Graphene wall surface configuration intelligent decision method for healthy living scene

Abstract

The application discloses a graphene wall surface configuration intelligent decision method for a healthy living scene, relates to the technical field of indoor environment intelligent control, and comprises the following steps: a temperature distribution model and a wall surface heat transfer characteristic model of a living space are established, a heat transfer schematic diagram between different rooms is constructed according to the space structure and the wall heat conduction parameter of each room, and the flow direction and the time difference of heat in each room are determined. Through the establishment of the temperature distribution model and the wall surface heat transfer characteristic model, the beat offset record and the delayed release control are combined, the timing coordination of the multi-room heating process is realized, local heat peaks are avoided, and the thermal comfort is improved; meanwhile, through the reverse heat dissipation and the energy slow-release operation mode of periodic cooling compensation, heat is evenly transferred in the space, energy consumption is optimized, and the stability and health of the living environment are maintained.

Description

Technical Field

[0001] This invention relates to the field of intelligent indoor environment control technology, specifically to an intelligent decision-making method for graphene wall configuration in healthy living scenarios. Background Technology

[0002] Graphene wall panel configuration decisions for healthy living scenarios refer to the process of scientifically deciding on the placement, area ratio, thickness combination, and heat conduction path of graphene functional wall panels in residential, health care, hotel, and apartment spaces, based on indoor health environment requirements and comprehensively considering multiple factors such as temperature, humidity, air quality, radiation comfort, and energy consumption. This decision-making method collects and analyzes big data from living spaces, including real-time environmental monitoring data, resident behavior data, and climate change data. It combines this with the thermal conductivity, far-infrared radiation, antibacterial and deodorizing properties of graphene materials, as well as their humidity regulation characteristics, to analyze the impact of different wall panel configurations on indoor thermal and humidity environments and air cleanliness, determining the most suitable matching scheme for human comfort zones. Its core lies in the dynamic integration of big data processing with building material performance parameters, enabling real-time response and optimization to resident health needs. This drives the transformation of graphene wall panel configuration from experience-based design to data-driven intelligent decision-making, promoting the evolution of living spaces from simple heat preservation and energy saving to proactive adjustment for health and comfort.

[0003] Existing technologies have the following shortcomings: In existing technologies, the heating control of multi-room graphene walls typically employs independent adjustment, resulting in a lack of global coordination in the heating rhythm of each room. This can easily lead to misalignment of heating cycles during operation. When heating overlaps in different areas of the wall, energy release cannot be dispersed, creating a cumulative effect at spatial boundaries, leading to sudden localized temperature rises and abnormal heat peaks. This phenomenon not only causes uneven temperature distribution on the wall surface but also easily leads to mismatches in material thermal expansion and contraction, causing structural hazards such as bulging and cracking of the finish layer. Furthermore, it may interfere with the feedback judgment of the temperature control system, generating erroneous adjustment commands and affecting the overall thermal comfort and energy balance of the living space.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent decision-making method for graphene wall configuration in healthy living scenarios, so as to solve the problems in the background art mentioned above.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a smart decision-making method for graphene wall configuration in healthy living scenarios, comprising the following steps:

[0007] Establish a temperature distribution model and a wall heat transfer characteristic model for the living space. Based on the spatial structure and wall thermal conductivity parameters of each room, construct a heat transfer diagram between different rooms, determine the flow direction and time difference of heat between rooms, and obtain the heat transfer law between multiple rooms. Based on the heat transfer diagram, the temperature change curves of adjacent rooms are compared over time. The difference between the start time of temperature rise and the end time of temperature drop is extracted to generate asynchronous feature data of the heating process, forming a beat offset record, which is used to identify the heat accumulation trend. Based on the beat offset records, energy change analysis is performed on the spatial regions where heat convergence occurs, the correlation parameters between the duration of the temperature peak and the heating rate are calculated, the heat peak risk areas are identified, and the temperature difference abrupt change points are marked in the risk areas to obtain the key location data of the heat peak. Based on the key location data of the heat peak, the heating control sequence is rearranged, and time intervals and delayed release parameters are set so that the heating stages of each room are carried out sequentially, controlling the temporal distribution of the heat release process and reducing the concentrated effect caused by the simultaneous superposition of energy. Based on the rearranged heating sequence parameters, a cooling compensation cycle is periodically inserted during the heating process. By alternating between short-term reverse heat dissipation and slow energy release, the temperature distribution of each room is dynamically adjusted to achieve balanced heat transfer between multiple rooms and maintain the overall thermal balance and thermal comfort of the living space.

[0008] Preferably, the steps for constructing the heat transfer diagram are as follows:

[0009] Establish a temperature distribution model and a wall heat transfer characteristic model for the living space. Based on the geometric dimensions of each room, the orientation of the walls, the layers of the enclosure structure and the location of the openings, form a set of spatial geometric parameters and determine the heat transfer path.

[0010] Based on the set of spatial geometric parameters and the thermal conductivity parameters of the wall, the thermal conductivity, heat capacity, density and surface radiation properties of the wall material are integrated to generate a set of wall heat transfer characteristic parameters, so that the wall forms an energy coupling relationship in heat transfer.

[0011] Based on the set of wall heat transfer characteristic parameters, the spatial distribution of temperature changes in each room is calculated, a temperature distribution model between rooms is established, and a continuous heat flow boundary condition is introduced to ensure that energy transfer remains continuous at the interface.

