Phase change material phase change temperature calibration method and system

Abstract

The present invention relates to the field of material testing technology and discloses a method and system for calibrating the phase change temperature of a phase change material. The method comprises: collecting surface temperature distribution data and crystal structure parameters of the phase change material using a dual-modal synchronous monitor and establishing a temperature-structure correlation matrix; determining the surface temperature distribution data corresponding to the mutation moment based on the temperature-structure correlation matrix when the crystal structure parameters undergo a sudden change, and calculating the initial phase change temperature range; constructing a nonlinear 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 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; comparing the offset between the actual phase change position of the reference material and the theoretical position, and reversely correcting the corrected phase change temperature based on the offset to obtain a final calibration temperature. The present invention can improve the accuracy of phase change temperature calibration of phase change materials.

Description

Technical Field

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

[0002] Traditional phase-change material (PCM) temperature calibration typically relies on single-mode data (e.g., temperature or crystal structure parameters), making it difficult to simultaneously monitor the real-time correlation between temperature distribution and crystal structure changes. Furthermore, existing technologies fail to fully consider the impact of heating rate on the phase-change temperature range, making calibration results susceptible to interference from experimental conditions.

[0003] For example, traditional infrared temperature measurement or X-ray diffraction techniques cannot accurately capture the temperature-structure relationship at the critical moment of phase transition due to asynchronous data acquisition. Furthermore, linear compensation models struggle to accurately correct for phase transition hysteresis and thermal expansion effects. These issues lead to systematic errors in phase transition temperature calibration, limiting the realization of high-precision applications. Summary of the Invention

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

[0005] To achieve the above-mentioned purpose, the present invention provides a method for calibrating the phase change temperature of a phase change material, comprising:

[0006] The surface temperature distribution data and crystal structure parameters of phase change materials are collected based on a dual-mode synchronous monitor;

[0007] Establishing a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters;

[0008] When the crystal structure parameters suddenly change, the surface temperature distribution data corresponding to the sudden change moment is determined based on the temperature-structure correlation matrix, and the initial phase change temperature range of the phase change material is calculated;

[0009] Constructing a nonlinear 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 nonlinear mapping model to obtain a corrected phase change temperature of the phase change material;

[0010] Inputting the corrected phase transition temperature into a gradient temperature control module containing a standard sample, wherein the gradient temperature control module includes a reference material forming a preset temperature difference along the axial direction, wherein the phase transition point of the reference material is known;

[0011] The offset between the actual phase change position of the reference material and the theoretical position is compared, and the corrected phase change temperature is reversely corrected based on the offset to obtain a final calibration temperature of the phase change material.

[0012] Optionally, the collecting of surface temperature distribution data and crystal structure parameters of the phase change material based on a dual-mode synchronous monitor includes:

[0013] An infrared thermal imager and an X-ray diffractometer are synchronously arranged in a dual-modal synchronous monitor, wherein the infrared thermal imager and the X-ray diffractometer are time-stamp aligned by a synchronous trigger signal;

[0014] When the dual-modal 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, while the X-ray diffractometer continuously collects the crystal structure parameters of the phase change material, wherein the crystal structure parameters include lattice constant and diffraction peak intensity.

[0015] Optionally, establishing a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters includes:

[0016] Mapping the surface temperature distribution data at the same time stamp into a two-dimensional temperature field grayscale image;

[0017] extracting a lattice constant change rate from the crystal structure parameters, and converting the lattice constant change rate into a structural response coefficient;

[0018] Based on the same time stamp, the two-dimensional temperature field grayscale image and the structural response coefficient are spatially aligned to obtain a temperature-structure correlation matrix of the phase change material.

[0019] Optionally, the conditions for determining whether the crystal structure parameters have undergone a sudden change include:

[0020] performing a second-order derivative operation on the structural response coefficient to obtain a derivative change curve of the structural response coefficient;

[0021] Extracting extreme points whose absolute values ​​exceed a preset threshold from the derivative change curve;

[0022] 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.

[0023] Optionally, constructing a nonlinear mapping model between the initial phase change temperature range and the heating rate includes:

[0024] Extract the upper boundary value from the initial phase change temperature range and lower boundary value and the upper limit boundary value, the lower limit boundary value and the heating rate Together they form the input feature vector ;

[0025] The input feature vector is input into a preconfigured support vector regression algorithm, which includes a kernel function and a loss function, wherein:

[0026] The kernel function is a radial basis function, and the expression of the radial basis function is as follows:

[0027] ;

[0028] Where, is the function value of the radial basis function, is the kernel function bandwidth parameter, is the first feature vector in the input Sample points, is the first feature vector in the input Sample points, is an exponential function, is the first feature vector in the input Sample points and The Euclidean distance of sample points;

[0029] The loss function is the Huber loss function, and the expression of the Huber loss function is as follows:

[0030] ;

[0031] Where, is the function value of the Huber loss function, is the prediction error, is the robustness threshold;

[0032] The support vector regression algorithm is iteratively trained using multiple sets 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, wherein the expression of the dynamic compensation function is as follows:

[0033] ;

[0034] Where, is the phase transition 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;

[0035] The dynamic compensation function is applied to the boundary values ​​of the initial phase transition temperature interval, and the median and half-peak width of the modified phase transition temperature are output. The median is determined by the center point of the compensated temperature interval, and the half-peak width is calculated by the span of the compensated temperature interval. The expression of the median is as follows:

[0036] ;

[0037] Where, is the median value of the modified 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;

[0038] The expression of the half-peak width is as follows:

[0039] ;

[0040] Where, is the half-peak width of the modified 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.

[0041] Optionally, the gradient temperature control module includes:

[0042] Setting an axial center temperature reference point of the gradient temperature control module according to the median value, wherein the temperature value of the axial center temperature reference point is the median value;

[0043] The axial temperature gradient step length of the gradient temperature control module is calculated based on the half-peak width to generate a preset temperature difference that is linearly related to the half-peak width, wherein the calculation formula of the axial temperature gradient step length is as follows:

[0044] ;

[0045] Where, is the axial temperature gradient step size, is the half-peak width, is the thermal expansion compensation coefficient, is the thermal conductivity of the gradient temperature control module;

[0046] Along the axial direction of the gradient temperature control module, with the axial center temperature reference point as the starting point, heating units are configured step by step according to the axial temperature gradient step to form a linear temperature gradient distribution including at least five temperature nodes;

[0047] The reference material is fixedly arranged at each temperature node of the linear temperature gradient distribution.

[0048] Optionally, the arrangement of the reference materials satisfies:

[0049] The reference materials at different phase transition points are arranged in a ring array at corresponding temperature nodes of the linear temperature gradient distribution, wherein the adjacent ring spacing is calculated based on the inverse proportional relationship of the axial temperature gradient step length. The calculation formula of the adjacent ring spacing is as follows:

[0050] ;

[0051] Where, is the coefficient of thermal expansion, is the axial temperature gradient step size, is the distance between adjacent rings;

[0052] A phase change point-temperature coordinate mapping table is established based on the known phase change points of the reference material and the node temperature values ​​of the linear temperature gradient distribution, wherein the phase change point-temperature coordinate mapping table is used to calibrate the theoretical position of the reference material.

