Building design product use effect simulation data processing system and method

Abstract

The invention relates to the technical field of architectural design data processing, and discloses an architectural design product use effect simulation data processing system and method, and the system comprises an architectural design product use simulation information processing module, an architectural design product use simulation processing module, and an architectural design product optimization suggestion analysis output module. A voice recognition device collects building design product use scene simulation motion parameters in real time, and in combination with an intelligent recognition algorithm and building design product modeling motion instruction parameters, space motion instruction search of a building design product model needed by experiencers in use scene simulation operation is carried out; building design product use scene simulation motion instructions can be accurately and efficiently identified; and based on the augmented reality equipment, the three-dimensional building design software and the building design product use scene simulation motion instruction parameters, presenting an immersive and real building design product use scene simulation space for experiencers.

Description

Technical Field

[0001] The present invention relates to the technical field of architectural design data processing, and in particular to a system and method for processing architectural design product use effect simulation data. Background Art

[0002] Architectural design means that before a building is built, the designer, in accordance with the construction task, makes a comprehensive idea in advance of the problems that exist or may occur during the construction process and use, formulates solutions and plans to solve these problems, and expresses them in drawings and documents. It serves as a common basis for material preparation, construction organization work, and the cooperation and collaboration of various types of work in production and construction. It is convenient for the entire project to proceed smoothly within the predetermined investment limit, in accordance with the carefully considered predetermined plan, in a unified pace. And the completed buildings fully meet the various requirements and uses expected by users and society. However, before the existing architectural design products are completed, they cannot be simulated by experts, customers, and the public for real-life use effects, nor can they accurately analyze the optimization suggestions for architectural design products for various types of people.

[0003] The Chinese invention patent application with publication number CN114239119A discloses an optimization design scheme and judgment method for architectural design. Statistical prediction of the building's construction production standards and information, statistical prediction of the building's materials and information qualifications of each manufacturing unit, statistical prediction and analysis of the building's energy-saving design standards, statistical prediction of the building's building safety standards, statistical prediction of the building's sunlight, noise, and greening intimacy standards, and statistical prediction of the building's building traffic accessibility and the building's own coordinated accessibility parameters. To achieve more in line with the requirements of today's national development, fully affirm that being suitable for human habitation is the mission of the building itself, and by optimizing and judging the building itself and the surroundings of the building, it can highlight the intimacy between the building and people. However, the above technical solutions cannot achieve the simulation of the use effect experience feedback in the real scene of the architectural design product design stage. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In order to solve the problem that the above-mentioned existing architectural design products cannot be simulated by experts, customers, and the public for real-scene usage effects before construction is completed, and cannot accurately analyze the optimization suggestions for architectural design products for various types of people, the above purposes are achieved: accurately collecting architectural design product models and experiencer identity information, intelligently identifying experiencer identity types, accurately collecting architectural design product usage scenario simulation motion information, scientifically identifying architectural design product usage scenario simulation motion instructions, autonomously executing architectural design product usage scenario simulation operations, efficiently collecting experiencer architectural design product optimization suggestion information, and intelligently screening the best architectural design product optimization suggestion information.

[0006] (II) Technical solution

[0007] The present invention is implemented by the following technical scheme: a method for processing data of simulation of use effect of architectural design products, the method comprising the following steps:

[0008] S1. Collect architectural design product model data and experience personnel identity feature data;

[0009] S2, performing identification processing on the identity type of the experiencer based on the identity feature data of the experiencer, the identity data of the expert type experiencer, and the identity data of the customer type experiencer to generate identity type identification data of the experiencer;

[0010] S3, based on the identification data of the experiencer's identity type and the architectural design product model data, the architectural design product model is displayed to the experiencer of a specific identity type;

[0011] S4, collect motion data of architectural design product usage scenarios;

[0012] S5, analyzing and processing the spatial motion instructions of the architectural design product model required by the experiencer in the use scenario simulation operation according to the architectural design product use scenario simulation motion data and the architectural design product modeling motion instruction data, generating the architectural design product use scenario simulation motion instruction data and executing the architectural design product use scenario simulation operation;

[0013] S6. Collect optimization suggestion data of architectural design products;

[0014] S7. Screening and processing of optimization suggestion parameters for architectural design products for experiencers of different identity types based on the experiencer identity type identification data and the architectural design product optimization suggestion data, generating optimal architectural design product optimization suggestion data and outputting feedback.

[0015] Preferably, the steps of collecting the architectural design product model data and the identity feature data of the experiencer are as follows:

[0016] S11. The designer uploads the 3D model data package of the architectural design product online through the data collection dialog box and generates the architectural design product model data A moxing ;

[0017] The experiencer inputs personal identity characteristic information online through the data collection dialog box and generates experiencer identity characteristic data I, wherein the experiencer identity characteristic data includes the experiencer's name, occupation and ID number; the experiencer represents a person who participates in the simulated experience of the use effect of the architectural design product.

[0018] Preferably, the identity type identification processing of the experiencer is performed based on the experiencer identity feature data, the expert type experiencer identity data, and the customer type experiencer identity data, and the operation steps of generating the experiencer identity type identification data are as follows:

[0019] S21. Establishing expert type experience personnel identity data set A=(a 1 ,…,a m ,…,a ε ), m=1,2,3,…,ε; where a m represents the identity data of the mth expert type experiencer, ε represents the maximum number of expert type experiencers, and the expert type experiencer identity data represents the identity information of professionals in the field of architectural design who participate in the simulated experience of the use effect of architectural design products;

[0020] Establish customer type experience personnel identity data set A'=(a' 1 ,…,a' n ,…,a' φ ), n=1,2,3,...,φ; where a' n represents the identity data of the nth customer type experiencer, φ represents the maximum number of customer type experiencers, and the customer type experiencer identity data represents the identity information of the customer who participates in the simulated experience of the use effect of the architectural design product;

[0021] S22, using a bidirectional search algorithm to compare the experiencer identity feature data I with the expert type experiencer identity data a in the expert type experiencer identity data set A. m and the customer type experience personnel identity data a' in the customer type experience personnel identity data set A' n Perform identity feature keyword matching to search for the identity type corresponding to the experiencer identity feature data I and generate experiencer identity type identification data A shenfen ;

[0022] When I and a mThe identity feature keyword matching is successful, indicating that the experiencer is an expert type experiencer, and the experiencer identity type identification data A is output. shenfen For expert type;

[0023] When I and a' n If the identity feature keyword match is successful, it means that the experiencer is a customer type experiencer, then the experiencer identity type identification data A is output. shenfen For customer type;

[0024] When I and a m and a' n If the identity feature keyword matching fails, it means that the experiencer is a public type experiencer, then the experiencer identity type identification data A is output. shenfen For public type.

