Temperature difference-deformation decoupling method for in-situ monitoring of thermal expansion coefficient

Abstract

The invention discloses a temperature difference-deformation decoupling method for thermal expansion coefficient in-situ monitoring, and belongs to the technical field of material physical property testing, and the method comprises the following steps: obtaining high spatial resolution temperature distribution data and full-field deformation data; performing three-dimensional reconstruction on the high-spatial-resolution temperature distribution data to generate dynamic temperature field data; theoretical thermal stress is calculated based on the dynamic temperature field data and the material mechanical parameters, and interference deformation data is generated; a dynamic correction coefficient is introduced to decouple full-field deformation data, and a real thermal expansion deformation field is output; calculating a thermal expansion coefficient based on the real thermal expansion deformation field and the temperature change trend data; and monitoring a uniformity index of a real thermal expansion deformation field, and adjusting a dynamic correction coefficient and a material mechanical parameter on line. According to the method, the temperature field and the deformation field are synchronously collected, thermal stress interference deformation caused by temperature difference is theoretically calculated and eliminated, and a closed-loop feedback optimization mode is combined, so that high-precision dynamic monitoring of the thermal expansion coefficient of the material under the non-uniform temperature condition can be realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of material physical performance testing, and in particular to a temperature difference-deformation decoupling method for in-situ monitoring of thermal expansion coefficient. BACKGROUND

[0002] Thermal expansion coefficient is an inherent physical property representing the degree of size change of a material with temperature change. In the fields of aerospace, precision instruments, microelectronic packaging, etc., materials and structures need to work in a wide temperature range, so accurate determination of thermal expansion coefficient is of great significance to structural design, reliability evaluation and failure analysis. The characterization of this property belongs to the category of material thermal physical property analysis.

[0003] In the prior art, common methods for measuring the thermal expansion coefficient of a material include push-rod dilatometer, optical interference method and strain gauge method. The push-rod dilatometer calculates the average linear expansion coefficient by measuring the elongation of a small sample heated in a uniform temperature furnace. Some advanced methods also start to use optical measurement techniques such as digital image correlation to track the speckle displacement on the surface of the material to obtain the strain field during heating, and then calculate the thermal expansion coefficient.

[0004] However, the above prior art solutions are usually based on an ideal premise that the sample being measured is in a completely uniform temperature field. In actual applications and many experimental scenarios, especially for larger-sized components or during rapid temperature rise and fall, it is extremely difficult to achieve absolute uniform distribution of temperature, and temperature gradients inevitably occur. This uneven temperature distribution will cause uncoordinated expansion trends in the material, resulting in internal stress, and the mechanical deformation caused by this thermal stress will be superimposed on the pure thermal expansion deformation, so that the total deformation measured directly cannot accurately reflect the true size change, and thus the calculated thermal expansion coefficient will have deviations. SUMMARY

[0005] To solve the above problems, the present application provides a temperature difference-deformation decoupling method for in-situ monitoring of thermal expansion coefficient, which adopts the method of synchronous acquisition of temperature field and deformation field, theoretical calculation and elimination of thermal stress interference deformation caused by temperature difference, and combination of closed-loop feedback optimization, so as to realize high-precision dynamic monitoring of the thermal expansion coefficient of the material under non-uniform temperature conditions.

[0006] The above object can be achieved by the following solution: A temperature difference-deformation decoupling method for in-situ monitoring of thermal expansion coefficient, comprising: acquiring high spatial resolution temperature distribution data of a surface or a key area of a measured material, and synchronously collecting full-field deformation data of the surface of the measured material to generate a temperature-deformation multi-source data set; performing three-dimensional reconstruction on the high spatial resolution temperature distribution data to generate dynamic temperature field data; calculating theoretical thermal stress caused by uneven temperature distribution based on the dynamic temperature field data and material mechanical parameters to generate interference deformation data; performing real-time decoupling operation on the full-field deformation data by using the interference deformation data, introducing a dynamic correction coefficient to obtain a real thermal expansion deformation field; calculating a thermal expansion coefficient based on the real thermal expansion deformation field and temperature change trend data extracted from the dynamic temperature field data; monitoring uniformity indexes of the real thermal expansion deformation field, and judging whether the uniformity indexes exceed a preset threshold value to adjust the dynamic correction coefficient and the material mechanical parameters online.

