Phase change material phase change temperature calibration method and system

Abstract

The invention relates to the technical field of material testing, and discloses a phase change temperature calibration method and system for a phase change material, and the method comprises the steps: collecting the surface temperature distribution data and crystal structure parameters of the phase change material based on a bimodal synchronous monitor, and building a temperature-structure incidence matrix; when the parameters of the crystal structure suddenly change, determining surface temperature distribution data corresponding to a sudden change moment based on the temperature-structure incidence matrix, and calculating an initial phase change temperature interval; constructing a nonlinear mapping model of the initial phase-change temperature interval and the heating rate, and performing dynamic compensation on the initial phase-change temperature interval based on the nonlinear mapping model to obtain a corrected phase-change temperature; inputting the corrected phase change temperature into a gradient temperature control module containing a standard sample; and comparing the offset of the actual phase change position and the theoretical position of the reference material, and reversely correcting and correcting the phase change temperature based on the offset to obtain the final calibration temperature. The calibration accuracy of the phase change temperature of the phase change material can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of material testing, and particularly to a method and system for calibrating the phase change temperature of a phase change material. Background Art

[0002] Traditional calibration of the phase change temperature of phase change materials usually relies on single-modal data (such as temperature or crystal structure parameters), making it difficult to synchronously monitor the real-time correlation between temperature distribution and crystal structure changes. In addition, the existing technology does not fully consider the influence of the heating rate on the phase change temperature range, resulting in the calibration results being easily interfered by experimental conditions.

[0003] For example, traditional infrared thermometry or X-ray diffraction techniques cannot accurately capture the temperature-structure correspondence at the critical moment of phase change due to asynchronous data acquisition; at the same time, it is difficult for the linear compensation model to accurately correct the phase change hysteresis and thermal expansion effects. These problems lead to systematic errors in the calibration of the phase change temperature, restricting the realization of high-precision application scenarios. Summary of the Invention

[0004] The present invention provides a method and system for calibrating the phase change temperature of a phase change material, and its main purpose is to solve the problem of low accuracy in calibrating the phase change temperature of a phase change material.

[0005] To achieve the above object, a method for calibrating the phase change temperature of a phase change material provided by the present invention includes: Collecting surface temperature distribution data and crystal structure parameters of the phase change material based on a dual-modal synchronous monitor; Establishing a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters; When the crystal structure parameters mutate, determining the surface temperature distribution data corresponding to the mutation moment based on the temperature-structure correlation matrix, and calculating the initial phase change temperature range of the phase change material; Constructing a non-linear mapping model between the initial phase change temperature range and the heating rate, and dynamically compensating the initial phase change temperature range based on the non-linear mapping model to obtain the corrected phase change temperature of the phase change material; Inputting the corrected phase change temperature into a gradient temperature control module containing a standard sample, where the gradient temperature control module includes a reference material that forms a preset temperature difference along the axis, and the phase change point of the reference material is known; Comparing the offset between the actual phase change position and the theoretical position of the reference material, and reversely correcting the corrected phase change temperature based on the offset to obtain the final calibrated temperature of the phase change material.

[0006] Optionally, the collecting surface temperature distribution data and crystal structure parameters of the phase change material based on a dual-modal synchronous monitor includes: In a dual - mode synchronous monitor, an infrared thermal imager and an X - ray diffractometer are synchronously arranged. Among them, the infrared thermal imager and the X - ray diffractometer achieve timestamp alignment through a synchronous trigger signal; When the dual - mode synchronous monitor scans at a set rate, the infrared thermal imager records the surface temperature distribution data of the phase - change material in real time, and at the same time, the X - ray diffractometer continuously collects the crystal structure parameters of the phase - change material. Among them, the crystal structure parameters include lattice constants and diffraction peak intensities.

[0007] Optionally, establishing the temperature - structure correlation matrix of the phase - change material based on the surface temperature distribution data and the crystal structure parameters includes: Mapping the surface temperature distribution data at the same timestamp into a two - dimensional temperature - field grayscale image; Extracting the lattice constant change rate from the crystal structure parameters and converting the lattice constant change rate into a structure response coefficient; Based on the same timestamp, performing spatial registration on the two - dimensional temperature - field grayscale image and the structure response coefficient to obtain the temperature - structure correlation matrix of the phase - change material.

[0008] Optionally, the determination conditions for the mutation of the crystal structure parameters include: Performing a second - order derivative operation on the structure response coefficient to obtain the derivative change curve of the structure response coefficient; Extracting the extreme points whose absolute values exceed a preset threshold from the derivative change curve; Taking the timestamp corresponding to the extreme point as the mutation moment and determining that the crystal structure parameters mutate at the mutation moment.

[0009] Optionally, constructing the non - linear mapping model between the initial phase - change temperature range and the heating rate includes: Extracting the upper - bound value and the lower - bound value from the initial phase - change temperature range, and combining the upper - bound value, the lower - bound value and the heating rate to jointly form an input feature vector ; Inputting the input feature vector into a pre - configured support vector regression algorithm. The support vector regression algorithm includes a kernel function and a loss function, where: The kernel function is a radial basis function, and the expression of the radial basis function is as follows: ; In the formula, is the function value of the radial basis function, is the kernel function bandwidth parameter, is the th sample point in the input feature vector, is the th sample point in the input feature vector, is the exponential function, is the Euclidean distance between the th sample point and the th sample point in the input feature vector; The loss function is the Huber loss function, and the expression of the Huber loss function is as follows: ; In the formula, is the function value of the Huber loss function, is the prediction error, is the robustness threshold; The support vector regression algorithm is iteratively trained using multiple groups of calibration data of historical phase change materials until the loss function converges, and a dynamic compensation function associated with the heating rate is generated. Among them, the expression of the dynamic compensation function is as follows: ; In the formula, is the phase change hysteresis factor, is the thermal expansion compensation coefficient, is the upper boundary value, is the lower boundary value, is the heating rate, is the function value corresponding to the dynamic compensation function; The dynamic compensation function is applied to the boundary values of the initial phase change temperature range, and the median and full width at half maximum of the corrected phase change temperature are output. Among them, the median is determined by the center point of the compensated temperature range, and the full width at half maximum is calculated from the span of the compensated temperature range. The expression of the median is as follows: ; In the formula, is the median of the corrected phase change temperature, is the upper boundary value, is the lower boundary value, is the heating rate, is the function value corresponding to the dynamic compensation function; The expression of the full width at half maximum is as follows: ; In the formula, is the full width at half maximum of the corrected phase change temperature, is the upper boundary value, is the lower boundary value, is the heating rate, is the function value corresponding to the dynamic compensation function.

[0010] Optionally, the gradient temperature control module includes: Set the axial center temperature reference point of the gradient temperature control module according to the median, where the temperature value of the axial center temperature reference point is the median; Based on the full width at half maximum, calculate the axial temperature gradient step of the gradient temperature control module, and generate a preset temperature difference that is linearly related to the full width at half maximum. The calculation formula of the axial temperature gradient step is as follows: ; In the formula, is the axial temperature gradient step, is the full width at half maximum, is the thermal expansion compensation coefficient, is the thermal conductivity of the gradient temperature control module; Along the axial direction of the gradient temperature control module, starting from the axial center temperature reference point, configure the heating units step by step according to the axial temperature gradient step to form a linear temperature gradient distribution including at least five temperature nodes; Fix the reference material at each temperature node of the linear temperature gradient distribution.

[0011] Optionally, the arrangement of the reference materials satisfies: Arrange the reference materials with different phase change points in a circular array at the corresponding temperature nodes of the linear temperature gradient distribution. The adjacent circular spacing is calculated based on the axial temperature gradient step in an inverse proportional relationship. The calculation formula of the adjacent circular spacing is as follows: ; In the formula, is the thermal expansion coefficient, is the axial temperature gradient step, is the adjacent circular spacing; Establish a phase change point - temperature coordinate mapping table according to the known phase change points of the reference materials and the node temperature values of the linear temperature gradient distribution. The phase change point - temperature coordinate mapping table is used to calibrate the theoretical positions of the reference materials.