[0025] Preferably, the operation steps of performing the display operation of the architectural design product model to the experiencer of a specific identity type based on the experiencer identity type identification data and the architectural design product model data are as follows:

[0026] S31, identifying data A based on the identity type of the experiencer shenfen The identity type of the experiencer is identified, and the architectural design product model data A moxing The three-dimensional architectural design software is imported and run, and the real-time image of the architectural design product model is transmitted to the augmented reality device through data, and the three-dimensional model of the architectural design product is displayed to the experience personnel of a specific identity type through the augmented reality device. The three-dimensional architectural design software includes any one of 3DSMax, SketchUp, and Revit; the augmented reality device includes any one of a head-mounted display, smart glasses, and an AR projector.

[0027] Preferably, the operation steps of collecting the simulated motion data of the use scenario of the architectural design product are as follows:

[0028] S41. In the process of displaying the three-dimensional model of the architectural design product to the experiencer of a specific identity type, the expected spatial motion information of the architectural design product model required by the experiencer in the augmented reality device is collected online through the voice recognition device, and the architectural design product usage scenario simulation motion data B is generated. dongzuo The architectural design product usage scenario simulation motion data includes a horizontal left shift value, a horizontal right shift value, a model magnification value, a model reduction value, a model left rotation angle, and a model right rotation angle of a three-dimensional model of the architectural design product in an augmented reality device.

[0029] Preferably, the steps of analyzing and processing the spatial motion instructions of the architectural design product model required by the experiencer in the use scenario simulation operation according to the architectural design product use scenario simulation motion data and the architectural design product modeling motion instruction data, generating the architectural design product use scenario simulation motion instruction data and executing the architectural design product use scenario simulation operation are as follows:

[0030] S51. Establishing a motion instruction data set for building design product modeling where b p represents the architectural design product modeling motion instruction data corresponding to the simulated motion parameters of the p-th architectural design product usage scenario, Indicates the maximum value of the number of types of motion parameter simulations for the use scenario of the architectural design product, wherein the architectural design product modeling motion instruction data indicates the use scenario simulation motion data B of the architectural design product dongzuo The motion control instruction data corresponding to the three-dimensional modeling space of the architectural design product in the three-dimensional architectural design software;

[0031] S52, using the architectural design product to simulate the motion data B dongzuo The architectural design product modeling motion instruction data set B is the architectural design product modeling motion instruction data set B. p Perform architectural design product usage scenario simulation motion parameter type character matching to search for the architectural design product usage scenario simulation motion data B dongzuo The corresponding architectural design product modeling motion instruction data b p And generate motion instruction data for architectural design product usage scenarios through data identification Execute and generate motion instruction data for architectural design product usage scenarios simulation The specific steps are as follows:

[0032] S521, initialization, update the pigeon population size N and the maximum number of iterations T;

[0033] S522, exploration phase, the number of iterations in the range of [0, t1] is the exploration phase, where t1 = 0.95xT. In the exploration phase, it is necessary to identify the position and target of the pigeon according to the motion command, calculate the speed of the pigeon identified by the motion command, and add the current position to the speed to get the new position, that is, search for the motion data B that is consistent with the architectural design product usage scenario simulation in the architectural design product modeling motion command data set B search space. dongzuo Matching architectural design product modeling motion instruction data b p The position of the pigeon is identified by the motion command, and the speed calculation formula of the pigeon is: in It represents the new speed of pigeon i in the j-dimensional space during the exploration phase, i.e. It represents the movement instruction recognition of pigeon i in the exploration phase with dimension The new speed in the search space of the architectural design product modeling motion instruction data set B; represents the original speed of pigeon i in the exploration phase in the j-dimensional space, that is, the original speed of pigeon i in the exploration phase in the j-dimensional space is The original speed in the search space of the architectural design product modeling motion instruction data set B; is a constant with a value of 0.2, t represents the current iteration number of the algorithm, represents an exponential function with base e, rand is a uniform random number in the interval [0,1], It represents the best position of the pigeon in the exploration phase of the motion instruction recognition in the j-dimensional space, that is, the optimal position of the pigeon in the exploration phase of the motion instruction recognition in the dimension is The architectural design product modeling motion instruction data set B is searched in the search space to find the motion data B that is simulated in the usage scenario of the architectural design product dongzuo Matching architectural design product modeling motion instruction data b p Location; It represents the original position of pigeon i in the exploration phase in the j-dimensional space according to the motion command recognition, that is, the original position of pigeon i in the exploration phase in the j-dimensional space according to the motion command recognition is The original position of the architectural design product modeling motion instruction data set B in the search space; the motion instruction recognition pigeon new position calculation formula in It represents the new position of pigeon i in the exploration phase in the j-dimensional space identified by the motion command, that is, the new position of pigeon i in the exploration phase in the j-dimensional space identified by the motion command is The new position in the search space of the architectural design product modeling motion instruction data set B;

[0034] S523, development phase, the number of iterations within the range of [t1, T] is the development phase, firstly, the motion instruction recognition pigeon group needs to be sorted in the search space of the architectural design product modeling motion instruction data set B, and the motion instruction recognition pigeon group is divided into two groups: excellent and ordinary. The excellent group of motion instruction recognition pigeons searches for motion data B that are consistent with the architectural design product usage scenario simulation in the search space of the architectural design product modeling motion instruction data set B. dongzuo Matching architectural design product modeling motion instruction data b p The position remains unchanged, while providing the architectural design product modeling motion instruction data b p The location of the architectural design product modeling motion instruction data b p Simulate motion data using scenarios of the architectural design product B dongzuoThe fitness value is used as a parameter for the general group of motion instruction recognition pigeon groups to determine their architectural design product modeling motion instruction data set B search space and architectural design product use scenario simulation motion data B dongzuo Matching architectural design product modeling motion instruction data b p The new position of the pigeon group is calculated by the common motion command:

