A revolving door optimization design method, device, equipment and medium

Abstract

The present invention provides an optimization design method, device, equipment and medium for a revolving door, which relates to the technical field of revolving doors, including obtaining first information, second information and third information; performing three-dimensional modeling and parameter setting processing according to the first information to construct fourth information, wherein the fourth information is a three-dimensional structural model of the revolving door including design parameters and performance indicators; performing crowd flow simulation processing according to the second information, the third information and the fourth information, and obtaining fifth information by introducing crowd flow congestion and traffic failure conditions; performing social simulation processing according to the fifth information to obtain sixth information; performing multi-objective optimization processing according to the sixth information and the fourth information, and obtaining an optimized design parameter combination by combining traffic efficiency, safety and energy consumption indicators. The present invention can not only improve the energy consumption efficiency of the revolving door, but also optimize the energy consumption indicators under the premise of ensuring traffic efficiency and safety.

Description

Technical Field

[0001] The present invention relates to the technical field of revolving doors, and in particular to an optimization design method, device, equipment and medium for a revolving door. Background Art

[0002] At present, revolving doors, as important entrance and exit equipment for public buildings, play a vital role in urban life. With the continuous advancement of urbanization and the increase in population mobility, public buildings such as shopping malls, office buildings, stations, airports, etc., welcome a large number of people every day. In these places, revolving doors are not only the main channels for people to enter and exit, but also an important part of urban transportation and building safety. However, the existing revolving door design has some limitations and cannot adapt well to the complex urban environment and human flow. The existing design methods are often based on experience and static models, and cannot fully consider dynamic factors such as building layout, human flow distribution and passage paths, resulting in low traffic efficiency, congestion and safety hazards.

[0003] Based on the above-mentioned shortcomings of the prior art, there is an urgent need for an optimized design method, device, equipment and medium for a revolving door. Summary of the invention

[0004] The purpose of the present invention is to provide a revolving door optimization design method, device, equipment and readable storage medium to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0005] In a first aspect, the present application provides a method for optimizing the design of a revolving door, comprising:

[0006] Acquire first information, second information and third information, wherein the first information includes initial structural features and parameter information of the revolving door, the second information includes architectural layout, crowd distribution and passage path information of the revolving door installation site, and the third information includes historical passage data;

[0007] Performing three-dimensional modeling and parameter setting processing according to the first information to construct fourth information, wherein the fourth information is a three-dimensional structural model of the revolving door including design parameters and performance indicators;

[0008] Performing pedestrian traffic simulation processing according to the second information, the third information and the fourth information, and obtaining fifth information by introducing pedestrian congestion and traffic failure conditions, wherein the fifth information is a result of pedestrian traffic scenario simulation;

[0009] Performing social simulation processing on the fifth information to obtain sixth information, wherein the sixth information includes crowd flow distribution and corresponding traffic conditions in different scenarios;

[0010] Multi-objective optimization processing is performed based on the sixth information and the fourth information, and an optimized design parameter combination is obtained by combining traffic efficiency, safety and energy consumption indicators. The optimized design parameter combination includes the size requirements of the revolving door, drive system parameters and sensor layout plan.

[0011] In a second aspect, the present application also provides an optimized design device for a revolving door, comprising:

[0012] an acquisition module, configured to acquire first information, second information and third information, wherein the first information includes initial structural features and parameter information of the revolving door, the second information includes architectural layout, crowd distribution and passage path information of the revolving door installation site, and the third information includes historical passage data;

[0013] A construction module, configured to perform three-dimensional modeling and parameter setting processing according to the first information, so as to construct fourth information, wherein the fourth information is a three-dimensional structural model of the revolving door including design parameters and performance indicators;

[0014] A simulation module, configured to simulate the pedestrian traffic situation according to the second information, the third information and the fourth information, and obtain fifth information by introducing pedestrian congestion and traffic failure, wherein the fifth information is a pedestrian traffic scenario simulation result;

[0015] A simulation module, configured to perform social simulation processing on the fifth information to obtain sixth information, wherein the sixth information includes crowd flow distribution and corresponding traffic conditions in different scenarios;

[0016] An optimization module is used to perform multi-objective optimization processing according to the sixth information and the fourth information, and obtain an optimized design parameter combination by combining traffic efficiency, safety and energy consumption indicators. The optimized design parameter combination includes the size requirements of the revolving door, drive system parameters and sensor layout plan.

[0017] In a third aspect, the present application also provides an optimization design device for a revolving door, comprising:

[0018] Memory for storing computer programs;

[0019] A processor is used to implement the steps of the revolving door optimization design method when executing the computer program.

[0020] In a fourth aspect, the present application further provides a medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned method for optimizing the design of a revolving door are implemented.

[0021] The beneficial effects of the present invention are:

[0022] The present invention transforms multiple objective functions into a composite objective function through mathematical programming and multi-objective optimization processing, and establishes constraint conditions of the optimization problem according to design and operation restrictions, thereby obtaining a mathematical expression of the optimization problem of the revolving door, and then searching the optimal solution space, extracting the parameter combination that meets the design requirements, which can not only improve the energy efficiency of the revolving door, but also optimize the energy consumption index under the premise of ensuring traffic efficiency and safety.

[0023] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 It is a schematic flow chart of the optimization design method of the revolving door described in the embodiment of the present invention;

[0026] Figure 2 It is a schematic diagram of the structure of the optimized design equipment of the revolving door described in the embodiment of the present invention;

[0027] Figure 3 Flow chart of the multi-objective genetic algorithm described in an embodiment of the present invention.

