Method and system for evaluating thermal insulation performance of feathers

Abstract

The invention provides a method and system for evaluating the thermal insulation performance of feathers, and relates to the technical field of thermal insulation performance evaluation.The method specifically comprises the steps that a to-be-tested feather sample obtained after pretreatment is filled into a calorimeter test cabin; controlling the external environment temperature of the test cabin to be constant, and heating the sample at a constant power until the temperature reaches and is stabilized at a preset value; a step change is applied to the heating power, and time sequence temperature data of the sample are collected at the same time; constructing a heat conduction evaluation model based on the power increment and the temperature data, and calculating a thermal time coefficient representing the dynamic heat conduction process of the sample; calibrating a reference thermal time coefficient by testing a standard sample, and determining a thermal insulation performance evaluation index by combining the thermal time coefficient and a thermal inertia enhancement factor; and finally comparing the index with a grading threshold value, and evaluating the thermal insulation performance grade of the to-be-tested sample. According to the method, a reliable basis is provided for accurate grading of the feather heat preservation performance and model selection in a high-end application scene.

Description

Technical Field

[0001] This invention relates to the field of thermal insulation performance evaluation technology, specifically to a method and system for evaluating the thermal insulation performance of feathers. Background Technology

[0002] Feathers, as a highly efficient thermal insulation material found in nature, primarily rely on the multi-layered porous structure formed by feather fibers and vanes to achieve thermal barrier effects by trapping still air. They are widely used in clothing, home furnishings, and extreme environment protective equipment. The fineness, loft, and down content of the feather fibers directly affect their insulation capacity. Different types and processing techniques result in significant differences in insulation performance, making the establishment of precise quantitative evaluation methods crucial for product quality control and grading. Currently, the industry commonly uses traditional testing methods such as the static air thermal resistance method, which assesses performance by measuring the heat transfer rate under steady-state conditions. However, these methods primarily target macroscopic insulation effects and struggle to capture the dynamic thermal conductivity characteristics of feather materials under temperature fluctuations. Furthermore, the lack of standardized procedures for sample pretreatment and the stability of the testing environment leads to insufficient repeatability and comparability of evaluation results, failing to meet the demands of high-end applications for refined performance evaluation.

[0003] In the prior art, the method, apparatus, and electronic equipment for evaluating the thermal insulation performance of thermal insulation materials disclosed in CN113758965A evaluates thermal insulation performance by monitoring the actual average temperature and theoretical average temperature of the battery pack under varying ambient temperatures and constructing a loss function to solve for the heat dissipation coefficient. This method is primarily designed for applications involving thermal insulation materials in battery packs and does not consider the unique physical characteristics of lightweight, porous materials like feathers—whose thermal insulation effect highly depends on the air storage capacity provided by their fluffy structure. Furthermore, this approach lacks a standardized sample pretreatment process, failing to eliminate the interference of impurities and humidity in the feathers on the test results. Simultaneously, its test mode, based on overall changes in ambient temperature, makes it difficult to accurately capture the dynamic heat conduction process of the material. It does not introduce key parameters characterizing thermal response delay and lacks a calibration mechanism for calibrating benchmark parameters using standard samples, thus failing to establish a dedicated evaluation system for feather materials. This results in significant limitations in the quantitative grading and precise comparison of the thermal insulation performance of feathers.

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

[0005] The purpose of this invention is to provide a method and system for evaluating the heat-insulating performance of feathers, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for evaluating the thermal insulation performance of feathers, comprising the following steps: Step 1: The pretreated feather sample to be tested is uniformly filled into the calorimeter test chamber equipped with a heating unit and a temperature sensing unit. The pretreatment includes cleaning and drying. Step 2: Control the external ambient temperature of the calorimeter test chamber to be constant at the first preset temperature, start the heating unit to heat the feather sample to be tested at a constant power until the temperature of the feather sample to be tested detected by the temperature sensing unit is stable at the second preset temperature. Step 3: Apply a preset power increment to the input power of the heating unit to produce a step change, and simultaneously continuously collect the time-series temperature data of the feather sample to be tested in the test chamber at a preset sampling frequency. Step 4: Using the power increment and the time-series temperature data as input variables, construct a thermal conductivity evaluation model, and use the thermal conductivity evaluation model to determine the thermal time coefficient used to characterize the dynamic thermal conductivity process of the feather sample under test; Step 5: Based on the time-series temperature data, plot the dynamic thermal response curve and analyze its fitting curve function to obtain the thermal inertia enhancement factor used to characterize the synergistic effect of the internal pore structure and heat conduction path of the sample. Step 6: Calibrate the reference thermal time coefficient by testing standard samples. Based on the thermal time coefficient, the reference thermal time coefficient, and the thermal inertia enhancement factor, determine the thermal insulation performance evaluation index of the feather sample to be tested. The thermal insulation performance evaluation index is used to evaluate the thermal insulation performance of the feather sample to be tested. Step 7: Compare the thermal insulation performance evaluation index with the preset thermal insulation performance grading threshold to determine the thermal insulation performance level of the feather sample to be tested.

[0007] Furthermore, the specific execution process of step 1 is as follows: The feather samples to be tested were screened through a 30-mesh metal sieve to remove down, dust, and fiber impurities from the feathers. The screened feather samples were immersed in deionized water for 15-20 minutes, during which time stubborn stains on the surface of the feathers were brushed off with a soft brush. After brushing, the deionized water was replaced and the feathers were rinsed until the conductivity of the rinsing water was lower than that of the sample. Complete the cleaning process; The cleaned feather sample was laid flat on a breathable cotton tray and placed in a container with the temperature set to [temperature value missing]. Relative humidity set to In a constant temperature and humidity drying oven, the sample is weighed every 2 hours during the drying process. When the weight difference between two consecutive weighings is less than [value missing], the sample is considered dry. When the sample reaches a constant weight, stop drying and remove the sample. The feather sample, having reached constant weight, was fluffed up and evenly filled into the calorimeter test chamber. During filling, a glass rod was used to smooth the sample, and a gap was maintained between the upper surface of the sample and the top inner wall of the test chamber after filling. The reserved space is used to complete the preprocessing and filling operations.

[0008] Furthermore, the specific execution process of step 2 is as follows: The temperature control system of the calorimeter test chamber is activated to control and stabilize the temperature of the external environment of the test chamber at a first preset temperature. ; The heating unit is activated, causing it to heat the feather sample inside the test chamber at a constant power. The range of the constant power is as follows: to Simultaneously, the temperature data of the feather sample to be tested inside the chamber is continuously monitored by the temperature sensing unit at a preset first sampling frequency. When the temperature of the feather sample to be tested rises to the second preset temperature And in The temperature point is maintained for at least 10 minutes, during which the temperature fluctuation should not exceed [a certain value]. When the calorimeter test chamber reaches a steady-state thermal equilibrium, it is determined that the interior of the chamber has reached a steady-state thermal equilibrium.

[0009] Furthermore, in the steady-state thermal equilibrium state, the input power of the heating unit is instantaneously increased from the constant power value used to maintain the steady-state thermal equilibrium state by a preset power increment, causing a step change, wherein the power increment is equal to the constant power value. ; While applying the power increment, the sampling frequency of the temperature sensing unit is switched from the first sampling frequency used to establish a steady-state thermal equilibrium to a second sampling frequency with a higher frequency of not less than 1 time / second, and continuous acquisition begins for at least 300 seconds to record the time-series temperature data of the feather sample under test as a function of time. ; When the monitored rate of temperature change remains below When the temperature response reaches a new quasi-steady state within a second and exceeds 30 seconds, data acquisition is stopped.

