Indoor ecological environment design method and system based on digital twinning and storage medium

Abstract

The invention discloses an indoor ecological environment design method and system based on digital twinning and a storage medium, and relates to the technical field of indoor environment design. According to the indoor ecological environment design method based on digital twinning, an indoor digital twinning model including a space structure, material attributes and equipment layout is constructed, ecological environment data is periodically acquired and updated, and a comprehensive ecological state index is analyzed and generated; and when the indexes deviate from a preset interval, multi-scheme regulation and control simulation is executed in the twin model, equipment is driven to execute after standard reaching schemes are screened, and accurate recognition and stable regulation and control of ecological abnormities are achieved. And a comprehensive ecological state index is constructed, so that unified quantitative evaluation of the indoor ecological environment is realized, the problem of existing sensing data splitting is solved, and the normalization, accuracy and cross-scene applicability of ecological judgment are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of indoor environment design, and specifically to an indoor ecological environment design method, system and storage medium based on digital twins. Background Art

[0002] With the acceleration of urbanization and the improvement of living environment quality requirements, indoor ecological environment has become an important focus of building design and operation management. Traditional indoor environmental control systems mainly rely on air conditioning, fresh air, lighting and other equipment to independently adjust temperature, humidity, air quality and light environment, usually based on threshold setting or simple feedback mechanism. It is difficult to achieve coordinated optimization among multi-dimensional environmental elements, and it is also difficult to reflect the impact of building structure, material properties and space use on environmental conditions.

[0003] In recent years, with the development of technologies such as the Internet of Things, sensor networks, and building information models (BIM), the application of digital twins in the construction field has gradually expanded. Digital twins can map the physical structure, equipment layout, and dynamic environmental data of real spaces into virtual models, realize the full-cycle, real-time visualization and simulation prediction of building spaces, and provide new technical support for intelligent environmental management. In the field of indoor environmental control, studies have attempted to combine digital twins with building energy consumption simulation, air flow analysis, and other technologies to carry out intelligent system design for energy-saving regulation and comfort improvement.

[0004] Existing technologies include the indoor ecological environment design method, system and storage medium based on digital twins disclosed in the invention patent application with publication number: CN118364721A. The main technical solution of this application is: collecting indoor three-dimensional space environment data; building an indoor digital twin model based on the three-dimensional space environment data, and the digital twin model is used to simulate the indoor ecological environment in the whole cycle; determining the target environment design strategy in the digital twin model according to the preset user needs; and dynamically controlling the indoor smart devices using the target environment design strategy. The main purpose of this application is to accurately simulate the real indoor ecological environment and improve the quality of indoor ecological environment design.

[0005] Based on the above scheme, it is found that the limitations of the existing technology include at least the following problems. When formulating indoor ecological environment control strategies, the existing technology generally lacks a pre-control simulation verification mechanism, that is, once the control strategy is generated, it is directly sent to the equipment system for execution, and its environmental response effect is not predicted and evaluated based on the digital twin model before execution. This method can easily lead to uncontrollable control behavior results, especially under the interaction of multi-source physical factors, such as spatial thermal and humidity inertia, air flow path and material thermal response. The control results may deviate significantly from expectations. In addition, the strategy is directly applied without simulation verification, which can easily cause drastic fluctuations in the indoor ecological state, increased energy consumption or decreased user experience. Long-term operation may also cause reduced system stability and the risk of strategy failure. More importantly, the lack of a simulation evaluation mechanism makes it difficult for the system to achieve closed-loop optimization of the control logic, and it is also difficult to learn strategies and improve accuracy based on historical execution results. Summary of the invention

[0006] In response to the shortcomings of the existing technology, the present invention provides an indoor ecological environment design method, system and storage medium based on digital twins, which solves the problem that the existing technology lacks a simulation verification mechanism before the execution of the ecological control strategy, which easily leads to unpredictable control results and unstable execution effects.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: an indoor ecological environment design method based on digital twins, comprising the following steps: obtaining spatial structure data, building material data, and equipment layout data of the indoor space, and establishing a digital twin model of the indoor space; based on a set time period, obtaining the ecological environment data of the indoor space at intervals, and updating it to the digital twin model of the indoor space; based on the ecological environment data in the digital twin model of the indoor space, analyzing the comprehensive ecological status index of the indoor space, and performing judgment and analysis with a preset ecological status assessment interval; when the comprehensive ecological status index of the indoor space is outside the preset ecological status assessment interval, it is regarded as an abnormal ecological status of the indoor space, and an ecological regulation simulation analysis is performed in the digital twin model of the indoor space; when the results of the ecological regulation simulation analysis meet the expected standards, ecological regulation measures are taken for the indoor space.

[0008] Furthermore, the ecological environment data includes comfort perception data, air load data, and environmental regeneration data. The specific steps for analyzing the comprehensive ecological status index of the indoor space based on the ecological environment data in the digital twin model of the indoor space are as follows: based on the comfort perception data, air load data, and environmental regeneration data in the digital twin model of the indoor space, analyze the ecological environment index set of the indoor space, the ecological environment index set including the space comfort index, air load index, and ecological restoration index; conduct a comprehensive analysis of the ecological environment index set of the indoor space to obtain the comprehensive ecological status index of the indoor space.

[0009] Furthermore, the specific formula for calculating the comprehensive ecological status index of indoor space is as follows: ;in, is the comprehensive ecological status index of the indoor space. is the spatial comfort index of the indoor space, is the space comfort adjustment coefficient stored in the database, is the air load index of the indoor space, is the air load adjustment factor stored in the database, is the ecological restoration index of indoor space, It is the ecological restoration adjustment coefficient stored in the database.