[0012] Based on the temperature distribution model and the wall heat transfer characteristic model, a heat transfer diagram including heat flow direction, heat magnitude and time difference is constructed. The direction and time characteristics of heat flow between rooms are extracted to obtain the heat transfer law between multiple rooms.

[0013] Preferably, the steps for forming the beat offset record are as follows:

[0014] Based on the heat transfer diagram, the direction of heat flow and the amount of heat energy between the walls of each room and adjacent rooms in the living space are analyzed. The temperature change process of each room is recorded as a time series curve to form continuous temperature response data for the entire space.

[0015] By comparing the temperature change curves of adjacent rooms based on time series data, the difference between the start time of temperature rise and the end time of temperature drop is extracted, and the asynchronous characteristics of heating rhythm between rooms are converted into time difference data.

[0016] Based on the time difference data, asynchronous feature data of the heating process is generated, and a beat offset record is formed to establish a time series label for the heating rhythm between rooms;

[0017] By using beat offset records to perform overall analysis of temperature change curves, areas of concentrated and delayed heat transfer are identified, forming a dynamic mapping of heat flow and accumulation in multiple rooms, which is used to maintain the thermal balance and comfort of living spaces.

[0018] Preferably, during the generation of the beat offset record, the difference between the start time of temperature rise and the end time of temperature drop is continuously recorded in the form of a time series. A heating rhythm label is established by the change of the time difference, and the temperature response sequence between adjacent rooms is determined according to the heating rhythm label, so that the direction of heat transfer is consistent with the time delay characteristics, thereby improving the temporal coordination and spatial balance of heat flow.

[0019] Preferably, the steps for obtaining key location data of the thermal peak are as follows:

[0020] Based on the beat offset records, spatial correlation is performed on the temperature response differences of each room during the heating cycle to identify the areas where heat converges between adjacent rooms and to mark the overlapping time periods of heat energy at the interface.

[0021] Energy change analysis is performed in the identified heat convergence area, and the duration of the temperature peak is coupled with the heating rate for evaluation, forming a set of correlation parameters between the duration of the temperature peak and the heating rate.

[0022] Based on the correlation parameters between the duration of the temperature peak and the heating rate, the energy accumulation trend is analyzed, the heat peak risk area is screened and marked, and the spatial boundary and energy characteristics of the heat concentration area are determined.

[0023] Within the heat peak risk area, temperature abrupt change points are marked to form key location data of the heat peak, which includes location coordinates, time labels, temperature change amplitude, and heating rate information. This data is used for subsequent heating rhythm adjustment and graphene wall configuration optimization.

[0024] Preferably, the marking of temperature difference abrupt change points is based on the slope of the temperature curve and the temperature gradient. In the heat peak risk area, the node with the most obvious change in heating rate and the longest duration of temperature peak is selected as the marker point. By continuously marking, a dataset of key locations of heat peaks is formed, so that the spatial location of the heat concentration area and the energy change characteristics are accurately correlated in the time series.

[0025] Preferably, based on the key location data of the heat peak, the heating control sequence is rearranged, and time intervals and delayed release parameters are set to ensure that the heating stages of each room are performed sequentially and the time distribution of heat release is controlled as follows:

[0026] Based on the obtained data on key locations of heat peaks, the heat distribution characteristics of each room are analyzed, the data on key locations of heat peaks are correlated with the spatial location of the room, and the heating sequence framework is determined by combining the heat conduction direction of the wall and the heat flow path.

[0027] Based on the distribution of temperature abrupt change points in the data of key locations of the heat peak, time interval parameters are set to ensure that the heating start-up times of each room are staggered in time, so as to avoid the accumulation of energy and heat concentration.

[0028] By combining the characteristics of temperature difference abrupt change points in the data of key locations of the heat peak, the delayed release parameters are determined so that the heating stages of different rooms form a progressive relationship in terms of energy release rate, which promotes the gradual diffusion of heat along the transfer direction.

[0029] A heating control sequence rearrangement scheme is formed based on time interval parameters and delayed release parameters, so that the heating stages of each room unfold sequentially, controlling the temporal distribution of the heat release process and maintaining the thermal balance and thermal comfort of the living space.

[0030] Preferably, during the process of forming the heating control sequence rearrangement scheme, the time interval parameters and delayed release parameters are dynamically adjusted according to the temperature gradient distribution in the key location data of the heat peak, so that the start-up sequence of the heating stage is consistent with the direction of heat transfer, thereby forming a continuous heat diffusion path in the spatial range, ensuring the stability of the heat release process and the uniformity of the heat field distribution.

[0031] Preferably, based on the heating sequence parameters, a cooling compensation cycle is periodically inserted during the heating operation. The steps for dynamically adjusting the temperature distribution in each room through alternating short-term reverse heat dissipation and slow energy release are as follows:

[0032] Based on the rearranged heating sequence parameters, the temperature change trend during the multi-room heating process is analyzed to determine the heat transfer sequence and energy accumulation period between rooms, and the temperature growth rate is used as the basis for setting the cooling compensation cycle.

[0033] After determining the time point of the cooling compensation cycle, a short-term reverse heat dissipation process is implemented, so that the wall at the peak energy stage releases some heat to the low temperature area through reverse heat conduction, thereby realizing the redistribution of heat in the space.