[0028] Markings in the figure: 800, optimized design equipment for revolving door; 801, processor; 802, memory; 803, multimedia component; 804, I / O interface; 805, access component. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0030] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0031] Embodiment 1:

[0032] This embodiment provides an optimization design method for a revolving door.

[0033] See also Figure 1 , the figure shows that the method includes step S100, step S200, step S300, step S400 and step S500.

[0034] Step S100, obtaining first information, second information and third information, wherein the first information includes initial structural features and parameter information of the revolving door, the second information includes architectural layout, crowd distribution and passage path information of the revolving door installation site, and the third information includes historical passage data;

[0035] It is understandable that the basic structure and parameter characteristics of the revolving door include the size, material, number of door leaves, door leaf width, door frame structure, opening and closing method, sensor type, etc. of the revolving door. By analyzing the structural characteristics of the revolving door in detail, it is possible to provide necessary reference for subsequent three-dimensional modeling and parameter setting. For example, understanding the size and material of the revolving door can affect its stability and durability, while the opening and closing method and sensor type are directly related to traffic efficiency and safety. The building layout, crowd distribution and traffic path information of the revolving door installation site include the building floor plan, floor layout map and crowd path map. By analyzing this information, it is possible to understand the environmental conditions of the revolving door, including the surrounding building structure, crowded areas and the design of the traffic path. The historical traffic data records the traffic conditions of the revolving door in the past period of time, including traffic volume, traffic time, congestion, etc. By analyzing the historical traffic data, it is possible to understand the traffic conditions of the revolving door in different time periods, seasons and activities.

[0036] Step S200: Perform three-dimensional modeling and parameter setting processing according to the first information to construct and obtain fourth information, where the fourth information is a three-dimensional structural model of the revolving door including design parameters and performance indicators;

[0037] Specifically, first, the initial structural features and parameter information of the revolving door provided in the first information, such as size, material, number of door leaves, etc., are used to perform three-dimensional modeling using computer-aided design software. In the modeling process, the actual structural characteristics of the revolving door, such as the rotation axis, the motion trajectory of the door leaves, the sensor layout position, etc., need to be taken into account. Through accurate modeling, the real structure of the revolving door can be presented in the three-dimensional model. Next, according to the design parameters and performance indicators, the three-dimensional model is parameterized. The design parameters include the parameters of the drive system, the layout of the sensor, the speed of the door, etc.; and the performance indicators include the traffic efficiency, safety performance, etc. By setting these parameters in the three-dimensional model, the performance of the revolving door under different design schemes can be simulated, evaluated and optimized. This step can accurately simulate the real structure and operation mechanism of the revolving door through three-dimensional modeling and parameter setting, providing a reliable basis for subsequent optimization design; integrating the design parameters and performance indicators into the three-dimensional model allows the performance of different design schemes to be evaluated in a virtual environment, providing a scientific basis for the selection of the optimization scheme.

[0038] Step S300, performing pedestrian traffic simulation processing according to the second information, the third information and the fourth information, and obtaining fifth information by introducing pedestrian congestion and traffic failure conditions, the fifth information being a pedestrian traffic scenario simulation result;

[0039] First, using the architectural layout, crowd flow distribution and traffic path information of the revolving door installation site provided by the second information, a virtual environment for crowd flow is established in the three-dimensional model, including determining the location of the traffic door, the passage for crowd flow in and out, possible congestion points, etc. At the same time, combined with the historical traffic data in the third information, the distribution and change of crowd flow can be reasonably simulated. Then, the three-dimensional structural model of the revolving door in the fourth information is integrated into the virtual environment, and the revolving door operation parameters and crowd flow behavior rules in the simulation are set in combination with the information provided in the second and third information. This includes setting the speed of the revolving door, the response rules of the sensor, the speed and density of the crowd, etc. Subsequently, the simulation technology is used to simulate the crowd flow. By introducing different crowd flow distribution, traffic path selection, revolving door operation status and other factors, the crowd flow conditions in different scenarios can be simulated, including the occurrence of smooth traffic, congestion, failure and the like. The final simulation results can help to better understand the operation of the revolving door under different conditions and provide a reference for subsequent optimization design.

[0040] Step S400: Performing social simulation processing on the fifth information to obtain sixth information, where the sixth information includes crowd flow distribution and corresponding traffic conditions in different scenarios;

[0041] It is understandable that this step first uses the simulated pedestrian flow obtained in the fifth information as input to construct a social simulation model. This model can cover the distribution of pedestrian flow in different scenarios, including peak and trough periods in different time periods, pedestrian density distribution in different areas, etc., while taking into account the influence of other factors, such as the impact of weather, holidays and other factors on pedestrian flow. Next, social simulation technology is used to simulate individual interactions and behaviors in a simulated environment. This includes people's walking path selection in different situations, the simulation of the use of revolving doors, etc. By running the simulation model, the distribution of pedestrian flow in different scenarios and the corresponding traffic conditions are obtained. This information can reflect the operating conditions of the revolving door under different conditions, including the performance of traffic efficiency, safety, etc. Social simulation processing can more realistically simulate the behavior and interaction of pedestrian flow, and provide more reliable data support for evaluating the performance of revolving doors in actual use.

[0042] Step S500, performing multi-objective optimization processing according to the sixth information and the fourth information, obtaining an optimized design parameter combination by combining traffic efficiency, safety and energy consumption indicators, wherein the optimized design parameter combination includes the size requirements of the revolving door, drive system parameters and sensor layout plan.

