A human body dressing recommendation method based on ambient temperature

Abstract

The application discloses a human body dressing recommendation method based on environment temperature, comprising the following steps: S1, a human body physiological heat regulation mathematical model is established, a human body active regulation and passive regulation heat transfer process under different indoor and outdoor environments is simulated, and human body heat feeling change rules under different indoor and outdoor environments are revealed; S2, a clothing porous medium heat and mass transfer mechanism and an air layer distribution rule under clothes are analyzed, a clothing and air layer heat and moisture transfer coupling model is established, a human body skin surface heat and moisture transfer boundary condition is constructed, and a human body heat and moisture transfer mechanism under different indoor and outdoor environments is revealed; S3, finite difference method is used for discrete solution of the above numerical model, and the established numerical model is verified and optimized; and S4, a clothing basic style visual database is established in combination with the human body heat transfer model. The application provides the human body dressing recommendation method based on the environment temperature, and provides more scientific decision for clothing collocation of consumers under different environments.

Description

Technical Field

[0001] This invention relates to the field of clothing recommendation technology, and more particularly to a method for recommending clothing based on ambient temperature. Background Technology

[0002] The frequent occurrence of extreme weather events in recent years has posed a severe challenge to human safety and health. Appropriate clothing has become the simplest and most effective way to ensure thermal comfort in extreme environments. Currently, most people rely on their own experience and climate parameters to determine their daily clothing choices. However, actual surveys have found that this approach can easily lead to being too cold or too hot, resulting in inappropriate attire. This is especially true when we rely solely on temperature to determine clothing choices, ignoring factors such as ambient humidity, wind speed, and the individual's work status; the probability of inappropriate clothing increases significantly in these cases. While weather forecasts do provide clothing suggestions for different temperatures and weather conditions, their practicality remains questionable.

[0003] Patent publication number CN109800357A discloses a weather-based clothing recommendation method and system. The method includes: establishing a user's body model; scanning all of the user's clothing and storing the scan data; the scan data includes clothing images, colors, sizes, materials, and styles; obtaining current weather information; and recommending clothing to the user based on the body model, the weather information, and the scan data. This invention relies on specialized instrument models, making the process complex and costly. Ordinary instruments struggle to obtain accurate data, thus failing to provide precise clothing recommendations tailored to the user's needs.

[0004] Patent CN108733829A discloses an intelligent clothing recommendation device and method. The device includes a weighing sensor at each clothing hanging position to acquire weight information when clothing is present at that position. A pre-established conversion relationship between clothing weight and suitable ambient temperature is used to determine the appropriate ambient temperature for the clothing based on its weight. The device then selects weather conditions including temperature information for the city chosen by the user, or acquires the outdoor temperature information of the device's location, and matches recommended clothing to the user based on this temperature information. When the user opens the device's door, the recommended clothing is moved sequentially to the door for selection based on the ambient temperature. However, this invention only recommends clothing of different weights based on ambient temperature. Many factors influence clothing comfort, such as humidity and airflow, so the recommendations may not always be ideal.

[0005] The invention disclosed in CN107066628A proposes a clothing recommendation method and apparatus. The method includes: obtaining a first feature vector of clothing to be recommended; inputting the first feature vector into a machine learning model for learning to obtain target attributes of the clothing to be recommended; and generating target clothing recommendations for the user based on current weather information and the target attributes of the clothing to be recommended. However, this invention does not consider human temperature perception and is therefore impractical.

[0006] The literature with DOI number 10.16454 / j.cnki.issn.1001-0564.2021.03.015 presents the research progress of clothing recommendation systems. This paper utilizes a literature survey to conduct a visual analysis of the publication volume and keywords of relevant domestic and international literature on clothing recommendation systems, summarizing the development trends of clothing recommendation systems. Based on this, the key technologies and methods of clothing recommendation systems are summarized from four aspects: sensory evaluation, fuzzy technology, collaborative filtering, and machine learning. While this literature considers the technology of clothing recommendation systems in several aspects, it fails to consider the changes in body temperature under different weather conditions and thus fails to provide personalized customization analysis for clothing choices.

[0007] Current technology does not yet provide suitable clothing for different people in different weather conditions based on the principle of heat and moisture transfer between the environment, clothing, and the human body, resulting in significant shortcomings in the application of human thermal comfort and personal protective equipment in extreme environments. Summary of the Invention

[0008] The purpose of this invention is to provide a method for recommending clothing based on ambient temperature. Based on the thermal and moisture balance relationship among the environment, clothing, and human body, the invention deconstructs the intelligent clothing matching system to provide consumers with more scientific decision-making for clothing matching in different environments.

[0009] The technical solution adopted in the human clothing recommendation method based on ambient temperature disclosed in this invention is as follows:

[0010] A method for recommending clothing for the human body based on ambient temperature includes the following steps:

[0011] S1. Establish a mathematical model of human physiological thermoregulation. By simulating the heat transfer process of human active and passive regulation under different indoor and outdoor environments, obtain various human thermophysiological indicators and reveal the pattern of human thermal sensation change under different indoor and outdoor environments.

[0012] S2, analyze the heat and mass transfer mechanism of porous media in clothing and the distribution law of the air layer under clothing, establish a coupled model of heat and moisture transfer between clothing and the air layer under clothing, construct the boundary conditions of heat and moisture transfer on the surface of human skin, clarify the coupling method of the "environment-clothing-human body" heat and moisture transfer model, and reveal the heat and moisture transfer mechanism of the human body in different indoor and outdoor environments.