[0034] After the short-term reverse heat dissipation ends, an energy release phase is implemented. By reducing the heat release rate of the wall, the temperature gradually transitions in the space, establishing a dynamic thermal equilibrium state.

[0035] Based on the alternation of short-term reverse heat dissipation and energy slow release phases, a periodic cycle regulation is formed, which enables the heat to be evenly transferred between multiple rooms, maintaining the overall thermal balance and thermal comfort of the living space.

[0036] Preferably, during the short-term reverse heat dissipation process, the heat energy is diffused from the high-temperature area to the adjacent low-temperature area by controlling the instantaneous switching of the heat conduction direction of the wall. During the energy release phase, the heat release rate is continuously reduced, so that the temperature difference between rooms is gradually balanced. Thus, the stability of heat transfer and the uniformity of spatial temperature distribution are achieved in the periodic cycle.

[0037] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0038] This invention establishes a temperature distribution model and a wall heat transfer characteristic model during multi-room heating operation, enabling accurate control of the direction and time difference of heat flow in space. Dynamic identification of heat transfer patterns is achieved through cycle offset recording. By reconstructing the timing of each room's heating phase and controlling delayed release, heat is distributed in layers in time and space, avoiding localized heat peaks caused by simultaneous energy release. This results in a more balanced temperature distribution on the wall surface, reducing structural stress concentration caused by thermal expansion and contraction, thereby improving the stability of graphene walls and the thermal comfort of living spaces.

[0039] This invention introduces a dynamic balance in heat transfer between different rooms by periodically inserting cooling compensation cycles and alternating short-term reverse heat dissipation and slow energy release during heating operation. This creates a continuous and balanced heat transfer path between rooms, effectively dissipating accumulated heat and optimizing overall energy consumption. Temperature fluctuations in living spaces are controlled, maintaining a stable and comfortable thermal environment, thus achieving the unified goal of energy conservation and healthy living. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0041] Figure 1 This is a flowchart illustrating the intelligent decision-making method for configuring graphene walls in a healthy living environment, as described in this invention. Detailed Implementation

[0042] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0043] This invention provides, for example Figure 1 The intelligent decision-making method for graphene wall panel configuration in healthy living scenarios, as shown, includes the following steps:

[0044] Establish a temperature distribution model and a wall heat transfer characteristic model for the living space. Based on the spatial structure and wall thermal conductivity parameters of each room, construct a heat transfer diagram between different rooms, determine the flow direction and time difference of heat between rooms, and obtain the heat transfer law between multiple rooms. To ensure that graphene wall panel configuration decisions better align with the thermal environment characteristics of healthy living spaces, a multi-dimensional heat analysis and conduction relationship modeling of the living space were conducted. This resulted in the establishment of a temperature distribution model and a wall heat transfer characteristic model, thereby obtaining the heat transfer patterns between multiple rooms. The specific implementation steps are as follows: A comprehensive spatial analysis of the living space's structural layout is conducted, establishing a complete set of spatial geometric parameters based on the geometric dimensions of each room, wall orientation, enclosure structure layers, and opening locations. By dividing each room into zones—exterior walls, interior partitions, ceilings, and floors—the distribution and connectivity of the walls within the overall space are determined. Based on the interface characteristics between the building's floor plan and the rooms, potential heat transfer boundary areas are identified, and the thermal coupling paths within these boundary areas are determined. During this process, a preliminary framework for the wall's heat transfer characteristics is formed based on the wall's heat conduction path length, interlayer material composition, thickness ratio, and thermal resistance characteristics. This model describes the possible paths of heat transfer from one room to adjacent rooms by recording the heat conduction direction and heat flux density differences of each wall surface, providing a structural basis for subsequent temperature distribution calculations. The key point of this step is establishing a clear correspondence between the building's geometry and heat transfer paths, ensuring that every heat flow channel in the space can be expressed in terms of geometric and thermal parameters.

[0045] After obtaining complete spatial structural parameters and wall thermal conductivity parameters, the thermal properties of the walls in different rooms are described based on the wall heat transfer characteristic model. This step determines the thermal conductivity and heat storage capacity of each wall surface during heat transfer by integrating the thermal conductivity, heat capacity, density, and surface radiation properties of the wall materials. For walls with multi-layered composite structures, the interlayer paths for heat penetration are calculated according to the arrangement of the materials in each layer, and the heat transfer mode in the vertical and parallel directions is defined with the interlayer contact interface as the boundary. In this way, each wall is assigned an independent set of heat transfer characteristic parameters, so that the influence of different components of the wall on heat flow can be accurately reflected in the subsequent establishment of heat transfer relationships. In the process of establishing the model, the temperature field of the living space is divided into multiple thermal zone units, and the walls are used as the energy transfer medium of the thermal zones, so that the wall heat transfer characteristic model can be directly coupled with the spatial temperature distribution model.