[0043] It should be noted that this step establishes a multi-objective optimization model, taking traffic efficiency, safety and energy consumption indicators as the optimization objective functions. Traffic efficiency is measured by indicators such as average waiting time and traffic speed; safety is evaluated by indicators such as anti-pinch performance and accident rate; energy consumption indicators are considered through power consumption, operating efficiency and other aspects. By weighting or multi-criteria decision analysis of these objective functions, an optimization objective function that comprehensively considers traffic efficiency, safety and energy consumption can be obtained. Finally, optimization methods such as mathematical programming or evolutionary algorithms are used to obtain the optimal design parameter combination that meets the design requirements. These parameter combinations will enable the revolving door to achieve the best overall performance in different scenarios.

[0044] It should be noted that step S200 includes step S210, step S220, step S230, step S240 and step S250.

[0045] Step S210: performing parameterized modeling processing on the first information to obtain seventh information, where the seventh information is a geometric model of the revolving door;

[0046] Specifically, the geometric shape of the revolving door is first modeled, which involves the description of the geometric properties of the door, such as shape, size, and curvature. Through parametric modeling technology, these geometric properties can be expressed by parameters, which facilitates subsequent adjustment and optimization. Secondly, it is also necessary to consider the components of the revolving door, such as door leaves, door frames, etc. The shapes and positions of these components will also be included in the parametric modeling to more accurately describe the structure of the revolving door. When establishing the parametric model, the various forms and models of revolving doors that may exist are further considered. Therefore, it is necessary to design a universal parametric model that can be applied to different types of revolving doors and has certain flexibility and scalability. Through this step, the geometric model of the revolving door is obtained, which provides a basis for subsequent three-dimensional modeling and parameter setting, and helps to better understand and design the structure of the revolving door.

[0047] Step S220: Perform finite element mesh processing on the seventh information to obtain eighth information, where the eighth information includes a finite element mesh model of the revolving door;

[0048] Specifically, the finite element method will be used to first divide the geometric model of the revolving door into multiple small units, and then a mathematical model will be established inside each small unit to describe the mechanical behavior within the unit. Next, material properties, constraints and loading conditions are assigned to each small unit to fully describe the mechanical properties of the revolving door. These conditions include mechanical properties such as elastic modulus, Poisson's ratio, density, as well as external loading and boundary constraints. Through finite element mesh processing, the distribution of mechanical parameters such as displacement, stress, strain, etc. of the revolving door on each small unit can be obtained. This information will help further analyze the mechanical properties of the revolving door, such as structural strength and stability, and provide a basis for subsequent analysis.

[0049] Step S230: Performing modal-stiffness analysis processing on the eighth information to obtain ninth information, where the ninth information includes dynamic characteristics and static strength data of the revolving door;

[0050] It is understood that modal analysis is used to determine the natural vibration frequencies and modes of the structure, as well as the modal damping ratios corresponding to these vibration frequencies. Through modal analysis, the characteristics of the revolving door under free vibration, such as natural frequencies, modes, etc., can be understood. Stiffness analysis is used to evaluate the response of the structure when subjected to external loads, including deformation of the structure, stress distribution, etc. Through stiffness analysis, the strength and stiffness of the revolving door under static loading, as well as possible stress concentration areas and instability can be evaluated.

[0051] Step S240: Perform sensitivity analysis processing according to the ninth information, and obtain tenth information by calculating the influence of the design variables on the performance index of the revolving door, where the tenth information is sensitivity data of the revolving door design parameters;

[0052] It can be understood that sensitivity analysis is a method for evaluating the degree of influence of design parameters on system performance indicators. Specifically, a set of design parameters, such as the size of the revolving door, drive system parameters, and sensor layout scheme, are first determined. Then, using numerical simulation or analysis tools, these parameters are changed within the design parameter range, and the impact of each parameter change on the performance indicators is recorded. Performance indicators include but are not limited to traffic efficiency, safety, and energy consumption. The degree of influence of each design parameter on these performance indicators will be evaluated, and the results will be presented in the form of sensitivity data, i.e., the tenth information. Through sensitivity analysis, it can be determined which design parameters have the greatest impact on the performance indicators of the revolving door, thereby providing an important reference for optimizing the design. These sensitivity data will help optimize the design parameter combination of the revolving door to improve its performance indicators such as traffic efficiency, safety, and energy consumption.

[0053] Step S250: Integrate the ninth information and the tenth information into the seventh information to obtain the fourth information.

[0054] It is understandable that this step considers the influence of dynamic characteristics and static strength data on design parameters, and combines the comprehensive sensitivity evaluation of design parameters to obtain a three-dimensional structural model of the revolving door that comprehensively considers performance indicators and design parameters. It should be noted that step S250 includes step S251, step S252 and step S253.

[0055] Step S251: Analyze and calculate the geometric model in the seventh information according to the ninth information, and identify and obtain an optimized node set;

[0056] It can be understood that this step uses mathematical modeling and calculation methods to dissect and evaluate the geometric model in detail to determine the nodes that have a critical impact on the overall performance. These nodes represent the weak points of the structure, performance bottlenecks, or the locations of key parameters in the geometric model. By identifying and locating these optimization nodes, we can more accurately understand the impact of design parameters on various parts of the geometric model, providing an important reference for subsequent optimization design.

[0057] Step S252, performing fitting processing according to the sensitivity data in the tenth information, and obtaining a matching result by matching it with the corresponding optimization node in the geometric model;

[0058] Specifically, this step uses the fitting algorithm of the mathematical model to match the sensitivity data with the key nodes of the geometric model. The matching process ensures that the sensitivity data can be accurately applied to the specific parts of the geometric model, so as to better understand the scope and degree of influence of the design parameters. The matching results will provide key reference information to help more accurately determine which parts need to be optimized to improve overall performance.