[0007] Optionally, the generating of the temperature-deformation multi-source data set comprises: measuring the measured material by using a fast scanning infrared thermal imager or a distributed multi-point micro temperature sensor array to generate high spatial resolution temperature distribution data; measuring the surface of the measured material by using a digital image correlation method or a laser speckle interference method to generate full-field deformation data; and synchronously integrating the high spatial resolution temperature distribution data and the full-field deformation data to generate the temperature-deformation multi-source data set.

[0008] Optionally, the generating of the dynamic temperature field data comprises: establishing three-dimensional geometric information of the measured material, and taking the high spatial resolution temperature distribution data as a boundary condition to generate three-dimensional boundary temperature data; and solving a non-steady-state heat conduction equation inside the material based on the three-dimensional boundary temperature data to generate the dynamic temperature field data.

[0009] Optionally, the generating of the interference deformation data comprises: calculating a theoretical thermal stress distribution based on the dynamic temperature field data and the material mechanical parameters to generate theoretical thermal stress data; and calculating mechanical strain and performing integral processing based on the theoretical thermal stress data to generate the interference deformation data.

[0010] Optionally, the calculating of the mechanical strain and the integral processing comprises: calculating a mechanical strain tensor based on the theoretical thermal stress data by using an elastic modulus and a Poisson's ratio of the material according to a linear elastic theory to generate mechanical strain data; and performing numerical integration on the mechanical strain data in a three-dimensional geometric domain of the material to generate the interference deformation data.

[0011] Optionally, the real-time decoupling operation comprises: calculating the interference deformation data and the dynamic correction coefficient to generate corrected interference deformation data; and subtracting the corrected interference deformation data from the full-field deformation data to obtain the real thermal expansion deformation field.

[0012] Optionally, the calculating the thermal expansion coefficient comprises: extracting deformation values of the real thermal expansion deformation field at target regions or key points to generate thermal expansion deformation value data; extracting overall average temperature changes of the dynamic temperature field data at corresponding regions or key points to generate temperature change trend data; and calculating the thermal expansion coefficient according to a definition relationship of the thermal expansion coefficient based on the thermal expansion deformation value data and the temperature change trend data.

[0013] Optionally, the online adjustment of the dynamic correction coefficient and the material mechanics parameter comprises: calculating a displacement gradient standard deviation of the real thermal expansion deformation field to generate a uniformity index; adjusting the dynamic correction coefficient to generate an updated dynamic correction coefficient when the uniformity index exceeds a preset threshold; and optimizing an elastic modulus parameter in the material mechanics parameter when it is detected that the real thermal expansion deformation field has a displacement discontinuous region.

[0014] Optionally, the optimization of the elastic modulus parameter in the material mechanics parameter comprises: inversely calculating an optimized elastic modulus parameter according to a displacement gradient standard deviation minimization target; and recalculating the theoretical thermal stress distribution by using the optimized elastic modulus parameter to generate new interference deformation data.

[0015] Based on the same inventive concept, the application further provides a temperature difference-deformation decoupling system for in-situ monitoring of a thermal expansion coefficient, which comprises: a synchronous acquisition module configured to acquire high spatial resolution temperature distribution data of a surface or a key region of a measured material and simultaneously acquire full-field deformation data of the surface of the measured material to generate temperature-deformation multi-source data sets; a temperature field reconstruction module configured to perform three-dimensional reconstruction on the high spatial resolution temperature distribution data to generate dynamic temperature field data; an interference deformation module configured to calculate theoretical thermal stress caused by uneven temperature distribution based on the dynamic temperature field data and material mechanics parameters to generate interference deformation data; a real-time decoupling module configured to perform real-time decoupling operation on the full-field deformation data by using the interference deformation data to introduce a dynamic correction coefficient to obtain a real thermal expansion deformation field; a thermal expansion coefficient calculation module configured to calculate a thermal expansion coefficient based on the real thermal expansion deformation field and temperature change trend data extracted from the dynamic temperature field data; and a collaborative optimization module configured to monitor a uniformity index of the real thermal expansion deformation field, judge whether the uniformity index exceeds a preset threshold, and online adjust the dynamic correction coefficient and the material mechanics parameter.

