Material heat insulation index determination method, system, device and equipment and storage medium

Abstract

The invention relates to a material heat insulation index determination method, system and device, equipment and a storage medium. The method comprises the steps that the first surface temperature of a to-be-detected material and environment parameters of the environment where the to-be-detected material is located are obtained, and the environment parameters comprise the environment temperature, the dew point temperature, the total solar radiation illumination, the second surface temperature of a standard blackboard placed in the environment and the third surface temperature of a standard whiteboard placed in the environment; determining an actually measured thermal insulation index according to the first surface temperature, the second surface temperature and the third surface temperature; and correcting the actually measured thermal insulation index according to the correction model and the environmental parameters to obtain a standard thermal insulation index of the to-be-detected material, the standard thermal insulation index being a thermal insulation index of the to-be-detected material in a standard environment. The correction model is a model determined according to the standard heat insulation index label, the sample actually measured heat insulation index and the sample environment parameter corresponding to the sample actually measured heat insulation index. The method can determine the thermal insulation index of the material.

Description

Technical Field

[0001] This application relates to the field of database technology, and in particular to a method, system, apparatus, device, and storage medium for determining the thermal insulation index of a material. Background Technology

[0002] The thermal insulation index is a key comprehensive indicator for evaluating the thermal insulation performance of building exterior surface materials (especially roof and wall thermal insulation coatings). Currently, in internationally accepted standards, the thermal insulation index is determined by calculating a theoretical thermal insulation index based on the solar reflectivity and thermal emissivity of the material under fixed standard environmental conditions (such as solar radiation irradiance of 1000 W / m², ambient temperature of 310K, etc.).

[0003] However, in practical engineering applications, building exterior materials are exposed to complex and variable natural environments. Parameters such as solar radiation, ambient temperature, humidity, and wind speed are constantly changing. It is difficult to construct an outdoor environment that meets theoretical values ​​during actual testing, making it impossible to accurately measure the thermal insulation performance of actual building exterior materials. Therefore, there is an urgent need for a method to determine the thermal insulation index of materials under natural conditions. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, system, apparatus, equipment, and storage medium for determining the thermal insulation index of a material in a natural environment, which can address the above-mentioned technical problems.

[0005] In a first aspect, this application provides a method for determining the thermal insulation index of a material, including:

[0006] The first surface temperature of the material to be tested and the environmental parameters of the environment in which the material to be tested is located are obtained. The environmental parameters include ambient temperature, dew point temperature, total solar radiation irradiance, second surface temperature of a standard blackboard placed in the environment, and third surface temperature of a standard whiteboard placed in the environment.

[0007] The measured thermal insulation index is determined based on the first surface temperature, the second surface temperature, and the third surface temperature.

[0008] The measured thermal insulation index is corrected based on the correction model and environmental parameters to obtain the standard thermal insulation index of the material to be tested. The standard thermal insulation index is the thermal insulation index of the material to be tested under standard conditions. The correction model is determined based on the standard thermal insulation index label, the measured thermal insulation index of the sample, and the sample environmental parameters corresponding to the measured thermal insulation index of the sample.

[0009] In one embodiment, the measured thermal insulation index is corrected based on a correction model and environmental parameters to obtain the standard thermal insulation index of the material under test, including:

[0010] The first result is determined by multiplying the measured thermal insulation index by the first correction factor;

[0011] The second result is determined based on the environmental parameters and the corresponding correction coefficients.

[0012] The sum of the first and second results is used as the standard thermal insulation index.

[0013] In one embodiment, determining the second result based on environmental parameters and correction coefficients corresponding to the environmental parameters includes:

[0014] The third result is determined by multiplying the ambient temperature by the second correction factor;

[0015] The fourth result is determined by multiplying the dew point temperature by the third correction factor;

[0016] The fifth result is determined by multiplying the total solar irradiance by the fourth correction factor;

[0017] The second result is determined based on the sum of the third, fourth, and fifth results and the fifth correction coefficient.

[0018] In one embodiment, the modified model is a multiple linear regression model, and the process of determining the modified model includes:

[0019] Obtain a sample dataset, which includes multiple input data and standard thermal insulation index labels corresponding to each input data. The input data includes the measured thermal insulation index of the sample and the sample environmental parameters corresponding to the measured thermal insulation index of the sample.

[0020] Based on the sample dataset and the multiple linear regression method, a modified model is determined.

[0021] In one embodiment, obtaining the sample dataset includes:

[0022] The sample first surface temperature of the sample material in different environments within a preset time period is obtained, as well as the initial sample environment parameters corresponding to the sample first surface temperature in each environment within the preset time period. The initial sample environment parameters include sample environment temperature, sample dew point temperature, sample total solar radiation irradiance, sample second surface temperature of a standard blackboard placed in the environment, and sample third surface temperature of a standard whiteboard placed in the environment.