[0010] Furthermore, the comfort perception data includes indoor temperature values, indoor humidity values, and indoor light intensity values. The specific steps for analyzing the spatial comfort index of the indoor space are as follows: obtain a comfort perception parameter set and a comfort perception allowable deviation set of the indoor space, wherein the comfort perception parameter set includes indoor temperature parameter values, indoor humidity parameter values, and indoor light intensity parameter values, and the comfort perception allowable deviation set includes a maximum allowable deviation of indoor temperature, a maximum allowable deviation of indoor humidity, and a maximum allowable deviation of indoor light intensity; comprehensively analyze the comfort perception data in the digital twin model of the indoor space, combined with the comfort perception parameter set and the comfort perception allowable deviation set of the indoor space, to obtain the spatial comfort index of the indoor space.

[0011] Furthermore, the air load data includes indoor carbon dioxide concentration values, indoor particulate matter concentration values, indoor volatile organic compound concentration values, and indoor wind speed values. The specific steps for analyzing the air load index of the indoor space are as follows: obtain the air load parameter set of the indoor space, and the air load parameter set includes indoor carbon dioxide concentration parameter values, indoor particulate matter concentration parameter values, indoor volatile organic compound concentration parameter values, and indoor wind speed parameter values; comprehensively analyze the air load data in the digital twin model of the indoor space in combination with the air load parameter set of the indoor space to obtain the air load index of the indoor space.

[0012] Furthermore, the specific formula for calculating the air load index of the indoor space is as follows: ;in, is the air load index of the indoor space, is the indoor carbon dioxide concentration value in the digital twin model of the indoor space, is the reference value of indoor carbon dioxide concentration in indoor space, is the indoor particulate matter concentration value in the digital twin model of the indoor space, is the indoor particulate matter concentration parameter value of the indoor space, is the indoor volatile organic compound concentration value in the digital twin model of the indoor space, is the reference value of indoor volatile organic compound concentration in indoor space, is the pollutant concentration adjustment coefficient stored in the database, is the indoor wind speed value in the digital twin model of the indoor space, is the indoor wind speed parameter value of the indoor space, It is the wind speed adjustment coefficient stored in the database.

[0013] Furthermore, the environmental regeneration data includes the transpiration rate value of indoor plants and the thermal lag time of walls. The specific steps for analyzing the ecological restoration index of indoor space are as follows: obtaining the maximum allowable thermal lag parameter value of indoor space; comprehensively analyzing the environmental regeneration data in the digital twin model of indoor space in combination with the maximum allowable thermal lag parameter value of indoor space to obtain the ecological restoration index of indoor space.

[0014] Furthermore, the specific steps for conducting ecological regulation simulation analysis in the digital twin model of indoor space are as follows: based on the comprehensive ecological status index of indoor space, identify abnormal factor sets and use them as factors to be regulated; construct several groups of controllable factor combinations, each group is a type of strategy configuration; initialize the regulation simulation process in the digital twin model of indoor space; execute regulation scheme simulation in parallel in the digital twin model of indoor space, and screen the optimal regulation simulation results.

[0015] The indoor ecological environment design system based on digital twins includes: a model building unit, which is used to obtain spatial structure data, building material data, and equipment layout data of the indoor space, and establish a digital twin model of the indoor space; an acquisition and update unit, which is used to obtain the ecological environment data of the indoor space at intervals based on a set time period, and update it to the digital twin model of the indoor space; an ecological environment analysis unit, which is used to analyze the comprehensive ecological status index of the indoor space based on the ecological environment data in the digital twin model of the indoor space; an ecological environment judgment unit, which is used to judge and analyze the comprehensive ecological status index of the indoor space with a preset ecological status assessment interval; a simulation analysis unit, which is used to regard the ecological status of the indoor space as abnormal when the comprehensive ecological status index of the indoor space is outside the preset ecological status assessment interval, and to perform ecological regulation simulation analysis in the digital twin model of the indoor space; an ecological regulation unit, which is used to take ecological regulation measures for the indoor space when the results of the ecological regulation simulation analysis meet the expected standards.

[0016] A computer-readable storage medium is used to store a program, which, when executed by a processor, implements the indoor ecological environment design method based on digital twins as described above.

[0017] The present invention has the following beneficial effects: (1) This indoor ecological environment design method based on digital twins introduces three types of ecological indicators, namely, space comfort index, air load index and ecological restoration index. Independent calculation models are established based on indoor temperature, humidity and light parameters, pollutant concentration and wind speed parameters, plant transpiration rate and thermal hysteresis parameters, and a comprehensive ecological status index is further constructed to uniformly measure the overall ecological status of the indoor environment. This structure overcomes the problem of fragmentation of various types of perception data and difficulty in uniformly evaluating the degree of ecological quality in the existing technology. It has good indicator normalization and comparability. It can perform quantitative calculations based on the actual value of each index and the adjustment coefficient stored in the database, and supports consistent judgment of the ecological status under different functional rooms and different building structure conditions, thereby improving the integrity, logic and cross-scenario applicability of the ecological environment evaluation.

[0018] (2) After detecting an abnormality in the comprehensive ecological status index, the indoor ecological environment design method based on digital twins does not directly execute the control strategy. Instead, it first conducts ecological control simulation analysis in the digital twin model, performs virtual execution on multiple control parameter combinations, calculates their expected impact values ​​on various ecological status indicators, and screens out strategy solutions that meet the set standards before issuing actual control instructions. This mechanism effectively solves the problems of lack of pre-execution verification of control strategies, uncertainty in control effects, and deviation of control results from expectations in existing technologies. Through pre-control simulation calculation and standard screening mechanism, invalid or excessive regulation can be avoided, the stability of the control process and the clarity of the execution goals are improved, and a basic support is provided for establishing a traceable data chain between subsequent control behaviors and changes in ecological status.

[0019] (3) The indoor ecological environment design method based on digital twin collects the ecological environment data of the indoor space at intervals according to a preset time period, and continuously and dynamically updates it to the digital twin model to form a real-time synchronized multi-parameter environmental state field. During operation, this mechanism can dynamically obtain the changing trends of parameters such as temperature and humidity, air pollution concentration, and wind speed fluctuations, and construct an ecological index evolution trajectory based on actual time series data. Compared with the single sampling or staged measurement method commonly used in existing technologies, it realizes the continuity of ecological perception and the timeliness of model-driven, providing a more accurate and real-time data basis for subsequent ecological status judgment and regulation simulation. At the same time, this mechanism can also be used to analyze the ecological response delay and trend feedback after the execution of regulatory behavior, providing quantitative support for strategy optimization.