[0012] Optionally, comparing the offset between the actual phase change position and the theoretical position of the reference material includes: Real - time capture the droplet deformation characteristic images generated by the reference material during the phase change process through a high - speed camera, where the droplet deformation characteristic images include the geometric center coordinates of the phase change interface; Extract the actual coordinate values of the geometric center coordinates from the droplet deformation characteristic image, and perform a difference calculation with the theoretical coordinate values of the corresponding temperature nodes in the phase change point-temperature coordinate mapping table to generate the center coordinate offset of the reference material. ; Calculate the temperature compensation amount of the phase change material based on the axial thermal expansion coefficient of the gradient temperature control module and the center coordinate offset. The temperature compensation amount is the product of the center coordinate offset and the axial thermal expansion coefficient. The calculation formula for the temperature compensation amount is as follows: ; In the formula, is the thermal expansion coefficient, is the thermal conductivity of the gradient temperature control module, is the center coordinate offset of the reference material, is the temperature compensation amount of the phase change material; Determine the offset between the actual phase change position and the theoretical position of the reference material based on the temperature compensation amount.

[0013] Optionally, the reverse correction of the corrected phase change temperature based on the offset to obtain the final calibration temperature of the phase change material includes: Determine the deviation direction and deviation magnitude of the actual phase change position of the reference material relative to the theoretical position based on the offset; Perform a reverse adjustment on the corrected phase change temperature based on the deviation direction and the deviation magnitude to obtain the final calibration temperature of the phase change material, where: When the offset is positive, lower the corrected phase change temperature; When the offset is negative, raise the corrected phase change temperature.

[0014] To solve the above problems, the present invention also provides a phase change temperature calibration system for a phase change material. The system includes: A data synchronous acquisition module for acquiring the surface temperature distribution data and crystal structure parameters of the phase change material based on a dual-mode synchronous monitor; An association matrix construction module for establishing a temperature-structure association matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters; An initial phase change temperature interval generation module for determining the surface temperature distribution data corresponding to the mutation moment based on the temperature-structure association matrix when the crystal structure parameters mutate, and calculating the initial phase change temperature interval of the phase change material; An initial temperature range dynamic compensation module is used to construct a non - linear mapping model between the initial phase change temperature range and the heating rate, and dynamically compensate the initial phase change temperature range based on the non - linear mapping model to obtain the corrected phase change temperature of the phase change material; A data input module is used to input the corrected phase change temperature into a gradient temperature control module containing a standard sample. The gradient temperature control module includes a reference material with a preset temperature difference formed along the axis, and the phase change point of the reference material is known; A temperature reverse correction module is used to compare the offset between the actual phase change position and the theoretical position of the reference material, and reverse correct the corrected phase change temperature based on the offset to obtain the final calibrated temperature of the phase change material.

[0015] In the present invention, a dual - mode synchronous monitor (infrared thermal imager and X - ray diffractometer) is used to align the time stamps of the temperature distribution and crystal structure parameters, solving the problem of data fragmentation in traditional methods, and improving data correlation and analysis accuracy; a non - linear mapping model based on support vector regression is constructed, and the initial phase change temperature range is dynamically compensated by combining historical data, effectively correcting phase change hysteresis and thermal expansion effects, and reducing calibration errors; by comparing the offset between the actual and theoretical phase change positions of the reference material through the gradient temperature control module, the corrected temperature is reverse corrected to form a closed - loop optimization process, significantly improving the accuracy of the final calibrated temperature; an artificial intelligence algorithm (such as the Huber loss function) is used to enhance the robustness of the model to abnormal data, which is applicable to various phase change materials and complex experimental conditions. Brief Description of the Drawings

[0016] Figure 1 It is a schematic flow chart of a method for calibrating the phase change temperature of a phase change material provided by an embodiment of the present invention; Figure 2 It is a functional module diagram of a system for calibrating the phase change temperature of a phase change material provided by an embodiment of the present invention; The implementation, functional characteristics and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. Detailed Embodiments

[0017] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0018] An embodiment of the present application provides a method for calibrating the phase change temperature of a phase change material. The execution subject of the method for calibrating the phase change temperature of the phase change material includes at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided in the embodiment of the present application. In other words, the method for calibrating the phase change temperature of the phase change material can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server, or a cloud server cluster, etc. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, Content Delivery Network (CDN), and big data and artificial intelligence platforms.

[0019] Referring to Figure 1 As shown, it is a schematic flowchart of the method for calibrating the phase change temperature of a phase change material provided by an embodiment of the present invention. In this embodiment, the method for calibrating the phase change temperature of the phase change material includes: S1. Collect the surface temperature distribution data and crystal structure parameters of the phase change material based on a dual-mode synchronous monitor.

[0020] In the embodiment of the present invention, the collecting of the surface temperature distribution data and crystal structure parameters of the phase change material based on a dual-mode synchronous monitor includes: Synchronously arrange an infrared thermal imager and an X-ray diffractometer in the dual-mode synchronous monitor, wherein the infrared thermal imager and the X-ray diffractometer achieve timestamp alignment through a synchronous trigger signal; When the dual-mode synchronous monitor scans at a set rate, the infrared thermal imager records the surface temperature distribution data of the phase change material in real time, and at the same time the X-ray diffractometer continuously collects the crystal structure parameters of the phase change material, wherein the crystal structure parameters include lattice constants and diffraction peak intensities.

[0021] In the embodiment of the present invention, the dual-mode synchronous monitor is a monitoring device integrating an infrared thermal imager and an X-ray diffractometer, which can synchronously collect two different types of data, namely the surface temperature distribution data and crystal structure parameters of the phase change material, providing multi-dimensional information for subsequent analysis.

[0022] Specifically, an infrared thermal imager is an instrument that uses an infrared detector and an optical imaging objective lens to receive the infrared radiation energy distribution pattern of the measured target and reflects it onto the photosensitive element of the infrared detector, thereby obtaining an infrared thermal image. In the present invention, it is used to record the surface temperature distribution data of the phase change material in real time.

[0023] Specifically, an X-ray diffractometer is an instrument that analyzes the crystal structure by measuring the diffraction of X-rays in a crystal. In the present invention, it is used to continuously collect crystal structure parameters of the phase change material, such as lattice constants and diffraction peak intensities.

[0024] Specifically, timestamp alignment is to precisely synchronize the time stamps of the data recorded by the infrared thermal imager and the X-ray diffractometer, ensuring that the surface temperature distribution data and crystal structure parameters collected correspond to the state of the phase change material at the same moment, and guaranteeing the relevance and accuracy of the data.

[0025] Specifically, lattice constants describe the basic parameters of the crystal structure, reflecting the arrangement rules of atoms or molecules in the crystal. Their changes can characterize the changes in the crystal structure and are one of the important bases for judging whether a phase change occurs.

[0026] Specifically, the diffraction peak intensity is the intensity of the diffraction peak in the X-ray diffraction pattern, which is related to factors such as the types, quantities, and arrangement patterns of atoms in the crystal. Its changes can also reflect the changes in the crystal structure during the phase change process.

[0027] Furthermore, the infrared thermal imager and the X-ray diffractometer are reasonably installed inside the dual-mode synchronous monitor to ensure that the optical and electronic systems of both can operate normally and do not interfere with each other.

[0028] Furthermore, connect the synchronous trigger signal device, which is respectively connected to the control units of the infrared thermal imager and the X-ray diffractometer, and set appropriate trigger parameters so that both can record data at the same time rhythm during startup and operation to complete timestamp alignment.

[0029] Furthermore, when the dual-mode synchronous monitor starts and scans the phase change material at a pre-set scanning rate, the infrared thermal imager uses its own infrared detection elements to capture the infrared radiation emitted by the surface of the phase change material in real time and converts it into an electrical signal or digital signal related to temperature. After signal processing and image reconstruction, surface temperature distribution data is generated; at the same time, the X-ray diffractometer emits X-rays to irradiate the phase change material, receives the diffracted X-ray signals, and obtains crystal structure parameters such as lattice constants and diffraction peak intensities through the analysis and calculation of these signals.