[0023] Remove the sample environmental parameters that do not meet the preset conditions from the initial sample environmental parameters within the preset time period to obtain the sample environmental parameters. The preset conditions include the sample environmental temperature being greater than or equal to the first preset threshold, and / or the sample total solar radiation irradiance being greater than or equal to the second preset threshold.

[0024] Based on the sample's second and third surface temperatures and the sample's first surface temperature corresponding to the sample's environmental parameters, the measured thermal insulation index of the sample material is determined.

[0025] Secondly, this application also provides a system for determining the thermal insulation index of a material, comprising:

[0026] The test specimen is a metal plate with an insulation layer as its substrate, and one side of the metal plate is coated with paint.

[0027] Standard whiteboard and standard blackboard;

[0028] An environmental parameter detection device is connected to the test piece, a standard white board, and a standard black board. It is used to collect the first surface temperature of the material to be tested in the test piece and the environmental parameters of the environment in which the test piece is located.

[0029] The controller, connected to the environmental parameter detection device, is used to acquire the first surface temperature of the material under test and the environmental parameters of the environment in which the material is located. The environmental parameters include ambient temperature, dew point temperature, total solar irradiance, the second surface temperature of a standard blackboard placed in the environment, and the third surface temperature of a standard whiteboard placed in the environment. The measured thermal insulation index is determined based on the first, second, and third surface temperatures. The measured thermal insulation index is then corrected based on the correction model and environmental parameters to obtain the standard thermal insulation index of the material under test. The standard thermal insulation index is the thermal insulation index of the material under test in a standard environment. The correction model is determined based on the standard thermal insulation index label, the measured thermal insulation index of the sample, and the sample environmental parameters corresponding to the measured thermal insulation index of the sample.

[0030] Thirdly, this application also provides a device for determining the thermal insulation index of a material, comprising:

[0031] The acquisition module is used to acquire the first surface temperature of the material to be tested, as well as the environmental parameters of the environment in which the material to be tested is located. The environmental parameters include ambient temperature, dew point temperature, total solar radiation irradiance, the second surface temperature of a standard blackboard placed in the environment, and the third surface temperature of a standard whiteboard placed in the environment.

[0032] The determination module is used to determine the measured thermal insulation index based on the first surface temperature, the second surface temperature, and the third surface temperature.

[0033] The correction module is used to correct the measured thermal insulation index based on the correction model and environmental parameters to obtain the standard thermal insulation index of the material to be tested. The standard thermal insulation index is the thermal insulation index of the material to be tested under standard conditions. The correction model is determined based on the standard thermal insulation index label, the measured thermal insulation index of the sample, and the sample environmental parameters corresponding to the measured thermal insulation index of the sample.

[0034] Fourthly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in any of the first aspects above.

[0035] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the first aspects above.

[0036] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described in any of the first aspects above.

[0037] The aforementioned method, system, apparatus, equipment, and storage medium for determining the thermal insulation index of materials acquire the first surface temperature of the material under test and the environmental parameters of the environment in which the material is located. These environmental parameters include ambient temperature, dew point temperature, total solar irradiance, the second surface temperature of a standard blackboard placed in the environment, and the third surface temperature of a standard whiteboard placed in the environment. The measured thermal insulation index is determined based on the first, second, and third surface temperatures. The measured thermal insulation index is then corrected using a correction model and the environmental parameters to obtain the standard thermal insulation index of the material under test. The standard thermal insulation index is the thermal insulation index of the material under test in a standard environment. The correction model is determined based on the standard thermal insulation index label, the measured thermal insulation index of the sample, and the sample environmental parameters corresponding to the measured thermal insulation index of the sample. This allows for the correction of the measured thermal insulation index in the natural environment to the standard conditions, making the measured thermal insulation index comparable across different environments. This addresses the pain point that existing general standards cannot be used for on-site performance evaluation and provides a scientific, unified, and reliable means of acceptance and evaluation for the application effect of building insulation materials in actual engineering projects. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a diagram illustrating the application environment of the material thermal insulation index determination method in one embodiment;

[0040] Figure 2 This is a schematic diagram of an environmental parameter detection device in one embodiment;

[0041] Figure 3 This is a schematic diagram of the structure of the test piece in one embodiment;

[0042] Figure 4 This is a flowchart illustrating a method for determining the thermal insulation index of a material in one embodiment;

[0043] Figure 5 This is a flowchart illustrating the steps for determining the corrected model in one embodiment;

[0044] Figure 6 This is a flowchart illustrating the steps for obtaining a sample dataset in one embodiment;

[0045] Figure 7 This is a flowchart illustrating the steps for determining the standard thermal insulation index of a material to be tested in one embodiment.