[0020] (4) The indoor ecological environment design system based on digital twin can realize a complete closed-loop process from indoor space physical modeling, dynamic collection of environmental data, ecological status calculation and analysis, regulation simulation evaluation to intelligent control execution. Each functional unit has relatively independent input and output logic. It can support the replacement, expansion or upgrade of different modules while maintaining the consistency of the overall data flow, improve the adaptability of the system to be deployed in different space types and hardware platforms, and establish a logical condition trigger mechanism between the ecological environment judgment unit and the simulation analysis unit, realizing the explicit decoupling of the judgment and execution process of the regulation behavior, ensuring that the system has a structural-level logical error-proofing capability between the control behavior generation and the result feedback, thereby enhancing the stability, flexibility and engineering maintainability of the ecological environment management system in engineering applications.

[0021] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of the indoor ecological environment design method based on digital twins of the present invention.

[0023] Figure 2 It is a line graph of the comprehensive ecological status index of the indoor space in six time periods in the indoor ecological environment design method based on digital twins of the present invention.

[0024] Figure 3 This is a flowchart of the specific steps for analyzing the spatial comfort index of indoor space in the indoor ecological environment design method based on digital twins of the present invention.

[0025] Figure 4 This is a system block diagram of the indoor ecological environment design based on digital twins of the present invention. DETAILED DESCRIPTION

[0026] See also Figure 1, the embodiment of the present invention provides a technical solution: an indoor ecological environment design method based on digital twins, comprising the following steps: obtaining spatial structure data, building material data, and equipment layout data of the indoor space, and establishing a digital twin model of the indoor space; based on a set time period (for example, five minutes), obtaining the ecological environment data of the indoor space at intervals, and updating it to the digital twin model of the indoor space; based on the ecological environment data in the digital twin model of the indoor space, analyzing the comprehensive ecological status index of the indoor space, and performing judgment analysis with a preset ecological status evaluation interval; when the comprehensive ecological status index of the indoor space is outside the preset ecological status evaluation interval, it is regarded as an abnormal ecological status of the indoor space, and an ecological regulation simulation analysis is performed in the digital twin model of the indoor space; when the results of the ecological regulation simulation analysis meet the expected standards, taking ecological regulation measures for the indoor space, which are specifically: comparing whether the boundary conditions used in the simulation are still consistent with the real current environment (for example, whether there are changes such as personnel flow and opening of external windows); If the difference is less than the set threshold (e.g., environmental state error ≤ 5%), the simulation result is confirmed to be valid and the actual control process is allowed to proceed; Call the device interface mapping table corresponding to the twin model to identify the object to be regulated and the control authority (such as air conditioning equipment number, outlet number, humidifier port); Establish a control parameter conversion model between the control scheme and the actual equipment (for example, the simulated temperature is adjusted to 22°C - the control command is HVAC: Mode: Cooling, Setpoint: 22); Initialize the control instruction queue; Send control instructions to the space control subsystem in sequence or in parallel through the Internet of Things platform (such as BACnet, Modbus, KNX and other protocols); The execution status of each device is uploaded in real time, and the twin model dynamically updates the control execution status after receiving feedback; If a command fails or a response fails, the system automatically calls a backup plan or prompts for manual intervention; Start the control feedback monitoring module to collect the indoor key parameter change curve according to the control cycle (such as every minute); Recalculate the comprehensive ecological status index in real time; If the comprehensive ecological status index reaches the standard and remains stable for the preset time (e.g., the fluctuation is less than ±5% within 10 minutes), the control is confirmed to be successful; Write the control plan ID, execution time, control equipment response, post-control environment data, CESI change curve, etc. into the database; Establish a mapping record between the control behavior log and the control result for subsequent control strategy iteration and self-learning optimization; If the simulation plan deviates too much from the actual execution result, the plan is marked as simulation deviation type, which is used to eliminate or adjust the simulation model parameters.

[0027] Among them, the spatial structure data includes the length, width, height of the room and walls, and the opening distribution of doors and windows.

[0028] Building material data includes basic material types for walls / floors / windows (e.g. brick walls, glass, wooden doors).

[0029] Equipment layout data includes the locations of equipment such as air conditioners and lights (e.g., air outlets, air inlets, and light positions).

[0030] Specifically, the ecological environment data includes comfort perception data, air load data, and environmental regeneration data. The specific steps for analyzing the comprehensive ecological status index of the indoor space based on the ecological environment data in the digital twin model of the indoor space are as follows: based on the comfort perception data, air load data, and environmental regeneration data in the digital twin model of the indoor space, analyze the ecological environment index set of the indoor space, the ecological environment index set includes the space comfort index, air load index, and ecological restoration index; conduct a comprehensive analysis of the ecological environment index set of the indoor space to obtain the comprehensive ecological status index of the indoor space.

[0031] The specific formula for calculating the comprehensive ecological status index of indoor space is as follows: ;in, is the comprehensive ecological status index of the indoor space. is the spatial comfort index of the indoor space, is the space comfort adjustment coefficient stored in the database, is the air load index of the indoor space, is the air load adjustment factor stored in the database, is the ecological restoration index of indoor space, It is the ecological restoration adjustment coefficient stored in the database.

[0032] It should be explained that the spatial comfort adjustment coefficient stored in the database , Air load adjustment factor , Ecological Restoration Adjustment Coefficient The specific acquisition steps are as follows: first, extract the temperature, humidity, light level, CO 2The original environmental data such as concentration, air flow rate, plant transpiration rate, etc. are collected; then, combined with the actually calculated spatial comfort index, air load index, and ecological restoration index, multiple regression or neural network methods are used to establish a nonlinear mapping relationship between the adjustment factor and the index; finally, the sensitivity factors in the mapping relationship are extracted and normalized and stored in the database as the adjustment coefficients of the three dimensions of spatial comfort, air load, and ecological restoration.