[0035] in represents the new position of the motion instruction recognition pigeon i in the j-dimensional space during the development stage, that is, the motion instruction recognition pigeon i in the development stage is in the dimension The new position in the search space of the architectural design product modeling motion instruction data set B; It represents the best position of the excellent group of pigeons in the development stage in the j-dimensional space. That is, the excellent group of pigeons in the development stage in the dimension is The architectural design product modeling motion instruction data set B is searched in the search space to find the motion data B that is simulated in the usage scenario of the architectural design product dongzuo The most matching architectural design product modeling motion instruction data b p The best location;

[0036] S524. When the algorithm meets the maximum number of iterations, output the simulated motion data B for the use scenario of the architectural design product. dongzuo Matching architectural design product modeling motion instruction data b p ;

[0037] S525, according to the architectural design product modeling motion instruction data b output in step S524 p Generate motion instruction data for architectural design product usage scenarios through data identification

[0038] S53: simulating motion instruction data using the scene of the architectural design product The three-dimensional model of the architectural design product is input into the three-dimensional architectural design software to perform spatial movement in the modeling space according to the motion control instructions. The real-time image of the spatial movement of the three-dimensional model of the architectural design product is simultaneously transmitted to the augmented reality device through data, and the augmented reality device is used to perform simulation operations on the usage scenarios of the architectural design product by the experience personnel.

[0039] Preferably, the steps of collecting architectural design product optimization suggestion data are as follows:

[0040] S61. When the simulation operation of the use scenario of the architectural design product is completed, the optimization suggestion information of the architectural design product by the experience personnel of different identity types is collected online through the voice recognition device and the optimization suggestion data set of the architectural design product is generated. where c′ u represents the u-th architectural design product optimization suggestion data collected by expert experience personnel, γ represents the maximum number of architectural design product optimization suggestion data collected by expert experience personnel; c″ v represents the vth architectural design product optimization suggestion data collected from customer type experience personnel, η represents the maximum number of architectural design product optimization suggestion data collected from customer type experience personnel; c″′ k represents the kth piece of architectural design product optimization suggestion data collected from the public type experiencers, and ι represents the maximum number of architectural design product optimization suggestion data collected from the public type experiencers.

[0041] Preferably, the steps of screening the optimization suggestion parameters of architectural design products for experiencers of different identity types based on the experiencer identity type identification data and the architectural design product optimization suggestion data, generating the best architectural design product optimization suggestion data and outputting feedback are as follows:

[0042] S71, identifying data A based on the identity type of the experiencer shenfen The corresponding experiencer identity type keyword classification is used to extract the recommended keywords of the architectural design product optimization suggestion data in the architectural design product optimization suggestion data set C, and the recommended keywords with the largest number of values ​​corresponding to the architectural design product optimization suggestions proposed by experiencers of different identity types are counted to generate the best architectural design product optimization suggestion keyword set. where d' 1 Indicates the best architectural design product optimization suggestion keywords corresponding to expert experience personnel, d' 2 The best architectural design product optimization suggestion keywords corresponding to customer type experience personnel, d' 3 Indicates the best architectural design product optimization suggestion keywords corresponding to expert experience personnel;

[0043] S72, using an iterative deepening search algorithm based on the best architectural design product optimization suggestion keywords in the best architectural design product optimization suggestion keyword set D and the experiencer identity type identification data A shenfen The corresponding experiencer identity type keyword classification searches for the architectural design product optimization suggestion data corresponding to the best architectural design product optimization suggestion keyword in the architectural design product optimization suggestion data set C, and generates the best architectural design product optimization suggestion data set where c′u1,zui represents the optimal architectural design product optimization suggestion data of the u1th best architectural design product optimization suggestion data collected by the expert experience personnel, c′ u2,zui Indicates the u2th best architectural design product optimization suggestion data collected by expert experience personnel, 1≤u1≤u≤u2≤γ;

[0044] c″ v1,zui Indicates the collection of the v1th best architectural design product optimization recommendation data of customer type experience personnel, c″ v2,zui Indicates the v2th best architectural design product optimization suggestion data collected by customer type experience personnel, 1≤v1≤v≤v2≤η;

[0045] c″′ k1,zui Indicates the k1th best architectural design product optimization suggestion data collected from public experience personnel, c″′ k2,zui Indicates the k2th best architectural design product optimization suggestion data collected from public experience personnel, 1≤k1≤k≤k2≤ι;

[0046] S73, pushing the best architectural design product optimization suggestion data set C′ to the architectural design product feedback terminal through data output.

[0047] A building design product use effect simulation data processing system, used to implement the building design product use effect simulation data processing method, the system includes a building design product use simulation information processing module, a building design product use simulation processing module, and a building design product optimization suggestion analysis output module;

[0048] The architectural design product use simulation information processing module includes an architectural design product model acquisition unit, an experiencer identity information acquisition unit, an expert type experiencer identity information storage unit, a customer type experiencer identity information storage unit, and an experiencer identity type identification unit;

[0049] The architectural design product model acquisition unit acquires architectural design product model data through a data acquisition dialog box; the experiencer identity information acquisition unit acquires experiencer identity feature data through a data acquisition dialog box; the expert type experiencer identity information storage unit is used to store expert type experiencer identity data; the customer type experiencer identity information storage unit is used to store customer type experiencer identity data; the experiencer identity type identification unit performs experiencer identity type identification processing based on the experiencer identity feature data, expert type experiencer identity data, and customer type experiencer identity data to generate experiencer identity type identification data;

[0050] The architectural design product use simulation processing module includes an architectural design product model display unit, an architectural design product use scenario simulation motion information collection unit, an architectural design product modeling motion instruction storage unit, an architectural design product use scenario simulation motion instruction analysis unit, and an architectural design product use scenario simulation operation execution unit;