[0046] Figure 8 This is a flowchart illustrating the method for determining the thermal insulation index of a material in another embodiment;

[0047] Figure 9 This is a structural block diagram of a material thermal insulation index determination device in one embodiment;

[0048] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0050] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0051] The thermal insulation index is a key comprehensive indicator for evaluating the thermal insulation performance of building exterior surface materials (especially roof and wall thermal insulation coatings). Currently, in internationally accepted standards, the thermal insulation index is determined by calculating a theoretical thermal insulation index based on the solar reflectivity and thermal emissivity of the material under fixed standard environmental conditions (such as solar radiation irradiance of 1000 W / m², ambient temperature of 310K, etc.).

[0052] However, in practical engineering applications, building exterior materials are exposed to complex and variable natural environments. Parameters such as solar radiation, ambient temperature, humidity, and wind speed are constantly changing. It is difficult to construct an outdoor environment that meets theoretical values ​​during actual testing, making it impossible to accurately measure the thermal insulation performance of actual building exterior materials. Therefore, there is an urgent need for a method to determine the thermal insulation index of materials under natural conditions.

[0053] In view of this, embodiments of this application provide a method for determining the thermal insulation index of a material that can be determined under natural conditions. The method for determining the thermal insulation index of a material provided in embodiments of this application can be applied to, for example... Figure 1 The material insulation index determination system shown includes a test piece 101, a standard white board 102, a standard black board 103, an environmental parameter detection device 104, and a controller 105. The substrate of the test piece 101 is a metal plate with an insulation layer, and one side of the metal plate is coated with paint. The environmental parameter detection device 104 is connected to the test piece 101, the standard white board 102, and the standard black board 103, and is used to collect the first surface temperature of the material to be tested in the test piece 101 and the environmental parameters of the environment in which the test piece is located. The controller 105 is connected to the environmental parameter detection device 104 and is used to acquire the first surface temperature of the material to be tested and the environmental parameters of the environment in which the material to be tested is located. The environmental parameters include ambient temperature, dew point temperature, total solar radiation irradiance, the second surface temperature of the standard black board placed in the environment, and the third surface temperature of the standard white board placed in the environment. The measured thermal insulation index is determined based on the first surface temperature, the second surface temperature, and the third surface temperature. The measured thermal insulation index is corrected based on the correction model and the environmental parameters to obtain the standard thermal insulation index of the material to be tested. The standard thermal insulation index is the thermal insulation index of the material to be tested in a standard environment. The correction model is a model determined based on the standard thermal insulation index label, the measured thermal insulation index of the sample, and the sample environmental parameters corresponding to the measured thermal insulation index of the sample.

[0054] like Figure 2 As shown, the environmental parameter detection device 104 may include a temperature sensor 1041 and a small weather station 1042, etc. The temperature sensor is respectively installed on the test piece 101, the standard white board 102, and the standard black board 103, and is used to collect the first surface temperature, the second surface temperature, and the third surface temperature. The small weather station is installed in the environment where the test piece 101, the standard white board 102, and the standard black board 103 are located, and is used to collect environmental parameters of the environment, including ambient temperature, dew point temperature, and total solar irradiance, etc. Figure 3As shown, this is a schematic diagram of an exemplary test piece 101. A 500mm×500mm×30mm polystyrene foam board is used as an insulation base 1011, and a 450mm×450mm×1.5mm aluminum plate 1012 is covered on it. The coating to be tested or the coating of the standard plate (dry film thickness 150-300μm) is coated on one side of the aluminum plate.

[0055] The controller 105 can be a computer device, including but not limited to various personal computers, laptops, smartphones, tablets, etc.

[0056] In one exemplary embodiment, such as Figure 4 As shown, a method for determining the thermal insulation index of a material is provided, which can be applied to... Figure 1 The following steps are used as an example of the controller in the example, including steps 401 to 403. Wherein:

[0057] Step 401: Obtain the first surface temperature of the material to be tested, as well as the environmental parameters of the environment in which the material to be tested is located.

[0058] The environmental parameters include ambient temperature, dew point temperature, total solar radiation, the second surface temperature of a standard blackboard placed in the environment, and the third surface temperature of a standard whiteboard placed in the environment.

[0059] Optionally, the controller can connect to an environmental parameter detection device to obtain the first surface temperature of the material to be tested and the environmental parameters of the environment in which the material is located. Alternatively, the environmental parameter detection device can send the detected first surface temperature and corresponding environmental parameters to the controller in real time or periodically. The controller stores the received first surface temperature and corresponding environmental parameters in a storage unit. Therefore, the controller can also obtain the first surface temperature of the material to be tested and the environmental parameters from its own storage unit. This embodiment of the application does not limit this aspect.

[0060] Optionally, the first surface temperature of the material to be tested and the environmental parameters of the environment may include data measured at different times. That is, there may be multiple first surface temperatures and environmental parameters. At one time, there may be one first surface temperature and the corresponding environmental parameter.