[0030] Specifically, collecting the surface temperature distribution data and crystal structure parameters of the phase change material based on the dual-mode synchronous monitor is the starting link of the entire phase change temperature calibration process, providing the original data for the subsequent establishment of the temperature-structure correlation matrix. Only by accurately collecting the surface temperature distribution data and crystal structure parameters can the connection between the two be further established, thereby determining the phase change temperature range. At the same time, the quality of the collected data directly affects the accuracy of the subsequent dynamic compensation and reverse correction steps. If there are errors in the collected data, the subsequent analysis and correction results will also be affected.

[0031] Generally speaking, traditional phase change temperature calibration methods often can only obtain temperature or structural information separately, and cannot achieve synchronous monitoring and correlation analysis of both. This step uses a dual-modal synchronous monitor, integrating an infrared thermal imager and an X-ray diffractometer and achieving timestamp alignment, solving the problems of asynchronous data acquisition and inability to correlate temperature and structural changes in real time in traditional methods, and improving the data acquisition efficiency and analysis accuracy.

[0032] S2. Establish a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters.

[0033] In the embodiment of the present invention, the establishment of the temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters includes: Map the surface temperature distribution data at the same timestamp into a two-dimensional temperature field grayscale image; Extract the lattice constant change rate from the crystal structure parameters, and convert the lattice constant change rate into a structure response coefficient; Based on the same timestamp, perform spatial registration on the two-dimensional temperature field grayscale image and the structure response coefficient to obtain the temperature-structure correlation matrix of the phase change material.

[0034] Specifically, the temperature-structure correlation matrix is a matrix used to describe the corresponding relationship between the surface temperature distribution of the phase change material and the crystal structure parameters. Through this matrix, it can be clearly seen how the crystal structure changes under different temperature conditions, providing an important basis for subsequent analysis of the phase change temperature.

[0035] Specifically, the two-dimensional temperature field grayscale image refers to presenting the surface temperature distribution data in the form of an image, where the grayscale value of each pixel represents the temperature magnitude at that position. In this way, the temperature distribution on the surface of the phase change material can be intuitively observed.

[0036] Specifically, the lattice constant change rate reflects the rate at which the lattice constant in the crystal structure changes over time or other factors. During the phase change process, the lattice constant will change, and its change rate can be used as an index to measure the degree of crystal structure change.

[0037] Specifically, the structure response coefficient is a coefficient obtained by converting the lattice constant change rate, which is used to more conveniently perform correlation analysis with the two-dimensional temperature field grayscale image to reflect the response degree of the crystal structure to temperature changes.

[0038] Specifically, spatial registration refers to corresponding and matching the two-dimensional temperature field grayscale image and the structure response coefficient in space, so that they can be accurately correlated at the same timestamp, thereby constructing a temperature-structure correlation matrix.

[0039] Further, mapping the surface temperature distribution data under the same timestamp into a two-dimensional temperature field grayscale image includes the following steps: First, determine the value range of the temperature data, for example, by statistically calculating the minimum value among all the surface temperature distribution data and the maximum value ; then, according to the grayscale value range of the grayscale image (usually ), establish the mapping relationship between the temperature value and the grayscale value. Assuming the temperature value is , the corresponding grayscale value can be calculated through the linear mapping formula ; finally, convert the temperature value at each position into a grayscale value according to the above mapping relationship and arrange it in the form of a two-dimensional image to obtain the two-dimensional temperature field grayscale image.

[0040] Further, extracting the lattice constant change rate from the crystal structure parameters and converting the lattice constant change rate into a structural response coefficient includes the following steps: For the lattice constants in the crystal structure parameters collected at different time points ( represents the time point), calculate the change amount of the lattice constant between adjacent time points ; the lattice constant change rate , where is the time interval between adjacent time points; the conversion of the structural response coefficient can be determined according to specific experimental data and theoretical models. For example, it can be through a linear transformation ( and are constants fitted according to experimental data) to convert the lattice constant change rate into a structural response coefficient.

[0041] Specifically, based on the same timestamp, spatially registering the two-dimensional temperature field grayscale image and the structural response coefficient includes the following steps: Determine the spatial coordinate systems corresponding to the two-dimensional temperature field grayscale image and the structural response coefficient to ensure their spatial consistency; based on the same timestamp, associate the grayscale value of the two-dimensional temperature field grayscale image at each position with the corresponding structural response coefficient. They can be stored in a matrix, where the rows and columns of the matrix correspond to the spatial positions respectively, and the matrix elements are the combination of the temperature grayscale value and the structural response coefficient at that position, thus obtaining a temperature-structure correlation matrix.

[0042] Furthermore, by processing and correlating temperature data and crystal structure data to form a temperature-structure correlation matrix, the correspondence between the temperature distribution of phase change materials and the crystal structure changes can be intuitively displayed, which helps researchers quickly understand and analyze the phase change process; the temperature and structure information are spatially aligned so that the two are accurately correlated at the same timestamp, avoiding data misalignment and errors, and improving the accuracy of subsequent analysis of phase change temperature; the temperature-structure correlation matrix provides a unified data basis for subsequent steps such as determining the initial temperature range of phase change and constructing nonlinear mapping models, facilitating further calculations and analysis.

[0043] Specifically, this step takes the surface temperature distribution data and crystal structure parameters collected in the previous step, processes and correlates them, and provides critical intermediate data for determining the moment of crystal structure parameter mutation and calculating the initial phase transition temperature range of the phase change material. Without an accurate temperature-structure correlation matrix, subsequent steps will be unable to accurately determine the temperature range within which the phase transition occurs.

[0044] In general, traditional methods for studying phase-change materials often study temperature and structure changes separately, making it difficult to intuitively demonstrate the real-time correlation between the two. This step integrates and correlates temperature and structure information by establishing a temperature-structure correlation matrix, providing a new analytical perspective for phase-change material research and breaking through the limitations of traditional methods.

[0045] S3. When the crystal structure parameters mutate, the surface temperature distribution data corresponding to the mutation moment is determined based on the temperature-structure correlation matrix, and the initial phase change temperature range of the phase change material is calculated.

[0046] In an embodiment of the present invention, the conditions for determining whether the crystal structure parameters have undergone a mutation include: performing a second-order derivative operation on the structural response coefficient to obtain a derivative change curve of the structural response coefficient; Extracting extreme points whose absolute values exceed a preset threshold from the derivative change curve; The timestamp corresponding to the extreme point is used as the mutation moment, and it is determined that the crystal structure parameter mutates at the mutation moment.

[0047] Specifically, when a phase change material undergoes a phase change, its crystal structure undergoes significant changes, and the crystal structure parameters (such as lattice constant, diffraction peak intensity, etc.) change drastically accordingly.

[0048] In detail, the temperature-structure correlation matrix is a matrix obtained by spatially aligning the surface temperature distribution data and crystal structure parameters of the phase change material based on the same timestamp, which is used to intuitively present the correspondence between temperature and crystal structure changes.

[0049] Specifically, the structural response coefficient is converted from the lattice constant change rate in the crystal structure parameters, and is used to measure the response degree of the crystal structure to temperature changes, facilitating the correlation analysis with temperature data.

[0050] Specifically, the second derivative operation refers to the mathematical operation of taking the second derivative of the structural response coefficient with respect to time (or other relevant variables). Through the second derivative, the change situation of the structural response coefficient change rate can be reflected, thereby more sensitively capturing the mutation characteristics of the structural response coefficient.

[0051] Specifically, the derivative change curve refers to the curve plotted with time (or other relevant variables) as the abscissa and the second derivative of the structural response coefficient as the ordinate, which can visually display the change trend of the structural response coefficient change rate.

[0052] Specifically, the preset threshold is a numerical standard preset according to experimental experience, material characteristics or theoretical analysis, and is used to judge whether the extreme points in the derivative change curve represent a real mutation of the crystal structure parameters, avoiding misjudgment.