[0046] After obtaining the heat transfer characteristics of the walls, spatial distribution calculations are performed for temperature changes in each room to establish a temperature distribution model for the living space. This step uses the thermal conductivity parameters of each wall as input conditions, treating each room as an independent but interconnected thermal energy node, and describing the temperature response between different rooms through the heat flow transfer relationship within the walls. By analyzing the thermal resistance, heat capacity, and thermal radiation characteristics of the walls, the temperature gradient changes under steady-state and unsteady-state conditions are calculated, ensuring that the average temperature of each room, the wall surface temperature, and the interface temperature distribution can be determined within a unified thermal equilibrium framework. To ensure the spatial continuity of the model, continuous heat flow boundary conditions are introduced at the boundaries between rooms, allowing energy transfer between adjacent rooms to remain continuous at the boundaries, thus reflecting the actual process of heat flowing from one room to another. Through this temperature distribution model, the temperature field profile of the entire living space can be obtained, revealing the heat flow trend and directionality between different rooms from a spatial perspective, providing a basis for constructing a heat transfer diagram.

[0047] Based on temperature distribution and wall heat transfer characteristic models, the heat transfer relationships between rooms are visualized and organized to construct a schematic diagram of heat transfer between multiple rooms. This diagram uses heat flow direction, heat magnitude, and time difference as basic elements, forming a complete heat transfer network by continuously connecting the heat flow paths of each room. In the diagram, the heat flow direction is driven by the temperature gradient, reflecting the dynamic process of heat flowing from a higher-temperature room to a lower-temperature room; the heat magnitude is quantified based on the wall's thermal conductivity parameters and the space's volumetric heat capacity; the time difference is determined by analyzing the delay relationship between the room's temperature rise and fall processes, used to characterize the temporal sequence and rhythm of heat propagation between rooms. By presenting the heat flow direction, energy magnitude, and transfer time difference in a unified manner, the dominant and secondary heat transfer paths between rooms can be intuitively identified, and the heat transfer patterns between different rooms can be further extracted. These patterns reflect the flow direction, speed, and delay characteristics of heat in space, providing a data foundation for subsequent heating rhythm coordination and graphene wall configuration decisions.

[0048] Based on the heat transfer diagram, the temperature change curves of adjacent rooms are compared over time. The difference between the start time of temperature rise and the end time of temperature drop is extracted to generate asynchronous feature data of the heating process, forming a beat offset record, which is used to identify the heat accumulation trend.

[0049] To fully characterize the temperature change features during the heating process of multi-room graphene walls, a time-series comparison method for temperature response between different rooms is established by analyzing heat transfer diagrams. This method extracts the difference between the start time of temperature rise and the end time of temperature drop, generating asynchronous feature data of the heating process, forming a beat offset record, and is used to identify heat accumulation trends. The specific implementation steps are as follows: Based on a heat transfer diagram, a comprehensive analysis of the heat flow direction and heat energy magnitude of the walls in each room and adjacent rooms within a living space is conducted. The temperature response of each room is treated as a continuous curve changing over time, recording the complete process of temperature gradually increasing from its initial value to its peak and then gradually decreasing during heating. On this basis, the temperature change curves of each room are arranged in a time series, so that each time point corresponds to the actual temperature change in each room, forming a time series data of the continuous temperature response across the entire space. In this way, the starting point of temperature rise, the ending point of temperature fall, and the rate of temperature change in each room can be completely mapped in the time dimension, thus providing a structured data foundation for subsequently extracting the time difference between temperature rise and temperature fall, while revealing the sequential relationship and mutual coupling characteristics of the responses of different rooms in heat transfer.

[0050] For the established time-series data, the temperature change curves of adjacent rooms are compared segment by segment. The starting time of temperature rise in each room during the heating process is analyzed in relation to the ending time of temperature drop in the adjacent rooms. During the comparison, the difference between the start time of each temperature rise and the corresponding end time of the temperature drop is recorded, quantifying the asynchronous characteristics of the heating rhythm between rooms into continuous data. This step not only captures the delayed or advanced phenomena in the thermal response of each room but also forms an overall picture of the rhythm differences between multiple rooms, thus providing a clear temporal basis for analyzing spatial areas where heat may be concentrated or delayed. In this way, the relative order and time interval of temperature response between rooms can be obtained without interfering with the actual wall heating operation, enabling continuous tracking of heat distribution.

[0051] Based on the time difference between the start time of temperature rise and the end time of temperature drop, asynchronous characteristic data of the heating process are generated and integrated into a beat offset record. In the process of forming the beat offset record, the time difference of the temperature curve in each room corresponds to a heating rhythm label, used to characterize the start delay and duration characteristics of each room within the heating cycle. By integrating the beat offset data of all adjacent rooms in the entire living space, a comprehensive network diagram of the heating rhythm of multiple rooms can be formed, clearly showing the heat transfer sequence, concentrated periods, and potential convergence areas in the space. The beat offset record, in the form of continuous data, reflects the asynchronous characteristics of the heating response between rooms, providing a foundation for subsequent analysis of potential heat accumulation trends. Simultaneously, the time labels clarify the start and end sequence and mutual influence relationships of each room during the heating process, enabling a systematic description of the temporal characteristics of heat distribution.

[0052] By utilizing the generated beat offset records, a comprehensive analysis of the temperature change curves in each room is performed to identify areas where heat may be concentrated or delayed, and to determine the spatial locations where temperature accumulation may occur during continuous heating. By analyzing the difference between the start time of temperature rise and the end time of temperature drop and its distribution across different rooms, heat accumulation trend characteristics are extracted. The differences in temperature response between rooms during continuous heating are spatially correlated, forming a dynamic map of heat flow and accumulation across multiple rooms. This map reveals the heat superposition relationship between adjacent rooms, delayed responses, and potential locations of local heat peaks. It provides a sufficient basis for optimizing the heating rhythm and making scientific decisions regarding graphene wall configuration, enabling continuous control of temperature response and heat distribution during multi-room heating, thereby maintaining the overall thermal balance and comfort of the living space.