[0010] Furthermore, using the step change in input power and the time-series temperature data as input variables, a thermal conductivity evaluation model is constructed, and the thermal time coefficient used to characterize the dynamic thermal conductivity process of the feather sample under test is determined using the thermal conductivity evaluation model. The expression for the thermal conductivity evaluation model is as follows: ;

[0011] In the formula, The thermal time coefficient of the feather sample is used to characterize the delay in the change of the response power of the feather sample. The higher the value, the slower the thermal response of the feather sample and the higher its heat preservation performance. This is time-series temperature data. for arrive Time variable; This represents the temperature of the feather sample under steady-state thermal equilibrium before the power increment is applied; It is a natural constant; The time to begin applying the power increment, The time it takes for the temperature response to enter a new quasi-steady state; This is the attenuation factor, used to adjust the degree to which the model pays attention to temperature change data at different times; For power increment; The specific heat capacity of the feather sample to be tested was obtained through experiments.

[0012] Furthermore, the specific process for obtaining the thermal inertia enhancement factor in step 5 includes: Based on the collected time-series temperature data Plot the dynamic thermal response curve of the feather sample to be tested; The logic behind plotting the dynamic thermal response curve is as follows: based on the collected time-series temperature data... Plot points in a coordinate system with time as the horizontal axis and temperature as the vertical axis; then, using data visualization software, connect adjacent data points sequentially in chronological order to form a continuous temperature-time change curve, i.e., the dynamic thermal response curve. For the dynamic thermal response curve in the time interval [ , Nonlinear regression fitting is performed within the function to obtain the fitted curve. ; Calculate the coefficient of determination between the dynamic thermal response curve and the fitted curve. And the coefficient of determination The numerical mapping is given by the thermal inertia enhancement factor. The mapping relationship is as follows: ;

[0013] in, This is a thermal inertia enhancement factor, used to quantify the contribution of the internal pore structure of feather samples to the heat flow delay effect. A higher value indicates a stronger synergistic insulation effect between the internal pore structure of the feather and the heat conduction path; This is the preset scaling factor.

[0014] Furthermore, in step 6, the specific process of calibrating the reference thermal time coefficient by testing the standard sample is as follows: Select a standard feather sample with known thermal insulation performance and stable physical properties, and repeat steps 1 to 4 under the same test conditions to calculate several thermal time coefficient measurements of the standard feather sample. Take the arithmetic mean of these measurements as the reference thermal time coefficient. Based on the aforementioned thermal time coefficient, reference thermal time coefficient, and thermal inertia enhancement factor, the thermal insulation performance evaluation index of the feather sample to be tested is determined using the following formula: ;

[0015] In the formula, The thermal insulation performance evaluation index is used for the feather sample to be tested. The thermal time coefficient of the feather sample to be tested; As the reference thermal time coefficient; The specific heat capacity of the feather sample to be tested; Specific heat capacity of standard feather sample; It is a thermal inertia enhancement factor; It is a natural constant; This is a temperature influence factor, used to adjust the degree of influence of temperature changes on thermal insulation performance; The temperature of the feather sample under test when the temperature response enters a new quasi-steady state; This indicates the temperature of the feather sample under steady-state thermal equilibrium before the power increment is applied.

[0016] Furthermore, the thermal insulation performance evaluation index is compared with a preset thermal insulation performance grading threshold. Based on the comparison results, the thermal insulation performance level and evaluation result of the feather sample to be tested are determined. The specific logic is as follows: Preset first evaluation threshold Second evaluation threshold and the third evaluation threshold And satisfy: ; like If the insulation performance of the tested feather sample is deemed insufficient, the insulation performance will be classified as Grade D. like If the thermal insulation performance of the feather sample is determined to be Grade C, the evaluation result is that the thermal insulation performance is qualified. like If the thermal insulation performance of the feather sample is determined to be Grade B, the evaluation result is that the thermal insulation performance is good. like If the thermal insulation performance of the tested feather sample is rated as Grade A, the evaluation result is that the thermal insulation performance is excellent.

[0017] The present invention also provides an evaluation system for the thermal insulation performance of feathers, the evaluation system for performing the above-described evaluation method for the thermal insulation performance of feathers, comprising: The sample processing module is used to uniformly fill the pre-treated feather sample into the calorimeter test chamber, which has a heating unit and a temperature sensing unit. The pre-treatment includes cleaning and drying. The steady-state construction module is used to control the external ambient temperature of the calorimeter test chamber to be constant at a first preset temperature, and to start the heating unit to heat the feather sample to be tested at a constant power until the temperature of the feather sample to be tested detected by the temperature sensing unit is stable at the second preset temperature. The testing module is used to apply a preset power increment to the input power of the heating unit, causing it to produce a step change, and simultaneously continuously collect the time-series temperature data of the feather sample to be tested in the test chamber at a preset sampling frequency. The thermal time coefficient calculation module is used to construct a thermal conductivity evaluation model with the power increment and the time-series temperature data as input variables, and to determine the thermal time coefficient used to characterize the dynamic thermal conductivity process of the feather sample under test using the thermal conductivity evaluation model. The curve fitting module is used to plot the dynamic thermal response curve based on the time-series temperature data and analyze its fitting curve function to obtain the thermal inertia enhancement factor used to characterize the synergistic effect of the sample's internal pore structure and heat conduction path. The index generation module is used to calibrate the reference thermal time coefficient by testing standard samples, and determine the thermal insulation performance evaluation index of the feather sample to be tested based on the thermal time coefficient, the reference thermal time coefficient and the thermal inertia enhancement factor. The thermal insulation performance evaluation index is used to evaluate the thermal insulation performance of the feather sample to be tested. The rating module is used to compare the thermal insulation performance evaluation index with the preset thermal insulation performance grading threshold to determine the thermal insulation performance level of the feather sample to be tested.