[0053] Specifically, the extreme point refers to the point where the function value is locally maximum or minimum in the derivative change curve. In the present invention, these extreme points are considered to be possibly related to the mutation moment of the crystal structure parameters.

[0054] Specifically, the mutation moment refers to the specific time point when the crystal structure parameters mutate. Determining this moment is crucial for accurately judging the start time of the phase change and calculating the initial phase change temperature range.

[0055] Specifically, the initial phase change temperature range refers to the temperature range where the phase change begins to occur initially determined during the phase change process, providing a basis for more accurately determining the phase change temperature subsequently.

[0056] Further, performing a second derivative operation on the structural response coefficient to obtain a derivative change curve includes the following steps: Assume that the structural response coefficient is a function of time . Using the mathematical derivative formula and calculation method, take the first derivative of to obtain , and then take the derivative of to obtain the second derivative ; taking time as the independent variable and as the dependent variable, plot the values calculated at different time points to form a derivative change curve.

[0057] Further, extracting the extreme points whose absolute values exceed the preset threshold from the derivative change curve includes the following steps: Traverse each data point in the derivative change curve and calculate the absolute value of each point ( representing different time points); compare the absolute value of each point with a preset threshold and when , check whether this point is an extreme point (i.e., the function value of this point is greater than or less than the function values of its adjacent points). If it is an extreme point, record it

[0058] Furthermore, take the time point corresponding to the extreme point as the mutation moment and determine that the crystal structure parameters mutate at this moment, including the following steps For the recorded extreme points, obtain their corresponding timestamps ; according to the temperature-structure correlation matrix, find the surface temperature distribution data corresponding to the timestamp ; from these surface temperature distribution data, select the maximum value and the minimum value of the temperature, so as to determine the initial phase change temperature interval .

[0059] Specifically, by performing second-order derivative operations and judging the mutation moment of the crystal structure parameters with a preset threshold, the time point when the phase change starts to occur can be determined more accurately. Compared with the traditional method that only relies on a single parameter or empirical judgment, the accuracy is higher; the accurately calculated initial phase change temperature interval provides reliable basic data for subsequent construction of a non-linear mapping model and dynamic compensation, which helps to further improve the accuracy of phase change temperature calibration; this method based on mathematical operations and threshold judgment reduces the interference of human factors, makes the analysis of the phase change process more objective and reliable, and enhances the credibility of the research results

[0060] Specifically, this step is analyzed based on the temperature-structure correlation matrix established in the previous step. The accurate correlation matrix guarantees the determination of the surface temperature distribution data corresponding to the mutation moment, and the determined initial phase change temperature interval provides input data for subsequent construction of a non-linear mapping model related to the heating rate. It is a key link in the entire phase change temperature calibration process. If the mutation moment is judged inaccurately, subsequent temperature interval calculation and dynamic compensation will both have deviations, affecting the final calibration result

[0061] S4. Construct a non-linear mapping model between the initial phase change temperature interval and the heating rate, and perform dynamic compensation on the initial phase change temperature interval based on the non-linear mapping model to obtain the corrected phase change temperature of the phase change material

[0062] In the embodiment of the present invention, the construction of the non-linear mapping model between the initial phase change temperature interval and the heating rate includes Extract the upper boundary value from the initial phase change temperature range and the lower boundary value , and combine the upper boundary value, the lower boundary value and the heating rate to form an input feature vector ; Input the input feature vector into a pre-configured support vector regression algorithm. The support vector regression algorithm includes a kernel function and a loss function, where: The kernel function is a radial basis function, and the expression of the radial basis function is as follows: ; In the formula, is the function value of the radial basis function, is the kernel bandwidth parameter, is the th sample point in the input feature vector, is the th sample point in the input feature vector, is the exponential function, is the Euclidean distance between the th sample point and the th sample point in the input feature vector; The loss function is the Huber loss function, and the expression of the Huber loss function is as follows: ; In the formula, is the function value of the Huber loss function, is the prediction error, is the robustness threshold; Use multiple groups of calibration data of historical phase change materials to iteratively train the support vector regression algorithm until the loss function converges, and generate a dynamic compensation function associated with the heating rate. Among them, the expression of the dynamic compensation function is as follows: ; In the formula, is the phase change hysteresis factor, is the thermal expansion compensation coefficient, is the upper boundary value, is the lower boundary value, is the heating rate, is the function value corresponding to the dynamic compensation function; Apply the dynamic compensation function to the boundary values of the initial phase change temperature range, and output the median and full width at half maximum (FWHM) of the corrected phase change temperature, where the median is determined by the center point of the compensated temperature range, and the FWHM is calculated from the span of the compensated temperature range. The expression for the median is as follows: ; In the formula, is the median of the corrected phase change temperature, is the upper boundary value, is the lower boundary value, is the heating rate, is the function value corresponding to the dynamic compensation function; The expression for the FWHM is as follows: ; In the formula, is the FWHM of the corrected phase change temperature, is the upper boundary value, is the lower boundary value, is the heating rate, is the function value corresponding to the dynamic compensation function.

[0063] Specifically, the non - linear mapping model is a mathematical model that can describe the complex, non - simple linear relationship between the initial phase change temperature range and the heating rate. Compared with the linear model, it can more accurately reflect the relationship between the two in the actual situation, because during the phase change process, the influence of the heating rate on the phase change temperature range is not a simple linear change.

[0064] Specifically, the initial phase change temperature range is the approximate temperature range at which the phase change material begins to undergo phase change determined by the previous steps, including the upper and lower boundary values, providing basic data for the subsequent accurate calculation of the phase change temperature.

[0065] Specifically, the heating rate is the rate of change of temperature with time during the heating process of the phase change material, which is an important factor affecting the phase change process. Different heating rates may cause changes in the phase change temperature range.

[0066] Specifically, the input feature vector is a vector composed of the upper boundary value, lower boundary value, and heating rate of the initial phase change temperature range, which is used as the input data of the support vector regression algorithm to train the model to learn the relationship between them.

[0067] Specifically, the support vector regression algorithm is a machine learning algorithm for regression analysis. It finds an optimal hyperplane to fit the data, minimizing the error between the predicted value and the true value. In the present invention, it is used to construct the relationship model between the initial phase change temperature range and the heating rate.

[0068] Specifically, the kernel function (radial basis function) is used in the support vector regression algorithm to map low-dimensional data to a high-dimensional space, so that it is easier to find a linearly separable hyperplane in the high-dimensional space. The radial basis function calculates the function value according to the Euclidean distance between sample points. The kernel function bandwidth parameter controls the "width" of the function and affects the complexity and generalization ability of the model.

[0069] Specifically, the loss function (Huber loss function) is used to measure the difference between the model prediction value and the true value. The Huber loss function combines the advantages of the squared loss function and the absolute value loss function. When the prediction error is small, the squared loss function is adopted to make the model training more stable; when the prediction error is large, the absolute value loss function is adopted, which has better robustness to outliers. The robustness threshold is used to control the switching between the two loss calculation methods.

[0070] Specifically, the phase change hysteresis factor is a parameter that reflects the phase change hysteresis phenomenon caused by various physical mechanisms during the phase change process. It reflects the influence of the heating rate and the span of the initial phase change temperature range on the phase change hysteresis in the dynamic compensation function and is used to compensate for the influence of the phase change hysteresis on the phase change temperature.

[0071] Specifically, the thermal expansion compensation coefficient is a coefficient introduced to consider the influence of thermal expansion of the phase change material on the phase change temperature during the heating process. It is used in the dynamic compensation function to correct the effect of the thermal expansion factor on the phase change temperature.

[0072] Specifically, the dynamic compensation function is a function obtained by training through the support vector regression algorithm. It dynamically adjusts the phase change temperature according to the initial phase change temperature range and the heating rate, and compensates for the temperature deviation caused by factors such as phase change hysteresis and thermal expansion.

[0073] Specifically, the corrected phase change temperature is a value closer to the true phase change temperature obtained after dynamic compensation. It is determined by the median and the full width at half maximum calculated from the boundary values of the initial phase change temperature range by the action of the dynamic compensation function, and is more accurate than the initial phase change temperature range.