[0061] The hemispherical emissivity of both standard blackboards and standard whiteboards is between 0.89 and 0.90. The solar reflectivity of the standard blackboard is 0.04-0.06, and that of the standard whiteboard is 0.79-0.81.

[0062] Step 402: Determine the measured thermal insulation index based on the first surface temperature, the second surface temperature, and the third surface temperature.

[0063] The measured thermal insulation index can be the measured thermal insulation index at a specific moment in time, such as the measured thermal insulation index of the material to be tested at a specific point in time. Alternatively, the measured thermal insulation index can be the measured thermal insulation index within a preset time period, such as the measured thermal insulation index of the material to be tested over an hour or a day.

[0064] The measured thermal insulation index reflects the relative thermal insulation performance of the tested component relative to a standard black board and a standard white board under local real-time weather conditions. The measured thermal insulation index can be determined by the ratio of the first difference between the second surface temperature and the first surface temperature to the second difference between the second surface temperature and the third surface temperature.

[0065] For example, taking the measured thermal insulation index as the measured thermal insulation index within a preset time period as an example, the measured thermal insulation index can be expressed by the following formula:

[0066]

[0067] in, This indicates the measured thermal insulation index. This represents the average temperature of the second surface over a preset time period. This represents the average temperature of the third surface over a preset time period. This represents the first surface temperature at time t within a preset time period, where T is the duration of the preset time period.

[0068] Optionally, when calculating the measured heat insulation index within a preset time period according to the above formula, since the first surface temperature and environmental parameters are continuously collected data, the above data can be filtered to select data that meets the following filtering conditions for calculation: the ambient temperature is greater than or equal to the first preset threshold, and / or the total solar radiation irradiance is greater than or equal to the second preset threshold.

[0069] Environmental parameters may also include wind speed; therefore, the above screening criteria may also include wind speed being within a first preset range.

[0070] For example, solar radiation irradiance ≥600 W / m², ambient temperature ≥20℃, and wind speed between 2 and 6 m / s.

[0071] Understandably, screening the first surface temperature and environmental parameters to obtain those that meet the screening criteria can avoid the influence of extreme data on the measured thermal insulation index and ensure the accuracy of the calculation.

[0072] Step 403: Correct the measured thermal insulation index according to the correction model and environmental parameters to obtain the standard thermal insulation index of the material to be tested.

[0073] Among them, the standard thermal insulation index is the thermal insulation index of the material under test under standard conditions. The correction model is a model determined based on the standard thermal insulation index label, the measured thermal insulation index of the sample, and the sample environment parameters corresponding to the measured thermal insulation index of the sample. The standard thermal insulation index label is the theoretical thermal insulation index of the material under test under standard conditions, which can be calculated based on the solar reflectivity and thermal emissivity of the material under standard conditions.

[0074] Optionally, the correction model can be a pre-trained neural network model or a mathematical statistical model, and the embodiments of this application do not limit it.

[0075] In one possible implementation, when the correction model is a pre-trained neural network model, the measured thermal insulation index and environmental parameters can be input as input data into the correction model, and the output of the correction model can be used as the standard thermal insulation index of the material to be tested.

[0076] The parameters of the initial correction model can be trained using the standard thermal insulation index label, the measured thermal insulation index of the sample, and the sample environmental parameters corresponding to the measured thermal insulation index of the sample as the training dataset. In this way, during the training process, the initial correction model can fully realize the mapping relationship between the measured thermal insulation index of the sample, the sample environmental parameters, and the corresponding standard thermal insulation index label.

[0077] Once the modified model is trained, the measured thermal insulation index and environmental parameters are input into the modified model, which can then output the corresponding standard thermal insulation index based on the learned mapping relationship.

[0078] In another possible implementation, when the modified model is a mathematical statistical model, the measured thermal insulation performance and environmental parameters can be used as independent variables and input into the modified model for mathematical calculation to obtain the standard thermal insulation index of the material to be tested, with the standard thermal insulation index as the dependent variable.

[0079] Understandably, when the measured heat insulation index is the measured heat insulation index within a preset time period, the environmental parameters input into the correction model can be the average values ​​of various environmental parameters within the preset time period, such as the average ambient temperature, the average dew point temperature, and the average total solar radiation irradiance.

[0080] The aforementioned method for determining the thermal insulation index of materials involves acquiring the first surface temperature of the material under test, as well as environmental parameters of the environment in which the material is located. These environmental parameters include ambient temperature, dew point temperature, total solar irradiance, the second surface temperature of a standard blackboard placed in the environment, and the third surface temperature of a standard whiteboard placed in the environment. The measured thermal insulation index is then determined based on these three surface temperatures. Finally, the measured thermal insulation index is corrected using a correction model and the environmental parameters to obtain the standard thermal insulation index of the material under test. The standard thermal insulation index represents the thermal insulation index of the material under test in a standard environment. The correction model is determined based on the standard thermal insulation index label, the measured thermal insulation index of the sample, and the corresponding environmental parameters of the sample. This method allows for the correction of the measured thermal insulation index in the natural environment to the standard conditions, making the measured thermal insulation index comparable across different environments. This addresses the limitation of existing general standards being unsuitable for on-site performance evaluation and provides a scientific, unified, and reliable means of acceptance and evaluation for the application of building insulation materials in practical engineering projects.