[0013] S3. The numerical model above is solved by discrete solution using the finite difference method to verify and optimize the established numerical model.

[0014] S4 establishes a visual database of basic clothing styles, combined with a human body heat transfer model, to provide users with reference solutions for daily clothing matching.

[0015] As a preferred embodiment, the mathematical model of human physiological thermoregulation in step S1 is divided into two parts: a passive system and an active system. The passive system calculates the heat exchange between different layers of tissues inside the human body. The active system actively regulates and controls human thermophysiology through the central nervous system, including blood expansion / contraction, shivering, and sweating.

[0016] As a preferred approach, numerical simulation of the passive system:

[0017] Based on the physiological characteristics of different parts of the human body, the human thermoregulation model is divided into 34 segments, mainly including the face, head, upper arm, forearm, hand, chest, shoulder, abdomen, back, buttock, thigh, calf and foot. Each segment is mainly divided into 5 layers, from the inside out: core layer, muscle layer, fat layer, dermis layer and epidermis layer. Based on the heat exchange principle of each tissue layer, the transient heat transfer equations of different tissue layers are established as follows: (1) to (5):

[0018] Core layer:

[0019] Muscle layer:

[0020] Fat layer:

[0021] Dermis:

[0022] Epidermis:

[0023] In the formula, C is the heat capacity of the core layer, T is the temperature of each layer of the human body, t is the exposure time, k is the thermal conductivity of each layer of the human body, and Q is the heat generation rate of the human body. Here, ρ represents the countercurrent heat exchange ratio, w represents the blood perfusion rate, ρ represents the density of each tissue layer, c represents the specific heat of each tissue layer, subscript c represents the core layer, subscript m represents metabolic heat production, subscript bas represents basal metabolic heat production, subscript add represents additional heat production, subscript b represents blood, subscript s represents shivering, subscript w represents work done, and subscript respiration represents respiration. The body's heat production is derived from basal metabolic heat production q. m，bas Additional metabolic heat production q m，add , work q w and tremors producing heat q S It consists of four parts.

[0024] As a preferred approach, active system numerical simulation:

[0025] The human body's active thermoregulation system consists of four parts: vasoconstriction, vasodilation, shivering, and sweating. Under different environments, the human active thermoregulation system can receive external temperature signals and increase heat production and slow heat dissipation by increasing shivering and reducing blood flow. Assuming the threshold range that inhibits the excitation of human temperature-sensing neurons is the ineffective region, meaning that the human body maintains thermal equilibrium and does not produce thermoregulation when its temperature is within the ineffective region (T0), the human body will exhibit thermoregulation. unllzone When the body's blood vessels constrict, shivering increases, and sweating decreases, the body loses heat loss to the external environment and increases heat production. Therefore, based on the division of the temperature ineffective region, the active thermal regulation equation of the human body under different environments is obtained, and the control parameters are revised according to the weight of each segment of the human body, which are used as the input parameter values ​​of the model.

[0026] Among them, the blood perfusion rate of the human body w b It is affected by hot and cold signals, and is determined by the baseline blood perfusion rate (w). m，bas ) and additional blood perfusion rate (w b，add It consists of two parts, taking into account the effects of vasoconstriction / vasodilation, and the calculation equation is as follows (6):

[0027]

[0028] In the formula, S v and S c These are the vasodilation and vasoconstriction control coefficients, D. L and S T These are the vasodilation and vasoconstriction signals in the active regulation function, respectively. Err is the temperature signal deviation, and the blood perfusion rate of the muscle layer is also related to the human body's work and trembling.

[0029] The extra metabolic heat q generated by the human body when it receives hot or cold signals. m，add It can be calculated using the following temperature equation formula (7):

[0030]

[0031] At the same time, due to the extra work done by the human body (q) w ) and trembling (q S The metabolic heat generated by the muscle layer can be calculated using the following formulas (8) and (9):

[0032] q w =58.2(Met-0.778)A seg Merf

[0033] q s =C ch Err(1)+S ch (Wrms-Clds)+P ch Clds(1)CldsChit

[0034] In the formula, Met represents the metabolic heat generated by the body's extra work, Merf is the metabolic heat distribution coefficient of the muscle layer, and A seg C represents the area of ​​each segment of the human body, Chit is the heat distribution coefficient of muscle layer tremor, and C ch S is the core layer of the head's tremor control coefficient. ch p represents the tremor control coefficient for different skin segments of the human body. ch , where Wrms and Clds are the tremor control coefficients for the core layer of the head and other skin segments, respectively;

[0035] The human body may produce sweat under different working conditions. The amount of sweat depends on factors such as ambient temperature, level of human activity, and clothing parameters. The heat loss E caused by sweat evaporation is significant. sw The calculation is performed using the following formula (10):

[0036]

[0037] In the formula, C sw S is the control coefficient for sweating in the core layer of the head. sw P represents the sweating control coefficient for different skin layers of the human body. sw SKINS is the sweat control coefficient for the core layer of the head and other skin segments, and the weighting coefficient for human vasoconstriction thermoregulation.

[0038] As a preferred option, the dynamic modeling of heat and moisture transfer in the porous media of clothing in step S2 is performed.