[0033] The specific implementation example of calculating the comprehensive ecological status index of indoor space is as follows, and the following parameters are available: The spatial comfort index of the indoor space is approximately: 0.872.

[0034] The spatial comfort adjustment coefficient stored in the database is approximately: 0.944.

[0035] The air load index of the indoor space is approximately: 0.436.

[0036] The air load adjustment factor stored in the database is approximately: 0.762.

[0037] The ecological restoration index of indoor space is approximately: 0.524.

[0038] The ecological restoration adjustment coefficient stored in the database is approximately: 0.683.

[0039] Substituting the above data into the specific formula for calculating the comprehensive ecological status index of indoor space, we get: The comprehensive ecological status index of indoor space = (((0.832)^0.944)+ln(1+(0.436)^0.762))×exp(-((0.524)^0.683))≈0.803.

[0040] In addition, specific real-time examples of the comprehensive ecological status index of indoor space in several time periods are as follows. The comprehensive ecological status index of indoor space in six time periods is shown in Table 1 and Figure 2 As shown: Table 1 Examples of comprehensive ecological status index data of indoor spaces in six time periods In this implementation plan, by modeling the three types of ecological and environmental data, namely comfort perception, air load and environmental regeneration, as spatial comfort index, air load index and ecological restoration index respectively, and further constructing a comprehensive ecological status index based on the adjustment coefficient, the unified quantitative integration of multi-source heterogeneous environmental parameters is achieved. The system extracts the original environmental data of different spaces in multiple time periods, and combines it with the actual index output results. It uses algorithms such as multivariate regression or neural networks to construct a nonlinear mapping relationship between the adjustment factor and the index, extracts representative sensitivity factors from them and normalizes them, generates adjustment coefficients and stores them in the database. This mechanism not only enhances the model's adaptability to different building structures, spatial functions and usage scenarios, but also improves the weight expression and dynamic adjustment capabilities of each sub-index in the comprehensive calculation, ensuring that the index calculation results are targeted, adjustable and sensitive to environmental responses, providing a high-accuracy data basis and parameter support for subsequent ecological status judgment, anomaly identification and regulation simulation.

[0041] Specifically, if Figure 3 As shown, the comfort perception data includes indoor temperature value, indoor humidity value, and indoor light intensity value. The specific steps for analyzing the spatial comfort index of the indoor space are as follows: obtain the comfort perception parameter set and the comfort perception allowable deviation set of the indoor space, the comfort perception parameter set includes the indoor temperature parameter value, the indoor humidity parameter value, and the indoor light intensity parameter value, and the comfort perception allowable deviation set includes the maximum allowable deviation of the indoor temperature, the maximum allowable deviation of the indoor humidity, and the maximum allowable deviation of the indoor light intensity; comprehensively analyze the comfort perception data in the digital twin model of the indoor space, combined with the comfort perception parameter set and the comfort perception allowable deviation set of the indoor space, to obtain the spatial comfort index of the indoor space.

[0042] The indoor temperature value indicates the actual current indoor temperature value, which can be measured and obtained by a room temperature sensor.

[0043] The indoor humidity value indicates the current relative humidity of the indoor air and can be measured by a room humidity sensor.

[0044] The indoor light intensity value (current illuminance value) indicates the luminous flux per unit area and can be measured by a light intensity sensor.

[0045] The indoor temperature reference value refers to the ideal indoor temperature benchmark value set based on the current space function, usage scenario and human thermal comfort model. It can be determined according to international standards such as "GB / T 18883-2002 Indoor Air Quality Standard" or ASHRAE55, or it can be customized based on the nature of the building's use (such as 23°C for nursing homes and 22°C for classrooms).

[0046] The indoor humidity reference value refers to the target humidity value set to ensure human thermal comfort and air health. It is usually set at around 50% with reference to the ASHRAE comfort model, GB / T 18204 and other standards. It can be modified according to the function of the space (such as exhibition space, office area) or seasonal climate characteristics.

[0047] The indoor light intensity parameter value is the target illumination value used to ensure visual comfort and work efficiency. It is set according to the classification requirements for different functional spaces in the "GB50034-2013 Architectural Lighting Design Standard" (such as 150lux in corridors and 500lux in offices). It can be set at the building lighting design stage or dynamically configured by the lighting control system. It is usually written to the database during the initialization process of the digital twin model.

[0048] The maximum allowable deviation of indoor temperature indicates the acceptable temperature deviation range for users in a specific space. It usually depends on the human body's ability to adapt to the thermal environment (such as ±2°C). This value can be set by environmental experts' experience or obtained through long-term user behavior model learning.

[0049] The maximum allowable deviation of indoor humidity refers to the range of humidity variation that the human body or equipment can tolerate near the comfort reference value. It is usually set to ±10%. This range is determined based on environmental standards and human comfort models, and can also be expanded and adjusted due to space functions (such as archives, libraries) or regional humidity control requirements.

[0050] The maximum allowable deviation of indoor light intensity refers to the acceptable illuminance fluctuation range (such as ±100 lux) for maintaining visual clarity and rhythmic lighting. This parameter usually comes from lighting design standards, visual fatigue models or user-defined settings. It is used as the trigger threshold of the dimming algorithm in intelligent lighting control systems (such as DALI and KNX). It can also be linked with spatial location and time period to generate differentiated settings.

[0051] Among them, the specific formula for calculating the spatial comfort index of indoor space is as follows: ;in, is the spatial comfort index of the indoor space, is the indoor temperature value in the digital twin model of the indoor space, is the indoor temperature parameter value of the indoor space, is the maximum allowable deviation of the indoor temperature of the indoor space, is the temperature adjustment coefficient stored in the database, is the indoor humidity value in the digital twin model of the indoor space, is the indoor humidity parameter value of the indoor space, is the maximum allowable deviation of indoor humidity in indoor space, is the humidity adjustment coefficient stored in the database, is the indoor light intensity value in the digital twin model of the indoor space, is the indoor light intensity parameter value of the indoor space, is the maximum allowable deviation of indoor light intensity in indoor space, It is the light intensity adjustment coefficient stored in the database.