[0016] Compared with the prior art, the application has the following advantages: The present application separates the pure real thermal expansion deformation by actively identifying, calculating and decoupling the thermal stress interference deformation caused by non-uniform temperature from the total measured deformation, thereby separating the pure real thermal expansion deformation. The method fundamentally eliminates the main error source faced by the traditional technology under non-uniform thermal working conditions, and significantly improves the accuracy and reliability of the thermal expansion coefficient measurement.

[0017] The present application uses full-field synchronous measurement technology to obtain temperature and deformation data, and can continuously monitor the thermal expansion coefficient during the entire heating or cooling process. This provides the dynamic relationship of the thermal expansion coefficient with temperature, compared with the traditional method which can only give the average value in a wide temperature range, the present method realizes more comprehensive material performance characterization and has the ability to evaluate the material in real time in situ.

[0018] The present application integrates a closed-loop feedback and optimization mechanism, which can adjust and correct the coefficient online or optimize the core material mechanics parameters by monitoring the rationality of the decoupled physical field. This self-correcting ability makes the system have strong adaptability and robustness to the uncertainty of the initial model parameters, ensuring stable and accurate measurement results under changing test conditions.

[0019] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and obtained by the structure indicated in the specification, claims and drawings. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0021] Figure 1 is a flowchart of a temperature difference-deformation decoupling method for in-situ monitoring of thermal expansion coefficient according to an embodiment of the present application.

[0022] Figure 2 is a three-dimensional distribution diagram of real thermal expansion deformation field according to an embodiment of the present application.

[0023] Figure 3 is a diagram of the relationship between thermal expansion coefficient and temperature according to an embodiment of the present application.

[0024] Figure 4 is a schematic diagram of adaptive adjustment of dynamic correction coefficient according to an embodiment of the present application.

[0025] Figure 5is a structural schematic view of a temperature difference-deformation decoupling system for in-situ monitoring of thermal expansion coefficient according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0027] With reference to Figure 1 An embodiment of the present application provides a temperature difference-deformation decoupling method for in-situ monitoring of thermal expansion coefficient. The method adopts synchronous acquisition of temperature field and deformation field, theoretical calculation and elimination of thermal stress interference deformation caused by temperature difference, and a closed-loop feedback optimization mode, and can realize high-precision dynamic monitoring of the thermal expansion coefficient of a material under non-uniform temperature conditions.

[0028] The method according to the embodiment specifically comprises the following steps. acquire high spatial resolution temperature distribution data of a surface or a key region of a measured material, and synchronously acquire full-field deformation data of the surface of the measured material, to generate a temperature-deformation multi-source data set; perform three-dimensional reconstruction on the high spatial resolution temperature distribution data, to generate dynamic temperature field data; based on the dynamic temperature field data and material mechanics parameters, calculate theoretical thermal stress caused by uneven temperature distribution, to generate interference deformation data; perform real-time decoupling operation on the full-field deformation data by using the interference deformation data, introduce a dynamic correction coefficient, and obtain a real thermal expansion deformation field; based on the real thermal expansion deformation field and temperature variation trend data extracted from the dynamic temperature field data, calculate a thermal expansion coefficient; monitor a uniformity index of the real thermal expansion deformation field, judge whether the uniformity index exceeds a preset threshold, and adjust the dynamic correction coefficient and the material mechanics parameters online.