[0039] Clothing differs from ordinary engineering solid materials, having a porous media structure with three phases: gas, liquid, and solid. Based on fractal geometry theory and the Monte Carlo method, a multi-scale complex structure of porous materials is constructed, and the following assumptions are made: the gas, liquid, and solid phases inside the clothing maintain thermodynamic equilibrium during human movement; since the thickness of clothing is much smaller than its surface area, most studies only consider the one-dimensional heat and moisture transfer process along the thickness direction of the clothing, ignoring the influence of multi-dimensional heat and moisture transfer; incident radiation on the surface of clothing can penetrate into the clothing to a certain depth, but there is an exponential decay phenomenon during the transfer process; considering the influence of moisture diffusion, phase change, and adsorption or desorption on heat transfer, based on this, the transient heat transfer equation within the clothing layer is established as formula (11):

[0040]

[0041] In the formula, the left side represents the heat storage capacity of the clothing system, the first term on the right side represents the conductive heat transfer of the clothing system, the second term on the right side represents the radiative heat transfer of the clothing system, the third term on the right side represents the latent heat change caused by the phase change of moisture, and the fourth term on the right side represents the latent heat change caused by the adsorption / desorption of moisture by fibers. Where p fab 、(c p ) fab k fab These represent the density, specific heat capacity, and thermal conductivity of each layer of clothing, respectively; T represents the temperature value at different times and locations; and q represents the temperature value at different locations. rad h is the incident radiation heat flux. vap with h abs These are the enthalpy changes of water evaporation / condensation and adsorption / desorption, respectively, m vs m vl m ls These are the mass conversion rates of the gas phase to the solid phase, the gas phase to the liquid phase, and the liquid phase to the solid phase, respectively.

[0042] Driven by the vapor concentration and pressure difference between the inner and outer surfaces of the garment, and based on Darcy's law and Fick's diffusion law, the gas phase mass conservation equation is established as formula (12):

[0043]

[0044] In the formula, the first term on the left represents the water vapor content in the pores of the garment; the second term on the left represents Darcy flow driven by pressure difference; the first term on the right represents molecular diffusion driven by concentration difference; and the second and third terms on the right represent the phase transition and adsorption rates of water, respectively. Where p v ε represents the gas phase concentration in the clothing. g V represents the gas phase volume fraction in clothing. g D represents the Darcy velocity of the gas phase inside the garment. f The Fick diffusion coefficient is the coefficient of diffusion within the garment.

[0045] Phase change, hygroscopicity, and desorption of water (m vl m vs m ls The heat-moisture coupling process inside clothing is related to the moisture concentration difference and the hygroscopic properties of fibers, and can be expressed by the following calculation formulas (13) to (16):

[0046] m vl,cond =h m,fad α s (p v -p v,sat ) p v ≥p v,sat

[0047]

[0048]

[0049]

[0050] In the formula, h m,fad α is the convective mass transfer coefficient inside the garment. s p is the specific surface area of ​​the fabric per unit volume. v,sat The saturated water vapor concentration d represents the volume fraction threshold for liquid water in a flowing state. f R represents the diameter of the fiber. f，ep R represents the moisture content at the fiber surface equilibrium moment. f γ represents the transient moisture content of the fiber. ls This represents the percentage of free water adsorbed by the fiber.

[0051] As a preferred approach, regarding the discrete solution of the numerical model:

[0052] The heat and moisture transfer within the clothing system involves coupling between different phases, as well as mutual coupling between heat transfer and moisture transfer. The proposed models mainly include the human body thermal regulation model, the internal heat transfer model of clothing, and the mass conservation model of moisture, all of which belong to nonlinear partial differential equations. In order to reduce the error of the model calculation, the implicit finite difference method is used to discretize the model, construct a tridiagonal matrix, and use the Thomas iteration method to solve the nonlinear equation system.

[0053] First, the mass conservation equations for solid and liquid phase moisture are solved to obtain the percentages of solid and liquid water inside the garment, thus further determining the percentage of gaseous phase moisture inside the garment. Second, the mass conservation equation for gaseous phase moisture is solved to obtain the concentration ρv of water vapor inside the garment. Finally, based on the above results, the temperature distribution T of the human body and garment system can be obtained. Using the results as new initial conditions, the heat and moisture transfer at the next moment is calculated according to the above solution process. The mesh generation accuracy of this model is 1.5 × 10⁻⁶. -5 To increase the accuracy and stability of the calculations, the time interval for model iteration is 1×10^m. -1 s.

[0054] As a preferred option, the accuracy of the prediction results in step S4 is also verified.

[0055] An outdoor human clothing experiment was conducted to verify and optimize the accuracy and reliability of the established clothing recommendation system based on subjective evaluations and objective physiological responses of the wearer. The experiment acquired overall and local thermal sensations, subjective comfort, and skin temperature of the human body while wearing clothing to verify whether the recommended clothing could maintain thermal comfort in this environment. The subjective thermal sensation score reflects whether the human body is thermally neutral under the corresponding environmental conditions. A thermal sensation score close to 0 indicates that the subject's temperature sensation is moderate, and the recommended clothing is suitable for the corresponding environmental conditions. The subjective comfort score directly reflects whether the human body is comfortable while wearing the recommended clothing; a higher comfort score indicates greater comfort. There is a certain correlation between thermal sensation and comfort scores: the further the thermal sensation score deviates from 0, the lower the comfort score; the closer the thermal sensation score is to 0, the higher the comfort score. Average skin temperature reflects whether the human body is thermally comfortable under the corresponding environmental conditions from an objective physiological perspective. The judgment is based on the functional relationship between average skin temperature and corresponding activity level when the human body is in a thermally comfortable state.