[0018] Compared with the prior art, the beneficial effects of the present invention are: This invention employs a standardized sample pretreatment process. First, impurities are removed through screening; then, the sample is washed with deionized water to a specific water quality standard; finally, it is dried at constant temperature and humidity to a constant weight. Next, standardized filling ensures no gaps or accumulation in the sample, effectively eliminating interference from impurities, humidity, and filling variations in the feathers on the test results and significantly improving the uniformity of the evaluation criteria. By constructing a precise steady-state thermal equilibrium, maintaining a constant external ambient temperature, heating the feather sample to a target temperature and keeping it stable, and then applying a specific power step change, high-frequency temperature data is acquired and combined with a thermal conductivity assessment model to calculate the thermal time coefficient. This method achieves precise capture of the dynamic heat conduction process and thermal response delay of feathers, overcoming the shortcomings of traditional methods that only focus on macroscopic thermal insulation effects. Furthermore, by calibrating the reference thermal time coefficient through standard samples, specific heat capacity and temperature influence factors are introduced to construct a thermal insulation performance evaluation index. Based on preset thresholds, multiple evaluation levels are divided, forming a dedicated quantitative evaluation system for feather materials. This not only solves the problem of lacking a dedicated calibration mechanism, but also provides a reliable basis for the precise grading, quality control, and selection of feather thermal insulation performance in high-end application scenarios, significantly improving the repeatability, comparability, and practicality of the evaluation results. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a parallel coordinate graph of thermal parameters, specific heat capacity, and thermal insulation performance evaluation index; Figure 3 A 3D bar graph showing thermal parameters and thermal insulation performance evaluation indices; Figure 4 This is a schematic diagram of the overall system modules of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0021] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0022] Example: Please see Figures 1-3 The present invention provides a technical solution: The evaluation method for the thermal insulation performance of feathers includes the following specific steps: Step 1: The pretreated feather sample to be tested is uniformly filled into the calorimeter test chamber equipped with a heating unit and a temperature sensing unit. The pretreatment includes cleaning and drying. In this embodiment, the specific execution process of step 1 is as follows: The feather samples to be tested were screened through a 30-mesh metal sieve to remove down, dust, and fiber impurities from the feathers. The screened feather samples were immersed in deionized water for 15-20 minutes, during which time stubborn stains on the surface of the feathers were brushed off with a soft brush. After brushing, the deionized water was replaced and the feathers were rinsed until the conductivity of the rinsing water was lower than that of the sample. Complete the cleaning process; The cleaned feather sample was laid flat on a breathable cotton tray and placed in a container with the temperature set to [temperature value missing]. Relative humidity set to In a constant temperature and humidity drying oven, the sample is weighed every 2 hours during the drying process. When the weight difference between two consecutive weighings is less than [value missing], the sample is considered dry. When the sample reaches a constant weight, stop drying and remove the sample. The feather sample, having reached constant weight, was fluffed up and evenly filled into the calorimeter test chamber. During filling, a glass rod was used to smooth the sample, and a gap was maintained between the upper surface of the sample and the top inner wall of the test chamber after filling. The reserved space is used to complete the preprocessing and filling operations.

[0023] The sample pretreatment and standardized filling procedures specified in Step 1 are the physical basis and primary prerequisite for ensuring the accuracy, repeatability, and comparability of subsequent test results. This step, through a series of standardized processes including screening, cleaning, drying, constant weight determination, and standardized filling, systematically eliminates key interfering factors commonly found in feather samples, such as impurities, surface grease, residual moisture, and uneven filling density. Specifically, cleaning until the conductivity of the effluent is below a specific standard ensures the cleanliness of the sample surface and controllable ion residue; drying to a constant weight precisely controls the initial moisture content of the sample, avoiding significant errors in thermal measurements caused by moisture evaporation or absorption; and emphasizing "fluffy unfolding, uniform filling, no accumulation gaps, and reserved space" is to reproduce the typical fluffy state of feathers in actual use within the test chamber, ensuring the representativeness of the heat transfer path. Without this step, the initial state of the feather sample will be highly uncertain, directly causing the establishment of the steady-state thermal equilibrium in step 2 to be erratic. The dynamic temperature response data collected in step 3 will contain a large amount of noise introduced by factors other than the material's own properties, ultimately making the thermal time coefficient calculated in step 4 and the evaluation index generated in step 5 unreliable and incomparable.

[0024] Compared to existing technologies, the core advantage of step 1 in this solution lies in its establishment of a specific and quantifiable sample pretreatment standard tailored to the characteristics of feather materials. Existing technologies typically lack detailed specifications for the pretreatment process of the tested materials themselves, or only provide generalized descriptions. This invention, however, deeply recognizes that feathers, as a natural, easily contaminated, humidity-sensitive, and morphologically variable porous material, require standardized pre-test conditions. By introducing specific quantitative indicators, step 1 transforms the preparation process, which originally relied on operator experience, into an objective and reproducible standardized operation. This not only fundamentally improves the consistency and reliability of the measurement results of this method, but also enables fair comparison and accurate grading of feather samples from different batches and sources on the same benchmark, solving the long-standing pain point of existing technologies where inconsistent initial sample conditions lead to large deviations in evaluation results and an inability to effectively compare samples.

[0025] Step 2: Control the external ambient temperature of the calorimeter test chamber to be constant at the first preset temperature, start the heating unit to heat the feather sample to be tested at a constant power until the temperature of the feather sample to be tested detected by the temperature sensing unit is stable at the second preset temperature. In this embodiment, the specific execution process of step 2 is as follows: The temperature control system of the calorimeter test chamber is activated to control and stabilize the temperature of the external environment of the test chamber at a first preset temperature. Wherein, the first preset temperature Set to a constant value within the range of 15℃ to 25℃; The heating unit is activated, causing it to heat the feather sample inside the test chamber at a constant power. The range of the constant power is as follows: to Simultaneously, the temperature data of the feather sample to be tested inside the chamber is continuously monitored by the temperature sensing unit at a preset first sampling frequency. When the temperature of the feather sample to be tested rises to the second preset temperature And in The temperature point is maintained for at least 10 minutes, during which the temperature fluctuation should not exceed [a certain value]. When the temperature reaches a steady-state thermal equilibrium, the calorimeter test chamber is determined to be in a stable thermal equilibrium state; the second preset temperature is set to a constant value within the range of 35°C to 40°C.

[0026] Step 2 is the core foundation and key prerequisite of the entire evaluation method. Its significance lies in creating a stable, controllable, and reproducible initial thermal environment for subsequent dynamic testing. By precisely controlling the external temperature of the test chamber to be constant and heating the feather sample with constant power until its internal temperature reaches and stabilizes at the target value, this process ensures that the sample is in a thermally saturated state where heat input and dissipation are in balance from the initial state. This carefully established steady state eliminates interference caused by uneven initial temperature or unstable heat flow to subsequent transient thermal response testing. This ensures that the temperature change data collected after applying a power step in Step 3 purely reflects the thermal inertia of the feather sample itself, rather than the noise of the transition process when the system has not reached equilibrium. Therefore, Step 2 is the decisive step in ensuring the accuracy and reliability of the subsequently extracted thermal time coefficient, thereby making the entire evaluation result highly repeatable and comparable.

[0027] Compared to existing technologies, the advantage of this step lies in its proactive method of constructing a steady state and directly exciting the sample. Existing technologies rely on slow changes in the external environment as test excitation, which results in weak, uncontrollable excitation signals, long test cycles, and responses easily affected by the complex structure of the test object. In contrast, step 2 of this invention proactively and rapidly establishes a steady state through an internal heating unit, and then applies a power step with precisely controllable amplitude and timing as an excitation signal based on this steady state. This method not only significantly shortens the test time and improves efficiency, but more importantly, it achieves direct and powerful excitation of the feather sample itself, generating a more significant and purer thermal response signal. This avoids the signal attenuation and background noise problems caused by indirect and passive testing methods in existing technologies, making the capture of the intrinsic thermal properties of feather materials more sensitive and direct, and particularly suitable for the precise characterization of lightweight, porous materials with low heat capacity, such as feathers.

[0028] Step 3: Apply a preset power increment to the input power of the heating unit to produce a step change, and simultaneously continuously collect the time-series temperature data of the feather sample to be tested in the test chamber at a preset sampling frequency. In this embodiment, the input power of the heating unit is instantaneously increased by a preset power increment from a constant power value used to maintain steady-state thermal equilibrium, causing a step change. The power increment is equal to the constant power value. ; While applying the power increment, the sampling frequency of the temperature sensing unit is switched from the first sampling frequency used to establish a steady-state thermal equilibrium to a second sampling frequency with a higher frequency of not less than 1 time / second, and continuous acquisition begins for at least 300 seconds to record the time-series temperature data of the feather sample under test as a function of time. ; When the monitored rate of temperature change remains below When the temperature response reaches a new quasi-steady state within a second and exceeds 30 seconds, data acquisition is stopped.