[0081] In one exemplary embodiment, such as Figure 5 As shown, the modified model is a multiple linear regression model, and the process of determining the modified model includes steps 501 to 502. Wherein:

[0082] Step 501: Obtain the sample dataset.

[0083] The sample dataset includes multiple input data and standard thermal insulation index labels corresponding to each input data. The input data includes the measured thermal insulation index of the sample and the sample environmental parameters corresponding to the measured thermal insulation index of the sample.

[0084] Optionally, the correction model can be determined by the controller itself; alternatively, to save the controller's computing resources, the correction model can also be determined by a server or cloud server and sent to the controller after determination. This embodiment describes the example of the controller determining the correction model itself.

[0085] The controller takes a sample of a material's measured thermal insulation index and the corresponding environmental parameters as input data (i.e., independent variables), and the dependent variable corresponding to this input data is the material's standard thermal insulation index label. This standard thermal insulation index label is the material's theoretical thermal insulation index under standard environmental conditions, which can be calculated based on the material's solar reflectivity and thermal emissivity under standard environmental conditions.

[0086] For example, the measured thermal insulation index of different materials in different regions and environments and the corresponding sample environment parameters can be obtained, and a sample dataset can be formed by combining the standard thermal insulation index label of the material.

[0087] Step 502: Determine the modified model based on the sample dataset and the multiple linear regression method.

[0088] Alternatively, the input data can be used as the independent variable, and the standard insulation index as the dependent variable. The mathematical form of the modified model can be expressed as:

[0089]

[0090] in, The standard thermal insulation index, To measure the thermal insulation index, b, c, and d are the model coefficients to be determined. For ambient temperature, Dew point temperature, This represents the total solar irradiance.

[0091] The coefficients of the above model can be solved using the least squares method and the sample dataset, which will not be elaborated further in the embodiments of this application.

[0092] Optionally, the sample dataset can be divided into a training set and a test set. The model coefficients are determined through the training set, and the model effect of the modified model is verified through the test set. If the error between the standard thermal insulation index determined based on the modified model and the standard thermal insulation index label meets the preset threshold for a set of input data, then the training is considered complete, and the final modified model is obtained.

[0093] In one exemplary embodiment, such as Figure 6 As shown, optionally, obtaining the sample dataset includes the following steps 601 to 603. Wherein:

[0094] Step 601: Obtain the sample first surface temperature of the sample material under different environments within a preset time period, and the initial sample environment parameters corresponding to the sample first surface temperature under each environment within the preset time period.

[0095] The initial sample environment parameters include sample ambient temperature, sample dew point temperature, sample total solar irradiance, sample second surface temperature of a standard blackboard placed in the environment, and sample third surface temperature of a standard whiteboard placed in the environment.

[0096] Optionally, the controller can obtain environmental parameters from different climate regions across the country, as well as the first surface temperature of the sample material, from an environmental parameter detection device or from a storage unit.

[0097] For example, the environmental parameter detection device can conduct simultaneous detection in different climates across the country, detecting the first surface temperature of the sample material and the initial sample environmental parameters of the environment in which the sample material is located under various conditions within a preset time period.

[0098] It is understandable that there are multiple initial sample environment parameters, including initial sample environment parameters at different times within a preset time period.

[0099] Step 602: Remove the sample environment parameters that do not meet the preset conditions from the initial sample environment parameters within the preset time period to obtain the sample environment parameters.

[0100] The preset conditions include the sample ambient temperature being greater than or equal to a first preset threshold, and / or the sample total solar irradiance being greater than or equal to a second preset threshold.

[0101] Optionally, data cleaning can be performed on the initial sample environment parameters, such as handling missing values ​​and removing outliers.

[0102] Outlier handling may include removing environmental parameters of samples that do not meet preset conditions within a preset time period. Step 602 can refer to step 402 and will not be repeated here.

[0103] Step 603: Determine the measured thermal insulation index of the sample material based on the sample's second surface temperature, third surface temperature, and first surface temperature corresponding to the sample's environmental parameters.

[0104] The process of determining the measured thermal insulation index of the sample in step 603 can be referred to step 402, and will not be repeated here.