[0059] Step S253: Based on the matching result, the sensitivity data is mapped to the spatial coordinate system of the set model to obtain fourth information.

[0060] It should be noted that this step, by matching the matched sensitivity data with the spatial coordinate system of the geometric model, can more clearly understand the spatial distribution and influence of different design parameters in the entire geometric model. This process is similar to creating a sensitivity map on the geometric model to guide which areas need to be focused on and optimized. Such spatial mapping can provide a more intuitive and detailed data perspective, which helps to develop more effective optimization strategies to improve the design parameters of the revolving door and enhance its overall performance.

[0061] It should be noted that step S300 includes step S310, step S320, step S330 and step S340.

[0062] Step S310: Perform crowd flow simulation processing according to the second information, and obtain eleventh information by creating pedestrians representing different ages, genders and clothing and assigning preset behavior rules. The eleventh information is a basic model for crowd flow simulation;

[0063] This step uses a probability and statistics-based model to simulate the behaviors of different groups of people in the revolving door passage scenario, such as travel speed, passage method, and reaction to the surrounding environment, which helps to more realistically reflect the actual passage situation.

[0064] Step S320: performing pattern recognition processing according to the third information, and obtaining twelfth information by identifying peak traffic hours, common congestion points, and past pedestrian pinching events, wherein the twelfth information includes pedestrian traffic patterns and potential anti-pinch risk points;

[0065] It should be noted that this step uses pattern recognition technology to analyze pedestrian traffic data. This technology can extract useful patterns and features from a large amount of data to help understand the pattern of pedestrian traffic and identify potential safety risk points. Furthermore, a method combining deep learning algorithms and traditional graph theory with complex network theory is also used; through deep learning, complex patterns and associations in data can be automatically discovered, and pedestrian traffic can be regarded as patterns in space and time, thereby identifying different traffic patterns and behavioral patterns. At the same time, with the help of graph theory and complex network theory, a network model of pedestrian traffic is constructed to study the connectivity and traffic path characteristics between different areas and possible congestion points. The comprehensive use of these analysis methods helps to have a more comprehensive understanding of the structure and dynamics of pedestrian traffic, and provides strong support for the discovery of potential safety hazards.

[0066] Step S330: performing prediction processing according to the eleventh information and the twelfth information, simulating pedestrian behavior changes under different situations by using a probability model, and combining the fault tree analysis to predict the impact of the passage failure on the operation of the revolving door to obtain the thirteenth information, the thirteenth information is a simulation result under the conditions of pedestrian congestion and passage failure;

[0067] It is understandable that the probability model is used to simulate changes in pedestrian behavior under different circumstances. These circumstances may include changes in population density, changes in pedestrian travel speed, and the impact of emergencies on pedestrian behavior. Through the simulation of the probability model, the dynamic changes in pedestrian traffic under different circumstances can be predicted, providing more accurate input conditions for the operation of the revolving door. At the same time, the fault tree analysis method is also combined to analyze and evaluate various factors that may cause revolving door traffic failures. These factors involve equipment failures, human errors, uncontrollable factors and other situations. By constructing a fault tree, the cause-and-effect relationship between different events can be clearly described, and the potential impact of various factors on the operation of the revolving door can be evaluated. This step comprehensively considers the simulation results under the conditions of congestion and traffic failure, which can better understand the operation of the revolving door in a complex environment.

[0068] Step S340, performing anti-pinch optimization simulation processing according to the thirteenth information and the fourth information, predicting the response of the sensor and the operation adjustment of the revolving door by combining the pedestrian's body shape, movement speed and clothing thickness factors, and obtaining the fifth information.

[0069] Based on these prediction results, the sensitivity of the sensor can be adjusted and the operating parameters of the revolving door can be optimized to improve its adaptability and safety for different pedestrians.

[0070] It should be noted that step S400 includes step S410, step S420, step S430 and step S440.

[0071] Step S410: performing scene analysis processing according to the fifth information, defining different simulation scenes and performing parameterized processing on the scenes to simulate different crowd flows and revolving door operation conditions to obtain fourteenth information, the fourteenth information being a simulation scene set;

[0072] It is understandable that the parameterization process aims to make specific settings and adjustments to the relevant factors in each scenario so as to accurately simulate different passenger flows and revolving door operating conditions.

[0073] Step S420: performing pattern recognition processing on the fourteenth information based on a preset hidden Markov model, and obtaining fifteenth information by identifying implicit states and transition probabilities of crowd behaviors in different scenarios, wherein the fifteenth information is a recognition result of a crowd behavior pattern;

[0074] It should be noted that the hidden Markov model is a statistical model used to model time series data. Its characteristics are that it can handle the relationship between the observation sequence and the state sequence, and infer the hidden state sequence through the observation sequence. In the model, different simulation scenarios are regarded as different observation sequences, and the state of crowd behavior is the implicit state sequence. Then, by analyzing the observation sequence and using the parameter estimation method of the hidden Markov model, the implicit state of crowd behavior and the transition probability between states are inferred, so as to better understand the regularity and characteristics of crowd behavior.

[0075] Step S430: constructing a social simulation framework according to the fifteenth information, and obtaining sixteenth information by simulating the interaction and behavior of individuals in space, wherein the sixteenth information is a social simulation model;

[0076] It should be noted that social simulation is a computer simulation-based method used to simulate the dynamic evolution of human behavior and social systems. Specifically, first, according to the crowd behavior pattern obtained in the fifteenth information, different behavior states are mapped to the simulation model. These behavior states include the direction, speed, density, etc. of human movement. Then, using computer simulation technology, a virtual simulation environment is constructed in space, and virtual characters representing individuals are placed in it. These virtual characters will interact and move according to the preset behavioral rules and the behavioral patterns in the fifteenth information. By simulating the interaction and behavior of individuals in space, the dynamic changes and mutual influence of crowds in different scenarios can be observed.