[0029] Specifically, by synchronously collecting the high-precision temperature field and the full-field deformation field on the surface of the measured material, a multi-source data set is constructed to accurately associate the thermal input and mechanical response in space and time. The core is a decoupling idea based on a physical model, that is, the total deformation measured in the experiment is considered as the linear superposition of the intrinsic thermal expansion deformation of the material and the internal thermal stress deformation caused by the non-uniform temperature distribution. The method reconstructs the measured surface temperature data into a three-dimensional dynamic temperature field, and uses it as a thermal load to perform thermal-mechanical coupling simulation combined with material mechanical parameters (mainly including the elastic modulus, Poisson's ratio and an initially estimated thermal expansion coefficient) to theoretically calculate the thermal stress deformation caused by temperature difference, that is, the interference deformation data. Then, the interference deformation field calibrated by the dynamic correction coefficient is subtracted from the total deformation field measured in the experiment, so as to separate the pure real thermal expansion deformation field. Finally, a closed-loop feedback mechanism is established to adjust the dynamic correction coefficient and the material mechanical parameters in reverse and online by monitoring the uniformity of the real thermal expansion deformation field, which is a physical characteristic, so that the decoupling model can adaptively approach the physical reality, thereby realizing the accurate calculation of the thermal expansion coefficient. The present application can realize in-situ, dynamic and high-precision monitoring of the thermal expansion coefficient of the material. By actively calculating and stripping the thermal stress deformation caused by the temperature gradient, which is the core interference term, the method fundamentally overcomes the systematic errors existing in the traditional measurement method under the condition of non-uniform temperature field, greatly improving the accuracy and reliability of the measurement results. The full-field measurement characteristic can capture the overall behavior of the material rather than the local response, and the closed-loop design of dynamic correction and online optimization endows the system with strong adaptive ability and robustness, so that it can effectively cope with uncertain factors such as inaccurate model parameters.

[0030] Optionally, the generating of the temperature-deformation multi-source data set comprises: measuring the measured material by using a fast scanning infrared thermal imager or a distributed multi-point micro temperature sensor array to generate high spatial resolution temperature distribution data; measuring the surface of the measured material by using a digital image correlation method or a laser speckle interference method to generate full-field deformation data; synchronously integrating the high spatial resolution temperature distribution data and the full-field deformation data to generate a temperature-deformation multi-source data set.

[0031] Specifically, first, the surface temperature and deformation of the measured material are synchronously measured. In terms of temperature data acquisition, a fast scanning infrared thermal imager can be used to face the surface of the measured material, and through non-contact measurement, the thermal radiation intensity of the material surface can be captured in real time and converted into a two-dimensional temperature distribution map. To ensure data accuracy, the fast scanning infrared thermal imager needs to have high refresh rate and high pixel resolution, thereby generating a series of high spatial resolution temperature distribution data that are continuous in time and fine in space. Alternatively, a distributed multi-point miniature temperature sensor array, such as a miniature thermocouple or fiber grating sensor array, can be arranged on the key areas of the surface of the measured material to directly contact and collect real-time temperature values of multiple points, also forming high spatial resolution temperature distribution data. In terms of deformation data acquisition, the digital image correlation method is synchronously used. This method needs to prepare a random speckle pattern on the surface of the measured material in advance, and a high-resolution camera is used to continuously shoot a series of digital images during the deformation of the material under heat. By comparing and analyzing the displacement and changes of the same sub-regions in images at different times, the digital image correlation algorithm is used to calculate the displacement vector field of all points in the entire field of view, thereby generating full-field deformation data. This full-field deformation data completely describes the displacement of each point on the material surface during heating. To effectively integrate the data, the temperature acquisition system and the deformation acquisition system must be controlled by a synchronous trigger device to ensure that each frame of temperature distribution map and each frame of deformation field are strictly aligned in time. Finally, these high spatial resolution temperature distribution data and full-field deformation data with the same time stamp are paired and integrated to form a time series data set, each data point of which contains surface temperature field and deformation field information at a specific time, and finally constitutes the temperature-deformation multi-source data set necessary for subsequent decoupling analysis. This technical solution synchronously acquires high spatial resolution temperature field and full-field deformation data, and constructs an integrated data set that accurately associates heat input and mechanical response in time and space, providing an indispensable high-fidelity input for subsequent precise separation of thermal expansion deformation and thermal stress deformation, thereby significantly improving the accuracy and reliability of in-situ monitoring of thermal expansion coefficient.

[0032] Optionally, the generating dynamic temperature field data comprises: establishing three-dimensional geometric information of the measured material, and generating three-dimensional boundary temperature data by taking the high spatial resolution temperature distribution data as a boundary condition; solving a non-steady-state heat conduction equation inside the material based on the three-dimensional boundary temperature data to generate dynamic temperature field data.