[0052] It should be explained that the temperature adjustment coefficient stored in the database , humidity adjustment coefficient , Light intensity adjustment coefficient The specific acquisition steps are as follows: collect the correlation data between different temperature, humidity and light environment parameters and user comfort feedback scores (or environmental evaluation indicators) in multiple historical space samples, combine the standard deviation range of each type of physical parameter and the adjustment equipment capabilities (such as air conditioning response time, dehumidification efficiency, and illumination change response speed) to perform multidimensional regression or machine learning modeling, establish the response weight of physical deviation to comfort perception or recovery efficiency, extract the independent influencing factors of temperature, humidity, and light, and use them as adjustment coefficients after normalization. , , Stored in database.

[0053] In this implementation scheme, by acquiring the comfort perception data such as temperature, humidity and light of the indoor space, and combining the corresponding parameter values ​​and maximum allowable deviation values, a quantitative calculation model of the space comfort index is established, which can effectively evaluate the degree of deviation between the current indoor environment and the ideal comfort state. Compared with the traditional method based on single parameter threshold judgment, this method introduces a multidimensional ecological perception index system, and combines the importance and regulation sensitivity of each physical parameter with the adjustment coefficient to perform weighted processing, so that the index calculation is more in line with the actual human perception experience. The adjustment coefficient is obtained through regression or machine learning analysis between historical space sample data and user comfort feedback. It has the characteristics of strong adaptability and high scene versatility. It can automatically reflect the actual influence of various parameters on comfort under different environmental structures and equipment configurations, thereby improving the scientificity and accuracy of the space comfort index. Through this structured and adjustable model design, a robust comfort evaluation basis is provided for subsequent comprehensive ecological index calculation and intelligent regulation judgment.

[0054] Specifically, the air load data includes indoor carbon dioxide concentration values, indoor particulate matter concentration values, indoor volatile organic compound concentration values, and indoor wind speed values. The specific steps for analyzing the air load index of the indoor space are as follows: obtain the air load parameter set of the indoor space, and the air load parameter set includes indoor carbon dioxide concentration parameter values, indoor particulate matter concentration parameter values, indoor volatile organic compound concentration parameter values, and indoor wind speed parameter values; comprehensively analyze the air load data in the digital twin model of the indoor space in combination with the air load parameter set of the indoor space to obtain the air load index of the indoor space.

[0055] Among them, the indoor carbon dioxide concentration value is a gas concentration indicator that measures the indoor ventilation conditions and the intensity of human respiratory metabolic emissions. It is measured in ppm and is collected in real time through wall-mounted or ceiling-mounted CO2 infrared sensors. It can also be obtained through feedback from the built-in detection module of the HVAC system.

[0056] The indoor particulate matter concentration value refers to the real-time mass concentration of PM2.5 (inhalable fine particulate matter), measured in μg / m³, and is usually obtained through a laser scattering air quality sensor.

[0057] The indoor volatile organic compound concentration value reflects the mixed concentration level of TVOC (including formaldehyde, benzene, toluene, etc.) gaseous harmful substances. The unit is mg / m³ or ppm, which can be collected by a high-sensitivity metal oxide sensor or an electrochemical VOC sensor.

[0058] The indoor wind speed value refers to the air flow speed per unit time, and its unit is m / s. It is a dynamic parameter that reflects the air exchange efficiency and pollution dilution capacity of the space. It can be obtained by real-time measurement through ultrasonic anemometers, thermal film wind speed sensors and other equipment.

[0059] The indoor carbon dioxide concentration parameter value refers to the CO set under the premise of ensuring good ventilation and human health. 2 The upper limit reference value of concentration is usually set at no more than 1000 ppm based on GB / T 18883-2002 Indoor Air Quality Standard or ASHRAE62.1 standard. This value is usually generated by combining the building use (such as conference rooms, classrooms), ventilation type (natural / mechanical ventilation) and occupancy density conditions through air quality assessment models or historical monitoring data fitting.

[0060] The indoor particulate matter concentration reference value is used to characterize the acceptable upper limit of indoor PM2.5 particle size suspended particle pollution. It is generally set according to the 75μg / m³ limit specified in the "Indoor Air Quality Standard". It can also be adjusted due to regional background pollution, filtration device efficiency, and the needs of special-purpose places (such as purification laboratories and medical institutions). This value can be derived from the regional reference value published by the environmental monitoring department, the filtration level of the building's fresh air system, or obtained through a pollution risk assessment model.

[0061] The reference value of indoor volatile organic compound concentration is the upper limit of healthy exposure set for indoor volatile pollutants such as formaldehyde, benzene, and TVOC. The standard is based on the requirements for TVOC concentration limits in GB / T 18883 or GB / T 50325 (generally not higher than 0.6 mg / m³). During the initial construction of the system, a predictive assessment will be conducted based on building materials, furniture release sources, and ventilation conditions, and combined with historical air quality monitoring data or sensor sampling modeling results.

[0062] The indoor wind speed parameter is a parameter for evaluating air replacement efficiency and pollutant dilution capacity. It indicates the optimal wind speed range for maintaining good air flow without causing thermal discomfort or local disturbance. It is usually set to 0.3-0.5m / s based on ASHRAE wind environment standards or indoor comfort requirements. The system can perform simulation extraction through CFD simulation or BIM wind speed simulation module based on HVAC system specifications, fresh air volume settings, room volume and other parameters. It also supports real-time wind speed sensor sampling feedback as a basis for setting value correction.