[0056] The beneficial effects of the human body clothing recommendation method based on ambient temperature disclosed in this invention are as follows: Unlike existing clothing fashion style matching systems that do not consider the comfort of wearing clothing, this method is based on the thermal and moisture balance relationship between the "environment-clothing-human body", and in particular, it introduces the theoretical system of multiple disciplines such as biological heat transfer and fluid dynamics to deconstruct the intelligent clothing matching system, providing consumers with more scientific decisions on clothing matching in different weather and situations. Attached Figure Description

[0057] Figure 1 This is a flowchart of a method for recommending clothing for the human body based on ambient temperature, according to the present invention.

[0058] Figure 2 This is a mesh diagram of the partial differential equation for a human clothing recommendation method based on ambient temperature according to the present invention. Detailed Implementation

[0059] The present invention will be further described and illustrated below with reference to specific embodiments and the accompanying drawings:

[0060] Please refer to Figure 1 A method for recommending clothing for the human body based on ambient temperature includes the following steps:

[0061] S1. Establish a mathematical model of human physiological thermoregulation. By simulating the heat transfer process of human active and passive regulation under different indoor and outdoor environments, obtain various human thermophysiological indicators and reveal the changing patterns of human thermal sensation under different indoor and outdoor environments.

[0062] The mathematical model of human physiological thermoregulation in step S1 is divided into two parts: a passive system and an active system. The passive system calculates the heat exchange between different layers of tissues inside the human body. The active system actively regulates and controls human thermophysiology through the central nervous system, including blood expansion / contraction, shivering, and sweating.

[0063] Numerical simulation of passive systems:

[0064] Based on the physiological characteristics of different parts of the human body, the human thermoregulation model is divided into 34 segments, mainly including the face, head, upper arm, forearm, hand, chest, shoulder, abdomen, back, buttock, thigh, calf and foot. Each segment is mainly divided into 5 layers, from the inside out: core layer, muscle layer, fat layer, dermis layer and epidermis layer. Based on the heat exchange principle of each tissue layer, the transient heat transfer equations of different tissue layers are established as follows: (1) to (5):

[0065] Core layer:

[0066] Muscle layer:

[0067] Fat layer:

[0068] Dermis:

[0069] Epidermis:

[0070] In the formula, C is the heat capacity of the core layer, T is the temperature of each layer of the human body, t is the exposure time, k is the thermal conductivity of each layer of the human body, and Q is the heat generation rate of the human body. Here, ρ represents the countercurrent heat exchange ratio, w represents the blood perfusion rate, ρ represents the density of each tissue layer, c represents the specific heat of each tissue layer, subscript c represents the core layer, subscript m represents metabolic heat production, subscript bas represents basal metabolic heat production, subscript add represents additional heat production, subscript b represents blood, subscript s represents shivering, subscript w represents work done, and subscript respiration represents respiration. The body's heat production is derived from basal metabolic heat production q. m，bas Additional metabolic heat production q m，add , work q w and tremors producing heat q S It consists of four parts.

[0071] Numerical simulation of active systems:

[0072] The human body's active thermoregulation system consists of four parts: vasoconstriction, vasodilation, shivering, and sweating. Under different environments, the human active thermoregulation system can receive external temperature signals and increase heat production and slow heat dissipation by increasing shivering and reducing blood flow. Assuming the threshold range that inhibits the excitation of human temperature-sensing neurons is the ineffective region, meaning that the human body maintains thermal equilibrium and does not produce thermoregulation when its temperature is within the ineffective region (T0), the human body will exhibit thermoregulation. unllzone When the body's blood vessels constrict, shivering increases, and sweating decreases, the body loses heat loss to the external environment and increases heat production. Therefore, based on the division of the temperature ineffective region, the active thermal regulation equation of the human body under different environments is obtained, and the control parameters are revised according to the weight of each segment of the human body, which are used as the input parameter values ​​of the model.

[0073] Among them, the blood perfusion rate of the human body w b It is affected by hot and cold signals, and is determined by the baseline blood perfusion rate (w). m，bas ) and additional blood perfusion rate (w b，add It consists of two parts, taking into account the effects of vasoconstriction / vasodilation, and the calculation equation is as follows (6):

[0074]

[0075] In the formula, S v and S c These are the vasodilation and vasoconstriction control coefficients, D. L and S T These are the vasodilation and vasoconstriction signals in the active regulation function, respectively. Err is the temperature signal deviation, and the blood perfusion rate of the muscle layer is also related to the human body's work and trembling.