[0033] Specifically, first, the precise three-dimensional geometric information of the measured material is established. This can be directly constructed by computer-aided design software, or the actual measured material is reverse engineered using three-dimensional laser scanning technology to obtain its complete three-dimensional digital model. Subsequently, the high spatial resolution temperature distribution data obtained in the previous step is used as the boundary condition for thermal analysis. The specific operation is to accurately assign the corresponding outer surface of the three-dimensional geometric model with the two-dimensional surface temperature field map collected synchronously through coordinate mapping algorithm, forming the three-dimensional boundary temperature data varying with time. For the surfaces not directly measured, the boundary conditions can be set as adiabatic or convective heat exchange with the environment according to the actual situation. Based on this three-dimensional boundary temperature data, the internal temperature field is reconstructed by solving the non-steady-state heat conduction equation inside the material, which is the basic physical law describing the propagation of heat in the medium. Its mathematical expression is as follows: , In the equation, represents the temperature field varying with spatial position and time , i.e. the dynamic temperature field data to be solved; is the density of the measured material, is the specific heat capacity of the material, is the thermal conductivity of the material, and the three are inherent physical parameters of the material, which can be obtained by consulting the material manual or experimental measurement; represents the divergence operator, represents the gradient operator. This partial differential equation is usually solved by numerical methods such as finite element method. First, the three-dimensional geometric information is meshed, and then the three-dimensional boundary temperature data is applied to the surface nodes of the model. At each time step, the temperature values of all nodes inside the model at the corresponding time are calculated by iterative solution. By repeating this calculation process on the entire time sequence of the temperature-deformation multi-source data set, a series of three-dimensional data describing the evolution of the complete temperature distribution inside the material with time is obtained, i.e. the final dynamic temperature field data. This technical solution successfully expands the two-dimensional surface temperature information measured by non-contact measurement to the three-dimensional temperature field inside the entire material by establishing a three-dimensional geometric model and solving the non-steady-state heat conduction equation, overcoming the limitation that the internal temperature gradient information cannot be obtained by surface measurement, so as to accurately grasp the temperature change history and spatial distribution of any point inside the material during the heating process.

[0034] Optionally, the generating interference deformation data comprises: calculating the theoretical thermal stress distribution based on the dynamic temperature field data and the material mechanical parameters, and generating theoretical thermal stress data; calculating the mechanical strain and performing integral processing based on the theoretical thermal stress data, and generating interference deformation data.

[0035] Specifically, to generate the interference deformation data, the method first performs a thermal-mechanical coupling analysis based on the generated dynamic temperature field data and pre-determined or set material mechanical parameters to calculate a theoretical thermal stress distribution. The material mechanical parameters mainly include an elastic modulus , a Poisson's ratio , and an initial estimated thermal expansion coefficient . The calculation process is usually implemented by means of finite element analysis software. The dynamic temperature field data is applied to a three-dimensional geometric model of the measured material at a specific time point as a thermal load. Due to the uneven temperature distribution inside the material, different parts produce different free thermal expansion tendencies, and this incoordination will cause mutual constraints inside the material, thereby generating internal stress, i.e., the theoretical thermal stress. According to the thermal elastic-plastic mechanics theory, the software solves the equilibrium equation under the given temperature field and mechanical boundary conditions, and outputs the stress tensor distribution in the entire three-dimensional model, which is the theoretical thermal stress data. After obtaining the theoretical thermal stress data, the mechanical strain is calculated and integrated. The mechanical strain is the elastic or plastic strain caused by the theoretical thermal stress, which is distinguished from the thermal expansion strain directly caused by the temperature change. According to the generalized Hooke's law, the corresponding mechanical strain tensor can be calculated from the theoretical thermal stress data. Finally, the mechanical strain field is spatially integrated in the entire three-dimensional geometric domain of the material, and the displacement field determined by the strain field is obtained. This displacement field completely describes the structural shape change caused by the internal stress due to uneven temperature, which is not the intrinsic thermal expansion behavior of the material, but a deformation component that interferes with it, and therefore is defined as the interference deformation data. By introducing the finite element simulation based on the physical model, the internal thermal stress and the deformation caused by it, which cannot be directly measured, are quantitatively calculated, the interference part caused by the uneven temperature distribution in the total deformation of the measured material is separated, and the interference deformation data that can be used for subsequent decoupling operation is generated. This lays a key physical foundation for accurately extracting the real and pure thermal expansion information from the complex mixed deformation signal, greatly improves the pertinence and effectiveness of the subsequent decoupling operation, and thus ensures that the finally calculated thermal expansion coefficient can more truly reflect the intrinsic physical properties of the material.