[0105] For example, by conducting simultaneous tests in different climate regions across the country (such as Shenzhen, Hangzhou, Xiong'an, Chongqing, and Kashgar), taking a preset time period of one day as an example, environmental parameters and corresponding measured heat insulation indices of the samples are obtained to obtain a sample dataset, and then the correction model is determined. The specific form of the correction model can be:

[0106]

[0107] Table 1 shows the error comparison between the standard thermal insulation index (corrected value) determined by the modified model and the corresponding standard thermal insulation index label (standard value). As can be seen from Table 1, the error value is small, and the coefficient of determination of the above modified model is 0.945, indicating that the modified model has high accuracy and reliability.

[0108] Table 1

[0109]

[0110] In one exemplary embodiment, such as Figure 7 As shown, optionally, the measured thermal insulation index is corrected according to the correction model and environmental parameters to obtain the standard thermal insulation index of the material to be tested, including the following steps 701 to 703. Wherein:

[0111] Step 701: Determine the first result based on the product of the measured heat insulation index and the first correction coefficient.

[0112] Step 702: Determine the second result based on the environmental parameters and the correction coefficients corresponding to the environmental parameters.

[0113] Optionally, a third result is determined based on the product of ambient temperature and a second correction factor, a fourth result is determined based on the product of dew point temperature and a third correction factor, a fifth result is determined based on the product of total solar irradiance and a fourth correction factor, and a second result is determined based on the sum of the third result, the fourth result, the fifth result, and the fifth correction factor.

[0114] Step 703: The sum of the first result and the second result is used as the standard thermal insulation index.

[0115] Optionally, the modified model establishes a quantitative relationship between the standard thermal insulation index, the measured thermal insulation index, and environmental parameters. As can be seen from the above embodiments, the modified model can be expressed as:

[0116]

[0117] in, The first result is given, and e is the first correction factor. As the second result, As the third result, This is the second correction factor. As the fourth result, This is the third correction factor. This is the fifth result, and d is the fourth correction coefficient.

[0118] It is understandable that the above environmental parameters are all average values ​​when determining the standard thermal insulation index within the preset time period.

[0119] The above method determines the first result by multiplying the measured thermal insulation index by the first correction coefficient, and determines the second result by the environmental parameters and the corresponding correction coefficients. The sum of the first and second results is used as the standard thermal insulation index. This method can accurately correct the measured thermal insulation index and obtain the standard thermal insulation index. At the same time, the above correction model is simple and intuitive, the parameters are highly interpretable, and each correction coefficient can directly reflect the degree of influence of the variables.

[0120] As an optional implementation method, such as Figure 8 As shown, the method for determining the thermal insulation index of materials provided in this application embodiment may include the following specific steps:

[0121] Step 801: Obtain the sample first surface temperature of the sample material under different environments within a preset time period, and the initial sample environment parameters corresponding to the sample first surface temperature under each environment within the preset time period.

[0122] The initial sample environment parameters include sample ambient temperature, sample dew point temperature, sample total solar radiation irradiance, sample second surface temperature of a standard blackboard placed in the environment, and sample third surface temperature of a standard whiteboard placed in the environment.

[0123] Step 802: Remove the sample environment parameters that do not meet the preset conditions from the initial sample environment parameters within the preset time period to obtain the sample environment parameters.

[0124] The preset conditions include the sample ambient temperature being greater than or equal to a first preset threshold, and / or the sample total solar irradiance being greater than or equal to a second preset threshold.

[0125] Step 803: Determine the measured thermal insulation index of the sample material based on the sample's second surface temperature, third surface temperature, and first surface temperature corresponding to the sample's environmental parameters.

[0126] Step 804: Use the measured thermal insulation index of the sample and the sample environment parameters corresponding to the measured thermal insulation index of the sample as input data, and obtain the standard thermal insulation index label corresponding to each input data.

[0127] Step 805: Determine the sample dataset based on multiple sets of input data and the standard thermal insulation index labels corresponding to each set of input data.

[0128] Step 806: Determine the modified model based on the sample dataset and the multiple linear regression method.

[0129] Step 807: Obtain the first surface temperature of the material to be tested, as well as the environmental parameters of the environment in which the material to be tested is located.

[0130] Step 808: Determine the measured thermal insulation index based on the first surface temperature, the second surface temperature, and the third surface temperature.

[0131] Step 809: Determine the first result based on the product of the measured heat insulation index and the first correction coefficient.

[0132] Step 810: Determine the third result based on the product of the ambient temperature and the second correction factor.

[0133] Step 811: Determine the fourth result based on the product of the dew point temperature and the third correction factor.

[0134] Step 812: Determine the fifth result based on the product of the total solar irradiance and the fourth correction factor.

[0135] Step 813: Determine the second result based on the sum of the third result, the fourth result, the fifth result, and the fifth correction coefficient.

[0136] Step 814: The sum of the first result and the second result is used as the standard thermal insulation index.

[0137] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0138] Based on the same inventive concept, such as Figure 1 As shown in the embodiments of this application, a material thermal insulation index determination system for implementing the above-mentioned method for determining the material thermal insulation index is also provided, comprising:

[0139] The test specimen is a metal plate with an insulation layer as its substrate, and one side of the metal plate is coated with paint.