[0029] Step 3 is the key turning point in this method, shifting from steady-state characterization to dynamic performance evaluation. Its core significance lies in actively applying a controllable and quantifiable thermal perturbation and capturing the complete transient thermal response of the feather sample to this perturbation at a high frequency. This step moves the test conditions from static equilibrium to dynamic non-equilibrium, enabling the observation and recording of the dynamic processes of heat conduction and storage within the porous structure of the feather. The collected time-series temperature data contains thermal inertia information reflecting the essential thermal insulation performance of the feather and is the sole data source for calculating the thermal time coefficient in subsequent steps. Therefore, Step 3 is the core bridge connecting the carefully prepared initial state with the final quantitative evaluation result, directly determining the accuracy and reliability of the extracted feature parameters.

[0030] Compared to existing technologies, the significant advantage of this step lies in the active controllability of its excitation signal and the high signal-to-noise ratio of the response signal. Existing technologies rely on the slow heating / cooling of an ambient temperature chamber as excitation. This excitation signal has a low rate of change, a long period, and is easily affected by environmental fluctuations, resulting in a weak and slow-changing thermal response signal with a low signal-to-noise ratio, making it difficult to accurately extract the dynamic characteristics of the material. Step 3 of this invention uses an instantaneous step change in the power of the heating unit as excitation. This excitation has precise amplitude, accurate timing, and an extremely short rise time, making it a powerful and transient active excitation. This excitation can elicit a significant and rapid thermal response in the sample. Combined with high-frequency sampling, it can accurately capture subtle dynamics of temperature changes. This method not only greatly shortens the testing time and improves efficiency, but more importantly, it obtains high-quality, high-resolution transient response data, laying a solid foundation for subsequent accurate calculation of the thermal time coefficient. It is particularly suitable for characterizing the intrinsic thermal insulation properties of materials like feathers that are sensitive to rapid thermal changes.

[0031] Step 4: Using the power increment and the time-series temperature data as input variables, construct a thermal conductivity evaluation model, and use the thermal conductivity evaluation model to determine the thermal time coefficient used to characterize the dynamic thermal conductivity process of the feather sample under test; In this embodiment, the power increment and the time-series temperature data are used as input variables to construct a thermal conductivity evaluation model, and the thermal time coefficient used to characterize the dynamic thermal conductivity process of the feather sample under test is determined using the thermal conductivity evaluation model. The expression for the thermal conductivity evaluation model is as follows: ;

[0032] In the formula, The thermal time coefficient of the feather sample is used to characterize the delay in the change of the response power of the feather sample. The higher the value, the slower the thermal response of the feather sample and the higher its heat preservation performance. This is time-series temperature data. for arrive Time variable; This represents the temperature of the feather sample under steady-state thermal equilibrium before the power increment is applied; It is a natural constant; Let the time to begin applying the power increment be... ; The time it takes for the temperature response to enter a new quasi-steady state; This is the attenuation factor, used to adjust the model's focus on temperature changes over different time periods. ; For power increment; The specific heat capacity of the feather sample to be tested was obtained through experiments.

[0033] Among them, the specific heat capacity of the feather sample to be tested The method for obtaining the specific heat capacity is as follows: Differential scanning calorimetry (DSC) is used to perform thermal analysis on the feather sample to be tested. The sample and a standard reference with a known specific heat capacity are scanned under the same conditions. By comparing the heat flow response signals of the two samples within the temperature range of 20℃ to 40℃, and subtracting the background, the average specific heat capacity of the feather sample within this temperature range is calculated. .

[0034] In this formula, the dependent variable The dynamic characteristics of the temperature response delay of the tested feather sample after being subjected to a power step change were quantitatively characterized. Specifically, The value reflects the magnitude of the inertia of heat transfer within the sample, that is, the rate of temperature change from the initial steady state to the new quasi-steady state. A higher value indicates a slower response to thermal disturbances, a longer retention time of heat within the material, and better thermal insulation performance. The technical advantage of this parameter lies in quantifying the dynamic thermal conduction process of feathers into a clearly defined physical indicator. This allows for comparison of the thermal insulation performance of different samples using a unified numerical value, improving the objectivity and accuracy of the evaluation and providing a reliable basis for the precise grading and application selection of feather materials.

[0035] Temperature and power changes together affect the dependent variable. Size: It reflects the dynamic process of temperature change; the larger its integral value, the better. The higher the value, the slower the thermal response; As the intensity of the excitation signal increases, its increase will make the temperature response more significant, thus achieving the same thermal insulation performance. The value increases; As a decay factor, it adjusts the model's focus weight on data from the early or late stages of temperature changes, thus affecting the integral results.

[0036] and The integral values ​​are negatively correlated. The integral term represents the dynamic temperature rise process after exponential decay weighting. The smaller the value, the slower the temperature response of the feather sample after being subjected to thermal excitation, and the greater the thermal inertia. Therefore, the calculated... A higher value indicates better thermal insulation performance. The applied power increment... A larger temperature reading and slower temperature change in the feather sample indicate that the feather sample has high thermal inertia and good heat retention properties. In this case, the calculated... Higher values; conversely, if the values ​​are the same If the temperature response is rapid, then The value decreased. The specific heat capacity of the feather sample being tested... This reflects its own heat storage capacity. Under the same external thermal excitation, if two samples exhibit similar temperature responses, the sample with a smaller specific heat capacity means that it needs to absorb less heat for heat storage, thus indirectly indicating that it has poorer thermal conductivity, higher thermal resistance, stronger insulation ability for heat exchange, and better heat preservation performance. The value is correspondingly high. Therefore, A higher value indicates a slower thermal response and better insulation performance of the tested feather sample. These physical quantities work together to determine the thermal performance. The final value and the level of thermal insulation performance it reflects.

[0037] The formal rationality of this thermal conductivity assessment model lies in its establishment of a direct and self-consistent relationship between the physical process of dynamic temperature rise and the thermal time coefficient through a reciprocal structure. The integral term in the model's denominator... The key is that it uses exponential decay weighting to highlight the temperature rise data in the initial stage of the temperature response. This means that samples with a more significant and faster initial temperature rise have a larger integral value, indicating poorer thermal insulation performance; while samples with good thermal insulation performance have a smaller integral value due to their large thermal inertia and slow initial temperature rise. Based on this, the reciprocal of the entire integral term is reasonably transformed into a measure of the thermal response delay: a large integral value corresponds to a small reciprocal, indicating a fast response and poor thermal insulation; a small integral value corresponds to a large reciprocal, indicating a slow response and good thermal insulation. This is used to eliminate dimensional interference and system bias caused by the difference between input power and the specific heat capacity of the sample itself, and to ensure that the thermal time coefficient can purely characterize the intrinsic thermal inertia of the feather material under fixed excitation.