[0036] Optionally, the calculating the mechanical strain and performing the integration processing comprises: based on the theoretical thermal stress data, calculating a mechanical strain tensor according to the linear elastic theory by using the elastic modulus and the Poisson's ratio of the material, to generate mechanical strain data; performing numerical integration on the mechanical strain data in the three-dimensional geometric domain of the material, to generate the interference deformation data.

[0037] Specifically, to realize the conversion from the theoretical thermal stress data to the interference deformation data, firstly, the mechanical strain tensor caused by the theoretical thermal stress needs to be calculated based on the linear elastic theory. This process utilizes the elastic modulus and Poisson's ratio of the material, which are inherent mechanical properties of the material and can be obtained by experiments or consulting standard material databases. For a three-dimensional isotropic material, the relationship between the mechanical strain components and the theoretical thermal stress components follows the generalized Hooke's law, and the specific calculation expression is: , , , , , , wherein , , are the normal mechanical strain components along the coordinate axis directions; , , are the shear mechanical strain components; , , are the normal stress components extracted from the theoretical thermal stress data; , , are the corresponding shear stress components. is the shear modulus of the material, and the relationship between the shear modulus and the elastic modulus and Poisson's ratio is Theoretical thermal stress data is substituted into the above formula at stress components of each point or each unit in the three-dimensional model, so that the mechanical strain distribution in the entire model can be calculated, and the mechanical strain data is generated. Then, numerical integration of the mechanical strain data in the three-dimensional geometric domain of the material is required to solve the displacement field caused thereby. In continuum mechanics, displacement and strain are related through geometric equations, and solving the displacement field is to solve the differential equation set. This integration process is usually completed in finite element analysis software, which calculates the mechanical strain data and applies appropriate displacement constraint conditions to prevent the model from producing rigid body displacement, and finally obtains a displacement field with the same format and dimension as the full-field deformation data by solving the node displacement in the entire three-dimensional geometric domain. The displacement field is the interference deformation data. The technical scheme clearly applies linear elastic theory and numerical integration to provide a rigorous and operable calculation path for the conversion from theoretical thermal stress to interference deformation. It accurately converts an abstract internal force field, i.e. theoretical thermal stress, into a physical quantity, i.e. deformation field, which can be directly compared with experimental measurement.

[0038] Optionally, the real-time decoupling operation includes: calculating the interference deformation data and the dynamic correction coefficient to generate corrected interference deformation data; subtracting the corrected interference deformation data from the full-field deformation data to obtain a real thermal expansion deformation field.