[0053] Based on the beat offset records, energy change analysis is performed on the spatial regions where heat convergence occurs, the correlation parameters between the duration of the temperature peak and the heating rate are calculated, the heat peak risk areas are identified, and the temperature difference abrupt change points are marked in the risk areas to obtain the key location data of the heat peak.

[0054] To identify key areas in living spaces where heat peaks may occur, energy changes are assessed through analysis of clock shift records. A correlation is established between the duration of temperature peaks and the rate of temperature rise, and abrupt temperature change points are marked, forming key location data for heat peaks. The specific implementation process is as follows:

[0055] Based on the generated cycle offset records, spatial correlations are performed on the temperature response differences of each room within the heating cycle, identifying areas where heat may converge between adjacent rooms. During this identification process, the offset data of the start time of temperature rise and the end time of temperature fall in different rooms are analyzed to determine the overlapping time periods of heat energy in the boundary areas. The spatial locations corresponding to these time periods are then calibrated, thus forming preliminary heat convergence areas. By dividing these heat convergence areas, each area is assigned specific spatial coordinates and the direction of heat inflow, allowing subsequent analyses of temperature peaks and heating rates to be conducted on a clearly defined spatial basis.

[0056] After identifying the heat convergence zones, energy change analysis is performed on the temperature variations in each zone, coupling the duration of the temperature peak with the warming rate within that zone for evaluation. During this process, by continuously recording the rate of temperature rise and the duration of the temperature peak, a set of correlation parameters between the temperature peak duration and the warming rate is formed. These correlation parameters reflect the intensity and development process of heat accumulation in the convergence zones, characterizing the dynamic distribution of heat in both spatial and temporal dimensions. This provides fundamental data for identifying heat peak risk areas, ensuring a full description of the dynamic thermal characteristics of each convergence zone.

[0057] Based on the correlation parameters between the duration of temperature peaks and the heating rate, heat peak risk areas are screened and calibrated. By analyzing the energy accumulation trends in each intersection region, areas with long temperature peak durations and rapid heating rates are identified as potential heat peak risk areas, and their spatial extent is defined. Calibration of risk areas involves clearly locating the boundaries of heat concentration areas in a spatial plane and combining this with the start and end times of the temperature curves to form multi-dimensional risk data. This ensures that each heat peak risk area includes not only its spatial location but also its energy change characteristics within the heating cycle.

[0058] Temperature abrupt change points are marked within the heat peak risk area to form key location data for the heat peak. The marking of these abrupt change points references the slope of the temperature curve and the temperature gradient, locating the nodes in the intersection area with the most significant changes in heating rate and the longest cumulative temperature peak time, thus clarifying their specific spatial location. By continuously marking the temperature abrupt change points in each heat peak risk area, a complete dataset of key locations for the heat peak is formed, including location coordinates, time labels, temperature change amplitude, and heating rate information. This key location data not only provides accurate spatial positioning of heat concentration areas but also reflects the dynamic characteristics of heat accumulation, providing sufficient implementation basis for subsequent heating rhythm adjustments and graphene wall configuration decisions. This enables targeted optimization of multi-room heat control in living spaces, achieving balanced heat distribution and maintaining environmental comfort.

[0059] Based on the key location data of the heat peak, the heating control sequence is rearranged, and time intervals and delayed release parameters are set so that the heating stages of each room are carried out sequentially, controlling the temporal distribution of the heat release process and reducing the concentrated effect caused by the simultaneous superposition of energy.

[0060] To coordinate the heating control sequence of the graphene wall surface in the living space with the heat release process, the heating sequence of each room was rearranged based on the key location data of the heat peak obtained in the previous step. By setting time intervals and delayed release parameters, the heating stages of different rooms were controlled to unfold sequentially, ensuring orderly heat transfer within the space and avoiding the concentrated effect caused by simultaneous energy accumulation. The specific implementation steps are as follows: Based on the obtained data on key locations of heat peaks, a comprehensive analysis of the heat distribution characteristics of each room in the living space is conducted. The key locations of heat peaks are mapped one-to-one with the spatial locations of the rooms, and the relationship between the heat peak risk areas and the direction of heat transfer is determined by combining the heat conduction direction of the walls and the heat flow paths of adjacent rooms. On this basis, the energy accumulation period and heat release rhythm of each room during the heating cycle are analyzed, dividing the rooms into three categories: the dominant heating zone, the transitional heating zone, and the heat equilibrium zone. This allows the heating stages of different zones to be sequentially arranged according to their heat peak risk levels. In this way, a preliminary framework for adjusting the heating sequence is formed, providing a clear physical basis for subsequent setting of time intervals and delayed release parameters. This step, through the spatial mapping of key heat peak location data, ensures that the arrangement of the heating sequence is consistent with the actual heat flow patterns, laying the foundation for dynamic heat balance control.