[0063] The specific formula for calculating the air load index of indoor space is as follows: ;in, is the air load index of the indoor space, is the indoor carbon dioxide concentration value in the digital twin model of the indoor space, is the reference value of indoor carbon dioxide concentration in indoor space, is the indoor particulate matter concentration value in the digital twin model of the indoor space, is the indoor particulate matter concentration parameter value of the indoor space, is the indoor volatile organic compound concentration value in the digital twin model of the indoor space, is the reference value of indoor volatile organic compound concentration in indoor space, is the pollutant concentration adjustment coefficient stored in the database, is the indoor wind speed value in the digital twin model of the indoor space, is the indoor wind speed parameter value of the indoor space, It is the wind speed adjustment coefficient stored in the database.

[0064] It should be explained that the pollutant concentration adjustment coefficient stored in the database , Wind speed adjustment coefficient The specific steps of obtaining are as follows: based on multiple historical spatial samples, CO 2 The response relationship between the concentration data of pollutants such as particulate matter and volatile organic compounds (VOC) and the spatial air load index, as well as the wind speed change data in the corresponding period and the mitigation effect data between them, is used to extract the nonlinear influence weights of each pollutant category and wind speed factor on the air load index by using multivariate regression, sensitivity analysis or machine learning methods; further combined with the performance boundaries of pollution control equipment (such as fresh air volume, filtration efficiency) and pollution index thresholds, normalized modeling and sensitivity segmentation processing are performed to finally form the pollutant concentration adjustment coefficient Wind speed adjustment factor .

[0065] In this embodiment, by obtaining the CO 2 The air load data such as concentration, particulate matter concentration, volatile organic compound concentration and wind speed value are combined with the corresponding parameter values ​​to construct the calculation model of air load index, which realizes the multi-factor comprehensive evaluation of indoor air pollution degree and ventilation capacity. Compared with the traditional method of relying only on a single concentration limit for threshold judgment, the index model can quantitatively reflect the true balance relationship between pollution load and dilution capacity through dynamic coupling analysis of pollutant concentration and wind speed factor. The system collects multiple historical space samples, combines the actual response results of air quality, and uses multivariate regression or machine learning methods to extract the nonlinear influence weights of each pollutant category and wind speed factor, and generates pollutant concentration adjustment coefficient and wind speed adjustment coefficient based on this, which improves the accuracy and adaptability of the model. After the adjustment coefficient is introduced, the influence proportion of pollution indicators in the comprehensive load index can be dynamically adjusted according to different room structures, usage functions or equipment performance, so that the air quality assessment results are closer to the actual risk level, providing a stable and reliable quantitative basis for subsequent control strategies.

[0066] Specifically, the environmental regeneration data includes the transpiration rate value of indoor plants and the thermal lag time of walls. The specific steps for analyzing the ecological restoration index of indoor space are as follows: obtaining the maximum allowable thermal lag parameter value of indoor space; comprehensively analyzing the environmental regeneration data in the digital twin model of indoor space in combination with the maximum allowable thermal lag parameter value of indoor space to obtain the ecological restoration index of indoor space.

[0067] Among them, the transpiration rate of indoor plants is an indicator that reflects the ability of plants to release water vapor through stomata per unit time and per unit area. It is measured in g / m²·h and is an important physical parameter for evaluating the ability of plants to regulate indoor temperature and humidity and their ecological restoration capabilities. This value can be measured by installing environmental sensing nodes close to the plants. The temperature and humidity change rate is combined with parameters such as plant species, leaf area index, and light conditions. It is calculated through plant physiological transpiration models (such as the Penman-Monteith model). It can also be inverted and analyzed through embedded soil moisture and leaf temperature sensors.

[0068] Wall thermal lag time refers to the delay time (in seconds or hours) required for heat to be transferred from the wall structure to the interior and cause a temperature response when the external temperature changes. This parameter is used to measure the thermal inertia of the building envelope and its buffering capacity against temperature fluctuations. It can be obtained through thermal simulation software (such as EnergyPlus, TRNSYS) or material physical properties in the building BIM model. The parameters involved include wall thickness, material thermal conductivity, specific heat capacity, density, etc.

[0069] The maximum allowable thermal hysteresis parameter value is the upper boundary value used to standardize the wall response capacity in the ecological restoration model. It represents the maximum delay time that the wall thermal response can tolerate under given building type and climate zone conditions. Exceeding this value will be regarded as a weak thermal environment regulation capacity. This parameter can be given by building energy conservation codes or thermal design standards (such as the thermal inertia determination conditions of enclosure structures in "GB50176 Building Energy Conservation Design Standard"), or it can be extracted through percentile regression of a large number of sample wall simulation results of different structural types.

[0070] Among them, the specific formula for calculating the ecological restoration index of indoor space is as follows: ;in, is the ecological restoration index of indoor space, is the transpiration rate value of indoor plants in the digital twin model of indoor space, is the plant transpiration regulation coefficient stored in the database, is the wall thermal lag time in the digital twin model of the indoor space, is the maximum allowable thermal hysteresis parameter value for indoor space, is the thermal hysteresis adjustment coefficient stored in the database.

[0071] It should be explained that the plant transpiration regulation coefficient stored in the database , Thermal hysteresis adjustment coefficient The specific steps for obtaining are as follows: first, based on multiple typical spatial samples, the transpiration rate per unit area of ​​different plant species under multiple periods of temperature, humidity, and light conditions are collected, and their sensitivity to ecological restoration efficiency (such as humidity stabilization time and thermal comfort recovery speed) is analyzed. The actual contribution rate of transpiration effect to the restoration index is extracted through regression fitting or response surface modeling, and the plant transpiration regulation coefficient is obtained after normalization. Secondly, combining the heat capacity, thermal conductivity and wall response curve of building materials, a dynamic relationship model between the wall thermal hysteresis time and the recovery index change is established. By fitting the curve slope with the adjustment hysteresis effect, the thermal hysteresis influence weight is extracted and standardized into the thermal hysteresis adjustment coefficient. .