[0053] Optionally, comparing the offset between the actual phase change position of the reference material and the theoretical position includes:

[0054] capturing, in real time, a characteristic image of droplet deformation generated by the reference material during the phase change process using a high-speed camera, wherein the characteristic image of droplet deformation includes the geometric center coordinates of the phase change interface;

[0055] The actual coordinate value of the geometric center coordinate is extracted from the droplet deformation characteristic image, and the actual coordinate value of the geometric center coordinate is differentially calculated with the theoretical coordinate value of the corresponding temperature node in the phase change point-temperature coordinate mapping table to generate the center coordinate offset of the reference material. ;

[0056] The temperature compensation amount of the phase change material is calculated 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:

[0057] ;

[0058] Where, is the coefficient of thermal expansion, 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;

[0059] The offset between the actual phase change position of the reference material and the theoretical position is determined based on the temperature compensation amount.

[0060] Optionally, the reversely correcting the modified phase change temperature based on the offset to obtain a final calibration temperature of the phase change material includes:

[0061] Determining the deviation direction and magnitude of the actual phase change position of the reference material relative to the theoretical position based on the offset;

[0062] The corrected phase change temperature is reversely adjusted based on the deviation direction and the deviation magnitude to obtain a final calibration temperature of the phase change material, wherein:

[0063] When the offset is a positive value, lowering the modified phase transition temperature;

[0064] When the offset is a negative value, the modified phase transition temperature is increased.

[0065] In order to solve the above problems, the present invention further provides a phase change material phase change temperature calibration system, the system comprising:

[0066] A data synchronization acquisition module is used to collect surface temperature distribution data and crystal structure parameters of phase change materials based on a dual-mode synchronous monitor;

[0067] A correlation matrix building module, configured to establish a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters;

[0068] an initial phase change temperature interval generating module, configured to determine the surface temperature distribution data corresponding to the mutation moment based on the temperature-structure correlation matrix when the crystal structure parameters undergo a mutation, and calculate the initial phase change temperature interval of the phase change material;

[0069] an initial temperature interval dynamic compensation module, configured to construct a nonlinear mapping model between the initial phase change temperature interval and the heating rate, and dynamically compensate the initial phase change temperature interval based on the nonlinear mapping model to obtain a corrected phase change temperature of the phase change material;

[0070] a data input module for inputting the corrected phase transition temperature into a gradient temperature control module containing a standard sample, wherein the gradient temperature control module comprises a reference material forming a preset temperature difference along the axial direction, wherein the phase transition point of the reference material is known;

[0071] The temperature reverse correction module is used to compare the offset between the actual phase change position of the reference material and the theoretical position, and reversely correct the modified phase change temperature based on the offset to obtain the final calibration temperature of the phase change material.

[0072] The present invention uses a dual-modal synchronous monitor (infrared thermal imager and X-ray diffractometer) to achieve timestamp alignment of temperature distribution and crystal structure parameters, solving the data fragmentation problem of traditional methods and improving data correlation and analysis accuracy; constructs a nonlinear mapping model based on support vector regression, combines historical data to dynamically compensate for the initial phase change temperature range, effectively corrects phase change hysteresis and thermal expansion effects, and reduces calibration errors; uses a gradient temperature control module to compare the actual and theoretical phase change position offsets of the reference material, reversely corrects the temperature, forms a closed-loop optimization process, and significantly improves the accuracy of the final calibration temperature; uses artificial intelligence algorithms (such as the Huber loss function) to enhance the model's robustness to abnormal data, making it suitable for a variety of phase change materials and complex experimental conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 A schematic flow chart of a method for calibrating the phase change temperature of a phase change material provided in one embodiment of the present invention;

[0074] Figure 2 A functional module diagram of a phase change material phase change temperature calibration system provided by one embodiment of the present invention;

[0075] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0076] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0077] The embodiment of the present application provides a phase change temperature calibration method for a phase change material. The execution subject of the phase change temperature calibration method for a phase change material includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the phase change temperature calibration method for a 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 it can be 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 networks (CDNs), and big data and artificial intelligence platforms.

[0078] Reference Figure 1 FIG. 1 is a flow chart of a method for calibrating the phase change temperature of a phase change material according to an embodiment of the present invention. In this embodiment, the method for calibrating the phase change temperature of a phase change material includes:

[0079] S1. Collect surface temperature distribution data and crystal structure parameters of phase change materials based on dual-mode synchronous monitoring.

[0080] In an embodiment of the present invention, the acquisition of surface temperature distribution data and crystal structure parameters of the phase change material based on a dual-modal synchronous monitor includes:

[0081] An infrared thermal imager and an X-ray diffractometer are synchronously arranged in a dual-modal synchronous monitor, wherein the infrared thermal imager and the X-ray diffractometer are time-stamp aligned by a synchronous trigger signal;

[0082] When the dual-modal 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, while the X-ray diffractometer continuously collects the crystal structure parameters of the phase change material, wherein the crystal structure parameters include lattice constant and diffraction peak intensity.

[0083] In an embodiment of the present invention, the dual-modal synchronous monitor integrates the monitoring equipment of an infrared thermal imager and an X-ray diffractometer, and 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.

[0084] In detail, 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 target being measured and reflect it on 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.

[0085] Specifically, an X-ray diffractometer is an instrument for analyzing 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 constant and diffraction peak intensity.

[0086] In detail, 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 collected surface temperature distribution data and crystal structure parameters correspond to the phase change material state at the same moment, thus ensuring the relevance and accuracy of the data.

[0087] In detail, the lattice constant describes the basic parameters of the crystal structure and reflects the arrangement rules of atoms or molecules in the crystal. Its change can characterize the change of the crystal structure and is one of the important bases for judging whether a phase transition occurs.

[0088] In detail, 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 type, number and arrangement of atoms in the crystal. Its changes can also reflect the changes in the crystal structure during the phase transition process.

[0089] Furthermore, an infrared thermal imager and an X-ray diffractometer are reasonably installed inside the dual-modal synchronous monitor to ensure that their optical and electronic systems can work normally and do not interfere with each other.

[0090] Furthermore, a synchronous trigger signal device is connected to the control units of the infrared thermal imager and the X-ray diffractometer respectively, and appropriate trigger parameters are set so that the two can record data at the same time rhythm during startup and operation, completing timestamp alignment.

[0091] Furthermore, when the dual-modal synchronous monitor is started 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 from 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 constant and diffraction peak intensity through analysis and calculation of these signals.

[0092] Specifically, collecting the surface temperature distribution data and crystal structure parameters of the phase change material based on a dual-modal synchronous monitor is the starting point of the entire phase change temperature calibration process, providing the raw 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 relationship 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.