[0061] After establishing the heating sequence framework, time interval parameters are set based on the distribution of temperature abrupt change points in the data of key heat peak locations. This ensures a controllable staggered heating start-up time for different rooms. This step, by adjusting the heating start-up time of adjacent rooms in zones, creates an orderly, intermittent distribution of heat release over time, preventing heat accumulation caused by multiple rooms simultaneously heating up. The time interval settings comprehensively consider differences in heat flow transfer delays, wall conduction rates, and heat capacity between rooms. Through reasonable interval sequence control, heat diffusion in the space is continuous, and heat release unfolds sequentially at different time points. In this way, energy release in key heat peak locations is effectively dispersed, the spatial temperature gradient is balanced, and the heating rhythm transitions smoothly over time, providing a foundation for implementing a delayed release strategy.

[0062] After setting the time intervals, the characteristics of temperature abrupt change points in the key locations of the heat peak are further combined to determine the delayed release parameters. This ensures that the heating stages of different rooms are not only staggered in time but also progressively related in terms of energy release rate. This step analyzes the heating rate and heat accumulation trend of each room to determine the specific duration for which heat release should be delayed in high-risk areas and sets the parameter ranges for delayed start-up and delayed cooling. In this way, the heating process of each room no longer enters the high heat release stage simultaneously, but rather progresses step by step according to the direction of heat transfer, allowing energy to be transferred in a fluctuating manner in space, forming a heat flow path that gradually diffuses from the heat peak risk area to the surrounding areas. The setting of delayed release parameters ensures that heat can be balanced during the release process, making the heat transfer process smoother, avoiding local high-temperature areas caused by energy superposition, and providing a guarantee for the stability of the overall heat release rhythm.

[0063] Based on the settings of the time interval parameters and delayed release parameters, a complete heating control sequence rearrangement scheme is formed. This scheme combines key heat peak location data with spatial thermal energy distribution characteristics to establish a time-series control model for heat release. In this step, the heating start-up sequence and duration of all rooms are arranged sequentially according to time, creating a hierarchical distribution of heat release in both time and space. The heating stages of each room are interconnected; when one room enters the cooling stage, an adjacent room enters the heating stage, thus forming a rhythmic alternating heat release process. In this way, the time-series distribution of heat release is optimized, and energy propagates continuously but non-overlappingly in space, reducing the concentrated effect caused by simultaneous energy superposition. Ultimately, the thermal field distribution of the living space achieves dynamic equilibrium, fully utilizing the thermal conductivity of the graphene wall between rooms, resulting in a more uniform overall temperature distribution and maintaining a long-term stable thermal comfort state in the living space.

[0064] Based on the rearranged heating sequence parameters, a cooling compensation cycle is periodically inserted during the heating process. The temperature distribution of each room is dynamically adjusted through alternating short-term reverse heat dissipation and slow energy release, so as to achieve balanced heat transfer between multiple rooms and maintain the overall thermal balance and thermal comfort of the living space.

[0065] To maintain thermal balance and overall thermal comfort across multiple rooms during heating operation, cooling compensation cycles are periodically inserted into the continuous heating process based on reprogrammed heating sequence parameters. This involves alternating short-term reverse heat dissipation and slow energy release to dynamically adjust the temperature distribution in each room, thereby achieving balanced heat transfer throughout the space. The specific implementation steps are as follows: Based on the established heating sequence parameters, the temperature change trends during the multi-room heating process are analyzed to determine the sequence of heat transfer and the heat accumulation period between different rooms. By comparing the temperature rise and fall patterns of each room during the heating phase, time periods with rapid temperature growth and relatively high energy density in continuous heating are identified and used as reference nodes for inserting cooling compensation cycles. In this process, the heating sequence parameters are combined with data on key heat peak locations to divide the time windows for heat release in each room, determining the start time, duration, and target of the cooling compensation cycle. This ensures that cooling compensation intervenes promptly during the heat accumulation phase, preventing localized heat buildup in the space. In this way, the setting of the cooling compensation cycle is coordinated with the rhythm of the heating sequence, resulting in a regular fluctuation in the heat flow throughout the living space over time.

[0066] After determining the timing of the cooling compensation cycle, a short-term reverse heat dissipation process is implemented, allowing the wall surface at its energy peak to release some heat to the lower-temperature areas through reverse heat conduction. This step dynamically adjusts the thermal conductivity of the graphene wall surface, causing the heat conduction-dominated relationship within the wall to reverse for a short period. This redirects heat energy that was originally being transferred into the room towards the interior of the wall structure or adjacent rooms, creating a short-term energy return flow. Through this reverse heat dissipation process, the instantaneous heat on the wall surface is released, reducing the accumulation of thermal stress within the wall and creating conditions for the subsequent energy release phase. Reverse heat dissipation not only lowers the local temperature but also redistributes the temperature difference between rooms, gradually balancing the heat gradient between areas and providing a continuous physical basis for maintaining the overall thermal stability of the living space.

[0067] After the short-term reverse heat dissipation process ends, an energy release phase is implemented. By gradually reducing the heat release rate from the walls, the temperature distribution within the space achieves a smooth transition. The core of this step lies in controlling the timing of heat release, allowing heat energy to gradually diffuse into adjacent rooms or the interior of the structure during transfer, thus causing localized high-temperature areas to release accumulated heat to the surrounding areas. During this process, the temperature difference formed during the reverse heat dissipation phase is reintegrated into the heat balance system. Through energy release, the redistribution of heat energy between different rooms is achieved, resulting in a gradual and uniform temperature diffusion throughout the space. Through this alternating operation, heat release no longer occurs in the form of instantaneous high power, but rather as a continuous, slow release of heat, creating a periodic correspondence between the heating and cooling processes in time. The duration of the energy release phase depends on the setting of the cooling compensation cycle. Its main function is to balance the temperature difference between rooms, ensuring that the overall heat flow direction of the space is consistent with the heating sequence, thereby establishing a dynamic thermal equilibrium state.