[0076] The extra metabolic heat q generated by the human body when it receives hot or cold signals. m，add It can be calculated using the following temperature equation formula (7):

[0077]

[0078] At the same time, due to the extra work done by the human body (q) w ) and trembling (q S The metabolic heat generated by the muscle layer can be calculated using the following formulas (8) and (9):

[0079] q w =58.2(Met-0.778)A seg Merf

[0080] q s =C ch Err(1)+S ch(Wrms-Clds)+P ch Clds(1)CldsChit

[0081] In the formula, Met represents the metabolic heat generated by the body's extra work, Merf is the metabolic heat distribution coefficient of the muscle layer, and A seg C represents the area of ​​each segment of the human body, Chit is the heat distribution coefficient of muscle layer tremor, and C ch S is the core layer of the head's tremor control coefficient. ch p represents the tremor control coefficient for different skin segments of the human body. ch , where Wrms and Clds are the tremor control coefficients for the core layer of the head and other skin segments, respectively;

[0082] The human body may produce sweat under different working conditions. The amount of sweat depends on factors such as ambient temperature, level of human activity, and clothing parameters. The heat loss E caused by sweat evaporation is significant. sw The calculation is performed using the following formula (10):

[0083]

[0084] In the formula, C sw S is the control coefficient for sweating in the core layer of the head. sw P represents the sweating control coefficient for different skin layers of the human body. sw SKINS is the sweat control coefficient for the core layer of the head and other skin segments, and the weighting coefficient for human vasoconstriction thermoregulation.

[0085] S2, analyze the heat and mass transfer mechanism of porous media in clothing and the distribution law of the air layer under clothing, establish a coupled model of heat and moisture transfer between clothing and the air layer under clothing, construct the boundary conditions of heat and moisture transfer on the surface of human skin, clarify the coupling method of the "environment-clothing-human body" heat and moisture transfer model, and reveal the heat and moisture transfer mechanism of the human body in different indoor and outdoor environments.

[0086] Modeling of heat and moisture transfer dynamics in porous media of clothing in step S2

[0087] Clothing differs from ordinary engineering solid materials, having a porous media structure with three phases: gas, liquid, and solid. Based on fractal geometry theory and the Monte Carlo method, a multi-scale complex structure of porous materials is constructed, and the following assumptions are made: the gas, liquid, and solid phases inside the clothing maintain thermodynamic equilibrium during human movement; since the thickness of clothing is much smaller than its surface area, most studies only consider the one-dimensional heat and moisture transfer process along the thickness direction of the clothing, ignoring the influence of multi-dimensional heat and moisture transfer; incident radiation on the surface of clothing can penetrate into the clothing to a certain depth, but there is an exponential decay phenomenon during the transfer process; considering the influence of moisture diffusion, phase change, and adsorption or desorption on heat transfer, based on this, the transient heat transfer equation within the clothing layer is established as formula (11):

[0088]

[0089] In the formula, the left side represents the heat storage capacity of the clothing system, the first term on the right side represents the conductive heat transfer of the clothing system, the second term on the right side represents the radiative heat transfer of the clothing system, the third term on the right side represents the latent heat change caused by the phase change of moisture, and the fourth term on the right side represents the latent heat change caused by the adsorption / desorption of moisture by fibers. Where p fab 、(c p ) fab k fab These represent the density, specific heat capacity, and thermal conductivity of each layer of clothing, respectively; T represents the temperature value at different times and locations; and q represents the temperature value at different locations. rad h is the incident radiation heat flux. vap with h abs These are the enthalpy changes of water evaporation / condensation and adsorption / desorption, respectively, m vs m vl m ls These are the mass conversion rates of the gas phase to the solid phase, the gas phase to the liquid phase, and the liquid phase to the solid phase, respectively.

[0090] Driven by the vapor concentration and pressure difference between the inner and outer surfaces of the garment, and based on Darcy's law and Fick's diffusion law, the gas phase mass conservation equation is established as formula (12):

[0091]

[0092] In the formula, the first term on the left represents the water vapor content in the pores of the garment; the second term on the left represents Darcy flow driven by pressure difference; the first term on the right represents molecular diffusion driven by concentration difference; and the second and third terms on the right represent the phase transition and adsorption rates of water, respectively. Where p v ε represents the gas phase concentration in the clothing. g V represents the gas phase volume fraction in clothing. g D represents the Darcy velocity of the gas phase inside the garment. f The Fick diffusion coefficient is the coefficient of diffusion within the garment.

[0093] Phase change, hygroscopicity, and desorption of water (m vl m vs m ls The heat-moisture coupling process inside clothing is related to the moisture concentration difference and the hygroscopic properties of fibers, and can be expressed by the following calculation formulas (13) to (16):

[0094] m vl,cond =h m,fad α s (p v -p v,sat ) p v ≥p v,sat

[0095]

[0096]

[0097]

[0098] In the formula, h m,fad α is the convective mass transfer coefficient inside the garment. s p is the specific surface area of ​​the fabric per unit volume. v,sat The saturated water vapor concentration d represents the volume fraction threshold for liquid water in a flowing state. f R represents the diameter of the fiber. f，ep R represents the moisture content at the fiber surface equilibrium moment. f γ represents the transient moisture content of the fiber. ls This represents the percentage of free water adsorbed by the fiber.

[0099] 8.S3, Use the finite difference method to discretely solve the above numerical model, verify and optimize the established numerical model. Regarding the discrete solution of the numerical model:

[0100] The heat and moisture transfer within the clothing system involves coupling between different phases, as well as mutual coupling between heat transfer and moisture transfer. The proposed models mainly include the human body thermal regulation model, the internal heat transfer model of clothing, and the mass conservation model of moisture, all of which belong to nonlinear partial differential equations. In order to reduce the error of the model calculation, the implicit finite difference method is used to discretize the model, construct a tridiagonal matrix, and use the Thomas iteration method to solve the nonlinear equation system.