[0093] In general, traditional phase transition temperature calibration methods often only capture temperature or structural information independently, failing to simultaneously monitor and correlate both. This step utilizes a dual-modal synchronous monitor that integrates an infrared thermal imager and an X-ray diffractometer, achieving timestamp alignment. This solves the issues of asynchronous data acquisition and the inability to correlate temperature and structural changes in real time in traditional methods, improving data acquisition efficiency and analysis accuracy.

[0094] S2. Establishing a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters.

[0095] In an embodiment of the present invention, establishing a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters includes:

[0096] Mapping the surface temperature distribution data at the same time stamp into a two-dimensional temperature field grayscale image;

[0097] extracting a lattice constant change rate from the crystal structure parameters, and converting the lattice constant change rate into a structural response coefficient;

[0098] Based on the same time stamp, the two-dimensional temperature field grayscale image and the structural response coefficient are spatially aligned to obtain a temperature-structure correlation matrix of the phase change material.

[0099] Specifically, the temperature-structure correlation matrix describes the relationship between the surface temperature distribution and the crystal structure parameters of a phase change material. This matrix clearly shows how the crystal structure changes under different temperature conditions, providing an important basis for subsequent analysis of phase transition temperatures.

[0100] Specifically, a two-dimensional temperature field grayscale image presents surface temperature distribution data in the form of an image, where the grayscale value of each pixel represents the temperature at that location. This allows for intuitive observation of the temperature distribution on the surface of the phase change material.

[0101] Specifically, the lattice constant change rate reflects the rate at which the lattice constant in a crystal structure changes over time or other factors. During a phase transition, the lattice constant changes, and its change rate can be used as an indicator to measure the degree of crystal structure change.

[0102] In detail, the structural 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.

[0103] In detail, spatial registration refers to the spatial matching of the two-dimensional temperature field grayscale image and the structural response coefficient so that they can be accurately associated at the same time stamp, thereby constructing the temperature-structure correlation matrix.

[0104] Furthermore, mapping the surface temperature distribution data at the same timestamp into a two-dimensional temperature field grayscale image includes the following steps:

[0105] First, determine the range of temperature data, for example, by counting the minimum value of all surface temperature distribution data. and maximum value ; Then according to the grayscale value range of the grayscale image (usually ), establish the mapping relationship between temperature value and grayscale value, assuming that the temperature value is , the corresponding gray value It can be achieved through the linear mapping formula Calculate; finally, convert the temperature value of each position into a grayscale value according to the above mapping relationship, and arrange them into the form of a two-dimensional image to obtain a two-dimensional temperature field grayscale map.

[0106] Furthermore, 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:

[0107] For the lattice constants of the crystal structure parameters collected at different time points ( represents a time point), calculate the change in lattice constant between adjacent time points ; Lattice constant change rate ,in is the time interval between adjacent time points; structural response coefficient The conversion can be determined based on specific experimental data and theoretical models, for example, by linear transformation ( and is the constant obtained by fitting the experimental data), and the lattice constant change rate is converted into the structural response coefficient.

[0108] In detail, based on the same timestamp, spatial registration of the 2D temperature field grayscale image with the structural response coefficient includes the following steps:

[0109] Determine the spatial coordinate system corresponding to the two-dimensional temperature field grayscale image and the structural response coefficient to ensure that the two are spatially consistent; 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 spatial positions, and the matrix elements are the combination of the temperature grayscale value and the structural response coefficient at that position, thereby obtaining the temperature-structure correlation matrix.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] In an embodiment of the present invention, the conditions for determining whether the crystal structure parameters have undergone a mutation include:

[0115] performing a second-order derivative operation on the structural response coefficient to obtain a derivative change curve of the structural response coefficient;

[0116] Extracting extreme points whose absolute values ​​exceed a preset threshold from the derivative change curve;

[0117] 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.

[0118] 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.

[0119] 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.

[0120] In detail, the structural response coefficient is converted from the rate of change of the lattice constant in the crystal structure parameters, and is used to measure the response degree of the crystal structure to temperature changes, which is convenient for correlation analysis with temperature data.

[0121] In detail, the second-order derivative operation refers to the mathematical operation of taking the second derivative of the structural response coefficient with respect to time (or other related variables). The second-order derivative can reflect the change in the rate of change of the structural response coefficient, thereby more keenly capturing the mutation characteristics of the structural response coefficient.

[0122] In detail, the derivative change curve refers to a curve drawn with time (or other related variables) as the horizontal coordinate and the second-order derivative of the structural response coefficient as the vertical coordinate, which can intuitively show the changing trend of the change rate of the structural response coefficient.

[0123] In detail, the preset threshold is a numerical standard set in advance based on experimental experience, material properties or theoretical analysis, and is used to determine whether the extreme point in the derivative change curve indicates a real mutation in the crystal structure parameters to avoid misjudgment.

[0124] Specifically, an extreme point refers to a point in the derivative curve where the function value is locally maximum or minimum. In the present invention, these extreme points are considered to be related to the moment of sudden change of crystal structure parameters.

[0125] In detail, the mutation moment refers to the specific time point when the crystal structure parameters mutate. Determining this moment is crucial for accurately determining the time when the phase transition begins and calculating the initial phase transition temperature range.

[0126] In detail, the initial phase transition temperature range refers to the temperature range in which the phase transition begins to occur, which is preliminarily determined during the phase transition process and provides a basis for the subsequent more accurate determination of the phase transition temperature.

[0127] Furthermore, performing a second-order derivative operation on the structural response coefficient to obtain a derivative change curve includes the following steps:

[0128] Assume that the structural response coefficients are time dependent Function . Using mathematical derivation formulas and calculation methods, Taking the first-order derivative we get , then Take the derivative and get the second-order derivative ; by time is the independent variable, As the dependent variable, the The values ​​are plotted to form a derivative change curve.

[0129] Furthermore, extracting extreme points whose absolute values ​​exceed a preset threshold from the derivative change curve includes the following steps:

[0130] Traverse each data point in the derivative change curve and calculate the absolute value of each point ( Represents different time points); the absolute value of each point is compared with the preset threshold For comparison, when , check whether the point is an extreme point (that is, the function value of the point is greater than or less than the function value of its adjacent points). If it is an extreme point, record it.

[0131] Furthermore, the time point corresponding to the extreme value point is taken as the mutation moment, and it is determined that the crystal structure parameters mutate at this moment, including the following steps:

[0132] For the recorded extreme points, get their corresponding timestamps ; Find the timestamp based on the temperature-structure correlation matrix Corresponding surface temperature distribution data; from these surface temperature distribution data, select the maximum temperature and minimum value , thereby determining the initial phase transition temperature interval .

[0133] In detail, by using second-order derivative operations and preset thresholds to judge the mutation moment of crystal structure parameters, the time point when the phase transition begins can be determined more accurately, which is more accurate than traditional methods that rely only on a single parameter or empirical judgment; the accurately calculated initial phase transition temperature range provides reliable basic data for the subsequent construction of nonlinear mapping models and dynamic compensation, which helps to further improve the accuracy of phase transition temperature calibration; this method based on mathematical operations and threshold judgment reduces the interference of human factors, makes the analysis of the phase transition process more objective and reliable, and enhances the credibility of the research results.