[0068] Based on the alternation of short-term reverse heat dissipation and energy slow release phases, the entire heating process is periodically cyclically adjusted to establish a long-term stable and coordinated pattern between the cooling compensation cycle and the heating sequence. Through this periodic insertion and alternation, each room receives dynamic temperature compensation during heating, resulting in a regular fluctuation in heat distribution over time, avoiding heat concentration caused by continuous heating in a single area. The cyclical setting of the cooling compensation cycle not only redistributes heat among different rooms but also keeps the overall living space's temperature fluctuation range within a comfortable range. As heating continues, periodic cooling compensation ensures a continuous and balanced heat transfer process between rooms, making the heat flow more coordinated in spatial distribution and maintaining thermal balance and stable comfort in the living environment over long-term operation. Ultimately, through the periodic alternation of short-term reverse heat dissipation and energy slow release, the heat transfer in the living space achieves balanced flow among multiple rooms, fully utilizing the thermal conductivity of the graphene wall surface, and achieving a coordinated and unified state in terms of temperature distribution, energy utilization, and comfort.

[0069] This invention establishes a temperature distribution model and a wall heat transfer characteristic model during multi-room heating operation, enabling accurate control of the direction and time difference of heat flow in space. Dynamic identification of heat transfer patterns is achieved through cycle offset recording. By reconstructing the timing of each room's heating phase and controlling delayed release, heat is distributed in layers in time and space, avoiding localized heat peaks caused by simultaneous energy release. This results in a more balanced temperature distribution on the wall surface, reducing structural stress concentration caused by thermal expansion and contraction, thereby improving the stability of graphene walls and the thermal comfort of living spaces.

[0070] This invention introduces a dynamic balance in heat transfer between different rooms by periodically inserting cooling compensation cycles and alternating short-term reverse heat dissipation and slow energy release during heating operation. This creates a continuous and balanced heat transfer path between rooms, effectively dissipating accumulated heat and optimizing overall energy consumption. Temperature fluctuations in living spaces are controlled, maintaining a stable and comfortable thermal environment, thus achieving the unified goal of energy conservation and healthy living.

[0071] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for intelligent decision making for graphene wall configuration for healthy living scenarios, characterized in that, Includes the following steps: Establish a temperature distribution model and a wall heat transfer characteristic model for the living space. Based on the spatial structure and wall thermal conductivity parameters of each room, construct a schematic diagram of heat transfer between different rooms and determine the direction and time difference of heat flow between each room. Based on the heat transfer diagram, the temperature change curves of adjacent rooms are compared over time. The difference between the start time of temperature rise and the end time of temperature drop is extracted to generate asynchronous feature data of the heating process and form a beat offset record. Based on the beat offset records, energy change analysis is performed on the spatial regions where heat convergence occurs, the correlation parameters between the duration of the temperature peak and the heating rate are calculated, the heat peak risk areas are identified, and the temperature difference abrupt change points are marked in the risk areas to obtain the key location data of the heat peak. Based on the key location data of the heat peak, the heating control sequence is rearranged, and time intervals and delayed release parameters are set so that the heating stages of each room are carried out sequentially, thereby controlling the temporal distribution of the heat release process. Based on the rearranged heating sequence parameters, a cooling compensation cycle is periodically inserted during the heating process, and the temperature distribution of each room is dynamically adjusted through alternating short-term reverse heat dissipation and slow energy release. 2.The method of claim 1, wherein, The steps for constructing a heat transfer diagram are as follows: Establish a temperature distribution model and a wall heat transfer characteristic model for the living space. Based on the geometric dimensions of each room, the orientation of the walls, the layers of the enclosure structure and the location of the openings, form a set of spatial geometric parameters and determine the heat transfer path. Based on the set of spatial geometric parameters and the thermal conductivity parameters of the wall, the thermal conductivity, heat capacity, density and surface radiation properties of the wall material are integrated to generate a set of wall surface heat transfer characteristic parameters. Based on the wall heat transfer characteristic parameter set, the spatial distribution of temperature changes in each room is calculated, a temperature distribution model between rooms is established, and a heat flow continuity boundary condition is introduced. Based on the temperature distribution model and the wall heat transfer characteristic model, a heat transfer diagram is constructed, and the direction and time characteristics of heat flow between rooms are extracted to obtain the heat transfer law between multiple rooms.

3. The intelligent decision-making method for graphene wall configuration in healthy living scenarios according to claim 1, characterized in that, The steps for generating a beat offset record are as follows: Based on the heat transfer diagram, the direction of heat flow and the amount of heat energy between the walls of each room and adjacent rooms in the living space are analyzed. The temperature change process of each room is recorded as a time series curve to form continuous temperature response data for the entire space. By comparing the temperature change curves of adjacent rooms based on time series data, the difference between the start time of temperature rise and the end time of temperature drop is extracted, and the asynchronous characteristics of heating rhythm between rooms are converted into time difference data. Based on the time difference data, asynchronous feature data of the heating process is generated, and a beat offset record is formed to establish a time series label for the heating rhythm between rooms; By using beat offset records to perform overall analysis of temperature change curves, heat concentration and delayed transfer areas are identified, forming a dynamic mapping of heat flow and accumulation in multiple rooms.