[0038] Step 4 is a crucial computational step in this method, transforming physical measurement data into core evaluation parameters. Its core significance lies in constructing a dedicated thermal conductivity assessment model to quantitatively extract the thermal time coefficient, which essentially characterizes the thermal inertia of the feather sample, from the dynamic temperature response data collected in Step 3. This step is not simply recording temperature changes; rather, based on the principle of unsteady-state thermal conduction, it utilizes an integral model incorporating a decay factor to perform in-depth analysis of the time-series temperature data. This model, through weighted integration, focuses on analyzing the dynamic process of temperature change, particularly the response characteristics in the initial stage, thus enabling the calculated thermal time coefficient to sensitively reflect the comprehensive ability of the feather material to store heat and delay heat transfer. The thermal time coefficient value is directly positively correlated with thermal insulation performance and forms the basis for subsequent quantitative evaluation and grading. Therefore, Step 4 is the core step in elevating experimental observation data into key indicators with clear physical meaning and evaluation value.

[0039] Compared to existing technologies, the significant advantage of this step lies in the directness and essentiality of its evaluation parameters. Existing technologies yield a heat dissipation coefficient that is a system-level parameter strongly correlated with the overall structure, mass, and heat capacity of the test object. It indirectly reflects the performance of the insulation material in a specific application scenario, but is not an inherent property of the material itself. In contrast, the thermal time coefficient defined and calculated in step 4 of this invention is a comprehensive parameter extracted directly from the dynamic thermal response of the feather sample, reflecting its intrinsic thermophysical properties and structural characteristics. It eliminates the influence of complex system structures and directly characterizes the thermal inertia of the material. This shift from "system performance" to "material properties" makes the evaluation results more universal and comparable, not only revealing the physical essence of feather insulation performance more scientifically, but also providing a unified, intrinsic performance evaluation benchmark for feather materials from different sources and in different forms.

[0040] Step 5: Based on the time-series temperature data, plot the dynamic thermal response curve and analyze its fitting curve function to obtain the thermal inertia enhancement factor used to characterize the synergistic effect of the internal pore structure and heat conduction path of the sample. In this embodiment, the specific process of obtaining the thermal inertia enhancement factor in step 5 includes: Based on the collected time-series temperature data Plot the dynamic thermal response curve of the feather sample to be tested; The logic behind plotting the dynamic thermal response curve is as follows: based on the collected time-series temperature data... Plot points in a coordinate system with time as the horizontal axis and temperature as the vertical axis; then, using data visualization software, connect adjacent data points sequentially in chronological order to form a continuous temperature-time change curve, i.e., the dynamic thermal response curve. For the dynamic thermal response curve in the time interval [ , Nonlinear regression fitting is performed within the function to obtain the fitted curve. ; The specific logic for constructing the fitting curve function is as follows: based on the collected time-series temperature data Plot the dynamic thermal response curve and select a composite function containing exponential decay terms and polynomial terms as the basic fitting model. Its expression is as follows: ;

[0041] In the formula, the parameter The initial reference for the thermal response is represented, and its value approaches the steady-state temperature before the step. ;parameter The rate of long-term linear trend of temperature change reflects the steady-state temperature rise rate of the system under a step power; parameters The amplitude characterizes the dynamic thermal response, reflecting the feather's instantaneous temperature rise potential and delay intensity under sudden power changes; parameters The key thermal inertia decay factor is the value of the function. The smaller the value, the slower the exponential decay, the stronger the thermal delay effect of the feather, and the better the thermal insulation performance. This function, through the coupling of linear and exponential terms, fully describes the dynamic process of feather temperature from rapid response to slow stabilization. Its parameters together quantify the thermal dynamic characteristics of feather materials. This form can effectively characterize the dynamic thermal characteristics of feather samples under step heating, including rapid heating and slow stabilization. Subsequently, the Levenberg-Marquardt nonlinear least squares algorithm was applied to iteratively optimize the model parameters. The fitting accuracy was ensured by minimizing the sum of squared residuals between the measured data and the fitted values. Based on this, no fewer than 100 iterations were set, and the coefficient of determination was incorporated into each iteration. The fitting quality is comprehensively evaluated by combining the randomness of the residual distribution, and the determination coefficients obtained within the preset number of iterations are finally selected. The highest fitting function is This provides a reliable basis for the accurate calculation of the thermal inertia enhancement factor.

[0042] Calculate the coefficient of determination between the dynamic thermal response curve and the fitted curve. And the coefficient of determination The numerical mapping is given by the thermal inertia enhancement factor. The mapping relationship is as follows: ;

[0043] in, This is a thermal inertia enhancement factor, used to quantify the contribution of the internal pore structure of feather samples to the heat flow delay effect. A higher value indicates a stronger synergistic insulation effect between the internal pore structure of the feather and the heat conduction path; The preset scaling factor. .

[0044] Coefficient of determination The value itself measures the degree to which the fitted curve interprets the actual dynamic thermal response data. A higher value indicates a stronger temperature change pattern in the feather sample under step heating, reflecting its internal pore structure's ability to fix air, form stable heat conduction paths, and delay heat flow—an external manifestation of enhanced thermal inertia. Therefore, [the value is missing from the original text]. As The computational core has a direct physical correlation. A preset scaling factor is introduced. , making The numerical range of the factor can be adjusted to match the magnitude of other evaluation factors, thereby ensuring that it contributes an appropriate weight in the subsequent comprehensive evaluation index formula, and maintaining the uniformity of the dimensions and the coordination of the calculation of the entire evaluation system.

[0045] Step 5 obtains the thermal inertia enhancement factor through nonlinear fitting of the dynamic thermal response curve, effectively quantifying the synergistic effect of the internal pore structure of the feather and the heat conduction path on heat flow delay, thereby transforming the microstructural characteristics of the material into calculable thermal insulation performance parameters. This step not only makes up for the shortcomings of traditional methods that only focus on macroscopic thermal resistance, but also reveals the structural essence of the thermal insulation performance of feathers from the mechanism level, enabling the evaluation system to simultaneously reflect the comprehensive influence of material composition and morphological characteristics on the thermal insulation effect, significantly improving the scientificity and completeness of the evaluation results, and providing a key basis for the screening and structural optimization of high-performance feather materials.

[0046] Step 6: Calibrate the reference thermal time coefficient by testing standard samples. Based on the thermal time coefficient, the reference thermal time coefficient, and the thermal inertia enhancement factor, determine the thermal insulation performance evaluation index of the feather sample to be tested. The thermal insulation performance evaluation index is used to evaluate the thermal insulation performance of the feather sample to be tested. In this embodiment, the specific process of calibrating the reference thermal time coefficient by testing the standard sample in step 6 is as follows: Select a standard feather sample with known thermal insulation performance and stable physical properties, and repeat steps 1 to 4 under the same test conditions to calculate several thermal time coefficient measurements of the standard feather sample. Take the arithmetic mean of these measurements as the reference thermal time coefficient. Based on the aforementioned thermal time coefficient and the reference thermal time coefficient, the thermal insulation performance evaluation index of the feather sample to be tested is determined using the following formula: ;

[0047] In the formula, The thermal insulation performance evaluation index is used for the feather sample to be tested. The thermal time coefficient of the feather sample to be tested; As the reference thermal time coefficient; The specific heat capacity of the feather sample to be tested; Specific heat capacity of standard feather sample; It is a thermal inertia enhancement factor; It is a natural constant; This is a temperature influence factor, used to adjust the degree of influence of temperature changes on thermal insulation performance. ; The temperature of the feather sample under test when the temperature response enters a new quasi-steady state; This indicates the temperature of the feather sample under steady-state thermal equilibrium before the power increment is applied.