[0134] Specifically, this step analyzes the temperature-structure correlation matrix established in the previous step. An accurate correlation matrix ensures the determination of the surface temperature distribution data corresponding to the mutation moment. The determined initial phase transition temperature range, in turn, provides input data for the subsequent construction of a nonlinear mapping model related to the heating rate, making it a critical step in the entire phase transition temperature calibration process. Inaccurate determination of the mutation moment can lead to deviations in subsequent temperature range calculations and dynamic compensation, affecting the final calibration results.

[0135] S4. Constructing a nonlinear 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 nonlinear mapping model to obtain a corrected phase change temperature of the phase change material.

[0136] In an embodiment of the present invention, the step of constructing a nonlinear mapping model between the initial phase change temperature range and the heating rate includes:

[0137] Extract the upper boundary value from the initial phase change temperature range and lower boundary value and the upper limit boundary value, the lower limit boundary value and the heating rate Together they form the input feature vector ;

[0138] The input feature vector is input into a preconfigured support vector regression algorithm, which includes a kernel function and a loss function, wherein:

[0139] The kernel function is a radial basis function, and the expression of the radial basis function is as follows:

[0140] ;

[0141] Where, is the function value of the radial basis function, is the kernel function bandwidth parameter, is the first feature vector in the input Sample points, is the first feature vector in the input Sample points, is an exponential function, is the first feature vector in the input Sample points and The Euclidean distance of sample points;

[0142] The loss function is the Huber loss function, and the expression of the Huber loss function is as follows:

[0143] ;

[0144] Where, is the function value of the Huber loss function, is the prediction error, is the robustness threshold;

[0145] The support vector regression algorithm is iteratively trained using multiple sets 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, wherein the expression of the dynamic compensation function is as follows:

[0146] ;

[0147] Where, is the phase transition 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;

[0148] The dynamic compensation function is applied to the boundary values ​​of the initial phase transition temperature interval, and the median and half-peak width of the modified phase transition temperature are output. The median is determined by the center point of the compensated temperature interval, and the half-peak width is calculated by the span of the compensated temperature interval. The expression of the median is as follows:

[0149] ;

[0150] Where, is the median value of the modified 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;

[0151] The expression of the half-peak width is as follows:

[0152] ;

[0153] Where, is the half-peak width of the modified 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.

[0154] Specifically, a nonlinear mapping model is a mathematical model that describes the complex, non-linear relationship between the initial phase transition temperature range and the heating rate. Compared to linear models, it more accurately reflects the relationship between the two in real-world situations, because the effect of the heating rate on the phase transition temperature range during the phase transition process is not a simple linear change.

[0155] Specifically, the initial phase change temperature range is the approximate temperature range at which the phase change material begins to undergo phase change, determined in the previous step, and includes an upper limit boundary value and a lower limit boundary value, providing basic data for subsequent accurate calculation of the phase change temperature.

[0156] In detail, the heating rate is the rate of change of temperature over 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 the phase change temperature range to change.

[0157] In detail, the input feature vector is a vector consisting of the upper boundary value, lower boundary value and heating rate of the initial phase transition temperature interval, which is used as the input data of the support vector regression algorithm to train the model to learn the relationship between them.

[0158] Specifically, the support vector regression algorithm is a machine learning algorithm used for regression analysis. It minimizes the error between the predicted value and the true value by finding an optimal hyperplane to fit the data. In the present invention, it is used to construct a relationship model between the initial phase transition temperature range and the heating rate.

[0159] Specifically, the kernel function (radial basis function) is used in the support vector regression algorithm to map low-dimensional data to a higher-dimensional space, making it easier to find a linearly separable hyperplane within the data. The radial basis function calculates its value based on the Euclidean distance between sample points. The kernel function bandwidth parameter controls the "width" of the function, affecting the model's complexity and generalization ability.

[0160] In detail, the loss function (Huber loss function) is used to measure the difference between the model's predicted value and the true value. The Huber loss function combines the advantages of the square loss function and the absolute value loss function. When the prediction error is small, the square loss function is used to make the model training more stable; when the prediction error is large, the absolute value loss function is used, which has better robustness to outliers. The robustness threshold is used to control the switching between the two loss calculation methods.

[0161] In detail, the phase change hysteresis factor reflects the parameters of 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 initial phase change temperature range on the phase change hysteresis in the dynamic compensation function, and is used to compensate for the influence of phase change hysteresis on the phase change temperature.

[0162] In detail, the thermal expansion compensation coefficient is a coefficient introduced to take into account the effect of thermal expansion of the phase change material on the phase change temperature during the heating process, and is used in the dynamic compensation function to correct the effect of the thermal expansion factor on the phase change temperature.

[0163] In detail, the dynamic compensation function is a function trained by the support vector regression algorithm, which dynamically adjusts the phase transition temperature according to the initial phase transition temperature range and the heating rate to compensate for the temperature deviation caused by factors such as phase transition hysteresis and thermal expansion.

[0164] In detail, the corrected phase transition temperature is a value closer to the true phase transition temperature obtained after dynamic compensation. It is determined by the median and half-peak width calculated by applying the dynamic compensation function to the boundary values ​​of the initial phase transition temperature interval, and is more accurate than the initial phase transition temperature interval.

[0165] In detail, the median is a key parameter of the corrected phase transition temperature, which is determined by the center point of the compensated temperature interval and represents the central estimated value of the corrected phase transition temperature.

[0166] In detail, the half-value width is a parameter reflecting the span of the modified phase transition temperature interval, which is used to describe the range of temperature change during the phase transition process. Together with the median value, it more comprehensively represents the characteristics of the modified phase transition temperature.

[0167] Furthermore, extracting boundary values ​​and forming an input feature vector includes the following steps:

[0168] The initial phase transition temperature range calculated above In , directly get the upper boundary value and lower boundary value ;Record the heating rate of the phase change material in the current experiment or measurement ;Will and Combine them into a vector in a certain order, for example , forming the input feature vector.

[0169] Furthermore, training using the support vector regression algorithm includes the following steps:

[0170] Select the pre-configured support vector regression algorithm and set the kernel function to radial basis function (according to the formula Calculation), the loss function is the Huber loss function (according to the formula ;

[0171] Prepare multiple sets of calibration data for a large number of historical phase change materials. Each set of data includes the upper and lower limits of the initial phase change temperature range and the corresponding heating rate, as well as the actual phase change temperature data that has been accurately measured or known (for calculating the prediction error).

[0172] The input feature vectors (consisting of the initial phase transition temperature interval boundary values ​​and the heating rate from the historical data) are sequentially fed into the support vector regression algorithm. The algorithm maps the data into a high-dimensional space using a kernel function and searches for an optimal hyperplane for fitting. During each training run, the error between the predicted value and the actual phase transition temperature is calculated, and the loss is calculated using the Huber loss function.