[0072] In this embodiment, by obtaining the indoor plant transpiration rate value and the wall thermal hysteresis time in the environmental regeneration data, combined with the maximum allowable thermal hysteresis parameter value, a calculation model of the ecological restoration index is constructed, which effectively quantifies the strength of the natural regulation ability in the space. The plant transpiration rate reflects the active regulation efficiency of the plant to fine-tune the humidity and heat, and the wall thermal hysteresis time measures the buffering capacity of the building envelope structure to external temperature fluctuations. By introducing the plant transpiration regulation coefficient and thermal hysteresis regulation coefficient obtained by training based on historical sample data, the system can identify the response weights of different plant species and building structures in the actual regulation process, and use them in the parameter weighting of the index calculation. Compared with the traditional design method that ignores the dynamics of the recovery process, the present invention can reflect the self-recovery potential of the ecosystem after disturbance, provide a basis for the regulation simulation under abnormal ecological conditions, and improve the objective evaluation ability of the recovery capacity of low-intervention spaces (such as green offices and energy-saving buildings). The index not only enhances the integrity of ecological assessment, but also provides basic parameter support for zoning regulation and energy consumption optimization.

[0073] Specifically, the specific steps for conducting ecological regulation simulation analysis in the digital twin model of indoor space are as follows: based on the comprehensive ecological status index of indoor space, identify the abnormal factor set and use it as the factor to be regulated, which is specifically: analyze the index that causes the abnormal index (such as space comfort index, air load index, ecological restoration index); call the ecological environment data recorded in the twin model to identify the main physical parameter set that deviates from the normal threshold in the current period, such as CO 2 concentration, temperature, PM2.5 concentration, light fluctuation, etc.; the abnormal factor set is passed into the simulation module as the factor set to be regulated.

[0074] Construct several groups of adjustable factor combinations (such as fresh air volume adjustment level, air conditioning temperature setting, humidifier output, plant light time), each group is a type of strategy configuration; each group of combinations includes the mapping relationship between the control factor and the expected impact target (such as increasing wind speed - reducing CO 2); All combinations are written into the strategy library of the twin model.

[0075] The control simulation process is initialized in the digital twin model of the indoor space. Specifically, without changing the real physical environment, the current indoor space structure, material response, equipment layout, and environmental boundary conditions are called in the digital twin environment; the initial state field of the control at the current time node (including full-parameter environmental fields such as temperature, humidity, scenery, etc.) is constructed; the control simulation engine is activated to prepare for parallel simulation of the impact responses of all control scheme groups.

[0076] The control scheme simulation is executed in parallel in the digital twin model of the indoor space, and the optimal control simulation results are screened. Specifically, each group of control schemes is simulated independently in the twin space based on the thermal and moisture coupling model, aerodynamic model, light and heat transfer model, etc. The simulation time covers a control cycle (such as 15 minutes), and the index change path under each group of simulations is collected; the comprehensive ecological status index and sub-indicator improvement after control are calculated for each group of simulation results, and all simulation scheme results are compared with the set expected control standards; if there are multiple schemes that meet expectations, the scheme with the best energy consumption, the shortest response time or the best user experience is given priority; finally, the control scheme ID + response indicator path + energy consumption prediction value are packaged and output as a candidate control scheme.

[0077] In this implementation plan, by introducing an ecological control simulation analysis mechanism into the digital twin model, it is possible to perform virtual calculations and optimal screening of the expected effects of multiple groups of control strategies before actually implementing the control measures. The system first identifies the key influencing factors of the abnormal comprehensive ecological status index, extracts the environmental physical parameters that currently deviate from the threshold, constitutes a set of factors to be controlled, and constructs multiple groups of control strategy combinations based on their impact paths, covering equipment operating parameters such as fresh air adjustment, air conditioning settings, and humidification control. Without affecting the actual environment, the system reproduces the structural layout, boundary conditions, and equipment performance in the twin space, initializes the state field, and activates the simulation engine. Each group of schemes is simulated in parallel based on the multi-physical field model. By calculating and evaluating the change paths of various ecological indexes in the simulation results, the system can quantitatively judge the ecological improvement effect, energy consumption performance, and response speed of each strategy, and finally selects the optimal strategy output as the candidate control instruction. This mechanism avoids the control deviation caused by blind execution of the strategy, improves the predictability and safety of the system behavior, and significantly enhances the robustness, energy saving, and transparency of strategy decision-making of the intelligent control system.

[0078] See also Figure 4, an embodiment of the present invention provides a technical solution: an indoor ecological environment design system based on digital twins, comprising: a model building unit, used to obtain spatial structure data, building material data, and equipment layout data of the indoor space, and establish a digital twin model of the indoor space; an acquisition and update unit, used to obtain the ecological environment data of the indoor space at intervals based on a set time period (for example, five minutes), and update it to the digital twin model of the indoor space; an ecological environment analysis unit, used to analyze the comprehensive ecological status index of the indoor space based on the ecological environment data in the digital twin model of the indoor space; an ecological environment judgment unit, used to judge and analyze the comprehensive ecological status index of the indoor space with a preset ecological status assessment interval; a simulation analysis unit, used to regard the ecological status of the indoor space as abnormal when the comprehensive ecological status index of the indoor space is outside the preset ecological status assessment interval, and perform ecological regulation simulation analysis in the digital twin model of the indoor space; an ecological regulation unit, used to take ecological regulation measures for the indoor space when the result of the ecological regulation simulation analysis meets the expected standard.

[0079] A computer-readable storage medium is used to store a program, which, when executed by a processor, implements the indoor ecological environment design method based on digital twins as described above.