[0048] In this formula, the dependent variable This index is used to quantitatively characterize the overall thermal insulation performance of a tested feather sample relative to a standard sample. By integrating the thermal time coefficient, specific heat capacity, the enhanced thermal inertia effect of the internal pore structure, and the influence of temperature changes during the testing process, it comprehensively reflects the sample's thermal insulation capability under dynamic thermal excitation. A higher value indicates better thermal insulation performance of the tested feather sample. Its technical advantage lies in integrating multiple independent physical parameters into a unified and comparable core evaluation index, eliminating the limitations of single-parameter evaluation, and achieving standardized and quantitative grading of feather thermal insulation performance. This provides a scientific and reliable decision-making basis for product quality control, material selection, and high-value-added applications.

[0049] thermal time coefficient ratio Specific heat ratio Thermal inertness enhancement factor and the effect of temperature difference Together they determine the dependent variable. Size: It is a core item, directly reflecting the thermal response delay capability of the test sample relative to the standard sample; Used to correct for the effects of differences in basic thermophysical properties between samples, ensuring the fairness of the evaluation; The quantification of the resistance and delay effect of the internal pore structure of the sample on heat flow is a manifestation of the structural heat preservation effect; This introduces a correction for the impact of temperature variation during the testing process on the thermal insulation performance. Factors are used to adjust the weight of this influence. These variables work together from four dimensions: thermal inertia, material nature, microstructure, and test conditions, and comprehensively determine the final thermal insulation performance evaluation index.

[0050] Thermal insulation performance evaluation index and , and All three are positively correlated, meaning that the larger the thermal time coefficient, the better the specific heat capacity characteristics, and the stronger the delay effect of the internal pore structure on heat flow of the sample, the higher its thermal insulation performance evaluation index, indicating that the thermal insulation performance is superior. and The correlation is negative because, under a power step excitation, the higher the steady-state temperature reached by the sample, the lower its thermal resistance or the greater the heat loss, thus weakening the overall thermal insulation performance evaluation. This effect is moderated by an exponential decay term. The factor determines the strength of this weakening effect.

[0051] The formula's formal rationality lies in its systematic integration of the core physical factors affecting the heat-insulating performance of feathers through the construction of a dimensionless exponent coupled with multiple factors. The formula uses a relative thermal time coefficient... As a core component, it directly characterizes the dynamic heat retention capacity of the sample; by introducing the specific heat ratio The intrinsic thermal properties of the material are normalized to eliminate interference from differences in basic physical properties; thermal inertia enhancement factor. The effect of microstructure on heat flow delay was further quantified; while the exponential decay term... This cleverly reflects the weakening effect of the actual temperature rise process on the thermal insulation performance, which is in line with the physical laws of heat conduction. This structure not only ensures the uniformity of dimensions and the comparability of results, but also highlights the synergistic influence of key parameters through the product relationship of various factors, so that the final evaluation index can stably and comprehensively reflect the overall thermal insulation performance of the feather material.

[0052] Table 1: Statistical Table of Thermal Insulation Performance Evaluation Index

[0053] It should be noted that the thermal parameters, specific heat capacity, and temperature difference terms mentioned in Table 1 correspond to the terms in the above formulas. , and item; Based on the data in Table 1, the changes in the feather insulation performance evaluation index are significantly correlated with the thermal parameters, specific heat capacity, and temperature difference. When the thermal parameters and specific heat capacity are at a high level, even if there are certain differences in the sample temperature change difference, the insulation performance evaluation index tends to show a high value, reflecting the positive impact of these two factors on the feather insulation performance. Conversely, when these two factors are at a low level, regardless of the fluctuations in the sample temperature change difference, the insulation performance evaluation index mostly remains in a low range, further confirming the role of the former two as key factors affecting the feather insulation performance.

[0054] Meanwhile, changes in the temperature difference term will regulate the thermal insulation performance evaluation index through the exponential term in the formula. When the thermal parameters and specific heat capacity are similar, the larger the temperature difference term is, the more obvious the weakening effect on the thermal insulation performance evaluation index will be. This makes the final value of the evaluation index show a characteristic opposite to the trend of the temperature difference, which is consistent with the regulation logic of the temperature-related factors on the thermal insulation performance evaluation results in the formula, and also consistent with the thermal conductivity characteristics of feather materials under temperature fluctuations.

[0055] Figure 2 The correlation between thermal parameters, specific heat capacity, and the final calculated thermal insulation performance evaluation index is presented in the form of a parallel coordinate graph. The graph shows that when both thermal parameters and specific heat capacity are in a high value range, the thermal insulation performance evaluation index is generally high, indicating that these two parameters have a significant positive impact on the thermal insulation performance of feathers. Conversely, if one or both values ​​are low, the evaluation index decreases accordingly. This graph visually reflects the synergistic effect of each core parameter in the comprehensive evaluation system, verifying the rationality of the evaluation formula and the effectiveness of the parameter weights.

[0056] Figure 3 The spatial distribution relationship between thermal parameters, insulation performance evaluation index, and sample number is further illustrated in a 3D bar chart. The height of the bars represents the magnitude of the insulation performance evaluation index, and the color intensity corresponds to the numerical level of the thermal parameters. It is clearly observed that samples with higher thermal parameters generally have higher corresponding evaluation index bars, further confirming the dominant role of the thermal time coefficient as a core evaluation parameter in determining the insulation performance level of feathers. This 3D visualization helps to understand the performance differences between samples from multiple dimensions, providing intuitive data support for the classification, selection, and process improvement of feather materials.

[0057] Step 6 is the core calibration step in this invention, enabling the transition from relative measurement to absolute evaluation and ensuring the comparability and accuracy of results. Its key significance lies in establishing a stable evaluation scale by introducing standard samples and a reference thermal time coefficient. This transforms the thermal time coefficient of the sample obtained in Step 4 into a dimensionless thermal insulation performance evaluation index that can be compared across batches and laboratories. This step not only includes simple ratio relationships but also innovatively introduces specific heat capacity and temperature influence factors, thereby providing refined compensation and correction for minor differences in thermophysical properties between samples and the impact of temperature variations during testing. This allows the final evaluation index to more purely and accurately reflect the differences in thermal insulation performance of feather samples due to differences in structure and material, eliminating the influence of systematic errors and fluctuations in testing conditions.

[0058] Compared with existing technologies, the significant advantage of this step lies in the scientific nature of its evaluation system and the universal comparability of its results. Existing technologies yield a dimensional absolute value for the heat dissipation coefficient, whose magnitude is heavily dependent on specific testing systems (such as the structure, mass, and temperature measurement point arrangement of the battery pack) and testing conditions (such as the range of ambient temperature variations). Results obtained under different systems or conditions cannot be directly compared, lacking a unified benchmark. In contrast, step 6 of this invention establishes a relative evaluation system independent of any specific testing system by calibrating benchmark parameters using standard samples and constructing a dimensionless evaluation index. This makes the evaluation indices of different feather samples obtained at different times and locations using the same standardized method directly comparable. This shift from "absolute system parameters" to "relative standard indices" greatly enhances the practical value of the evaluation results, providing a reliable and unified quantitative basis for the quality grading, pricing, and performance database establishment of feather materials, and overcoming the limitations of existing technologies where evaluation results are isolated and difficult to compare widely.