[0173] By continuously adjusting the parameters in the support vector regression algorithm (such as the kernel function bandwidth parameter , robustness threshold and other related parameters) so that the value of the loss function gradually decreases. When the loss function converges (that is, the loss value no longer decreases significantly), the training is considered complete.

[0174] Furthermore, generating a dynamic compensation function and calculating a corrected phase transition temperature include the following steps:

[0175] After the training is completed, the dynamic compensation function associated with the heating rate is obtained ,in and It is a parameter determined during the training process; the dynamic compensation function acts on the current initial phase change temperature interval boundary value and and heating rate According to the formula Calculate the median value of the corrected phase transition temperature according to the formula Calculate the half-peak width. The median value and half-peak width together determine the characteristics of the modified phase transition temperature.

[0176] In general, this step is a critical step for further precise temperature correction after determining the initial phase transition temperature range. The initial phase transition temperature range provides the foundational data for building the nonlinear mapping model, while the resulting corrected phase transition temperature provides a more accurate reference value for subsequent comparison and correction in the gradient temperature control module. If the dynamic compensation in this step is inaccurate, the subsequent reverse correction in the gradient temperature control module will lose its basis for accuracy, affecting the final calibration results.

[0177] In general, the impact of factors such as phase change hysteresis and thermal expansion on the phase change temperature was considered. By constructing a nonlinear mapping model and dynamic compensation, the interference of changes in the heating rate on the temperature calibration was effectively reduced, making the corrected phase change temperature closer to the true value and improving the accuracy of the phase change temperature calibration. The model was trained using historical data to adapt to the temperature calibration requirements of different phase change materials and experimental conditions. Even when faced with new phase change materials or changes in the experimental environment, as long as there is sufficient historical data, the model can learn the corresponding rules and perform accurate dynamic compensation. The model fully utilizes the information in the initial phase change temperature range, heating rate, and historical calibration data to explore the potential relationship between them, providing a more comprehensive basis for accurately calibrating the phase change temperature.

[0178] In general, the support vector regression algorithm is used to construct a nonlinear mapping model of the initial phase change temperature range and the heating rate, which breaks through the limitations of traditional linear analysis methods and can more accurately describe the relationship between the two in complex phase change processes. This innovative modeling method improves the analysis accuracy of factors affecting the phase change temperature; the phase change hysteresis factor and thermal expansion compensation coefficient are introduced, and the initial phase change temperature range is adjusted through a dynamic compensation function, taking into account 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.

[0179] S5. Inputting the corrected phase transition temperature into a gradient temperature control module containing a standard sample, wherein the gradient temperature control module comprises a reference material forming a preset temperature difference along the axial direction, wherein the phase transition point of the reference material is known.

[0180] In an embodiment of the present invention, the gradient temperature control module includes:

[0181] Setting an axial center temperature reference point of the gradient temperature control module according to the median value, wherein the temperature value of the axial center temperature reference point is the median value;

[0182] The axial temperature gradient step length of the gradient temperature control module is calculated based on the half-peak width to generate a preset temperature difference that is linearly related to the half-peak width, wherein the calculation formula of the axial temperature gradient step length is as follows:

[0183] ;

[0184] Where, is the axial temperature gradient step size, is the half-peak width, is the thermal expansion compensation coefficient, is the thermal conductivity of the gradient temperature control module;

[0185] Along the axial direction of the gradient temperature control module, with the axial center temperature reference point as the starting point, heating units are configured step by step according to the axial temperature gradient step to form a linear temperature gradient distribution including at least five temperature nodes;

[0186] The reference material is fixedly arranged at each temperature node of the linear temperature gradient distribution.

[0187] In an embodiment of the present invention, the arrangement of the reference materials satisfies:

[0188] The reference materials at different phase transition points are arranged in a ring array at corresponding temperature nodes of the linear temperature gradient distribution, wherein the adjacent ring spacing is calculated based on the inverse proportional relationship of the axial temperature gradient step length. The calculation formula of the adjacent ring spacing is as follows:

[0189] ;

[0190] Where, is the coefficient of thermal expansion, is the axial temperature gradient step size, is the distance between adjacent rings;

[0191] A phase change point-temperature coordinate mapping table is established based on the known phase change points of the reference material and the node temperature values ​​of the linear temperature gradient distribution, wherein the phase change point-temperature coordinate mapping table is used to calibrate the theoretical position of the reference material.

[0192] In detail, the corrected phase change temperature refers to the temperature value obtained after dynamic compensation of the initial phase change temperature range. Compared with the initial phase change temperature range, it is closer to the actual phase change temperature of the phase change material. It contains two key parameters, the median and the half-peak width, which are used for subsequent precise analysis.

[0193] In detail, 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, so as to compare the actual and theoretical phase change positions of the reference material, and then correct the corrected phase change temperature.

[0194] In detail, a standard sample is a material sample with known properties (such as a known phase transition point) that is used as a reference to evaluate and calibrate the phase transition temperature of a phase change material. Its properties are stable and the phase transition process can be accurately observed and analyzed.

[0195] In detail, 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 of the reference material at different temperatures, a basis is provided for calibrating the temperature of the phase change material.

[0196] In detail, 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.

[0197] In detail, the axial temperature gradient step size is used to measure the interval value of the temperature change between adjacent temperature nodes in the axial direction of the gradient temperature control module. It is calculated based on the half-peak width, thermal expansion compensation coefficient and thermal conductivity of the gradient temperature control module, and determines the density of the temperature gradient.

[0198] In detail, the preset temperature difference is calculated based on the half-peak width, and the temperature difference expected to be formed in the axial direction of the gradient temperature control module is such that different positions have different temperatures to simulate the state of the phase change material at different temperatures.

[0199] In detail, the linear temperature gradient distribution is a uniform and linear temperature distribution form formed by the temperature gradually changing according to a certain rule (with the axial temperature gradient step as the interval) in the axial direction of the gradient temperature control module, which ensures the regularity and predictability of temperature changes.

[0200] In detail, the temperature nodes are discrete temperature points set in the linear temperature gradient distribution, at which reference materials are fixedly set to observe the phase change of the reference materials at specific temperatures.

[0201] In detail, the annular array arranges reference materials with different phase change points at temperature nodes in a circular arrangement, so that the reference materials at each temperature node can be distributed in an orderly manner, which is convenient for observation and comparison.

[0202] In detail, the adjacent ring spacing is the distance between the rings where two adjacent layers of reference material are located in the ring array, which 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 reference material distribution.

[0203] In detail, the phase transition point-temperature coordinate mapping table is a table that records the correspondence between the known phase transition points of the reference material and the temperature nodes in the linear temperature gradient distribution. It is used to determine the theoretical phase transition position of the reference material at different temperatures and provide a reference for subsequent comparison of the actual phase transition position.

[0204] Furthermore, the axial center temperature reference point is set: the median value is obtained from the relevant data of the corrected phase transition temperature The median value is used as the temperature setting value of the axial center position of the gradient temperature control module to determine the core temperature point of the entire temperature gradient distribution.