[0077] Step S440: Run the simulation engine and perform statistical analysis according to the sixteenth information, and extract the average waiting time, traffic efficiency and safety index to obtain the sixth information.

[0078] It can be understood that the average waiting time refers to the average time people wait to pass through the revolving door; the traffic efficiency refers to the speed and efficiency of the revolving door passing the flow of people; the safety index involves the triggering of the anti-pinch safety sensor and the use of the emergency passage, etc.

[0079] It should be noted that step S500 includes step S510, step S520, step S530 and step S540.

[0080] Step S510: construct an objective function according to the sixth information, quantify and integrate the importance of each objective through multi-criteria decision analysis, and obtain seventeenth information, which is an initial objective function for optimization;

[0081] This objective function will serve as the basis for optimization in the subsequent optimization process to guide the adjustment and optimization of the revolving door system parameters, so that the system can achieve the best balance in terms of traffic efficiency, safety and user experience.

[0082] Step S520, performing sensitivity analysis processing according to the seventeenth information and the fourth information, identifying key design parameters by quantifying the influence of each design parameter on the initial objective function using the Sobol index method to obtain eighteenth information, the eighteenth information being the sensitivity analysis result;

[0083] It should be noted that the Sobol index method is a method for quantifying the impact of multiple parameters, which can accurately identify the key design parameters that contribute most to the objective function. In this process, the relationship between the objective function and each design parameter is mathematically modeled, and the first-order partial derivative of each design parameter is calculated. Next, the Sobol index method is used to calculate and quantify the first-order partial derivatives of each design parameter. These first-order partial derivatives show the contribution of each design parameter to the objective function, thereby determining which parameters have the greatest impact on system performance. Finally, based on the calculation results, the key design parameters with the most significant impact are identified, and these parameters will become the focus of adjustment in the subsequent optimization process. The calculation formula is:

[0084]

[0085] Where F represents the objective function, x i 、x j represents the design parameters, n represents the total number of design parameters, i and j represent the serial numbers of the design parameters, ε i represents the design parameter x i The first-order partial derivative of .

[0086] Step S530, performing mathematical programming processing according to the seventeenth information and the eighteenth information, converting the multi-objective optimization into a composite objective function by using a Pareto optimal algorithm, and establishing constraints of the optimization problem according to design and operation restrictions to obtain nineteenth information, wherein the nineteenth information is a mathematical expression of the optimization problem including the objective function and the constraints;

[0087] It should be noted that the Pareto optimal algorithm does not depend on the specific form of the problem and is applicable to various types of multi-objective optimization problems. In the design of revolving door systems, there are complex constraints and multiple decision variables. Traditional single-objective optimization methods may not be able to effectively handle this complexity. The Pareto optimal algorithm can overcome these challenges and find better solutions by effectively exploring the solution space and based on the diversity of objective functions and constraints. The formula involved is:

[0088] G(x)=w1·F1(x)+w2·F2(x)+w3·F3(x)+C(x);

[0089] Among them, G(x) represents the compliance objective function, x represents the design parameter vector, F1(x) represents the traffic efficiency objective function, F2(x) represents the safety objective function, F3(x) represents the energy consumption index objective function, C(x) represents the constraint condition, w1, w2 and w3 represent the traffic efficiency weight, safety weight and energy consumption weight respectively.

[0090] Step S540: performing optimization processing according to the nineteenth information, searching the optimal solution space by using a multi-objective genetic algorithm, and extracting a parameter combination that meets the design requirements to obtain an optimized design parameter combination.

[0091] It should be noted that step S540 includes step S541, step S542, step S543, step S544 and step S545.

[0092] Step S541, performing population initialization processing according to the nineteenth information to obtain an initial population, each individual in the initial population represents a possible combination of revolving door design parameters;

[0093] like Figure 3 As shown, in this step, according to the mathematical expression of the optimization problem defined in the nineteenth information, a set of possible combinations of revolving door design parameters needs to be generated to construct an initial population. Specifically, firstly, by considering the value range and constraints of the design parameters, the feasible value range of each design parameter can be determined. For example, the size requirements of the revolving door, the drive system parameters, and the layout scheme of the sensor. Then, according to these value ranges, a certain number of design parameter combinations can be randomly generated as individuals of the initial population. When generating the initial population, it is necessary to ensure the diversity and coverage of the individuals to fully explore the solution space. This can be achieved through methods such as random generation and uniform distribution. At the same time, it is necessary to ensure that the generated design parameter combinations meet the design requirements and constraints, such as not violating the size and safety requirements of the revolving door.

[0094] Step S542: Perform fitness calculation processing according to the initial population, and obtain the individual fitness value by calculating the objective function value of each individual;

[0095] The higher the fitness value, the higher the superiority of the individual in the solution space, that is, its design parameter combination is closer to the optimal solution.

[0096] Step S543, performing selection, crossover and mutation operations according to individual fitness values ​​to obtain a new generation population;

[0097] It can be understood that this step achieves the evolution and optimization of the population by simulating natural phenomena such as natural selection, inheritance and mutation.

[0098] Step S544, performing fitness evaluation and convergence test processing according to the new generation population, and iterating to obtain the final population;

[0099] This step can effectively monitor the convergence of the optimization algorithm through fitness evaluation and convergence test processing, and ensure that the algorithm can find a better solution within a limited number of iterations.

[0100] Step S545: extract the optimal solution according to the final population, and verify the anti-pinch performance to obtain the optimized design parameter combination.