[0051] The architectural design product model display unit performs a display operation of the architectural design product model to the experiencer of a specific identity type based on the experiencer identity type identification data and the architectural design product model data; the architectural design product use scenario simulation motion information collection unit collects architectural design product use scenario simulation motion data through a voice recognition device; the architectural design product modeling motion instruction storage unit is used to store architectural design product modeling motion instruction data; the architectural design product use scenario simulation motion instruction analysis unit performs spatial motion instruction analysis and processing of the architectural design product model required by the experiencer in the use scenario simulation operation according to the architectural design product use scenario simulation motion data and the architectural design product modeling motion instruction data, and generates architectural design product use scenario simulation motion instruction data; the architectural design product use scenario simulation operation execution unit performs the architectural design product use scenario simulation operation according to the architectural design product use scenario simulation motion instruction data;

[0052] The architectural design product optimization suggestion analysis and output module includes an architectural design product optimization suggestion collection unit, a best architectural design product optimization suggestion screening unit, and an architectural design product optimization suggestion output unit;

[0053] The architectural design product optimization suggestion collection unit collects architectural design product optimization suggestion data through a voice recognition device; the best architectural design product optimization suggestion screening unit screens architectural design product optimization suggestion parameters for experiencers of different identity types based on the experiencer identity type recognition data and the architectural design product optimization suggestion data to generate the best architectural design product optimization suggestion data; the architectural design product optimization suggestion output unit pushes the best architectural design product optimization suggestion data to the architectural design product feedback end through data output.

[0054] (III) Beneficial effects

[0055] The present invention provides a data processing system and method for simulating the use effect of architectural design products. It has the following beneficial effects:

[0056] 1. Through the cooperation between the architectural design product model collection unit and the experiencer identity information collection unit, the data collection dialog box is used to accurately obtain the architectural design product model parameters and the experiencer identity information, so as to provide reliable data support for the subsequent architectural design product usage scenario simulation and experiencer identity type identification; the expert type experiencer identity information storage unit, the customer type experiencer identity information storage unit, and the experiencer identity type identification unit cooperate with each other, and the expert type and customer type experiencer identity parameters are scientifically established. The identity type identification processing is carried out in combination with the intelligent search algorithm and the experiencer identity feature parameters, so as to realize the intelligent classification of the identity type of the experiencer in the architectural design product usage scenario simulation.

[0057] 2. Through the architectural design product model display unit, the architectural design product model usage scenario visualization display operation is carried out based on augmented reality equipment and three-dimensional architectural design software; the architectural design product usage scenario simulation motion information collection unit and the architectural design product usage scenario simulation motion instruction analysis unit cooperate with each other, and the architectural design product usage scenario simulation motion parameters are collected in real time through the voice recognition device. Combined with the intelligent recognition algorithm and the architectural design product modeling motion instruction parameters, the spatial motion instruction search of the architectural design product model required by the experience personnel in the usage scenario simulation operation is carried out, so as to realize accurate and efficient recognition of the architectural design product usage scenario simulation motion instructions; the architectural design product usage scenario simulation operation execution unit presents an immersive and realistic architectural design product usage scenario simulation space to the experience personnel based on augmented reality equipment, three-dimensional architectural design software and architectural design product usage scenario simulation motion instruction parameters, so as to realize the scientific verification of the usage effect of the architectural design product in the design stage and improve the quality of the architectural design product.

[0058] 3. Through the architectural design product optimization suggestion collection unit, voice recognition equipment is used to accurately collect the optimization suggestion parameters of architectural design products for experiencers of different identity types, providing real data support for improving the quality of architectural design products; the best architectural design product optimization suggestion screening unit and the architectural design product optimization suggestion output unit cooperate with each other to classify and screen the optimization suggestion parameters of architectural design products according to experiencers of different identity types, intelligently screen out the best architectural design product optimization suggestion parameters proposed by experiencers of different identity types, and push them to the architectural design product feedback end in a timely and efficient manner through data output, thereby realizing accurate classification and screening of architectural design product optimization suggestions for different groups of people, and improving the scientificity and efficiency of architectural design products. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A schematic diagram of a module of a building design product use effect simulation data processing system provided by the present invention;

[0060] Figure 2The present invention provides a flowchart of a method for processing data of simulation of the use effect of a building design product. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] The embodiments of the architectural design product use effect simulation data processing system and method are as follows:

[0063] Embodiment 1:

[0064] See also Figure 1 - Figure 2 A method for processing data of simulation of use effect of architectural design products, the method comprising the following steps:

[0065] S1. Collect architectural design product model data and experience personnel identity feature data;

[0066] S2. Perform identity type identification processing on the experiencer based on the experiencer identity feature data, expert type experiencer identity data, and customer type experiencer identity data to generate experiencer identity type identification data;

[0067] S3, based on the experiencer identity type identification data and the architectural design product model data, the architectural design product model is displayed to the experiencer of a specific identity type;

[0068] S4, collect motion data of architectural design product usage scenarios;

[0069] S5. Analyze and process the spatial motion instructions of the architectural design product model required by the experience personnel in the use scenario simulation operation according to the architectural design product use scenario simulation motion data and the architectural design product modeling motion instruction data, generate the architectural design product use scenario simulation motion instruction data and execute the architectural design product use scenario simulation operation;

[0070] S6. Collect optimization suggestion data of architectural design products;

[0071] S7. Based on the experiencer's identity type identification data and the architectural design product optimization suggestion data, the optimization suggestion parameters of architectural design products for experiencers of different identity types are screened and processed to generate the best architectural design product optimization suggestion data and output feedback.

[0072] For further information, see Figure 1- Figure 2 The steps for collecting architectural design product model data and experiencer identity feature data are as follows:

[0073] S11. The designer uploads the 3D model data package of the architectural design product online through the data collection dialog box and generates the architectural design product model data A moxing ;

[0074] The experiencer inputs personal identity characteristic information online through the data collection dialog box and generates experiencer identity characteristic data I, which includes the experiencer's name, occupation and ID number; the experiencer represents a person who participates in the simulated experience of the use effect of the architectural design product.