[0205] Furthermore, calculating the axial temperature gradient step and generating the preset temperature difference includes the following steps:

[0206] Known half-peak width , thermal expansion compensation coefficient and 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, the temperature of different positions is determined in sequence with the step as the interval, thereby generating a preset temperature difference and forming the basic framework of the linear temperature gradient distribution.

[0207] Furthermore, configuring the heating unit to form a linear temperature gradient distribution includes the following steps:

[0208] Along the axial direction of the gradient temperature control module, with the axial center temperature reference point as the starting point, according to the calculated axial temperature gradient step , install heating units at different positions. By controlling the power of the heating units, the temperature changes between adjacent heating units will meet the preset temperature difference, forming a linear temperature gradient distribution containing at least five temperature nodes. For example, if the axial center temperature reference point temperature is , the temperature of the first temperature node is , the second one is , and so on.

[0209] Furthermore, fixing the reference material comprises the following steps:

[0210] Place a reference material at each temperature node of the established linear temperature gradient distribution and ensure its position is fixed. A specific fixture or fixture can be used to ensure that the reference material does not move during the experiment, allowing for accurate observation of its phase transition.

[0211] Furthermore, arranging the reference materials and establishing a mapping table includes the following steps:

[0212] According to the phase transition points of different reference materials, they are arranged in a ring array at the corresponding temperature nodes. Calculate the spacing between adjacent rings ( is the thermal expansion coefficient), determine the position of each reference material in the annular array; record the phase transition point of each reference material and the temperature value of the temperature node where it is located, and establish a phase transition point-temperature coordinate mapping table. For example, for a phase transition point of The reference material, if it is located at a temperature of At the temperature node, record it in the mapping table Such a corresponding relationship.

[0213] In general, by constructing a gradient temperature control module with a linear temperature gradient distribution and rationally arranging reference materials with known phase change points, a stable and precise 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; the parameters of the gradient temperature control module are set based on the median and half-peak width of the corrected phase change temperature, so that the module is closely related to the corrected phase change temperature. Subsequently, the corrected phase change temperature is corrected by comparing the phase change of the reference material, and the final calibration temperature can be obtained more accurately; the standardized reference material arrangement method and mapping table establishment method make the experimental process more standardized and repeatable, which is convenient for different experimenters to operate and conduct comparative analysis under the same conditions.

[0214] Specifically, this step takes the previously obtained corrected phase transition temperature and uses it as a foundation to construct a gradient temperature control module. By setting the axial center temperature reference point and calculating the temperature gradient step size, the corrected phase transition temperature is incorporated into the temperature distribution of the gradient temperature control module. The established phase transition point-temperature coordinate mapping table provides a basis for subsequent comparison of the actual and theoretical phase transition positions of the reference material. This is an important prerequisite for achieving reverse correction of the corrected phase transition temperature and directly affects the accuracy of the final calibration temperature.

[0215] In general, the use of a gradient temperature control module containing a reference material to correct the temperature by comparing the actual and theoretical phase change positions is different from the traditional direct measurement or simple calculation method. This innovative correction method improves the accuracy and reliability of phase change temperature calibration; the unique gradient temperature control module design, including setting the temperature gradient according to the corrected phase change temperature, rationally arranging the reference materials and establishing a mapping table, solves the problems of inaccurate correction and difficult to control experimental conditions in traditional methods, and improves the overall level of phase change temperature calibration technology.

[0216] S6. Compare the offset between the actual phase change position of the reference material and the theoretical position, and reversely correct the modified phase change temperature based on the offset to obtain a final calibration temperature of the phase change material.

[0217] In an embodiment of the present invention, comparing the offset between the actual phase change position of the reference material and the theoretical position includes:

[0218] capturing, in real time, a characteristic image of droplet deformation generated by the reference material during the phase change process using a high-speed camera, wherein the characteristic image of droplet deformation includes the geometric center coordinates of the phase change interface;

[0219] The actual coordinate value of the geometric center coordinate is extracted from the droplet deformation characteristic image, and the actual coordinate value of the geometric center coordinate is differentially calculated with the theoretical coordinate value of the corresponding temperature node in the phase change point-temperature coordinate mapping table to generate the center coordinate offset of the reference material. ;

[0220] The temperature compensation amount of the phase change material is calculated 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:

[0221] ;

[0222] Where, is the coefficient of thermal expansion, 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;

[0223] The offset between the actual phase change position of the reference material and the theoretical position is determined based on the temperature compensation amount.

[0224] In an embodiment of the present invention, the reverse correction of the modified phase change temperature based on the offset to obtain a final calibration temperature of the phase change material includes:

[0225] Determining the deviation direction and magnitude of the actual phase change position of the reference material relative to the theoretical position based on the offset;

[0226] The corrected phase change temperature is reversely adjusted based on the deviation direction and the deviation magnitude to obtain a final calibration temperature of the phase change material, wherein:

[0227] When the offset is a positive value, lowering the modified phase transition temperature;

[0228] When the offset is a negative value, the modified phase transition temperature is increased.

[0229] In detail, the actual phase change position of the reference material is in the gradient temperature control module. When the reference material undergoes phase change, the actual spatial position of the phase change interface is determined by capturing the droplet deformation characteristic image with a high-speed camera and extracting the geometric center coordinates.

[0230] In detail, the theoretical phase change position of the reference material is determined based on the phase change point-temperature coordinate mapping table and the temperature distribution of the gradient temperature control module to determine the spatial position where the reference material should be when the phase change occurs under ideal circumstances.

[0231] In detail, the offset is the difference between the actual phase transition position and the theoretical phase transition position, which is calculated by coordinates and reflects the possible deviation between the corrected phase transition temperature and the true phase transition temperature.

[0232] In detail, the corrected phase transition temperature is the temperature value obtained after dynamic compensation of the initial phase transition temperature range, which is the basis for subsequent reverse correction, but there may still be a certain error with the true phase transition temperature.

[0233] In detail, the final calibration temperature is a value closer to the actual phase change temperature of the phase change material after the phase change temperature is corrected by reverse calibration, and is the final result of the entire phase change temperature calibration process.

[0234] In detail, the droplet deformation characteristic image is an image taken by a high-speed camera of the base material during the phase change process, in which the droplet shape changes due to the phase change. The image contains key information for determining the geometric center coordinates of the phase change interface.

[0235] In detail, the geometric center coordinates represent the coordinate values ​​of the center position of the phase change interface, which are usually expressed by abscissa and ordinate in a two-dimensional image and are extracted by analyzing the characteristic image of the droplet deformation.

[0236] In detail, the center coordinate offset is the difference between the actual geometric center coordinate value and the theoretical coordinate value, which is obtained by differential calculation and is used to measure the degree of deviation of the actual phase change position of the reference material from the theoretical position in the coordinate.

[0237] In detail, the temperature compensation amount is a value calculated based on the center coordinate offset and the axial thermal expansion coefficient of the gradient temperature control module. It is used to quantify the amplitude of the phase change temperature adjustment required to compensate for the phase change position deviation of the reference material caused by temperature difference.