[0074] Specifically, the median is a key parameter of the corrected phase change temperature, which is determined by the center point of the compensated temperature range and represents the central estimated value of the corrected phase change temperature.

[0075] Specifically, the full width at half maximum is a parameter that reflects the span of the corrected phase change temperature range and is used to describe the temperature change range during the phase change process. Together with the median, it more comprehensively represents the characteristics of the corrected phase change temperature.

[0076] Furthermore, extracting the boundary values and forming the input feature vector includes the following steps: From the initial phase change temperature range calculated previously directly obtain the upper limit boundary value and the lower limit boundary value ; record the heating rate of the phase change material in the current experiment or measurement ; combine and into a vector in a certain order, for example , to form an input feature vector

[0077] Furthermore, using the support vector regression algorithm for training includes the following steps: Select a pre-configured support vector regression algorithm, set the kernel function therein to the radial basis function (calculate according to the formula ), and the loss function to the Huber loss function (calculate according to the formula ; Prepare a large number of calibration data sets of historical phase change materials. Each data set contains the upper and lower limit boundary values of the initial phase change temperature range and the corresponding heating rate, as well as the accurately measured or known true phase change temperature data (used to calculate the prediction error); Input the input feature vector (composed of the initial phase change temperature range boundary values and the heating rate in the historical data) into the support vector regression algorithm in sequence. The algorithm maps the data to a high-dimensional space according to the kernel function and searches for the optimal hyperplane for fitting. In each training, calculate the error between the predicted value and the true phase change temperature, and calculate the loss value according to the Huber loss function

[0078] By continuously adjusting the parameters in the support vector regression algorithm (such as the kernel function bandwidth parameter , the robustness threshold and other related parameters), make the value of the loss function gradually decrease. When the loss function converges (that is, the loss value no longer decreases significantly), it is considered that the training is completed

[0079] Furthermore, generating a dynamic compensation function and calculating the corrected phase change temperature includes the following steps: After the training is completed, obtain the dynamic compensation function associated with the heating rate , where and are parameters determined during the training process; the dynamic compensation function acts on the current initial phase change temperature range boundary values and and the heating rate ; calculate the median of the corrected phase change temperature according to the formula , and calculate the full width at half maximum according to the formula . The median and the full width at half maximum together determine the characteristics of the corrected phase change temperature

[0080] Generally speaking, this step is a key link for further precisely correcting the temperature after determining the initial phase change temperature range. The initial phase change temperature range provides basic data for constructing the non-linear mapping model, and the obtained corrected phase change temperature provides a more accurate reference value for subsequent comparison and calibration in the gradient temperature control module. If the dynamic compensation in this step is inaccurate, the subsequent reverse calibration in the gradient temperature control module will lose an accurate basis, affecting the final calibration result.

[0081] Generally speaking, considering the influence of factors such as phase change hysteresis and thermal expansion on the phase change temperature, through constructing a non-linear mapping model and dynamic compensation, the interference of the heating rate change on temperature calibration is effectively reduced, making the corrected phase change temperature closer to the true value and improving the accuracy of phase change temperature calibration; training the model with historical data can adapt to the temperature calibration requirements under different phase change materials and experimental conditions. Even in the face of new phase change materials or changes in the experimental environment, as long as there is sufficient historical data, the model can learn the corresponding laws and perform accurate dynamic compensation; fully utilize the information in the initial phase change temperature range, heating rate, and historical calibration data, and explore the potential relationship between them, providing a more comprehensive basis for precisely calibrating the phase change temperature.

[0082] Generally speaking, using the support vector regression algorithm to construct a non-linear mapping model between the initial phase change temperature range and the heating rate breaks through the limitations of traditional linear analysis methods and can more accurately describe the relationship between the two in the complex phase change process. This innovative modeling method improves the analysis accuracy of the influencing factors of the phase change temperature; introducing the phase change hysteresis factor and the thermal expansion compensation coefficient, and adjusting the initial phase change temperature range through the dynamic compensation function, considering physical phenomena such as phase change hysteresis and thermal expansion that are easily ignored by traditional methods, significantly improving the accuracy of phase change temperature calibration.

[0083] S5. Input the corrected phase change temperature into the gradient temperature control module containing a standard sample. The gradient temperature control module includes a reference material that forms a preset temperature difference along the axis, and the phase change point of the reference material is known.

[0084] In the embodiment of the present invention, the gradient temperature control module includes: Set the axial center temperature reference point of the gradient temperature control module according to the median, where the temperature value of the axial center temperature reference point is the median; Based on the full width at half maximum, calculate the axial temperature gradient step of the gradient temperature control module, and generate a preset temperature difference that is linearly related to the full width at half maximum. The calculation formula of the axial temperature gradient step is as follows: ; In the formula, [[ID=^22]] is the axial temperature gradient step, is the full width at half maximum, is the thermal expansion compensation coefficient, is the thermal conductivity of the gradient temperature control module; Along the axial direction of the gradient temperature control module, starting from the axial center temperature reference point, heating units are configured step by step according to the axial temperature gradient step size to form a linear temperature gradient distribution including at least five temperature nodes; The reference material is fixedly arranged at each temperature node of the linear temperature gradient distribution.

[0085] In the embodiment of the present invention, the arrangement mode of the reference material satisfies: The reference materials with different phase change points are arranged in a circular array at the corresponding temperature nodes of the linear temperature gradient distribution, wherein the adjacent circular spacing is calculated and generated based on the axial temperature gradient step size according to an inverse proportional relationship, and the calculation formula of the adjacent circular spacing is as follows: ; In the formula, is the coefficient of thermal expansion, is the axial temperature gradient step size, is the adjacent circular spacing; According to the known phase change points of the reference material and the node temperature values of the linear temperature gradient distribution, a phase change point - temperature coordinate mapping table is established, wherein the phase change point - temperature coordinate mapping table is used to calibrate the theoretical position of the reference material.

[0086] Specifically, the corrected phase change temperature refers to the temperature value obtained after dynamically compensating the initial phase change temperature range. Compared with the initial phase change temperature range, it is closer to the true phase change temperature of the phase change material and includes two key parameters, the median value and the full width at half maximum, which are used for subsequent precise analysis.

[0087] Specifically, the gradient temperature control module is a device that can form a specific temperature gradient in its axial direction. By controlling the temperature distribution, it provides different temperature environments for the reference material to compare the actual and theoretical phase change positions of the reference material, and then corrects the corrected phase change temperature.

[0088] Specifically, the standard sample is a material sample with known characteristics (such as known phase change points), which is used as a reference for evaluating and correcting the phase change temperature of the phase change material, and its properties are stable and the phase change process can be accurately observed and analyzed.

[0089] Specifically, the reference material is a material used in the gradient temperature control module, and its phase change point is known. By observing the phase change situation of the reference material at different temperatures, it provides a basis for correcting the temperature of the phase change material.

[0090] Specifically, the axial center temperature reference point is a key temperature point set in the axial direction of the gradient temperature control module. The median value of the corrected phase change temperature is used as the temperature value of this point, which is the starting reference point for constructing a linear temperature gradient distribution.

[0091] Specifically, the axial temperature gradient step is the interval value used to measure the temperature change between adjacent temperature nodes in the axial direction of the gradient temperature control module. It is calculated based on the full width at half maximum, the thermal expansion compensation coefficient, and the thermal conductivity of the gradient temperature control module, and determines the density of the temperature gradient.

[0092] Specifically, the preset temperature difference is calculated based on the full width at half maximum, and is the temperature difference expected to be formed in the axial direction of the gradient temperature control module, so that different positions have different temperatures to simulate the states of the phase change material at different temperatures.

[0093] Specifically, the linear temperature gradient distribution is a uniform and linear temperature distribution form in which the temperature gradually changes according to a certain rule (at intervals of the axial temperature gradient step) in the axial direction of the gradient temperature control module, ensuring the regularity and predictability of the temperature change.

[0094] Specifically, the temperature nodes are discrete temperature points set in the linear temperature gradient distribution. At these points, reference materials are fixedly arranged to observe the phase change of the reference materials at specific temperatures.