[0039] Specifically, the experimentally measured full-field deformation data is decomposed into a real thermal expansion deformation and an interference deformation caused by temperature difference. The basis of this operation is that the total deformation is a linear superposition of the two components. First, since there may be deviations between the theoretical model and the actual physical process, for example, the material mechanics parameters used are not completely accurate, directly subtracting the theoretically calculated interference deformation data from the full-field deformation data will introduce errors. Therefore, a dynamic correction coefficient is introduced to calibrate the theoretical calculation results. The dynamic correction coefficient is mainly used to comprehensively compensate for the deviations between the theoretical calculation and the physical reality caused by factors such as temperature dependence of material mechanics parameters, model simplification, and measurement system errors, so as to improve the adaptability and accuracy of the decoupling model. The operation process is as follows: first, multiply the theoretically calculated interference deformation data by an initially set or real-time updated dynamic correction coefficient to generate corrected interference deformation data. This correction process bridges the gap between the theoretical model and the physical reality. Then, the full-field deformation data and the corrected interference deformation data are subtracted point by point in space. This operation is mathematically expressed as: , In this expression, is the displacement of the measured material surface at any point and time The true thermal expansion deformation field is the final output of this operation; It is the full-field deformation data obtained synchronously through experimental means such as digital image correlation method, representing the total displacement vector of the point; It is the interference deformation data calculated based on dynamic temperature field data and material mechanical parameters, representing the displacement vector caused by thermal stress; It is a dynamic correction coefficient that changes with time. It is a dimensionless scalar. Its initial value can be set to 1 and adjusted online in the subsequent steps according to the feedback of the decoupling results. This subtraction operation is performed synchronously on all data points in the entire measured field of view, thereby decomposing the experimentally measured mixed deformation field in real time, and finally obtaining a pure real thermal expansion deformation field caused only by the intrinsic thermal expansion effect of the material. Figure 2 As shown, the three-dimensional diagram is Coordinates and Coordinates are spatial references, The axis represents the displacement, and the grayscale color mapping intuitively shows the real thermal expansion deformation field obtained after the decoupling operation. This adaptive decoupling strategy can effectively compensate for systematic errors caused by inaccurate material parameters or simplified models, making the true thermal expansion deformation field separated from the complex measured deformation more accurate and reliable, greatly improving the accuracy and robustness of the final in-situ monitoring of the thermal expansion coefficient.

[0040] Optionally, the calculating the thermal expansion coefficient includes: Extracting the deformation of the real thermal expansion deformation field in the target area or key point to generate thermal expansion deformation data; Extracting the overall average temperature change of the dynamic temperature field data in the corresponding area or key point to generate temperature change trend data; Based on the thermal expansion deformation data and the temperature change trend data, the thermal expansion coefficient is calculated according to the definition relationship of the thermal expansion coefficient.

[0041] Specifically, to calculate the thermal expansion coefficient, this method uses the real thermal expansion deformation field and the reconstructed dynamic temperature field data that have been decoupled in the previous step. First, it is necessary to extract quantitative thermal expansion deformation data from the real thermal expansion deformation field. This operation can be performed in a predefined target area on the surface of the material being tested or between two key points along a specific direction. For example, a line with an initial length of The line segment is used as the measurement reference. By querying the displacement vectors of the two end points of the line segment at different times in the real thermal expansion deformation field, the length change of the line segment in a certain direction is calculated. This is the thermal expansion deformation data. Next, the corresponding temperature change needs to be extracted in the same time and space dimension. Specifically, the temperature value of the target region or key point is extracted from the dynamic temperature field data, and the overall average temperature change in the corresponding time period is calculated to generate temperature change trend data Finally, based on the two interrelated data sets, i.e. thermal expansion deformation variable data and temperature change trend data, the thermal expansion coefficient is calculated according to the physical definition relationship of the linear thermal expansion coefficient. The calculation formula is: , In the formula, is the thermal expansion coefficient to be solved; is the length change occurring in a specific time period extracted from the real thermal expansion deformation field, i.e. thermal expansion deformation variable data; is the initial length between the selected target region or key point at the initial reference temperature, which is a known geometric quantity; is the average temperature change occurring in the same time period and the same spatial position extracted from the dynamic temperature field data, i.e. temperature change trend data. By repeating this calculation in different temperature intervals, the relationship curve of the thermal expansion coefficient with temperature change can be obtained. As shown in Figure 3 , the graph takes temperature change as the horizontal coordinate and thermal expansion coefficient as the vertical coordinate, and the calculated value and the real value are represented by scatter plots and dashed lines, respectively, reflecting the dynamic change law of the material thermal expansion coefficient in different temperature intervals. The technical solution fundamentally eliminates the interference of deformation caused by thermal stress on the calculation result by establishing the calculation on the basis of the real thermal expansion deformation field which has been accurately decoupled, ensuring that the deformation variable used for calculation is purely caused by thermal expansion. At the same time, the method emphasizes the strict correspondence in space between the deformation measurement region and the temperature measurement region, ensuring the physical authenticity of the causal chain.