[0101] First, the mass conservation equations for solid and liquid phase moisture are solved to obtain the percentages of solid and liquid water inside the garment, thus further determining the percentage of gaseous phase moisture inside the garment. Second, the mass conservation equation for gaseous phase moisture is solved to obtain the concentration ρv of water vapor inside the garment. Finally, based on the above results, the temperature distribution T of the human body and garment system can be obtained. Using the results as new initial conditions, the heat and moisture transfer at the next moment is calculated according to the above solution process. The mesh generation accuracy of this model is 1.5 × 10⁻⁶. -5 To increase the accuracy and stability of the calculations, the time interval for model iteration is 1×10^m. -1 s.

[0102] Taking formula (11) as an example, the specific discretization process is as follows:

[0103] ① Establish a function relating time and location, uniformly dividing the location into {x1, x2, ..., xn}. i Divide the time interval evenly into {t1, t2, ..., t}. j}, specifically as Figure 2 As shown;

[0104] ② Set the spatial step size to 1.5 × 10 -5 m, with a time step of 1 second, each node can be represented as (x i ,t j By taking the forward difference with respect to the time derivative in formula (11), we obtain formula (17):

[0105]

[0106] ③ By differentiating the right side of equation (11) according to the CN difference scheme in the implicit difference method, we can obtain equation (18):

[0107]

[0108] ④ Substituting equations (17) and (18) into equation (11), we obtain the discrete form of the heat transfer equation inside the garment, as shown in equation (19):

[0109]

[0110] ⑤ To facilitate calculation and solution, define variable F. fab Specifically, as shown in equation (20):

[0111]

[0112] ⑥ Substituting equation (20) into equation (19), the final form of the heat transfer equation inside the garment is shown in equation (21):

[0113]

[0114] Based on the discretization method described above, other heat and moisture transfer equations and boundary conditions were also discretized to obtain a set of discrete equations. A program was written and solved using Matlab R2017a software to obtain results such as human skin temperature and heat flux density on the clothing surface.

[0115] S4: Establish a visual database of basic clothing styles, design interactive drafts for an intelligent recommendation system APP, and combine it with a human body heat transfer model to implement front-end page interaction effects on user terminals (iOS / Android) to provide users with reference solutions for daily clothing matching.

[0116] The above scheme also includes verifying the accuracy of the prediction results in step S4:

[0117] An outdoor human clothing experiment was conducted to verify and optimize the accuracy and reliability of the established clothing recommendation system based on subjective evaluations and objective physiological responses of the wearer. The experiment acquired overall and local thermal sensations, subjective comfort, and skin temperature of the human body while wearing clothing to verify whether the recommended clothing could maintain thermal comfort in this environment. The subjective thermal sensation score reflects whether the human body is thermally neutral under the corresponding environmental conditions. A thermal sensation score close to 0 indicates that the subject's temperature sensation is moderate, and the recommended clothing is suitable for the corresponding environmental conditions. The subjective comfort score directly reflects whether the human body is comfortable while wearing the recommended clothing; a higher comfort score indicates greater comfort. There is a certain correlation between thermal sensation and comfort scores: the further the thermal sensation score deviates from 0, the lower the comfort score; the closer the thermal sensation score is to 0, the higher the comfort score. Average skin temperature reflects whether the human body is thermally comfortable under the corresponding environmental conditions from an objective physiological perspective. The judgment is based on the functional relationship between average skin temperature and corresponding activity level when the human body is in a thermally comfortable state.

[0118] For example, when the human body is at a 2 MET activity level, the average skin temperature at which the human body feels thermally comfortable is about 32.5°C; when the human body is at a 4 MET activity level, the average skin temperature at which the human body feels thermally comfortable is about 29°C.

[0119] Unlike existing clothing fashion and style systems that do not consider the comfort and safety of clothing, this invention establishes a more accurate human body temperature regulation model through the interdisciplinary application of clothing science, engineering thermophysics, and human physiology. This represents a digital innovation in human safety and health assessment methods and clothing wearing patterns. Furthermore, unlike the heat and moisture transfer characteristics of conventional solid materials, existing models cannot reveal the complex relationship between heat and moisture transfer in clothing and human safety and comfort due to the porous structure and hygroscopic properties of clothing materials. This invention introduces the theories of porous media heat and mass transfer and fractal geometry to propose a multi-phase heat transfer and dynamics model of clothing from a microscopic perspective. This enables the prediction of human safety and health through clothing, providing a more adaptable and accurate method.

[0120] This invention provides a method for recommending clothing based on ambient temperature. Unlike existing clothing fashion style matching systems that do not consider the comfort of wearing clothing, this method is based on the thermal and moisture balance relationship between the environment, clothing, and human body. In particular, it introduces the theoretical system of multiple disciplines such as biological heat transfer and fluid dynamics to deconstruct the intelligent clothing matching system, providing consumers with more scientific decisions on clothing matching in different weather and situations.