[0095] Specifically, the circular array is a way of arranging reference materials with different phase change points in a circular pattern at the temperature nodes, so that the reference materials at each temperature node can be arranged orderly for easy observation and comparison.

[0096] Specifically, the adjacent circular spacing is the distance between adjacent circular rings where the reference materials are located in the circular array. It is calculated and determined according to the inverse proportional relationship between the axial temperature gradient step and the thermal expansion coefficient, ensuring the rationality of the distribution of the reference materials.

[0097] Specifically, the phase change point - temperature coordinate mapping table is a table recording the corresponding relationship between the known phase change points of the reference materials and each temperature node in the linear temperature gradient distribution, which is used to determine the theoretical phase change positions of the reference materials at different temperatures and provides a reference for subsequent comparison with the actual phase change positions.

[0098] Furthermore, set the axial center temperature reference point: Obtain the median value from the relevant data of the corrected phase change temperature , and use this median value as the temperature setting value at the axial center position of the gradient temperature control module, determining the core temperature point of the entire temperature gradient distribution.

[0099] Furthermore, calculating the axial temperature gradient step and generating the preset temperature difference includes the following steps: The full width at half maximum is known , coefficient of thermal expansion compensation and the thermal conductivity of the gradient temperature control module , according to the formula calculate the axial temperature gradient step ; According to the calculated axial temperature gradient step, in the axial direction of the gradient temperature control module, starting from the axial center temperature reference point, at this step interval, determine the temperatures at different positions in turn, so as to generate a preset temperature difference and form the basic framework of a linear temperature gradient distribution.

[0100] Furthermore, configuring the heating unit to form a linear temperature gradient distribution includes the following steps: Along the axis of the gradient temperature control module, starting from the axial center temperature reference point, according to the calculated axial temperature gradient step , install heating units at different positions. By controlling the power of the heating units, make the temperature change between adjacent heating units conform to the preset temperature difference, and form a linear temperature gradient distribution including at least five temperature nodes. For example, if the temperature of the axial center temperature reference point is , the temperature of the first temperature node is , the second is , and so on.

[0101] Furthermore, fixing the setting of the reference material includes the following steps: At each temperature node of the formed linear temperature gradient distribution, place the reference material and ensure its position is fixed. Specific jigs or fixing devices can be used to ensure that the reference material does not shift during the experiment, so as to accurately observe its phase change process.

[0102] Furthermore, arranging the reference materials and establishing a mapping table includes the following steps: According to the phase change points of different reference materials, arrange them in a circular array at the corresponding temperature nodes. Calculate the adjacent circular spacing ( is the coefficient of thermal expansion), determine the position of each reference material in the circular array; record the phase change point of each reference material and the temperature value of the temperature node where it is located, and establish a phase change point - temperature coordinate mapping table. For example, for a reference material with a phase change point of , if it is located at a temperature node with a temperature of , then record such a corresponding relationship in the mapping table.

[0103] Generally speaking, by constructing a gradient temperature control module with a linear temperature gradient distribution and reasonably arranging reference materials with known phase change points, a stable and accurate temperature environment is provided for comparing the actual and theoretical phase change positions of the reference materials, which helps to accurately judge the accuracy of the corrected phase change temperature. Based on the median and full width at half maximum of the corrected phase change temperature, the parameters of the gradient temperature control module are set, making the module closely related to the corrected phase change temperature. Subsequently, by comparing the phase change situation of the reference materials, the corrected phase change temperature is calibrated, and the final calibrated temperature can be obtained more accurately. The standardized arrangement method of reference materials and the mapping table establishment method make the experimental process more standardized and repeatable, facilitating operation and comparative analysis by different experimenters under the same conditions.

[0104] Specifically, this step follows the corrected phase change temperature obtained previously and constructs a gradient temperature control module based on it. By setting the axial center temperature reference point, calculating the temperature gradient step size and other operations, the corrected phase change temperature is incorporated into the temperature distribution of the gradient temperature control module. The established phase change point-temperature coordinate mapping table provides a basis for comparing the actual and theoretical phase change positions of the reference materials subsequently, and is an important prerequisite for realizing the reverse calibration of the corrected phase change temperature, directly affecting the accuracy of the final calibrated temperature.

[0105] Generally speaking, using the gradient temperature control module containing reference materials to calibrate the temperature by comparing the actual and theoretical phase change positions, different from the traditional direct measurement or simple calculation methods, this innovative calibration method improves the accuracy and reliability of the phase change temperature calibration. The unique design of the gradient temperature control module, including operations such as setting the temperature gradient according to the corrected phase change temperature, reasonably arranging the reference materials and establishing the mapping table, solves problems such as inaccurate calibration and difficult-to-control experimental conditions in traditional methods, and improves the overall level of the phase change temperature calibration technology.

[0106] S6. Compare the offset between the actual phase change position and the theoretical position of the reference material, and reverse calibrate the corrected phase change temperature based on the offset to obtain the final calibrated temperature of the phase change material.

[0107] In the embodiment of the present invention, the comparison of the offset between the actual phase change position and the theoretical position of the reference material includes: Real-time capture the droplet deformation characteristic image generated by the reference material during the phase change process through a high-speed camera, where the droplet deformation characteristic image includes the geometric center coordinates of the phase change interface; Extract the actual coordinate values of the geometric center coordinates from the droplet deformation characteristic image, and perform differential calculation with the theoretical coordinate values of the corresponding temperature nodes in the phase change point-temperature coordinate mapping table to generate the center coordinate offset of the reference material ; Calculate the temperature compensation amount of the phase change material based on the axial thermal expansion coefficient of the gradient temperature control module and the center coordinate offset amount, where the temperature compensation amount is the product of the center coordinate offset amount and the axial thermal expansion coefficient. The calculation formula for the temperature compensation amount is as follows: ; In the formula, is the thermal expansion coefficient, is the thermal conductivity of the gradient temperature control module, is the center coordinate offset amount of the reference material, is the temperature compensation amount of the phase change material; Determine the offset amount between the actual phase change position and the theoretical position of the reference material based on the temperature compensation amount.

[0108] In an embodiment of the present invention, the step of reversely correcting the corrected phase change temperature based on the offset amount to obtain the final calibrated temperature of the phase change material includes: Determine the deviation direction and deviation magnitude of the actual phase change position of the reference material relative to the theoretical position based on the offset amount; Perform reverse adjustment on the corrected phase change temperature based on the deviation direction and the deviation magnitude to obtain the final calibrated temperature of the phase change material, where: When the offset amount is positive, reduce the corrected phase change temperature; When the offset amount is negative, increase the corrected phase change temperature.

[0109] Specifically, the actual phase change position of the reference material is the actual spatial position where the phase change interface is located in the gradient temperature control module when the reference material undergoes a phase change. It is determined by capturing the droplet deformation characteristic image with a high-speed camera and extracting the geometric center coordinates.

[0110] Specifically, the theoretical phase change position of the reference material is the spatial position where the reference material should be located under ideal conditions when undergoing a phase change, determined according to the phase change point - temperature coordinate mapping table and combined with the temperature distribution of the gradient temperature control module.

[0111] Specifically, the offset amount is the difference between the actual phase change position and the theoretical phase change position, calculated through coordinates, and reflects the possible deviation between the corrected phase change temperature and the true phase change temperature.

[0112] Specifically, the corrected phase change temperature is the temperature value obtained after dynamically compensating the initial phase change temperature range. It is the basis for subsequent reverse correction, but there may still be a certain error from the true phase change temperature.

[0113] Specifically, the final calibrated temperature is the value closer to the true phase change temperature of the phase change material after reverse correction of the phase change temperature, which is the final result of the entire phase change temperature calibration process.

[0114] Specifically, the droplet deformation characteristic image is an image of the reference material captured by a high-speed camera during the phase change process, in which the shape of the droplet changes due to the phase change. This image contains key information for determining the geometric center coordinates of the phase change interface.