4. The intelligent decision-making method for graphene wall configuration in healthy living scenarios according to claim 3, characterized in that, During the generation of the beat offset record, the difference between the start time of temperature rise and the end time of temperature drop is continuously recorded in the form of a time series. The heating rhythm label is established by the change of the time difference, and the temperature response sequence between adjacent rooms is determined according to the heating rhythm label, so that the direction of heat transfer is consistent with the time delay characteristics.

5. The intelligent decision-making method for graphene wall configuration in healthy living scenarios according to claim 3, characterized in that, The steps for obtaining key location data of the thermal peak are as follows: Based on the beat offset records, spatial correlation is performed on the temperature response differences of each room during the heating cycle to identify the areas where heat converges between adjacent rooms and to mark the overlapping time periods of heat energy at the interface. Energy change analysis is performed within the identified heat convergence area, and the duration of the temperature peak is coupled with the heating rate for evaluation, forming a set of correlation parameters between the duration of the temperature peak and the heating rate. Based on the correlation parameters between the duration of the temperature peak and the heating rate, the energy accumulation trend is analyzed, the heat peak risk area is screened and marked, and the spatial boundary and energy characteristics of the heat concentration area are determined. Mark the points of sudden temperature changes within the heat peak risk area to form key location data of the heat peak. 6.The method of claim 5, wherein the method further comprises: determining a location of the graphene wall based on the health-oriented living scenario; and determining a size of the graphene wall based on the health-oriented living scenario. The marking of abrupt temperature change points is based on the slope of the temperature curve and the temperature gradient. In the heat peak risk area, the node with the most obvious change in heating rate and the longest duration of temperature peak is selected as the marker point. A dataset of key locations of heat peak is formed by continuous marking. 7.The method of claim 5, wherein the method further comprises: determining a location of the graphene wall based on the health-oriented living scene; and determining a size of the graphene wall based on the health-oriented living scene. Based on the data of key locations of the heat peak, the heating control sequence was rearranged, and time intervals and delayed release parameters were set to ensure that the heating stages of each room were performed sequentially and to control the time distribution of heat release. The steps are as follows: Based on the obtained data on key locations of heat peaks, the heat distribution characteristics of each room are analyzed, the data on key locations of heat peaks are correlated with the spatial location of the room, and the heating sequence framework is determined by combining the heat conduction direction of the wall and the heat flow path. Based on the distribution of temperature difference abrupt change points in the data of key locations of the heat peak, set time interval parameters so that the heating start-up times of each room are staggered in time. By combining the characteristics of temperature difference abrupt change points in the data of key locations of the heat peak, the delayed release parameters are determined so that the heating stages of different rooms form a progressive relationship in terms of energy release rate, which promotes the gradual diffusion of heat along the transfer direction. A heating control sequence rearrangement scheme is formed based on time interval parameters and delayed release parameters, so that the heating stages of each room unfold sequentially, controlling the temporal distribution of the heat release process. 8.The method of claim 7, wherein the method further comprises: determining a location of the graphene wall based on the health-oriented living scenario; and determining a size of the graphene wall based on the health-oriented living scenario. During the process of forming the heating control sequence rearrangement scheme, the time interval parameters and delayed release parameters are dynamically adjusted according to the temperature gradient distribution in the key location data of the heat peak, so that the start-up sequence of the heating stage is consistent with the direction of heat transfer, thereby forming a continuous heat diffusion path in the spatial range, ensuring the stability of the heat release process and the uniformity of the heat field distribution. 9.The method of claim 7, wherein the method further comprises: determining a location of the graphene wall based on the health-oriented living scene; and determining a size of the graphene wall based on the health-oriented living scene. Based on the heating sequence parameters, a cooling compensation cycle is periodically inserted during heating operation. The temperature distribution in each room is dynamically adjusted by alternating short-term reverse heat dissipation and slow energy release. The steps are as follows: Based on the rearranged heating sequence parameters, the temperature change trend during the multi-room heating process is analyzed to determine the heat transfer sequence and energy accumulation period between rooms, and the temperature growth rate is used as the basis for setting the cooling compensation cycle. After determining the time point of the cooling compensation cycle, a short-term reverse heat dissipation process is implemented, so that the wall at the peak energy stage releases some heat to the low temperature area through reverse heat conduction, thereby realizing the redistribution of heat in the space. After the short-term reverse heat dissipation ends, an energy release phase is implemented. By reducing the heat release rate of the wall, the temperature gradually transitions in the space, establishing a dynamic thermal equilibrium state. The alternation of short-term reverse heat dissipation and energy slow release phases forms a periodic cycle regulation, enabling balanced heat transfer among multiple rooms.

10. The intelligent decision-making method for graphene wall configuration in healthy living scenarios according to claim 9, characterized in that, During short-term reverse heat dissipation, by controlling the instantaneous switching of the heat conduction direction of the wall, heat energy is diffused from the high-temperature area to the adjacent low-temperature area, and the heat release rate is continuously reduced during the energy release phase, so that the temperature difference between rooms is gradually balanced, thereby achieving the stability of heat transfer and the uniformity of spatial temperature distribution in the periodic cycle.

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