[0238] In detail, the deviation direction is the offset direction of the actual phase change position relative to the theoretical position, which is divided into positive offset (the actual position is farther away from the reference point in a certain direction of the theoretical position) and negative offset (the actual position is closer to the reference point in the opposite direction of the theoretical position), which is determined by the positive or negative offset of the center coordinate.

[0239] In detail, the deviation size is the degree of offset between the actual phase change position and the theoretical position, which is measured by the absolute value of the center coordinate offset or according to a certain calculation method, and is used to determine the amplitude of the correction phase change temperature adjustment.

[0240] Furthermore, comparing the actual and theoretical phase change position offsets of the reference material includes the following steps:

[0241] During the operation of the gradient temperature control module, when the reference material begins to undergo phase change, the high-speed camera is started to capture the phase change process of the reference material in real time at a sufficiently high frame rate to obtain the characteristic image of the droplet deformation; image processing technology is used to identify the phase change interface from the captured characteristic image of the droplet deformation and determine the actual coordinate value of its geometric center coordinate. 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. The center coordinate offset is obtained by differential calculation (Assuming analysis in one dimension, it may be necessary to calculate the offset by integrating two-dimensional coordinates); the axial thermal expansion coefficient of the gradient temperature control module is known. and center coordinate offset , according to the formula (in Calculate the temperature compensation of the phase change material by using the thermal conductivity of the gradient temperature control module , in order to determine the offset between the actual phase change position of the reference material and the theoretical position.

[0242] In detail, the reverse correction of the phase transition temperature based on the offset includes the following steps:

[0243] Determine the direction and magnitude of the deviation: Based on the calculated center coordinate offset The positive or negative value of determines the direction of deviation. Indicates positive offset, Indicates a negative offset; the magnitude of the deviation is determined by Measure, or compensate for temperature 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 corrected phase change temperature needs to be lowered, that is, the final calibration temperature ( is the corrected phase transition temperature); if the offset is negative, the corrected phase transition temperature is increased, i.e. , thus obtaining the final calibration temperature.

[0244] In summary, by precisely comparing the actual and theoretical phase transition positions of the reference material, calculating the temperature compensation amount taking into account factors such as thermal expansion, and then performing a reverse correction to correct the phase transition temperature, errors introduced during the initial measurement and calculation processes are effectively eliminated, bringing the final calibration temperature closer to the true value and significantly improving the accuracy of phase transition temperature calibration. This reverse correction process, based on actual observations and precise calculations, provides a reliable error correction mechanism for phase transition temperature calibration. This method is not affected by the single influence of material properties or experimental environment, and can ensure the reliability of calibration results in a variety of situations.

[0245] Furthermore, this step is the key finishing link of the entire phase change temperature calibration process. It works closely with the previous acquisition, modeling, compensation and other steps to form a complete, closed-loop calibration system, which improves the scientificity and integrity of the phase change temperature calibration technology.

[0246] Specifically, this step builds upon the foundation established in the previous steps. The previously determined corrected phase change temperature provides the initial value for the reverse correction. The configuration of the gradient temperature control module and the establishment of a phase change point-temperature coordinate mapping table provide the necessary conditions for comparing actual and theoretical phase change positions. The parameters used to calculate the center coordinate offset and temperature compensation, such as the axial thermal expansion coefficient, are also determined or calculated in the previous steps. The results of this step ultimately determine the final calibration temperature of the phase change material, serving as a validation and optimization of all the previous steps.

[0247] Specifically, the method of reverse-correcting the temperature by comparing the actual and theoretical phase transition position offsets of a reference material overcomes the limitations of traditional phase transition temperature calibration, which relies solely on single measurements or simple compensation. This innovative strategy fully considers the multiple physical factors of the actual phase transition process, effectively improving the accuracy and reliability of the calibration. As a key step in the entire phase transition temperature calibration method, it works in conjunction with other steps to form an integrated whole. This reverse-correction mechanism improves the entire process, from data acquisition to temperature calibration.

[0248] like Figure 2 FIG. 1 is a functional module diagram of a phase change material phase change temperature calibration system provided by an embodiment of the present invention.

[0249] The phase-change material phase-change temperature calibration system 100 described in the present invention can be installed in an electronic device. Depending on the functionality implemented, the phase-change material phase-change temperature calibration system 100 may include a data synchronization acquisition module 101, a correlation matrix construction module 102, an initial phase-change temperature interval generation module 103, an initial temperature interval dynamic compensation module 104, a data input module 105, and a temperature reverse correction module 106. A module, also referred to as a unit, is a series of computer program segments that can be executed by an electronic device processor and perform a fixed function. These are stored in the electronic device's memory.

[0250] In this embodiment, the functions of each module / unit are as follows:

[0251] The data synchronization acquisition module 101 is used to collect surface temperature distribution data and crystal structure parameters of the phase change material based on the dual-mode synchronous monitor;

[0252] The correlation matrix building 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;

[0253] The initial phase change temperature interval generating module 103 is configured to determine the surface temperature distribution data corresponding to the mutation moment based on the temperature-structure correlation matrix when the crystal structure parameters undergo a mutation, and calculate the initial phase change temperature interval of the phase change material;

[0254] The initial temperature interval dynamic compensation module 104 is used to construct a nonlinear mapping model between the initial phase change temperature interval and the heating rate, and dynamically compensate the initial phase change temperature interval based on the nonlinear mapping model to obtain a corrected phase change temperature of the phase change material;

[0255] The data input module 105 is used to input the corrected phase transition temperature into a gradient temperature control module containing a standard sample, wherein the gradient temperature control module includes a reference material with a preset temperature difference formed along the axial direction, wherein the phase transition point of the reference material is known;

[0256] The temperature reverse correction module 106 is configured to compare the offset between the actual phase change position of the reference material and the theoretical position, and reversely correct the modified phase change temperature based on the offset to obtain a final calibration temperature of the phase change material.

[0257] In the several embodiments provided by the present invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the module division is merely a logical function division, and other division methods may be used in actual implementation.

[0258] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0259] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0260] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0261] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0262] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents 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 comprises: The surface temperature distribution data and crystal structure parameters of phase change materials are collected based on a dual-mode 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 suddenly change, the surface temperature distribution data corresponding to the sudden change moment is determined based on the temperature-structure correlation matrix, and the initial phase change temperature range of the phase change material is calculated; Constructing a nonlinear 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 nonlinear mapping model to obtain a corrected phase change temperature of the phase change material, wherein constructing the nonlinear 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 lower boundary value and the upper limit boundary value, the lower limit boundary value and the heating rate Together they form the input feature vector ; The input feature vector is input into a preconfigured support vector regression algorithm, which includes a kernel function and a loss function, wherein: The kernel function is a radial basis function, and the expression of the radial basis function is as follows: ； Where, is the function value of the radial basis function, is the kernel function bandwidth parameter, is the first Sample points, is the first Sample points, is an exponential function, is the first Sample points and The Euclidean distance of sample points; The loss function is the Huber loss function, and the expression of the Huber loss function is as follows: ； Where, 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 sets 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, wherein the expression of the dynamic compensation function is as follows: ； Where, is the phase transition 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 transition temperature interval, and the median and half-peak width of the modified phase transition temperature are output. The median is determined by the center point of the compensated temperature interval, and the half-peak width is calculated by the span of the compensated temperature interval. The expression of the median is as follows: ； Where, is the median value of the modified 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 half-peak width is as follows: ； Where, is the half-peak width of the modified 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; Inputting the corrected phase transition temperature into a gradient temperature control module containing a standard sample, wherein the gradient temperature control module includes a reference material forming a preset temperature difference along the axial direction, wherein the phase transition point of the reference material is known; The offset between the actual phase change position of the reference material and the theoretical position is compared, and the corrected phase change temperature is reversely corrected based on the offset to obtain a final calibration temperature of the phase change material.

