured to obtain first image information of the second template bent;
a third obtaining unit, configured to obtain first parameter information of the second template bent, where the first parameter information is actual parameter information of the second template bent;
a fourth obtaining unit, configured to obtain second attribute information through a neural network model according to the first image information and the first parameter information, where the second attribute information is actual attribute information of the second template bent;
a first judging unit, configured to judge whether the second attribute information is the same as the first attribute information, and obtain a first judgment result;
a fifth obtaining unit, configured to determine whether to obtain a first assembly instruction according to the first determination result;
and the first assembling unit is used for assembling and constructing the second template bent according to the first assembling instruction.
9. A BIM-based formwork racking construction apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1-7 when executing the program.
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