[0075] The identity type of the experiencer is identified based on the experiencer identity feature data, expert type experiencer identity data, and customer type experiencer identity data. The steps for generating experiencer identity type identification data are as follows:

[0076] S21. Establishing expert type experience personnel identity data set A=(a 1 ,…,a m ,…,a ε ), m=1,2,3,…,ε; where a m represents the identity data of the mth expert type experiencer, ε represents the maximum number of expert type experiencers, and the identity data of expert type experiencers represents the identity information of professionals in the field of architectural design who participate in the simulation experience of the use effect of architectural design products;

[0077] Establish customer type experience personnel identity data set A'=(a' 1 ,…,a' n ,…,a' φ ), n=1,2,3,...,φ; where a' n represents the identity data of the nth customer type experiencer, φ represents the maximum number of customer type experiencers, and the customer type experiencer identity data represents the identity information of the customer who participates in the simulated experience of the use effect of the architectural design product;

[0078] S22, using a bidirectional search algorithm to compare the experiencer identity feature data I with the expert type experiencer identity data a in the expert type experiencer identity data set A. m and the customer type experience personnel identity data a' in the customer type experience personnel identity data set A' n Perform identity feature keyword matching, search for the identity type corresponding to the experiencer identity feature data I and generate the experiencer identity type identification data A shenfen ;

[0079] When I and a m The identity feature keyword matching is successful, indicating that the experiencer is an expert type experiencer, and the experiencer identity type identification data A is output. shenfen For expert type;

[0080] When I and a' n If the identity feature keyword match is successful, it means that the experiencer is a customer type experiencer, then the experiencer identity type identification data A is output. shenfen For customer type;

[0081] When I and a m and a' n If the identity feature keyword matching fails, it means that the experiencer is a public type experiencer, then the experiencer identity type identification data A is output. shenfen For public type.

[0082] For further information, see Figure 1 - Figure 2 The operation steps of performing the display operation of the architectural design product model to the experiencer of a specific identity type based on the experiencer identity type identification data and the architectural design product model data are as follows:

[0083] S31. Identify data A based on the identity type of the experiencer shenfen Identify the identity type of the experiencer and convert the architectural design product model data A moxing The 3D architectural design software is imported and run, and the real-time image of the architectural design product model is transmitted to the augmented reality device through data. The 3D model of the architectural design product is displayed to experience personnel of a specific identity type through the augmented reality device. The 3D architectural design software includes any one of 3DSMax, SketchUp, and Revit; the augmented reality device includes any one of a head-mounted display, smart glasses, and an AR projector.

[0084] The steps for collecting motion data for architectural design product usage scenarios are as follows:

[0085] S41. In the process of displaying the three-dimensional model of the architectural design product to the experiencer of a specific identity type, the expected spatial motion information of the architectural design product model required by the experiencer in the augmented reality device is collected online through the voice recognition device, and the architectural design product usage scenario simulation motion data B is generated. dongzuo The architectural design product usage scenario simulation motion data includes the horizontal left shift value, horizontal right shift value, model magnification value, model reduction value, model left rotation angle and model right rotation angle of the three-dimensional model of the architectural design product in the augmented reality device.

[0086] According to the architectural design product usage scenario simulation motion data and the architectural design product modeling motion instruction data, the spatial motion instruction analysis and processing of the architectural design product model required by the experience personnel in the usage scenario simulation operation, the operation steps of generating the architectural design product usage scenario simulation motion instruction data and executing the architectural design product usage scenario simulation operation are as follows:

[0087] S51. Establishing a motion instruction data set for building design product modeling where b p represents the architectural design product modeling motion instruction data corresponding to the simulated motion parameters of the p-th architectural design product usage scenario, Indicates the maximum number of types of motion parameter types for the use scenario of the architectural design product. The architectural design product modeling motion instruction data indicates the use scenario of the architectural design product simulation motion data B dongzuo The motion control instruction data corresponding to the three-dimensional modeling space of the architectural design product in the three-dimensional architectural design software;

[0088] S52, simulate motion data using architectural design product scenarios B dongzuo The architectural design product modeling motion instruction data set B and the architectural design product modeling motion instruction data b p Perform character matching on the type of motion parameter for the use scenario of the architectural design product, and search for the motion data B for the use scenario of the architectural design product dongzuo Corresponding architectural design product modeling motion instruction data b p And generate motion instruction data for architectural design product usage scenarios through data identification Execute and generate motion instruction data for architectural design product usage scenarios simulation The specific steps are as follows:

[0089] S521, initialization, update the pigeon population size N and the maximum number of iterations T;

[0090] S522, exploration phase, the number of iterations in the range of [0, t1] is the exploration phase, where t1 = 0.95xT. In the exploration phase, it is necessary to identify the position and target of the pigeon according to the motion command, calculate the speed of the pigeon identified by the motion command, and add the current position to the speed to get the new position, that is, search for the motion data B that is consistent with the architectural design product usage scenario simulation in the architectural design product modeling motion command data set B search space. dongzuo Matching architectural design product modeling motion instruction data b p The position of the pigeon is identified by the motion command, and the speed calculation formula of the pigeon is: in It represents the new speed of pigeon i in the j-dimensional space during the exploration phase, i.e. It represents the movement instruction recognition of pigeon i in the exploration phase with dimension The new speed in the search space of the architectural design product modeling motion instruction data set B; represents the original speed of pigeon i in the exploration phase in the j-dimensional space, that is, the original speed of pigeon i in the exploration phase in the j-dimensional space is The original speed in the search space of the architectural design product modeling motion instruction data set B; is a constant with a value of 0.2, t represents the current iteration number of the algorithm, represents an exponential function with base e, rand is a uniform random number in the interval [0,1], It represents the best position of the pigeon in the exploration phase of the motion instruction recognition in the j-dimensional space, that is, the optimal position of the pigeon in the exploration phase of the motion instruction recognition in the dimension is The architectural design product modeling motion instruction data set B is searched in the search space to find the motion data B that is simulated in the usage scenario of the architectural design product dongzuo Matching architectural design product modeling motion instruction data b p Location; It represents the original position of pigeon i in the exploration phase in the j-dimensional space according to the motion command recognition, that is, the original position of pigeon i in the exploration phase in the j-dimensional space according to the motion command recognition is The original position of the architectural design product modeling motion instruction data set B in the search space; the motion instruction recognition pigeon new position calculation formula in It represents the new position of pigeon i in the exploration phase in the j-dimensional space identified by the motion command, that is, the new position of pigeon i in the exploration phase in the j-dimensional space identified by the motion command is The new position in the search space of the architectural design product modeling motion instruction data set B;