[0080] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0081] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. The indoor ecological environment design method based on digital twins is characterized by: The following steps are involved: Obtain spatial structure data, building material data, and equipment layout data of the indoor space, and establish a digital twin model of the indoor space; Based on the set time period, the ecological environment data of the indoor space is obtained at intervals and updated to the digital twin model of the indoor space; Based on the ecological environment data in the digital twin model of the indoor space, the comprehensive ecological status index of the indoor space is analyzed, and judgment and analysis are performed with the preset ecological status assessment interval; When the comprehensive ecological status index of the indoor space is outside the preset ecological status assessment range, the indoor space ecological status is regarded as abnormal, and an ecological regulation simulation analysis is performed in the digital twin model of the indoor space; When the results of the ecological control simulation analysis meet the expected standards, ecological control measures are taken for the indoor space.

2. The indoor ecological environment design method based on digital twin according to claim 1 is characterized in that: The ecological environment data includes comfort perception data, air load data, and environmental regeneration data. Based on the ecological environment data in the digital twin model of the indoor space, the specific steps for analyzing the comprehensive ecological status index of the indoor space are as follows: Based on the comfort perception data, air load data, and environmental regeneration data in the digital twin model of the indoor space, an ecological environment index set of the indoor space is analyzed, wherein the ecological environment index set includes a space comfort index, an air load index, and an ecological restoration index; A comprehensive analysis is conducted on the ecological environment index set of indoor space to obtain the comprehensive ecological status index of indoor space.

3. The indoor ecological environment design method based on digital twin according to claim 2 is characterized in that: The specific formula for calculating the comprehensive ecological status index of indoor space is as follows: ； in, , , , They are the comprehensive ecological status index of indoor space, space comfort index, air load index, and ecological restoration index. , , They are the space comfort adjustment coefficient, air load adjustment coefficient and ecological restoration adjustment coefficient stored in the database respectively.

4. The indoor ecological environment design method based on digital twin according to claim 2 is characterized in that: The comfort perception data includes indoor temperature value, indoor humidity value, and indoor light intensity value. The specific steps for analyzing the space comfort index of the indoor space are as follows: Acquire a comfort perception parameter set and a comfort perception allowable deviation set of the indoor space, wherein the comfort perception parameter set includes an indoor temperature parameter value, an indoor humidity parameter value, and an indoor light intensity parameter value, and the comfort perception allowable deviation set includes a maximum allowable deviation of the indoor temperature, a maximum allowable deviation of the indoor humidity, and a maximum allowable deviation of the indoor light intensity; The comfort perception data in the digital twin model of the indoor space is comprehensively analyzed together with the comfort perception parameter set and the comfort perception allowable deviation set of the indoor space to obtain the spatial comfort index of the indoor space.

5. The indoor ecological environment design method based on digital twin according to claim 2 is characterized in that: The air load data includes indoor carbon dioxide concentration value, indoor particulate matter concentration value, indoor volatile organic compound concentration value, and indoor wind speed value. The specific steps for analyzing the air load index of the indoor space are as follows: Acquire an air load parameter set of an indoor space, wherein the air load parameter set includes an indoor carbon dioxide concentration parameter value, an indoor particulate matter concentration parameter value, an indoor volatile organic compound concentration parameter value, and an indoor wind speed parameter value; The air load data in the digital twin model of the indoor space is comprehensively analyzed in combination with the air load parameter set of the indoor space to obtain the air load index of the indoor space.

6. The indoor ecological environment design method based on digital twin according to claim 5 is characterized in that: The specific formula for calculating the air load index of indoor space is as follows: ； in, is the air load index of the indoor space, , , , They are the indoor carbon dioxide concentration value, indoor particulate matter concentration value, indoor volatile organic compound concentration value, and indoor wind speed value in the digital twin model of the indoor space. , , , They are the indoor carbon dioxide concentration reference value, indoor particulate matter concentration reference value, indoor volatile organic compound concentration reference value, and indoor wind speed reference value of the indoor space. , They are the pollutant concentration adjustment coefficient and wind speed adjustment coefficient stored in the database respectively.

7. The indoor ecological environment design method based on digital twin according to claim 2 is characterized in that: The environmental regeneration data includes the transpiration rate value of indoor plants and the thermal hysteresis time of the wall. The specific steps for analyzing the ecological restoration index of the indoor space are as follows: Obtain the maximum allowable thermal hysteresis parameter value of the indoor space; The environmental regeneration data in the digital twin model of the indoor space is comprehensively analyzed in combination with the maximum allowable thermal hysteresis parameter value of the indoor space to obtain the ecological restoration index of the indoor space.

8. The indoor ecological environment design method based on digital twin according to claim 1 is characterized in that: The specific steps for conducting ecological regulation simulation analysis in the digital twin model of indoor space are as follows: Based on the comprehensive ecological status index of indoor space, identify the abnormal factor set and use it as the factor to be regulated; Construct several groups of controllable factor combinations, each group is a type of strategy configuration; Initialize the control simulation process in the digital twin model of the indoor space; The control scheme simulation is executed in parallel in the digital twin model of the indoor space, and the optimal control simulation results are screened.

9. An indoor ecological environment design system based on digital twins, applying the indoor ecological environment design method based on digital twins according to any one of claims 1 to 8, characterized in that: include: A model building unit is used to obtain the spatial structure data, building material data, and equipment layout data of the indoor space, and to build a digital twin model of the indoor space; An acquisition and update unit, used to acquire the ecological environment data of the indoor space at intervals based on a set time period, and update it into the digital twin model of the indoor space; The ecological environment analysis unit is used to analyze the comprehensive ecological status index of the indoor space based on the ecological environment data in the digital twin model of the indoor space; The ecological environment judgment unit is used to judge and analyze the comprehensive ecological state index of the indoor space and the preset ecological state assessment interval; A simulation analysis unit is used to regard the indoor space ecological state as abnormal when the comprehensive ecological state index of the indoor space is outside the preset ecological state assessment range, and to perform ecological regulation simulation analysis in the digital twin model of the indoor space; The ecological control unit is used to take ecological control measures for the indoor space when the ecological control simulation analysis results meet the expected standards.

10. A computer-readable storage medium for storing a program, characterized in that: When the program is executed by a processor, the indoor ecological environment design method based on digital twins as described in any one of claims 1 to 8 is implemented.

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