[0101] It should be noted that the anti-pinch performance verification includes using simulation software to simulate the pedestrian passage process, verifying the anti-pinch performance of the revolving door under normal use, and conducting field tests to verify the anti-pinch effect of the revolving door in various scenarios. The verification results will be used to evaluate the actual effect and feasibility of the optimized design parameter combination.

[0102] It should be noted that step S545 includes step S5451, step S5452, step S5453 and step S5454.

[0103] Step S5451, performing sorting processing according to the final population, and obtaining a non-dominated solution set by identifying mutually non-dominated solution sets in multiple objective functions using a non-dominated sorting algorithm;

[0104] It can be understood that through the non-dominated sorting algorithm, a set of solutions that are non-dominated among multiple objective functions is identified, that is, solutions that cannot improve the value of one objective function without compromising the values ​​of other objective functions. These solutions are considered optimal because they have no obvious room for improvement between multiple objectives. These solutions represent the best individuals in the population and have good performance on multiple objective functions.

[0105] Step S5452: perform distance calculation and crowding evaluation processing on all individuals in the non-dominated solution set to obtain an optimized solution set;

[0106] The distance between each individual in the non-dominated solution set is calculated. Common distance measurement methods include Euclidean distance, Manhattan distance, etc. These distance metrics can help evaluate the degree of dispersion between individuals, that is, the distribution in the solution space. For each individual, the crowding degree of other individuals around it is calculated, that is, the density of solutions around the individual. The crowding degree evaluation aims to maintain the diversity of the population so that the individuals in the optimal solution set have both good dispersion and high fitness.

[0107] Step S5453, performing weight distribution processing according to the optimized solution set to obtain the optimal solution set;

[0108] The optimal solution set obtained in this step has individuals with the best comprehensive performance and can effectively balance the trade-offs between various optimization objectives.

[0109] Step S5454: simulate the anti-pinch performance according to the optimal solution set, verify whether the anti-pinch performance of the selected optimal solution in actual use meets the safety standards through simulation based on sensor feedback, and obtain the verification result, and extract the optimized design parameter combination based on the verification result.

[0110] It should be noted that the anti-pinch performance simulation uses simulation tools or virtual environments to simulate various scenarios that may occur in the actual operation of the revolving door, including pedestrian entry and exit, traffic congestion, emergencies, etc. During the simulation process, by setting different parameter combinations, the operation of the revolving door is observed and tested in all directions to verify its anti-pinch performance; the simulation verification based on sensor feedback is to combine the feedback information of the sensor to monitor and analyze the operation of the revolving door in the simulation environment in real time. Through the data fed back by the sensor, the operating status of the revolving door in different situations can be evaluated, including whether the functions such as pinch detection and speed adjustment are working normally, so as to verify whether its anti-pinch performance meets the safety standards.

[0111] Embodiment 2:

[0112] This embodiment provides an optimization design device for a revolving door, the device comprising:

[0113] an acquisition module, configured to acquire first information, second information and third information, wherein the first information includes initial structural features and parameter information of the revolving door, the second information includes architectural layout, crowd distribution and passage path information of the revolving door installation site, and the third information includes historical passage data;

[0114] A construction module, configured to perform three-dimensional modeling and parameter setting processing according to the first information, so as to construct fourth information, wherein the fourth information is a three-dimensional structural model of the revolving door including design parameters and performance indicators;

[0115] A simulation module, configured to simulate the pedestrian traffic situation according to the second information, the third information and the fourth information, and obtain fifth information by introducing pedestrian congestion and traffic failure, wherein the fifth information is a pedestrian traffic scenario simulation result;

[0116] A simulation module, configured to perform social simulation processing on the fifth information to obtain sixth information, wherein the sixth information includes crowd flow distribution and corresponding traffic conditions in different scenarios;

[0117] An optimization module is used to perform multi-objective optimization processing according to the sixth information and the fourth information, and obtain an optimized design parameter combination by combining traffic efficiency, safety and energy consumption indicators. The optimized design parameter combination includes the size requirements of the revolving door, drive system parameters and sensor layout plan.

[0118] Embodiment 3:

[0119] Corresponding to the above method embodiment, this embodiment also provides an optimization design device for a revolving door. The optimization design device for a revolving door described below and the optimization design method for a revolving door described above can refer to each other.

[0120] Figure 2 8 is a block diagram of an optimization design device 800 for a revolving door according to an exemplary embodiment. Figure 2 As shown, the revolving door optimization design device 800 may include: a processor 801 and a memory 802. The revolving door optimization design device 800 may also include one or more of a multimedia component 803, an I / O interface 804, and a passage component 805.

[0121] The processor 801 is used to control the overall operation of the revolving door optimization design device 800 to complete all or part of the steps in the above-mentioned revolving door optimization design method. The memory 802 is used to store various types of data to support the operation of the revolving door optimization design device 800, and these data may include, for example, instructions for any application or method operated on the revolving door optimization design device 800, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 802 or sent through the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules can be keyboards, mice, buttons, etc. These buttons can be virtual buttons or physical buttons. The access component 805 is used for wired or wireless access between the revolving door optimization design device 800 and other devices. Wireless access, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding access component 805 can include: Wi-Fi module, Bluetooth module, NFC module.

[0122] In an exemplary embodiment, the revolving door optimization design device 800 can be implemented by one or more application specific integrated circuits (Application Specific Integrated Circuit, referred to as ASIC), digital signal processors (Digital Signal Processor, referred to as DSP), digital signal processing devices (Digital Signal Processing Device, referred to as DSPD), programmable logic devices (Programmable Logic Device, referred to as PLD), field programmable gate arrays (Field Programmable Gate Array, referred to as FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned revolving door optimization design method.