[0059] Step 7: Compare the thermal insulation performance evaluation index with the preset thermal insulation performance grading threshold to determine the thermal insulation performance level of the feather sample to be tested. In this embodiment, the thermal insulation performance evaluation index is compared with a preset thermal insulation performance grading threshold. Based on the comparison result, the thermal insulation performance level and evaluation result of the feather sample to be tested are determined. The specific logic is as follows: Preset first evaluation threshold Second evaluation threshold and the third evaluation threshold And satisfy: ; like If the insulation performance of the tested feather sample is deemed insufficient, the insulation performance will be classified as Grade D. like If the thermal insulation performance of the feather sample is determined to be Grade C, the evaluation result is that the thermal insulation performance is qualified. like If the thermal insulation performance of the feather sample is determined to be Grade B, the evaluation result is that the thermal insulation performance is good. like If the thermal insulation performance of the tested feather sample is rated as Grade A, the evaluation result is that the thermal insulation performance is excellent.

[0060] Among them, the first evaluation threshold Second evaluation threshold and the third evaluation threshold The method for obtaining the data is as follows: a large number of representative feather standard samples with known thermal insulation performance and covering different quality levels are tested, and cluster analysis is performed based on their actual performance or industry-recognized quality standards. The data is then calibrated by combining statistical distribution characteristics and expert experience, and finally the threshold range that can reasonably distinguish between the four performance levels of "insufficient", "qualified", "good" and "excellent" is determined, thereby establishing a scientific, objective and practically applicable grading standard.

[0061] Step 7 is the final output stage of this invention, transforming quantitative indices into qualitative decisions and converting technical data into practical application value. Its core significance lies in mapping the continuous thermal insulation performance evaluation index calculated in Step 6 to discrete grades and evaluation results with clear quality meanings by pre-setting explicit grading thresholds. This step transforms abstract numerical results into intuitive, easily understood quality grades that can be directly used to guide production and trade. For example, manufacturers can sort and price raw materials based on AD grades, and quality inspection departments can determine compliance based on these grades. It establishes a bridge between scientific measurement and market demand, enabling complex test data to ultimately serve practical quality control and business decisions.

[0062] Compared to existing technologies, the significant advantage of this step lies in the intuitiveness, practicality, and standardization of its evaluation results. Existing technologies typically stop at providing a physical parameter (such as the heat dissipation coefficient), which is highly specialized. The relationship between its value and the quality of heat insulation performance is not intuitive for non-professionals, and there is a lack of a universally accepted and unified grading standard, making it difficult to directly use data from different sources for comparison and grading decisions. In contrast, step 7 of this invention pre-sets a unified and fixed grading threshold and provides a clear quality description for each grade. This design allows any user to quickly and accurately understand the quality level of the feather sample based on the output grade without delving into the complex underlying principles and parameters. This greatly improves the usability of the evaluation results and the efficiency of decision support, solving the pain point of existing technologies where evaluation results are "numerical but lack gradation" and difficult to directly apply to market activities and quality management. It provides key technical support for the standardization and normalization of the feather industry.

[0063] Please see Figure 4 An evaluation system for the thermal insulation performance of feathers includes: The sample processing module is used to uniformly fill the pre-treated feather sample into the calorimeter test chamber, which has a heating unit and a temperature sensing unit. The pre-treatment includes cleaning and drying. The steady-state construction module is used to control the external ambient temperature of the calorimeter test chamber to be constant at a first preset temperature, and to start the heating unit to heat the feather sample to be tested at a constant power until the temperature of the feather sample to be tested detected by the temperature sensing unit is stable at the second preset temperature. The testing module is used to apply a preset power increment to the input power of the heating unit, causing it to produce a step change, and simultaneously continuously collect the time-series temperature data of the feather sample to be tested in the test chamber at a preset sampling frequency. The thermal time coefficient calculation module is used to construct a thermal conductivity evaluation model using the step change of the input power and the time-series temperature data as input variables, and to determine the thermal time coefficient used to characterize the dynamic thermal conductivity process of the feather sample under test using the thermal conductivity evaluation model. The curve fitting module is used to plot the dynamic thermal response curve based on the time-series temperature data and analyze its fitting curve function to obtain the thermal inertia enhancement factor used to characterize the synergistic effect of the sample's internal pore structure and heat conduction path. The index generation module is used to calibrate the reference thermal time coefficient by testing standard samples, and determine the thermal insulation performance evaluation index of the feather sample to be tested based on the thermal time coefficient, the reference thermal time coefficient and the thermal inertia enhancement factor. The thermal insulation performance evaluation index is used to evaluate the thermal insulation performance of the feather sample to be tested. The rating module is used to compare the thermal insulation performance evaluation index with the preset thermal insulation performance grading threshold to determine the thermal insulation performance level of the feather sample to be tested.

[0064] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0065] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0066] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0067] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for evaluating the heat retention performance of a feather, characterized by, The specific steps include: Step 1: uniformly fill the pretreated sample into the test chamber of the calorimeter with a heating unit and a temperature sensing unit, the pretreatment including cleaning and drying treatment; Step 2: control the external environment temperature of the test chamber to be constant at a first preset temperature, start the heating unit to heat the sample at a constant power until the temperature of the sample detected by the temperature sensing unit stabilizes at a second preset temperature; Step 3: apply a preset power increment to the input power of the heating unit to cause a step change, and simultaneously collect the time series temperature data of the sample in the test chamber at a preset sampling frequency; Step 4: use the power increment and the time series temperature data as input variables to build a heat conduction evaluation model, and use the heat conduction evaluation model to determine the thermal time coefficient for characterizing the dynamic heat conduction process of the sample; Step 5: based on the time series temperature data, draw a dynamic thermal response curve and analyze its fitting curve function to obtain a thermal inertia enhancement factor for characterizing the synergistic effect of the internal pore structure and the heat conduction path of the sample; Step 6: calibrate the reference thermal time coefficient by testing a standard sample, and determine the thermal insulation performance evaluation index of the sample based on the thermal time coefficient, the reference thermal time coefficient and the thermal inertia enhancement factor, the thermal insulation performance evaluation index being used to evaluate the thermal insulation performance of the sample; Step 7: compare the thermal insulation performance evaluation index with a preset thermal insulation performance classification threshold to determine the thermal insulation performance grade corresponding to the sample.

2. The method for evaluating the heat retention performance of a feather according to claim 1, characterized by: The specific execution process of step 1 is as follows: Screen the sample by a 30-mesh metal screen to remove the fluff, dust and fiber impurities in the sample; The screened feather sample to be tested is immersed in deionized water for 15-20 minutes, during which the stubborn stains attached to the surface of the feather are brushed with a soft brush. After brushing, the feather is rinsed with deionized water until the conductivity of the effluent water after rinsing is lower than , and the cleaning process is completed. The cleaned feather sample to be tested is laid on a ventilated cotton tray and placed in a constant temperature and humidity drying box with a temperature setting of and a relative humidity setting of . The sample is weighed every 2 hours during the drying process. When the weight difference between two consecutive weighings is less than , the sample is determined to have reached a constant weight state, the drying is stopped, and the sample is removed. The feather sample, having reached constant weight, was fluffed up and evenly filled into the calorimeter test chamber. During filling, a glass rod was used to smooth the sample, and a gap was maintained between the upper surface of the sample and the top inner wall of the test chamber after filling. The reserved space is used to complete the preprocessing and filling operations.