[0091] S523, development phase, the number of iterations within the range of [t1, T] is the development phase, firstly, the motion instruction recognition pigeon group needs to be sorted in the search space of the architectural design product modeling motion instruction data set B, and the motion instruction recognition pigeon group is divided into two groups: excellent and ordinary. The excellent group of motion instruction recognition pigeons searches for motion data B that are consistent with the architectural design product usage scenario simulation in the search space of the architectural design product modeling motion instruction data set B. dongzuo Matching architectural design product modeling motion instruction data b p The position remains unchanged, while providing architectural design product modeling motion instruction data b p Location, architectural design product modeling motion instruction data b p Simulate motion data with architectural design product usage scenarios dongzuoThe fitness value is used as a parameter for the general group of motion instruction recognition pigeon groups to determine their architectural design product modeling motion instruction data set B search space and architectural design product use scenario simulation motion data B dongzuo Matching architectural design product modeling motion instruction data b p The new position of the pigeon group is calculated by the common motion command:

[0092] in represents the new position of the motion instruction recognition pigeon i in the j-dimensional space during the development stage, that is, the motion instruction recognition pigeon i in the development stage is in the dimension The new position in the search space of the architectural design product modeling motion instruction data set B; It represents the best position of the excellent group of pigeons in the development stage in the j-dimensional space. That is, the excellent group of pigeons in the development stage in the dimension is The architectural design product modeling motion instruction data set B is searched in the search space to find the motion data B that is simulated in the usage scenario of the architectural design product dongzuo The most matching architectural design product modeling motion instruction data b p The best location;

[0093] S524. When the algorithm meets the maximum number of iterations, output the simulated motion data B for the use scenario of the architectural design product. dongzuo Matching architectural design product modeling motion instruction data b p ;

[0094] S525, based on the architectural design product modeling motion instruction data b output in step S524 p Generate motion instruction data for architectural design product usage scenarios through data identification

[0095] S53 simulates motion instruction data using scenarios of architectural design products The three-dimensional model of the architectural design product is input into the three-dimensional architectural design software to perform spatial movement in the modeling space according to the motion control instructions. The real-time image of the spatial movement of the three-dimensional model of the architectural design product is simultaneously transmitted to the augmented reality device through data, and the augmented reality device is used to perform simulation operations on the usage scenarios of the architectural design product by the experience personnel.

[0096] For further information, see Figure 1 - Figure 2 ,The steps for collecting architectural design product optimization suggestion data are as follows:

[0097] S61. When the simulation operation of the use scenario of the architectural design product is completed, the optimization suggestion information of the architectural design product by the experience personnel of different identity types is collected online through the voice recognition device and the optimization suggestion data set of the architectural design product is generated. where c′ u represents the u-th architectural design product optimization suggestion data collected by expert experience personnel, γ represents the maximum number of architectural design product optimization suggestion data collected by expert experience personnel; c″ v represents the vth architectural design product optimization suggestion data collected from customer type experience personnel, η represents the maximum number of architectural design product optimization suggestion data collected from customer type experience personnel; c″′ k represents the kth piece of architectural design product optimization suggestion data collected from the public type experiencers, and ι represents the maximum number of architectural design product optimization suggestion data collected from the public type experiencers.

[0098] The steps for screening and processing the optimization suggestion parameters of architectural design products for experiencers of different identity types based on the experiencer identity type identification data and the architectural design product optimization suggestion data, generating the best architectural design product optimization suggestion data and outputting feedback are as follows:

[0099] S71. Identify data A based on the identity type of the experiencer shenfen The corresponding experience personnel identity type keyword classification is used to extract the recommended keywords for architectural design product optimization suggestions from the architectural design product optimization suggestion data set C, and the recommended keywords with the largest number of architectural design product optimization suggestions proposed by experience personnel of different identity types are counted to generate the best architectural design product optimization suggestion keyword set. where d' 1 Indicates the best architectural design product optimization suggestion keywords corresponding to expert experience personnel, d' 2 The best architectural design product optimization suggestion keywords corresponding to customer type experience personnel, d' 3 Indicates the best architectural design product optimization suggestion keywords corresponding to expert experience personnel;

[0100] S72, using an iterative deepening search algorithm based on the best architectural design product optimization suggestion keywords in the best architectural design product optimization suggestion keyword set D and the experiencer identity type identification data A shenfen The corresponding experience personnel identity type keyword classification searches for the best architectural design product optimization suggestion keyword corresponding to the architectural design product optimization suggestion data set C, and generates the best architectural design product optimization suggestion data set where c′ u1,zuirepresents the optimal architectural design product optimization suggestion data of the u1th best architectural design product optimization suggestion data collected by the expert experience personnel, c′ u2,zui Indicates the u2th best architectural design product optimization suggestion data collected by expert experience personnel, 1≤u1≤u≤u2≤γ;

[0101] c″ v1,zui Indicates the collection of the v1th best architectural design product optimization recommendation data of customer type experience personnel, c″ v2,zui Indicates the v2th best architectural design product optimization suggestion data collected by customer type experience personnel, 1≤v1≤v≤v2≤η;

[0102] c″′ k1,zui Indicates the k1th best architectural design product optimization suggestion data collected from public experience personnel, c″′ k2,zui Indicates the k2th best architectural design product optimization suggestion data collected from public experience personnel, 1≤k1≤k≤k2≤ι;

[0103] S73. Push the best architectural design product optimization suggestion data set C′ to the architectural design product feedback terminal through data output.