[0140] Standard whiteboard and standard blackboard;

[0141] An environmental parameter detection device is connected to the test piece, a standard white board, and a standard black board. It is used to collect the first surface temperature of the material to be tested in the test piece and the environmental parameters of the environment in which the test piece is located.

[0142] A controller, connected to an environmental parameter detection device, is used to implement the steps described in any of the above method embodiments.

[0143] Based on the same inventive concept, this application also provides a material thermal insulation index determination device for implementing the above-described method for determining the material thermal insulation index. The solution provided by this device is similar to the solution described in the above-described method; therefore, the specific limitations in one or more embodiments of the material thermal insulation index determination device provided below can be found in the limitations of the material thermal insulation index determination method described above, and will not be repeated here.

[0144] In one exemplary embodiment, such as Figure 9 As shown, a material thermal insulation index determining device 900 is provided, including: an acquisition module 901, a determining module 902, and a correction module 903, wherein:

[0145] The acquisition module 901 is used to acquire the first surface temperature of the material to be tested, as well as the environmental parameters of the environment in which the material to be tested is located. The environmental parameters include the ambient temperature, dew point temperature, total solar radiation irradiance, the second surface temperature of the standard blackboard placed in the environment, and the third surface temperature of the standard whiteboard placed in the environment.

[0146] The determination module 902 is used to determine the measured thermal insulation index based on the first surface temperature, the second surface temperature, and the third surface temperature.

[0147] The correction module 903 is used to correct the measured thermal insulation index according to the correction model and environmental parameters to obtain the standard thermal insulation index of the material to be tested. The standard thermal insulation index is the thermal insulation index of the material to be tested under standard environment. The correction model is determined according to the standard thermal insulation index label, the measured thermal insulation index of the sample, and the sample environmental parameters corresponding to the measured thermal insulation index of the sample.

[0148] In one embodiment, the correction module 903 is specifically used to determine a first result based on the product of the measured thermal insulation index and a first correction coefficient; determine a second result based on environmental parameters and correction coefficients corresponding to the environmental parameters; and use the sum of the first result and the second result as the standard thermal insulation index.

[0149] In one embodiment, the correction module 903 is specifically configured to determine a third result based on the product of ambient temperature and a second correction coefficient; determine a fourth result based on the product of dew point temperature and a third correction coefficient; determine a fifth result based on the product of total solar irradiance and a fourth correction coefficient; and determine a second result based on the sum of the third result, the fourth result, the fifth result, and the fifth correction coefficient.

[0150] In one embodiment, the modified model is a multiple linear regression model. The determination module 902 is further used to obtain a sample dataset, wherein the sample dataset includes multiple input data and standard insulation index labels corresponding to each input data. The input data includes the measured insulation index of the sample and the sample environmental parameters corresponding to the measured insulation index of the sample. The modified model is determined based on the sample dataset and the multiple linear regression method.

[0151] In one embodiment, the determining module 902 is further configured to acquire the sample first surface temperature of the sample material under different environments within a preset time period, and the initial sample environment parameters corresponding to the sample first surface temperature under each environment within the preset time period. The initial sample environment parameters include the sample environment temperature, the sample dew point temperature, the sample total solar irradiance, the sample second surface temperature of a standard blackboard placed in the environment, and the sample third surface temperature of a standard whiteboard placed in the environment. Sample environment parameters that do not meet the preset conditions in the initial sample environment parameters within the preset time period are removed to obtain sample environment parameters. The preset conditions include the sample environment temperature being greater than or equal to a first preset threshold, and / or the sample total solar irradiance being greater than or equal to a second preset threshold. Based on the sample second surface temperature, the sample third surface temperature, and the sample first surface temperature corresponding to the sample environment parameters, the measured heat insulation index of the sample material is determined.

[0152] The modules in the aforementioned material insulation index determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0153] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 10 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for determining the thermal insulation index of a material.

[0154] Those skilled in the art will understand that Figure 10The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0155] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps described in any of the above method embodiments.

[0156] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps described in any of the above method embodiments.

[0157] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps described in any of the above method embodiments.

[0158] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0159] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0160] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method of determining a material insulation index, characterized by, The method comprises: acquiring a first surface temperature of a material to be detected and an environmental parameter of an environment in which the material to be detected is located, the environmental parameter comprising an environmental temperature, a dew point temperature, a total solar radiation illuminance, a second surface temperature of a standard blackboard placed in the environment, and a third surface temperature of a standard whiteboard placed in the environment; determining an actual measured thermal insulation index according to the first surface temperature, the second surface temperature, and the third surface temperature; correcting the actual measured thermal insulation index according to a correction model and the environmental parameter to obtain a standard thermal insulation index of the material to be detected, the standard thermal insulation index being a thermal insulation index of the material to be detected in a standard environment, and the correction model being a model determined according to a standard thermal insulation index label, a sample actual measured thermal insulation index, and sample environmental parameters corresponding to the sample actual measured thermal insulation index.