[0115] Specifically, the geometric center coordinates represent the coordinate values of the center position of the phase change interface, which are usually represented by the abscissa and ordinate in a two-dimensional image and are obtained by analyzing and extracting the droplet deformation characteristic image.

[0116] Specifically, the central coordinate offset is the difference between the actual geometric center coordinate value and the theoretical coordinate value, which is obtained through differential calculation and is used to measure the deviation degree of the actual phase change position of the reference material relative to the theoretical position in terms of coordinates.

[0117] Specifically, the temperature compensation amount is a value calculated based on the central coordinate offset and the axial thermal expansion coefficient of the gradient temperature control module, and is used to quantify the amplitude of adjustment required to correct the phase change temperature in order to compensate for the deviation of the phase change position of the reference material caused by temperature differences.

[0118] Specifically, the deviation direction is the deviation direction of the actual phase change position relative to the theoretical position, which is divided into positive deviation (the actual position is farther from the reference point in a certain direction of the theoretical position) and negative deviation (the actual position is closer to the reference point in the opposite direction of the theoretical position), and is determined by the positive or negative value of the central coordinate offset.

[0119] Specifically, the deviation magnitude is the degree of deviation between the actual phase change position and the theoretical position, which is measured by the absolute value of the central coordinate offset or according to a certain calculation method, and is used to determine the amplitude of adjustment for correcting the phase change temperature.

[0120] Furthermore, comparing the offset between the actual and theoretical phase change positions of the reference material includes the following steps: During the operation of the gradient temperature control module, when the reference material begins to undergo a phase change, start the high-speed camera to capture the phase change process of the reference material in real time at a high enough frame rate to obtain the droplet deformation characteristic image; use image processing technology to identify the phase change interface from the captured droplet deformation characteristic image and determine the actual coordinate value of its geometric center coordinates. Then, look up the phase change point - temperature coordinate mapping table to obtain the theoretical coordinate value of the geometric center of the phase change interface of the reference material at the corresponding temperature node. Obtain the central coordinate offset through differential calculation. (Assume the analysis is carried out in one - dimensional direction. In practice, the offset may need to be calculated by integrating two - dimensional coordinates); Given the axial thermal expansion coefficient of the gradient temperature control module and the central coordinate offset , according to the formula (where is the thermal conductivity of the gradient temperature control module) calculate the temperature compensation amount of the phase - change material, and thus determine the offset between the actual phase - change position and the theoretical position of the reference material.

[0121] Specifically, the reverse correction of the modified phase - change temperature based on the offset includes the following steps: Determine the deviation direction and magnitude: According to the calculated central coordinate offset , determine the deviation direction by the positive or negative value. represents a positive offset, represents a negative offset; the deviation magnitude is measured by , or measured by the magnitude of the temperature compensation amount ; if the offset is positive, it means that the temperature corresponding to the actual phase - change position is higher than the temperature corresponding to the theoretical position, and the modified phase - change temperature needs to be reduced, that is, the final calibrated temperature ( is the modified phase - change temperature); if the offset is negative, then increase the modified phase - change temperature, that is , so as to obtain the final calibrated temperature.

[0122] Generally speaking, by accurately comparing the actual and theoretical phase - change positions of the reference material, considering factors such as thermal expansion to calculate the temperature compensation amount, and then reversely correcting the modified phase - change temperature accordingly, the errors generated in the previous measurement and calculation processes are effectively eliminated, making the final calibrated temperature closer to the true value, and greatly improving the accuracy of the phase - change temperature calibration; The reverse - correction process based on actual observation and accurate calculation provides a reliable error - correction mechanism for the phase - change temperature calibration. This method is not affected by the single influence of material properties and experimental environment, and can ensure the reliability of the calibration results in various situations.

[0123] Further, this step is the key closing link of the entire phase - change temperature calibration process, which closely cooperates with the previous steps such as acquisition, modeling, and compensation, forming a complete and closed - loop calibration system, improving the scientificity and integrity of the phase - change temperature calibration technology.

[0124] Specifically, this step is based on the foundation built in the previous steps. The previously determined corrected phase transition temperature provides the initial value for the reverse correction here; the settings of the gradient temperature control module and the establishment of the phase transition point-temperature coordinate mapping table provide the necessary conditions for comparing the actual and theoretical phase transition positions; and the parameters used to calculate the central coordinate offset and temperature compensation amount, such as the axial thermal expansion coefficient, etc., are also determined or calculated in the previous steps. The result of this step ultimately determines the final calibration temperature of the phase change material and is a verification and optimization of all the previous steps.

[0125] Specifically, the method of reverse correcting the temperature by comparing the offset between the actual and theoretical phase transition positions of the reference material breaks through the limitation of relying only on single measurement or simple compensation in traditional phase transition temperature calibration. This innovative strategy fully considers various physical factors in the actual phase transition process and effectively improves the accuracy and reliability of calibration; as a key link in the entire phase transition temperature calibration method, it cooperates with other steps to form an organic whole. Through this reverse correction mechanism, the entire process from data acquisition to temperature calibration is improved.

[0126] As Figure 2 shown, it is a functional module diagram of a phase change material phase transition temperature calibration system provided by an embodiment of the present invention.

[0127] The phase change material phase transition temperature calibration system 100 described in the present invention can be installed in an electronic device. According to the functions achieved, the phase change material phase transition temperature calibration system 100 may include a data synchronous acquisition module 101, a correlation matrix construction module 102, an initial phase transition temperature range generation module 103, an initial temperature range dynamic compensation module 104, a data input module 105, and a temperature reverse correction module 106. The modules described in the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by a processor of an electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

[0128] In this embodiment, the functions of each module / unit are as follows: The data synchronous acquisition module 101 is used to collect the surface temperature distribution data and crystal structure parameters of the phase change material based on a dual-mode synchronous monitor; The correlation matrix construction module 102 is used to establish a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters; The initial phase transition temperature range generation module 103 is used to, when the crystal structure parameters mutate, determine the surface temperature distribution data corresponding to the mutation moment based on the temperature-structure correlation matrix, and calculate the initial phase transition temperature range of the phase change material; The initial temperature range dynamic compensation module 104 is configured to construct a non-linear mapping model between the initial phase change temperature range and the heating rate, and dynamically compensate the initial phase change temperature range based on the non-linear mapping model to obtain the corrected phase change temperature of the phase change material. The data input module 105 is configured to input the corrected phase change temperature into a gradient temperature control module containing a standard sample. The gradient temperature control module includes a reference material that forms a preset temperature difference along the axis, where the phase change point of the reference material is known. The temperature reverse correction module 106 is configured to compare the offset between the actual phase change position and the theoretical position of the reference material, and reverse correct the corrected phase change temperature based on the offset to obtain the final calibrated temperature of the phase change material.

[0129] In several embodiments provided by the present invention, it should be understood that the disclosed method and system can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0130] The modules described as separate components may or may not be physically separated. The components shown as modules may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0131] In addition, in each embodiment of the present invention, the functional modules can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a hardware plus software functional module.

[0132] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention.

[0133] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence is a theory, method, technology and application system that uses a digital computer or a machine controlled by a digital computer to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for calibrating the phase change temperature of a phase change material, characterized in that, The method includes: Collecting surface temperature distribution data and crystal structure parameters of the phase change material based on a bimodal synchronous monitor; Establishing a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters; When the crystal structure parameters mutate, determining the surface temperature distribution data corresponding to the mutation moment based on the temperature-structure correlation matrix, and calculating the initial phase change temperature range of the phase change material; Constructing a non-linear mapping model between the initial phase change temperature range and the heating rate, and dynamically compensating the initial phase change temperature range based on the non-linear mapping model to obtain the corrected phase change temperature of the phase change material; Inputting the corrected phase change temperature into a gradient temperature control module containing a standard sample, where the gradient temperature control module includes a reference material with a preset temperature difference formed along the axis, and the phase change point of the reference material is known; Comparing the offset between the actual phase change position and the theoretical position of the reference material, and reversely correcting the corrected phase change temperature based on the offset to obtain the final calibrated temperature of the phase change material.