2. The method for calibrating the phase change temperature of a phase change material according to claim 1, wherein: The method of collecting surface temperature distribution data and crystal structure parameters of the phase change material based on a dual-mode synchronous monitor includes: An infrared thermal imager and an X-ray diffractometer are synchronously arranged in a dual-modal synchronous monitor, wherein the infrared thermal imager and the X-ray diffractometer are time-stamp aligned by a synchronous trigger signal; When the dual-modal 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, while the X-ray diffractometer continuously collects the crystal structure parameters of the phase change material, wherein the crystal structure parameters include lattice constant and diffraction peak intensity.

3. The method for calibrating the phase change temperature of a phase change material according to claim 1, wherein: The step of 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 time stamp into a two-dimensional temperature field grayscale image; extracting a lattice constant change rate from the crystal structure parameters, and converting the lattice constant change rate into a structural response coefficient; Based on the same time stamp, the two-dimensional temperature field grayscale image and the structural response coefficient are spatially aligned to obtain a temperature-structure correlation matrix of the phase change material.

4. The method for calibrating the phase change temperature of a phase change material according to claim 3, wherein: 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.

5. The method for calibrating the phase change temperature of a phase change material according to claim 1, wherein: The gradient temperature control module includes: Setting an axial center temperature reference point of the gradient temperature control module according to the median value, wherein the temperature value of the axial center temperature reference point is the median value; The axial temperature gradient step length of the gradient temperature control module is calculated based on the half-peak width to generate a preset temperature difference that is linearly related to the half-peak width. The calculation formula of the axial temperature gradient step length is as follows: ； Where, is the axial temperature gradient step size, is the half-peak width, 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, with the axial center temperature reference point as the starting point, heating units are configured step by step according to the axial temperature gradient step 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.

6. The method for calibrating the phase change temperature of a phase change material according to claim 5, wherein: The arrangement of the reference materials satisfies: The reference materials with different phase transition points are arranged in a ring array at corresponding temperature nodes of the linear temperature gradient distribution, wherein the adjacent ring spacing is calculated based on the inverse proportional relationship of the axial temperature gradient step length. The calculation formula of the adjacent ring spacing is as follows: ； Where, is the coefficient of thermal expansion, is the axial temperature gradient step size, is the distance between adjacent rings; A phase change point-temperature coordinate mapping table is established based on the known phase change points of the reference material and the node temperature values ​​of the linear temperature gradient distribution, wherein the phase change point-temperature coordinate mapping table is used to calibrate the theoretical position of the reference material.

7. The method for calibrating the phase change temperature of a phase change material according to claim 6, wherein: The comparing the offset between the actual phase change position of the reference material and the theoretical position includes: capturing, in real time, a characteristic image of droplet deformation generated by the reference material during the phase change process using a high-speed camera, wherein the characteristic image of droplet deformation includes the geometric center coordinates of the phase change interface; The actual coordinate value of the geometric center coordinate is extracted from the droplet deformation characteristic image, and the actual coordinate value of the geometric center coordinate is differentially calculated with the theoretical coordinate value of the corresponding temperature node in the phase change point-temperature coordinate mapping table to generate the center coordinate offset of the reference material. ; The temperature compensation amount of the phase change material is calculated 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: ； Where, is the coefficient of thermal expansion, 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; The offset between the actual phase change position of the reference material and the theoretical position is determined based on the temperature compensation amount.

8. The method for calibrating the phase change temperature of a phase change material according to claim 1, wherein: The reversely correcting the modified phase change temperature based on the offset to obtain a final calibration temperature of the phase change material includes: Determining the deviation direction and magnitude of the actual phase change position of the reference material relative to the theoretical position based on the offset; The corrected phase change temperature is reversely adjusted based on the deviation direction and the deviation magnitude to obtain a final calibration temperature of the phase change material, wherein: When the offset is a positive value, lowering the modified phase transition temperature; When the offset is a negative value, the modified phase transition temperature is increased.

9. A phase change material phase change temperature calibration system, characterized in that: The system comprises: A data synchronization acquisition module is used to collect surface temperature distribution data and crystal structure parameters of phase change materials based on a dual-mode synchronous monitor; A correlation matrix building module, configured to establish a temperature-structure correlation matrix of the phase change material based on the surface temperature distribution data and the crystal structure parameters; an initial phase change temperature interval generating module, configured to determine the surface temperature distribution data corresponding to the mutation moment based on the temperature-structure correlation matrix when the crystal structure parameters undergo a mutation, and calculate the initial phase change temperature interval of the phase change material; An initial temperature interval dynamic compensation module is used to construct a nonlinear mapping model between the initial phase change temperature interval and the heating rate, and dynamically compensate the initial phase change temperature interval based on the nonlinear mapping model to obtain a corrected phase change temperature of the phase change material, wherein the construction of the nonlinear 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 lower boundary value and the upper limit boundary value, the lower limit boundary value and the heating rate Together they form the input feature vector ; The input feature vector is input into a preconfigured support vector regression algorithm, which includes a kernel function and a loss function, wherein: The kernel function is a radial basis function, and the expression of the radial basis function is as follows: ； Where, is the function value of the radial basis function, is the kernel function bandwidth parameter, is the first Sample points, is the first Sample points, is an exponential function, is the first Sample points and The Euclidean distance of sample points; The loss function is the Huber loss function, and the expression of the Huber loss function is as follows: ； Where, 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 sets 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, wherein the expression of the dynamic compensation function is as follows: ； Where, is the phase transition 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 transition temperature interval, and the median and half-peak width of the modified phase transition temperature are output. The median is determined by the center point of the compensated temperature interval, and the half-peak width is calculated by the span of the compensated temperature interval. The expression of the median is as follows: ； Where, is the median value of the modified 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 half-peak width is as follows: ； Where, is the half-peak width of the modified 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; a data input module for inputting the corrected phase transition temperature into a gradient temperature control module containing a standard sample, wherein the gradient temperature control module comprises a reference material forming a preset temperature difference along the axial direction, wherein the phase transition point of the reference material is known; The temperature reverse correction module is used to compare the offset between the actual phase change position of the reference material and the theoretical position, and reversely correct the modified phase change temperature based on the offset to obtain the final calibration temperature of the phase change material.

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