[0104] Embodiment 2:

[0105] See also Figure 1 - Figure 2 , a building design product use effect simulation data processing system, used to implement a building design product use effect simulation data processing method, the system includes a building design product use simulation information processing module, a building design product use simulation processing module, and a building design product optimization suggestion analysis output module;

[0106] The architectural design product use simulation information processing module includes an architectural design product model acquisition unit, an experiencer identity information acquisition unit, an expert type experiencer identity information storage unit, a customer type experiencer identity information storage unit, and an experiencer identity type identification unit;

[0107] An architectural design product model acquisition unit, which acquires architectural design product model data through a data acquisition dialog box; an experiencer identity information acquisition unit, which acquires experiencer identity feature data through a data acquisition dialog box; an expert type experiencer identity information storage unit, which is used to store expert type experiencer identity data; a customer type experiencer identity information storage unit, which is used to store customer type experiencer identity data; an experiencer identity type identification unit, which performs experiencer identity type identification processing based on experiencer identity feature data, expert type experiencer identity data, and customer type experiencer identity data to generate experiencer identity type identification data;

[0108] The architectural design product use simulation processing module includes an architectural design product model display unit, an architectural design product use scenario simulation motion information acquisition unit, an architectural design product modeling motion instruction storage unit, an architectural design product use scenario simulation motion instruction analysis unit, and an architectural design product use scenario simulation operation execution unit;

[0109] An architectural design product model display unit, which performs a display operation of the architectural design product model to an experiencer of a specific identity type based on the experiencer identity type recognition data and the architectural design product model data; an architectural design product use scenario simulation motion information collection unit, which collects architectural design product use scenario simulation motion data through a voice recognition device; an architectural design product modeling motion instruction storage unit, which is used to store architectural design product modeling motion instruction data; an architectural design product use scenario simulation motion instruction analysis unit, which performs spatial motion instruction analysis and processing of the architectural design product model required by the experiencer in the use scenario simulation operation according to the architectural design product use scenario simulation motion data and the architectural design product modeling motion instruction data, and generates architectural design product use scenario simulation motion instruction data; an architectural design product use scenario simulation operation execution unit, which performs an architectural design product use scenario simulation operation according to the architectural design product use scenario simulation motion instruction data;

[0110] The architectural design product optimization suggestion analysis and output module includes an architectural design product optimization suggestion collection unit, a best architectural design product optimization suggestion screening unit, and an architectural design product optimization suggestion output unit;

[0111] The architectural design product optimization suggestion collection unit collects architectural design product optimization suggestion data through voice recognition equipment; the best architectural design product optimization suggestion screening unit screens and processes the architectural design product optimization suggestion parameters for experiencers of different identity types based on the experiencer identity type recognition data and the architectural design product optimization suggestion data, and generates the best architectural design product optimization suggestion data; the architectural design product optimization suggestion output unit pushes the best architectural design product optimization suggestion data to the architectural design product feedback end through data output.

[0112] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for processing data of simulation of use effect of architectural design products, characterized in that: The method comprises the following steps: S1. Collect architectural design product model data and experience personnel identity feature data; S2, performing identification processing on the identity type of the experiencer based on the identity feature data of the experiencer, the identity data of the expert type experiencer, and the identity data of the customer type experiencer to generate identity type identification data of the experiencer; S3, based on the identification data of the experiencer's identity type and the architectural design product model data, the architectural design product model is displayed to the experiencer of a specific identity type; S4, collect motion data of architectural design product usage scenarios; S5, analyzing and processing the spatial motion instructions of the architectural design product model required by the experiencer in the use scenario simulation operation according to the architectural design product use scenario simulation motion data and the architectural design product modeling motion instruction data, generating the architectural design product use scenario simulation motion instruction data and executing the architectural design product use scenario simulation operation; S6. Collect optimization suggestion data of architectural design products; S7. Screening and processing of optimization suggestion parameters for architectural design products for experiencers of different identity types based on the experiencer identity type identification data and the architectural design product optimization suggestion data, generating optimal architectural design product optimization suggestion data and outputting feedback.

2. A method for processing architectural design product use effect simulation data according to claim 1, characterized in that: The S1 comprises the following steps: S11. The designer uploads the 3D model data package of the architectural design product online through the data collection dialog box and generates the architectural design product model data A moxing ; The experiencer inputs personal identity characteristic information online through the data collection dialog box and generates the experiencer identity characteristic data I.

3. A method for processing architectural design product use effect simulation data according to claim 2, characterized in that: The S2 comprises the following steps: S21. Establishing the expert experience personnel identity data set A = (a1, ..., a m ,…,a ε ), m=1,2,3,…,ε; where a m represents the identity data of the mth expert type experience personnel, and ε represents the maximum number of expert type experience personnel; Establish customer type experience personnel identity data set A'=(a'1,…,a' n ,…,a' φ ), n=1,2,3,...,φ; where a' n represents the identity data of the nth customer type experience personnel, and φ represents the maximum number of customer type experience personnel; S22, using a bidirectional search algorithm to compare the experiencer identity feature data I with the expert type experiencer identity data a in the expert type experiencer identity data set A. m and the customer type experience personnel identity data a' in the customer type experience personnel identity data set A' n Perform identity feature keyword matching to search for the identity type corresponding to the experiencer identity feature data I and generate experiencer identity type identification data A shenfen ; When I and a m If the identity feature keyword matching is successful, the experiencer identity type identification data A is output shenfen For expert type; When I and a' n If the identity feature keyword matching is successful, the experiencer identity type identification data A is output shenfen For customer type; When I and a m and a' n If the identity feature keyword matching fails, the experiencer identity type identification data A is output shenfen For public type.

4. A method for processing architectural design product use effect simulation data according to claim 3, characterized in that: The S3 comprises the following steps: S31, identifying data A based on the identity type of the experiencer shenfen The identity type of the experiencer is identified, and the architectural design product model data A moxing The three-dimensional architectural design software is imported and run, and the real-time image of the architectural design product model is transmitted to the augmented reality device through data. The three-dimensional model of the architectural design product is displayed to experience personnel of specific identity types through the augmented reality device.

5. A method for processing architectural design product use effect simulation data according to claim 4, characterized in that: The S4 comprises the following steps: S41. In the process of displaying the three-dimensional model of the architectural design product to the experiencer of a specific identity type, the expected spatial motion information of the architectural design product model required by the experiencer in the augmented reality device is collected online through the voice recognition device, and the architectural design product usage scenario simulation motion data B is generated. dongzuo .