[0121] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A method for recommending clothing for the human body based on ambient temperature, characterized in that, The method comprises the following steps: S1, a human physiological thermal regulation mathematical model is established, the heat transfer process of human active regulation and passive regulation under different indoor and outdoor environments is simulated, human thermal physiological indexes are obtained, and the human thermal sensation change law under different indoor and outdoor environments is revealed; S2, the heat and mass transfer mechanism of the clothing porous medium and the distribution law of the air layer under the clothing are analyzed, a heat and moisture transfer coupling model of the clothing and the air layer under the clothing is established, a heat and moisture transfer boundary condition of the human skin surface is constructed, a coupling method of the "environment-clothing-human" heat and moisture transfer model is determined, and the heat and moisture transfer mechanism of the dressed human body under different indoor and outdoor environments is revealed; S3, the finite difference method is used for discrete solving of the above numerical model, and the established numerical model is verified and optimized; the discrete solving of the numerical model: the heat and moisture transfer in the clothing system is coupled between different phases, and is also coupled between heat transfer and moisture transfer, the proposed model includes a human thermal regulation model, a clothing internal heat transfer model and a moisture mass conservation model, which all belong to nonlinear partial differential equations, in order to reduce the calculation error of the model, the implicit finite difference method is used for discrete analysis of the model, a three-diagonal matrix is constructed, and the Thomas iteration method is used to solve the nonlinear equation set; Firstly, the mass conservation equations of solid and liquid water are solved to obtain the percentages of solid and liquid water in the clothing, and then the percentage of gas phase is calculated. Secondly, the mass conservation equation of gas water is solved to obtain the concentration of water vapor in the clothing. Finally, the temperature distribution of the human-clothing system is obtained based on the above results. The results of the calculation are used as the new initial conditions, and the heat and moisture transfer at the next time is calculated according to the above solving process. The grid division accuracy of the model is m, in order to increase the accuracy and stability of the calculation, the time interval of the model iteration is s; S4, a clothing basic style visualization database is established, the human physiological thermal regulation mathematical model and the heat and moisture transfer coupling model of the clothing and the air layer under the clothing are combined, and reference schemes are provided for user daily clothing matching.

2. The method of claim 1, wherein the environmental temperature is determined by a temperature sensor. The human physiological thermal regulation mathematical model in step S1 is divided into passive system and active system: the passive system calculates the heat exchange between the internal tissues of the human body; The active system realizes human thermal physiological regulation and control through active regulation of the central system, including blood dilation / contraction, shivering and sweating.

3. The method of claim 2, wherein the ambient temperature is determined by a temperature sensor. Passive system numerical simulation: According to the physiological characteristics of different parts of the human body, the human thermal regulation model is divided into 34 sections, including face, head, upper arm, forearm, hand, chest, shoulder, abdomen, back, hip, thigh, lower leg and foot sections, each section is divided into 5 layers from inside to outside, which are core layer, muscle layer, fat layer, dermis layer and epidermis layer, based on the heat exchange principle of each layer of tissue, the transient heat transfer equations of different tissue layers are established in the following formulas (1) to (5): Core layer: muscle layer: Fatty layer: dermis layer: Epidermal layer: where C is the heat capacity of the core, T is the temperature of each layer of the body, t is the exposure time, k is the thermal conductivity of each layer of the body, Q is the rate of heat production by the body, and a is the counterflow heat exchange ratio, is the blood perfusion rate, is the density of each layer, c is the specific heat of each layer, subscript c is the core, subscript m is metabolic heat production, subscript bas is basal metabolic heat production, subscript add is additional heat production, subscript b is blood, subscript s is shivering, subscript w is work, subscript res is respiration, and the heat production by the body is composed of basal metabolic heat production , additional metabolic heat production , work , and shivering heat production .

4. The method of claim 3, wherein the environmental temperature is determined by a temperature sensor. Active system numerical simulation: The human active thermal regulation system is composed of four parts, namely vasoconstriction, vasodilation, shivering and sweating. In different environments, the human active thermal regulation system can accept the cold and hot signals from the external environment, increase the body shivering and reduce the blood flow to increase the heat production and slow down the heat dissipation. It is assumed that the threshold range of inhibiting the excitation of human temperature sensory neurons is the invalid area, that is, the human body temperature is within the invalid area, the human body maintains thermal equilibrium state and does not produce thermal regulation effect. When the temperature of a certain node of the human body is lower than the lower limit temperature of the invalid area , the human body vasoconstriction, shivering increases and the body surface sweating decreases, thereby reducing the heat dissipation of the human body to the external environment and increasing the heat production. Therefore, according to the division of the temperature invalid area, the human active thermal regulation equation in different environments is obtained, and the control parameter is revised according to the weight of each section of the human body, which is used as the input parameter value of the model. where the blood perfusion rate of the human body will be affected by the cold and hot signals, the basic blood perfusion rate and the additional blood perfusion rate Two parts, while considering the influence of vasodilation / vasoconstriction, the calculation equation is as follows Formula (6): wherein, and are vasodilation and vasoconstriction control coefficients, respectively, and are vasodilation and vasoconstriction signals in active regulation, respectively, is a temperature signal bias, and the blood perfusion rate of the muscle layer is also related to the human body's work and tremor. Metabolic heat production due to the cold and heat signals received by the human body may be calculated by the following temperature equation (7): Meanwhile, due to the additional work done by the human body and tremor The metabolic heat generated by the muscle layer can be calculated by the following formulas (8) and (9): where Met is the metabolic heat production due to the extra work of the human body, Merf is the metabolic heat production distribution coefficient of the muscle layer, is the area of each segment of the human body, Chit is the shivering heat production distribution coefficient of the muscle layer, is the shivering control coefficient of the core layer of the head, is the shivering control coefficient of the skin layer of each segment of the human body, is the shivering control coefficient of the core layer of the head and the skin layer of other segments, Wrms and Clds are the temperature heat signal and cold signal, respectively; The human body can produce sweat when working in different environments, and the amount of sweat depends on the factors of environmental temperature, human activity level, clothing parameters, and heat loss generated by sweat evaporation This is calculated by the following equation (10): wherein, SKINH is the head core layer sweat control coefficient, SKIN is the body segment skin layer sweat control coefficient, SKINH is the head core layer sweat control coefficient, and SKIN is the body segment skin layer sweat control coefficient.