[0123] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned revolving door optimization design method are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 802 including program instructions, and the above-mentioned program instructions can be executed by the processor 801 of the revolving door optimization design device 800 to complete the above-mentioned revolving door optimization design method.

[0124] Embodiment 4:

[0125] Corresponding to the above method embodiment, a readable storage medium is also provided in this embodiment. The readable storage medium described below and the optimization design method of a revolving door described above can refer to each other.

[0126] A readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the revolving door optimization design method of the above method embodiment.

[0127] The readable storage medium may specifically be a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or other readable storage medium that can store program codes.

[0128] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0129] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for optimizing the design of a revolving door, characterized in that: include: Acquire first information, second information and third information, wherein the first information includes initial structural features and parameter information of the revolving door, the second information includes architectural layout, crowd distribution and passage path information of the revolving door installation site, and the third information includes historical passage data; Performing three-dimensional modeling and parameter setting processing according to the first information to construct fourth information, wherein the fourth information is a three-dimensional structural model of the revolving door including design parameters and performance indicators; Performing pedestrian traffic simulation processing according to the second information, the third information and the fourth information, and obtaining fifth information by introducing pedestrian congestion and traffic failure, wherein the fifth information is a result of pedestrian traffic scenario simulation; Performing social simulation processing on the fifth information to obtain sixth information, wherein the sixth information includes crowd flow distribution and corresponding traffic conditions in different scenarios; Performing multi-objective optimization processing according to the sixth information and the fourth information, and obtaining an optimized design parameter combination by combining traffic efficiency, safety and energy consumption indicators, wherein the optimized design parameter combination includes size requirements of the revolving door, drive system parameters and sensor layout scheme; The sixth information is obtained by performing social simulation processing according to the fifth information, and the sixth information includes the distribution of crowds in different scenarios and the corresponding traffic conditions, including: Performing scene analysis processing according to the fifth information, defining different simulation scenes and performing parameterized processing on the scenes to simulate different crowd flows and revolving door operation conditions to obtain fourteenth information, wherein the fourteenth information is a set of simulation scenes; Performing pattern recognition processing on the fourteenth information based on a preset hidden Markov model, and obtaining fifteenth information by identifying implicit states and transition probabilities of crowd behaviors in different scenarios, wherein the fifteenth information is a recognition result of a crowd behavior pattern; Performing social simulation framework construction processing according to the fifteenth information, and obtaining sixteenth information by simulating the interaction and behavior of individuals in space, wherein the sixteenth information is a social simulation model; According to the sixteenth information, a simulation engine is run and statistical analysis is performed, and average waiting time, traffic efficiency and safety index are extracted to obtain sixth information; Wherein, a multi-objective optimization process is performed according to the sixth information and the fourth information, and an optimized design parameter combination is obtained by combining traffic efficiency, safety and energy consumption indicators, wherein the optimized design parameter combination includes the size requirements of the revolving door, the drive system parameters and the layout scheme of the sensor, including: Performing objective function construction processing according to the sixth information, quantifying and integrating the importance of each objective through multi-criteria decision analysis, and obtaining seventeenth information, wherein the seventeenth information is an initial objective function for optimization; Performing sensitivity analysis processing according to the seventeenth information and the fourth information, identifying key design parameters by quantifying the influence of each design parameter on the initial objective function using the Sobol index method, and obtaining eighteenth information, wherein the eighteenth information is a sensitivity analysis result; Performing mathematical programming processing according to the seventeenth information and the eighteenth information, converting the multi-objective optimization into a composite objective function by using a Pareto optimal algorithm, and establishing constraints of the optimization problem according to design and operation restrictions to obtain nineteenth information, wherein the nineteenth information is a mathematical expression of the optimization problem including the objective function and the constraints; An optimization process is performed according to the nineteenth information, an optimal solution space is searched by using a multi-objective genetic algorithm, and a parameter combination that meets the design requirements is extracted to obtain an optimized design parameter combination.

2. The optimization design method of a revolving door according to claim 1, characterized in that: Performing three-dimensional modeling and parameter setting processing according to the first information to construct fourth information includes: Performing parameterized modeling processing on the first information to obtain seventh information, wherein the seventh information is a geometric model of the revolving door; Performing finite element mesh processing on the seventh information to obtain eighth information, wherein the eighth information includes a finite element mesh model of the revolving door; Performing modal-stiffness analysis processing on the eighth information to obtain ninth information, wherein the ninth information includes dynamic characteristics and static strength data of the revolving door; Performing sensitivity analysis processing according to the ninth information, and obtaining tenth information by calculating the influence of the design variables on the performance index of the revolving door, wherein the tenth information is sensitivity data of the revolving door design parameters; The ninth information and the tenth information are integrated into the seventh information to obtain the fourth information.

3. The optimization design method of a revolving door according to claim 1, characterized in that: Performing pedestrian traffic simulation processing according to the second information, the third information, and the fourth information, and obtaining fifth information by introducing pedestrian congestion and traffic failure conditions, including: Performing crowd flow simulation processing according to the second information, obtaining eleventh information by creating pedestrians representing different ages, genders and clothing and assigning preset behavior rules, wherein the eleventh information is a basic model for crowd flow simulation; Performing pattern recognition processing according to the third information, obtaining twelfth information by identifying peak traffic hours, common congestion points, and past pedestrian pinching incidents, wherein the twelfth information includes pedestrian traffic patterns and potential anti-pinch risk points; Predictive processing is performed based on the eleventh information and the twelfth information, and the thirteenth information is obtained by simulating pedestrian behavior changes under different circumstances by using a probability model and predicting the influence of the passage failure on the operation of the revolving door in combination with the fault tree analysis, wherein the thirteenth information is a simulation result under the circumstances of pedestrian congestion and passage failure; Anti-pinch optimization simulation processing is performed based on the thirteenth information and the fourth information, and the fifth information is obtained by predicting the response of the sensor and the operation adjustment of the revolving door in combination with the pedestrian's body shape, movement speed and clothing thickness factors.