6. A method for processing data of simulation of use effect of architectural design products according to claim 5, characterized in that: The S5 comprises the following steps: S51. Establishing a motion instruction data set for building design product modeling where b p represents the architectural design product modeling motion instruction data corresponding to the simulated motion parameters of the p-th architectural design product usage scenario, Indicates the maximum value of the number of types of motion parameter simulations for the use scenario of the architectural design product, wherein the architectural design product modeling motion instruction data indicates the use scenario simulation motion data B of the architectural design product dongzuo The motion control instruction data corresponding to the three-dimensional modeling space of the architectural design product in the three-dimensional architectural design software; S52, using the architectural design product to simulate the motion data B dongzuo The architectural design product modeling motion instruction data set B is the architectural design product modeling motion instruction data set B. p Perform architectural design product usage scenario simulation motion parameter type character matching to search for the architectural design product usage scenario simulation motion data B dongzuo The corresponding architectural design product modeling motion instruction data b p And generate motion instruction data for architectural design product usage scenarios through data identification Execute and generate motion instruction data for architectural design product usage scenarios simulation The specific steps are as follows: S521, initialization, update the pigeon population size N and the maximum number of iterations T; S522, exploration phase, the number of iterations in the range of [0, t1] is the exploration phase, where t1 = 0.95xT. In the exploration phase, it is necessary to identify the position and target of the pigeon according to the motion command, calculate the speed of the pigeon identified by the motion command, and add the current position to the speed to get the new position, that is, search for the motion data B that is consistent with the architectural design product usage scenario simulation in the architectural design product modeling motion command data set B search space. dongzuo Matching architectural design product modeling motion instruction data b p location; S523, development phase, the number of iterations within the range of [t1, T] is the development phase, firstly, the motion instruction recognition pigeon group needs to be sorted in the search space of the architectural design product modeling motion instruction data set B, and the motion instruction recognition pigeon group is divided into two groups: excellent and ordinary. The excellent group of motion instruction recognition pigeons searches for motion data B that are consistent with the architectural design product usage scenario simulation in the search space of the architectural design product modeling motion instruction data set B. dongzuo Matching architectural design product modeling motion instruction data b p The position remains unchanged, while providing the architectural design product modeling motion instruction data b p The location of the architectural design product modeling motion instruction data b p Simulate motion data using scenarios of the architectural design product B dongzuo The fitness value is used as a parameter for the general group of motion instruction recognition pigeon groups to determine their architectural design product modeling motion instruction data set B search space and architectural design product use scenario simulation motion data B dongzuo Matching architectural design product modeling motion instruction data b p The new location of S524. When the algorithm meets the maximum number of iterations, output the motion data B simulated with the use scenario of the architectural design product dongzuo Matching architectural design product modeling motion instruction data b p ; S525, according to the architectural design product modeling motion instruction data b output in step S524 p Generate motion instruction data for architectural design product usage scenarios through data identification S53: simulating motion instruction data using the scene of the architectural design product The three-dimensional model of the architectural design product is input into the three-dimensional architectural design software to perform spatial movement in the modeling space according to the motion control instructions. The real-time image of the spatial movement of the three-dimensional model of the architectural design product is simultaneously transmitted to the augmented reality device through data, and the augmented reality device is used to perform simulation operations on the usage scenarios of the architectural design product by the experience personnel.

7. A method for processing architectural design product use effect simulation data according to claim 6, characterized in that: The S6 comprises the following steps: S61. When the simulation operation of the use scenario of the architectural design product is completed, the optimization suggestion information of the architectural design product by the experience personnel of different identity types is collected online through the voice recognition device and the optimization suggestion data of the architectural design product is generated. gather u=1,2,3,…,γ, v=1,2,3,…,η, k=1,2,3,…,ι; where c u surface represents the u-th architectural design product optimization suggestion data collected by the expert type experience personnel, and γ represents the collection of expert type experience The maximum number of architectural design product optimization suggestion data for personnel; c v represents the vth architectural design product optimization suggestion data collected from customer type experience personnel, and η represents the architectural design product optimization suggestion data collected from customer type experience personnel The maximum value of quantity; c k represents the kth piece of architectural design product optimization suggestion data collected from the public type experiencers, and ι represents the maximum number of architectural design product optimization suggestion data collected from the public type experiencers.

8. A method for processing architectural design product use effect simulation data according to claim 7, characterized in that: The S7 comprises the following steps: S71, identifying data A based on the identity type of the experiencer shenfen The corresponding experience personnel identity type keyword classification is used to extract the recommended keywords of the architectural design product optimization suggestion data in the architectural design product optimization suggestion data set C, and the recommended keywords with the largest number of values ​​corresponding to the architectural design product optimization suggestions proposed by experience personnel of different identity types are counted to generate the best architectural design product optimization suggestion keyword set. Among them, d'1 represents the best architectural design product optimization suggestion keywords corresponding to expert type experience personnel, d'2 represents the best architectural design product optimization suggestion keywords corresponding to customer type experience personnel, and d'3 represents the best architectural design product optimization suggestion keywords corresponding to expert type experience personnel; S72, using an iterative deepening search algorithm based on the best architectural design product optimization suggestion keywords in the best architectural design product optimization suggestion keyword set D and the experiencer identity type identification data A shenfen The corresponding experience personnel identity type keyword classification searches for the architectural design product optimization suggestion data corresponding to the best architectural design product optimization suggestion keyword in the architectural design product optimization suggestion data set C, and generates the best architectural design product Optimization suggestion data set where c u1,zui Indicates the collection of the best architectural design product optimization suggestion data of the expert type experience personnel, c u2,zui Indicates the u2th best architectural design product optimization suggestion data collected by expert experience personnel, 1≤u1≤u≤u2≤γ; c v1,zui Indicates the collection of the v1th best architectural design product optimization suggestion data of customer type experience personnel. c v2,zui Indicates the v2th best architectural design product optimization suggestion data collected by customer type experience personnel, 1≤v1≤v≤v2≤η; c k1,zui Indicates the collection of the k1th best architectural design product optimization suggestion data of the public type experience personnel, c k2,zui Indicates the k2th best architectural design product optimization suggestion data collected from public experience personnel, 1≤k1≤k≤k2≤ι; S73, pushing the best architectural design product optimization suggestion data set C to the architectural design product feedback terminal through data output.

9. A system for processing data of simulation of use effect of architectural design products, used to implement a method for processing data of simulation of use effect of architectural design products according to any one of claims 1 to 8, characterized in that: The system includes an architectural design product use simulation information processing module, an architectural design product use simulation processing module, and an architectural design product optimization suggestion analysis output module.

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