2. The phase change temperature calibration method of the phase change material according to claim 1, characterized in that The collecting surface temperature distribution data and crystal structure parameters of the phase change material based on a bimodal synchronous monitor includes: Synchronously arranging an infrared thermal imager and an X-ray diffractometer in the bimodal synchronous monitor, where the infrared thermal imager and the X-ray diffractometer achieve timestamp alignment through a synchronous trigger signal; When the bimodal synchronous monitor scans at a set rate, the infrared thermal imager records the surface temperature distribution data of the phase change material in real time, and at the same time the X-ray diffractometer continuously collects the crystal structure parameters of the phase change material, where the crystal structure parameters include lattice constant and diffraction peak intensity.

3. The phase change temperature calibration method of the phase change material according to claim 1, characterized in that The establishing a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters includes: Mapping the surface temperature distribution data at the same timestamp into a two-dimensional temperature field grayscale image; Extracting the lattice constant change rate from the crystal structure parameters and converting the lattice constant change rate into a structure response coefficient; Based on the same timestamp, performing spatial registration on the two-dimensional temperature field grayscale image and the structure response coefficient to obtain the temperature-structure correlation matrix of the phase change material.

4. The phase change temperature calibration method of the phase change material according to claim 3, characterized in that The determination conditions for the mutation of the crystal structure parameters include: Performing a second derivative operation on the structure response coefficient to obtain the derivative change curve of the structure response coefficient; Extracting extreme points with absolute values exceeding a preset threshold from the derivative change curve; Taking the timestamp corresponding to the extreme point as the mutation moment, and determining that the crystal structure parameters mutate at the mutation moment.

5. The phase change temperature calibration method of the phase change material according to claim 1, characterized in that, The constructing a non-linear mapping model between the initial phase change temperature range and the heating rate includes: Extract the upper boundary value from the initial phase change temperature range and the lower boundary value , and combine the upper boundary value, the lower boundary value and the heating rate to form an input feature vector ; Inputting the input feature vector into a pre-configured support vector regression algorithm, where the support vector regression algorithm includes a kernel function and a loss function, where: The kernel function is a radial basis function, and the expression of the radial basis function is as follows: ； Wherein, is the function value of the radial basis function, is the kernel function bandwidth parameter, is the th sample point in the input feature vector, is the th sample point in the input feature vector, is the exponential function, is the Euclidean distance between the th sample point and the th sample point in the input feature vector; The loss function is a Huber loss function, and the expression of the Huber loss function is as follows: ； In the formula, is the function value of the Huber loss function, is the prediction error, is the robustness threshold; Iteratively train the support vector regression algorithm using multiple sets of calibration data of historical phase change materials until the loss function converges, and generate a dynamic compensation function associated with the heating rate. The expression of the dynamic compensation function is as follows: ； In the formula, is the phase change hysteresis factor, is the thermal expansion compensation coefficient, is the upper limit boundary value, is the lower limit boundary value, is the heating rate, is the function value corresponding to the dynamic compensation function; Apply the dynamic compensation function to the boundary values of the initial phase change temperature range, and output the median and full width at half maximum of the corrected phase change temperature. The median is determined by the center point of the compensated temperature range, and the full width at half maximum is calculated from the span of the compensated temperature range. The expression of the median is as follows: ； In the formula, is the median of the corrected phase transition temperature, is the upper boundary value, is the lower boundary value, is the heating rate, is the function value corresponding to the dynamic compensation function; The expression of the full width at half maximum is as follows: ； In the formula, is the full width at half maximum of the corrected phase transition temperature, is the upper boundary value, is the lower boundary value, is the heating rate, is the function value corresponding to the dynamic compensation function.

6. The phase change temperature calibration method of the phase change material according to claim 5, wherein The gradient temperature control module includes: Set the axial center temperature reference point of the gradient temperature control module according to the median, where the temperature value of the axial center temperature reference point is the median; Calculate the axial temperature gradient step of the gradient temperature control module based on the full width at half maximum, and generate a preset temperature difference that is linearly related to the full width at half maximum. The calculation formula of the axial temperature gradient step is as follows: ； In the formula, is the axial temperature gradient step, is the full width at half maximum, is the thermal expansion compensation coefficient, is the thermal conductivity of the gradient temperature control module; Along the axial direction of the gradient temperature control module, starting from the axial center temperature reference point, configure heating units step by step according to the axial temperature gradient step to form a linear temperature gradient distribution including at least five temperature nodes; Fix the reference material at each temperature node of the linear temperature gradient distribution.

7. The phase change temperature calibration method of the phase change material according to claim 6, wherein The arrangement of the reference materials satisfies: Arrange the reference materials with different phase change points in a circular array at the corresponding temperature nodes of the linear temperature gradient distribution. The adjacent circular spacing is calculated based on the axial temperature gradient step in an inverse proportion relationship. The calculation formula of the adjacent circular spacing is as follows: ； In the formula, is the coefficient of thermal expansion, is the axial temperature gradient step, is the adjacent annular spacing; Establish a phase change point - temperature coordinate mapping table based on the known phase change points of the reference materials and the node temperature values of the linear temperature gradient distribution. The phase change point - temperature coordinate mapping table is used to calibrate the theoretical positions of the reference materials.

8. The phase change temperature calibration method of the phase change material according to claim 7, characterized in that, The comparison of the offset between the actual phase change position and the theoretical position of the reference material includes: Real - time capture the droplet deformation characteristic images generated by the reference material during the phase change process through a high - speed camera. The droplet deformation characteristic images include the geometric center coordinates of the phase change interface; Extract the actual coordinate values of the geometric center coordinates from the droplet deformation characteristic image, and perform a difference calculation with the theoretical coordinate values of the corresponding temperature nodes in the phase change point-temperature coordinate mapping table to generate the center coordinate offset of the reference material ; Calculate the temperature compensation amount of the phase change material based on the axial thermal expansion coefficient of the gradient temperature control module and the center coordinate offset. The temperature compensation amount is the product of the center coordinate offset and the axial thermal expansion coefficient. The calculation formula of the temperature compensation amount is as follows: ； Wherein, is the coefficient of thermal expansion, is the thermal conductivity of the gradient temperature control module, is the central coordinate offset of the reference material, is the temperature compensation amount of the phase change material; Determine the offset between the actual phase change position and the theoretical position of the reference material based on the temperature compensation amount.

9. The method for calibrating the phase change temperature of the phase change material according to claim 1, characterized in that, The reverse correction of the corrected phase change temperature based on the offset to obtain the final calibration temperature of the phase change material includes: Determine the deviation direction and deviation magnitude of the actual phase change position of the reference material relative to the theoretical position based on the offset; Perform a reverse adjustment on the corrected phase change temperature based on the deviation direction and the deviation magnitude to obtain the final calibration temperature of the phase change material, where: When the offset is positive, lower the corrected phase change temperature; When the offset is negative, raise the corrected phase change temperature.

10. A phase change temperature calibration system for a phase change material, characterized in that, The system includes: A data synchronization and acquisition module, configured to acquire the surface temperature distribution data and crystal structure parameters of the phase change material based on a bimodal synchronization monitor; An association matrix construction module, configured to establish a temperature-structure association matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters; An initial phase change temperature range generation module, configured to, when the crystal structure parameters mutate, determine the surface temperature distribution data corresponding to the mutation moment based on the temperature-structure association matrix, and calculate the initial phase change temperature range of the phase change material; An initial temperature range dynamic compensation module, configured to construct a non-linear mapping model between the initial phase change temperature range and the heating rate, and dynamically compensate the initial phase change temperature range based on the non-linear mapping model to obtain the corrected phase change temperature of the phase change material; A data input module, configured to input the corrected phase change temperature into a gradient temperature control module containing a standard sample, where the gradient temperature control module includes a reference material that forms a preset temperature difference along the axis, and the phase change point of the reference material is known; A temperature reverse correction module, configured to compare the offset between the actual phase change position and the theoretical position of the reference material, and reverse correct the corrected phase change temperature based on the offset to obtain the final calibrated temperature of the phase change material.

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