4. The optimization design method of a revolving door according to claim 1, characterized in that: According to the nineteenth information, optimization processing is performed, and the optimal solution space is searched by using a multi-objective genetic algorithm, and the parameter combination that meets the design requirements is extracted to obtain the optimized design parameter combination, including: Performing population initialization processing according to the nineteenth information to obtain an initial population, wherein each individual of the initial population represents a possible combination of revolving door design parameters; Performing fitness calculation processing according to the initial population, and obtaining an individual fitness value by calculating the objective function value of each individual; Perform selection, crossover and mutation operations according to the individual fitness values ​​to obtain a new generation of population; Performing fitness evaluation and convergence test processing according to the new generation population, iteratively obtaining a final population; The optimal solution extraction process is performed based on the final population, and the anti-pinch performance is verified to obtain the optimized design parameter combination.

5. The optimization design method of a revolving door according to claim 4, characterized in that: The optimal solution is extracted based on the final population, and the anti-pinch performance is verified to obtain an optimized design parameter combination, including: Sorting the final population, identifying mutually non-dominated solution sets in a plurality of objective functions by using a non-dominated sorting algorithm to obtain a non-dominated solution set; Perform distance calculation and crowding evaluation processing on all individuals in the non-dominated solution set to obtain an optimized solution set; Performing weight distribution processing according to the optimized solution set to obtain an optimal solution set; The anti-pinch performance is simulated according to the optimal solution set, and a verification result is obtained by verifying whether the anti-pinch performance of the selected optimal solution in actual use meets the safety standards through simulation based on sensor feedback, and an optimized design parameter combination is extracted based on the verification result.

6. An optimized design device for a revolving door, characterized in that: include: an acquisition module, configured to acquire first information, second information and third information, wherein the first information includes initial structural features and parameter information of the revolving door, the second information includes architectural layout, crowd distribution and passage path information of the revolving door installation site, and the third information includes historical passage data; A construction module, configured to perform three-dimensional modeling and parameter setting processing according to the first information, so as to construct fourth information, wherein the fourth information is a three-dimensional structural model of the revolving door including design parameters and performance indicators; A simulation module, configured to simulate the pedestrian traffic situation according to the second information, the third information and the fourth information, and obtain fifth information by introducing pedestrian congestion and traffic failure, wherein the fifth information is a pedestrian traffic scenario simulation result; A simulation module, configured to perform social simulation processing on the fifth information to obtain sixth information, wherein the sixth information includes crowd flow distribution and corresponding traffic conditions in different scenarios; an optimization module, configured to perform multi-objective optimization processing according to the sixth information and the fourth information, and obtain an optimized design parameter combination by combining traffic efficiency, safety and energy consumption indicators, wherein the optimized design parameter combination includes size requirements of the revolving door, drive system parameters and sensor layout scheme; Wherein, the simulation module includes: a first processing unit, configured to perform scene analysis processing according to the fifth information, and obtain fourteenth information by defining different simulation scenes and performing parameterized processing on the scenes to simulate different crowd flows and revolving door operation conditions, wherein the fourteenth information is a set of simulation scenes; a first recognition unit, performing pattern recognition processing on the fourteenth information based on a preset hidden Markov model, and obtaining fifteenth information by recognizing implicit states and transition probabilities of crowd behaviors in different scenarios, wherein the fifteenth information is a recognition result of a crowd behavior pattern; a first construction unit, configured to construct a social simulation framework according to the fifteenth information, and obtain sixteenth information by simulating the interaction and behavior of individuals in space, wherein the sixteenth information is a social simulation model; a first extraction unit, configured to perform simulation engine operation and statistical analysis processing according to the sixteenth information, and extract average waiting time, traffic efficiency and safety index to obtain sixth information; Wherein, the optimization module includes: A first construction unit is used to perform objective function construction processing according to the sixth information, quantify and integrate the importance of each objective through multi-criteria decision analysis, and obtain seventeenth information, wherein the seventeenth information is an initial objective function for optimization; A first analysis unit is used to perform sensitivity analysis processing according to the seventeenth information and the fourth information, and identify key design parameters by quantifying the influence of each design parameter on the initial objective function using the Sobol index method to obtain eighteenth information, wherein the eighteenth information is a sensitivity analysis result; a first planning unit, configured to perform mathematical planning processing according to the seventeenth information and the eighteenth information, by converting the multi-objective optimization into a composite objective function using a Pareto optimal algorithm, and establishing constraints of the optimization problem according to design and operation constraints to obtain nineteenth information, wherein the nineteenth information is a mathematical expression of the optimization problem including the objective function and the constraints; The first optimization unit is used to perform optimization processing according to the nineteenth information, search the optimal solution space by using a multi-objective genetic algorithm, and extract the parameter combination that meets the design requirements to obtain the optimized design parameter combination.

7. An optimization design device for a revolving door, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the revolving door optimization design method as claimed in any one of claims 1 to 5 when executing the computer program.

8. A medium, characterized in that: The medium stores a computer program, which, when executed by a processor, implements the steps of the method for optimizing the design of a revolving door as claimed in any one of claims 1 to 5.

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