5. The method of claim 1, wherein the method is based on an ambient temperature. Clothing porous medium heat and moisture transfer dynamics modeling in step S2 Clothing is different from ordinary engineering solid material, which is a porous medium structure, and exists in three phases of gas, liquid and solid. Based on fractal geometry theory and Monte Carlo method, the multi-scale complex structure of porous material is constructed, and the following assumptions are made: the gas phase, liquid phase and solid phase inside the clothing always maintain thermodynamic equilibrium during human movement; due to the fact that the thickness of clothing is much smaller than the surface area of clothing, most studies only consider one-dimensional heat and moisture transfer process along the thickness direction of clothing, ignoring the influence of multi-dimensional heat and moisture transfer; the incident radiation on the surface of clothing can enter the interior of clothing to a certain depth, but it decays exponentially during the transfer process; considering the influence of moisture diffusion, phase change and adsorption or desorption on heat transfer, the transient heat transfer equation in clothing layer is established as formula (11): Where the left side is the heat storage of the clothing system, the first term on the right side is the conduction heat of the clothing system, the second term on the right side is the radiation heat of the clothing system, the third term on the right side is the latent heat change caused by the phase change of water, and the fourth term on the right side is the latent heat change caused by the water being absorbed / desorbed by the fiber, wherein, , , are the density, the specific heat capacity and the thermal conductivity of each layer of clothing respectively, T is the temperature value at different times and different positions, is the incident radiant heat flux, and are the evaporation / condensation enthalpy change and the absorption / desorption enthalpy change of water respectively, , , are the mass conversion rate of the gas phase and the solid phase, the mass conversion rate of the gas phase and the liquid phase, and the mass conversion rate of the liquid phase and the solid phase respectively. The vapor concentration difference and pressure difference between the inner and outer surfaces of clothing drive, based on Darcy's law and Fick's diffusion law, the gas phase mass conservation equation is established as formula (12): where the first term on the left is the water vapor content in the garment porosity; the second term on the left is the Darcy flow driven by the pressure difference; the first term on the right is the molecular diffusion driven by the concentration difference; and the second and third terms on the right are the phase change and adsorption rates of water, respectively, where, is the gas phase concentration in the garment, is the gas phase volume fraction in the garment, is the Darcy movement rate of the gas phase inside the garment, is the Fickian diffusion coefficient inside the garment; Phase change of moisture , Absorption of moisture , Desorption of moisture The heat-moisture coupling process affecting the inside of the garment, which is related to the concentration difference of moisture and the moisture absorption characteristics of fibers, can be expressed by the following calculation formulas (13) to (16): wherein, is the convective mass transfer coefficient inside the garment, is the specific surface area per unit volume of fabric, is the saturated water vapor concentration, is the volume fraction threshold for liquid water in a flowing state, is the diameter size of the fiber, is the moisture content at the fiber surface equilibrium, is the fiber transient moisture content, is the percentage of free water adsorbed by the fiber.

6. The method of claim 1, wherein the ambient temperature is determined by a temperature sensor. It also includes verifying the accuracy of the prediction results in step S4: Outdoor human clothing experiments are carried out, and the accuracy and reliability of the established clothing recommendation system are verified and optimized based on the subjective evaluation and objective physiological response of the human body when wearing clothing; the experiment will obtain the overall and local thermal sensation, subjective comfort and skin temperature of the human body when wearing clothing, in order to verify whether the human body can maintain a thermal comfort state when wearing the recommended clothing in the environment; among them, the subjective thermal sensation score reflects whether the human body is in a thermal neutral state when wearing the recommended clothing in the corresponding environmental conditions from the subjective perspective of the subjects, when the thermal sensation score is close to 0, it indicates that the subjects feel moderate cold and heat, and the recommended clothing can adapt to the corresponding environmental conditions; the subjective comfort score directly reflects whether the human body is comfortable when wearing the recommended clothing, the higher the comfort score, the more comfortable the subjects feel; there is a certain correlation between thermal sensation and comfort scores, the more the thermal sensation score deviates from 0, the lower the comfort score; the closer the thermal sensation score is to 0, the higher the comfort score, and the average skin temperature of the human body reflects whether the human body is in a thermal comfort state when wearing the recommended clothing in the corresponding environmental conditions from the objective physiological perspective of the subjects, and the basis for judgment is the functional relationship between the average skin temperature and the corresponding activity level when the human body is in a thermal comfort state.

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