3. The method for evaluating the heat retention performance of a feather according to claim 1, characterized by: The specific execution process of step 2 is as follows: activating a thermostat system of the calorimeter test chamber to control and stabilize the temperature of the test chamber outside environment at a first preset temperature ; starting the heating unit to start heating the sample of the feather to be tested in the test chamber at a constant power, wherein the constant power is in a range of to ; and simultaneously monitoring the temperature data of the sample of the feather to be tested in the test chamber by the temperature sensing unit at a preset first sampling frequency; When the temperature of the feather sample to be tested rises to the second preset temperature And in The temperature point is maintained for at least 10 minutes, during which the temperature fluctuation should not exceed [a certain value]. When the calorimeter test chamber reaches a steady-state thermal equilibrium, it is determined that the interior of the chamber has reached a steady-state thermal equilibrium.

4. The method for evaluating the heat retention performance of a feather according to claim 3, characterized by: In the steady state thermal equilibrium condition, the input power of the heating unit is instantaneously increased by a preset power increment from a constant power value that maintains the steady state thermal equilibrium condition, so as to generate a step change, the power increment being ; Simultaneously with the application of the power increment, the sampling frequency of the temperature sensing unit is switched from a first sampling frequency at which a steady-state thermal equilibrium state is built to a second sampling frequency at which the sampling frequency is higher, the second sampling frequency being not less than 1 Hz, and a continuous acquisition of at least 300 seconds is started, time-series temperature data of the temperature of the feather sample under test as a function of time being recorded ; When the rate of change of temperature monitored continues to be below Each second and for more than 30 seconds, it is determined that the temperature response enters a new quasi-steady state and the data acquisition is stopped.

5. The method for evaluating the heat retention performance of a feather according to claim 4, characterized by: Use the step change of the input power and the time series temperature data as input variables to build a heat conduction evaluation model, and use the heat conduction evaluation model to determine the thermal time coefficient for characterizing the dynamic heat conduction process of the sample; The expression of the heat conduction evaluation model is as follows: ； In the formula, is the thermal time constant of the feather sample to be tested, used to characterize the delay of the feather sample to be tested in response to power changes. The higher the value, the slower the thermal response of the feather sample to be tested, and the higher the heat retention performance. is the time-temperature data, is the to time variable; represents the temperature of the feather sample to be tested in a steady state of thermal equilibrium before the power increment is applied; is a natural constant; is the time at which the power increment begins to be applied, is the time for the temperature response to enter a new quasi-steady state; is a decay factor used to adjust the degree of attention of the model to temperature change data at different times; is the power increment; is the specific heat capacity of the feather sample to be tested, which is obtained by experiment.

6. The method for evaluating the heat retention performance of a feather according to claim 1, characterized by: The specific process of obtaining the thermal inertia enhancement factor in step 5 includes: Based on the collected timing temperature data , draw the dynamic thermal response curve of the feather sample to be tested; The logic for drawing the dynamic thermal response curve is as follows: the time-series temperature data collected are plotted in a coordinate system with time as the horizontal coordinate and temperature as the vertical coordinate; then, using a data visualization software, each adjacent data point is sequentially connected in time order to form a continuous temperature-time change curve, i.e., the dynamic thermal response curve. For the dynamic thermal response curve in the time interval [ , Nonlinear regression fitting is performed within the function to obtain the fitted curve. ; calculating a determination coefficient between the dynamic thermal response curve and the fitted curve and mapping a value of the determination coefficient to the thermal inertia enhancement factor , the mapping relationship being as follows: wherein, is a thermal inertia enhancement factor, used to quantify the contribution of the internal porosity structure of the feather sample to the thermal flow retardation effect, The higher the value, the stronger the synergistic heat preservation effect of the internal porosity structure of the feather on the heat conduction path. is a preset scaling coefficient.

7. The method for evaluating the heat retaining performance of a feather according to claim 1, characterized by: In step 6, the specific process of calibrating the reference thermal time coefficient by testing a standard sample is as follows: Select a standard sample with known thermal insulation performance and stable physical properties, repeat the steps 1 to 4 under the same test conditions, calculate the thermal time coefficient of the standard sample, and take the arithmetic mean of the measured values as the reference thermal time coefficient; Determine the thermal insulation performance evaluation index of the sample based on the thermal time coefficient, the reference thermal time coefficient and the thermal inertia enhancement factor, and the formula is as follows: ； wherein, is the thermal retention performance evaluation index of the feather sample to be tested; is the thermal time constant of the feather sample to be tested; is the reference thermal time constant; is the specific heat capacity of the feather sample to be tested; is the specific heat capacity of the standard feather sample; is the thermal inertia enhancement factor; is the natural constant; is the temperature influence factor, used to adjust the degree of influence of temperature change on thermal retention performance; is the temperature of the feather sample to be tested when the temperature response enters a new quasi-steady state; represents the temperature of the feather sample to be tested in a steady-state thermal equilibrium state before the power increment is applied.

8. The method for evaluating the heat retention performance of a feather according to claim 7, characterized by: Compare the thermal insulation performance evaluation index with a preset thermal insulation performance classification threshold, and determine the thermal insulation performance grade corresponding to the sample and its evaluation result according to the comparison result, and the specific logic is as follows: a first evaluation threshold value , a second evaluation threshold value , and a third evaluation threshold value , and satisfy: ; If , it is determined that the heat preservation performance grade of the sample to be tested is D, and the evaluation result is that the heat preservation performance is insufficient. If , it is determined that the heat preservation performance grade of the test feather sample is C, and the evaluation result is that the heat preservation performance is qualified. If , it is determined that the heat preservation performance grade of the feather sample to be tested is B, and the evaluation result is that the heat preservation performance is good. If , it is determined that the heat retention performance of the sample to be measured is A level, and the evaluation result is that the heat retention performance is excellent.

9. A system for evaluating the thermal insulation performance of feathers, characterized in that: The evaluation system for the thermal insulation performance of the feather is used to execute the evaluation method for the thermal insulation performance of the feather according to any one of claims 1-8, and includes: a sample processing module, configured to uniformly fill a pretreated sample into a test chamber of a calorimeter having a heating unit and a temperature sensing unit, the pretreatment including cleaning and drying treatment; a steady state construction module, configured to control an external environment temperature of the test chamber to be constant at a first preset temperature, and to start the heating unit to heat the sample at a constant power until the temperature of the sample detected by the temperature sensing unit is stabilized at a second preset temperature; a test module, configured to apply a preset power increment to the input power of the heating unit to cause a step change, and to synchronously and continuously collect time-series temperature data of the sample in the test chamber at a preset sampling frequency; a thermal time constant calculation module, configured to use the power increment and the time-series temperature data as input variables to construct a heat conduction evaluation model, and to determine a thermal time constant for characterizing a dynamic heat conduction process of the sample by using the heat conduction evaluation model; a curve fitting module, configured to draw a dynamic heat response curve based on the time-series temperature data, and to analyze a fitting curve function of the dynamic heat response curve to obtain a thermal inertia enhancement factor for characterizing a synergistic effect of internal pore structure and heat conduction path of the sample; an index generation module, configured to calibrate a reference thermal time constant by using a standard sample, and to determine a thermal insulation performance evaluation index of the sample according to the thermal time constant, the reference thermal time constant and the thermal inertia enhancement factor, the thermal insulation performance evaluation index being used to evaluate the thermal insulation performance of the sample; a grade evaluation module, configured to compare the thermal insulation performance evaluation index with a preset thermal insulation performance grading threshold, and to determine a thermal insulation performance grade corresponding to the sample.

Images