2. The method of claim 1, wherein, The correction of the actual measured thermal insulation index according to the correction model and the environmental parameter to obtain the standard thermal insulation index of the material to be detected comprises: determining a first result according to a product of the actual measured thermal insulation index and a first correction coefficient; determining a second result according to the environmental parameter and a correction coefficient corresponding to the environmental parameter; taking a sum of the first result and the second result as the standard thermal insulation index.

3. The method of claim 2, wherein, The determination of the second result according to the environmental parameter and the correction coefficient corresponding to the environmental parameter comprises: determining a third result according to a product of the environmental temperature and a second correction coefficient; determining a fourth result according to a product of the dew point temperature and a third correction coefficient; determining a fifth result according to a product of the total solar radiation illuminance and a fourth correction coefficient; determining the second result according to a sum of the third result, the fourth result, the fifth result, and a fifth correction coefficient.

4. The method according to any one of claims 1 to 3, characterized in that, The correction model is a multiple linear regression model, and a determination process of the correction model comprises: acquiring a sample data set, wherein the sample data set comprises a plurality of input data and a standard thermal insulation index label corresponding to each input data, and the input data comprises a sample actual measured thermal insulation index and sample environmental parameters corresponding to the sample actual measured thermal insulation index; determining the correction model according to the sample data set and a multiple linear regression method.

5. The method of claim 4, wherein, The acquisition of the sample data set comprises: acquiring sample first surface temperatures of a sample material in different environments within a preset time period, and initial sample environmental parameters corresponding to the sample first surface temperatures of the sample material in the different environments within the preset time period, the initial sample environmental parameters comprising a sample environmental temperature, a sample dew point temperature, a sample total solar radiation illuminance, a sample second surface temperature of a standard blackboard placed in the environment, and a sample third surface temperature of a standard whiteboard placed in the environment; eliminating sample environmental parameters that do not meet a preset condition from the initial sample environmental parameters within the preset time period to obtain sample environmental parameters, the preset condition comprising that the sample environmental temperature is greater than or equal to a first preset threshold value, and / or the sample total solar radiation illuminance is greater than or equal to a second preset threshold value; and According to the sample second surface temperature, the sample third surface temperature and the sample first surface temperature corresponding to the sample environment parameter in the sample environment parameter, a sample measured heat insulation index corresponding to the sample material is determined.

6. A material thermal insulation index determination system characterized by, The system comprises: The to-be-tested piece has a metal plate with a heat preservation layer as a base, and one side of the metal plate is coated with paint; A standard white plate and a standard black plate; An environment parameter detection device connected with the to-be-tested piece, the standard white plate and the standard black plate, used for collecting a first surface temperature of a to-be-detected material in the to-be-tested piece and environment parameters of an environment where the to-be-tested piece is located; A controller connected with the environment parameter detection device, used for obtaining the first surface temperature of the to-be-detected material and the environment parameters of the environment where the to-be-detected material is located, wherein the environment parameters comprise an environment temperature, a dew point temperature, a total solar radiation intensity, a second surface temperature of the standard black plate placed in the environment and a third surface temperature of the standard white plate placed in the environment; a measured heat insulation index is determined according to the first surface temperature, the second surface temperature and the third surface temperature; the measured heat insulation index is corrected according to a correction model and the environment parameters, to obtain a standard heat insulation index of the to-be-detected material, wherein the standard heat insulation index is a heat insulation index of the to-be-detected material under a standard environment, and the correction model is a model determined according to a standard heat insulation index label, a sample measured heat insulation index and sample environment parameters corresponding to the sample measured heat insulation index.

7. A material thermal insulation index determination apparatus characterized by comprising: The device comprises: An obtaining module, used for obtaining a first surface temperature of a to-be-detected material and environment parameters of an environment where the to-be-detected material is located, wherein the environment parameters comprise an environment temperature, a dew point temperature, a total solar radiation intensity, a second surface temperature of a standard black plate placed in the environment and a third surface temperature of a standard white plate placed in the environment; A determining module, used for determining a measured heat insulation index according to the first surface temperature, the second surface temperature and the third surface temperature; A correcting module, used for correcting the measured heat insulation index according to a correction model and the environment parameters, to obtain a standard heat insulation index of the to-be-detected material, wherein the standard heat insulation index is a heat insulation index of the to-be-detected material under a standard environment, and the correction model is a model determined according to a standard heat insulation index label, a sample measured heat insulation index and sample environment parameters corresponding to the sample measured heat insulation index.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to implement the steps of the method in any one of claims 1 to 5.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 5.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 5.

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