[0042] Optionally, the online adjustment of the dynamic correction coefficient and the material mechanics parameter includes: calculating the displacement gradient standard deviation of the real thermal expansion deformation field to generate a uniformity index; when the uniformity index exceeds a preset threshold, adjusting the dynamic correction coefficient to generate an updated dynamic correction coefficient; when it is detected that the real thermal expansion deformation field has a displacement discontinuity region, optimizing the elastic modulus parameter in the material mechanics parameter.

[0043] Specifically, to realize online adjustment of the dynamic correction coefficient, the method establishes a closed-loop feedback control mechanism based on the quality of decoupling results. The core idea is that ideal pure thermal expansion should result in a uniform deformation field. Therefore, the uniformity of the real thermal expansion deformation field obtained after decoupling can be used as an index to evaluate the decoupling effect. First, the standard deviation of the displacement gradient of the real thermal expansion deformation field is calculated as the uniformity index. The specific operation is to perform spatial derivation on the real thermal expansion deformation field obtained in the previous step in the entire measurement area to obtain a displacement gradient field, which corresponds to a pure thermal expansion strain field in physics. Then, the standard deviation of all data points in the gradient field is calculated. A uniform deformation field should have a constant displacement gradient, and the standard deviation should be close to zero. Therefore, the smaller the standard deviation value, the better the uniformity of the real thermal expansion deformation field, and the more ideal the decoupling effect. This standard deviation is defined as the uniformity index. Second, the uniformity index is compared with a preset threshold. The setting of the preset threshold includes the signal-to-noise ratio of the measurement system . Specifically, the threshold is usually set to be about 3 times the displacement resolution of the measurement system, i.e. , to ensure that when the uniformity index exceeds the threshold, the indicated deformation non-uniformity has significant statistical significance rather than measurement noise. The displacement resolution can be determined by a calibration experiment of a digital image correlation system or a laser speckle interferometry system. If the index is lower than the threshold, it indicates that the current dynamic correction coefficient is appropriate, and the decoupling operation is successful. If the uniformity index exceeds the preset threshold, it indicates that the decoupling is insufficient, and there is still a non-uniform deformation component caused by thermal stress in the real thermal expansion deformation field, which usually means that the calculated interference deformation data is underestimated. At this time, the system will automatically adjust the dynamic correction coefficient to generate an updated dynamic correction coefficient. The adjustment adopts a proportional adjustment strategy, i.e. the adjustment amount of the dynamic correction coefficient is proportional to the degree to which the current uniformity index exceeds the preset threshold. The specific adjustment rule can be expressed as: , wherein is a proportional coefficient , the value of which affects the speed and stability of the adjustment, and the basic value (0.1-0.5) is determined by pre-experiment, the upper limit is taken for high thermal conductivity materials to accelerate convergence, and the lower limit is taken for high noise systems to ensure stability. The updated dynamic correction coefficient is: , wherein is the original dynamic correction coefficient. This updated coefficient will be used in the real-time decoupling operation of the next time step. Figure 4 As shown in the figure, the closed-loop adaptive adjustment rule of the dynamic correction coefficient of the present invention is reflected. The horizontal axis in the figure is the number of iterations, and the left vertical axis is the uniformity index. , the right vertical axis is the dynamic correction coefficient The curve shows that the uniformity index gradually decreases and stabilizes under feedback regulation, and the dynamic correction coefficient is adjusted proportionally based on the degree to which the uniformity index exceeds the threshold until the system converges to the optimal decoupling state. In addition, the system also monitors the presence of displacement discontinuities in the actual thermal expansion deformation field, that is, local areas where the displacement gradient changes suddenly.

[0044] This discontinuity is a purely thermal expansion behavior that is not physically realistic. It strongly indicates that the material mechanical parameters used in the theoretical model, especially the elastic modulus, may deviate significantly from the actual situation. When such a displacement discontinuity is detected, the system will suspend the adjustment of the dynamic correction coefficient and trigger the optimization procedure for the elastic modulus parameters. The detection of the displacement discontinuity is achieved by the following algorithm: Calculate the displacement gradient value between each adjacent pixel in the real thermal expansion deformation field ,in Indicates the The displacement of pixels, Indicates the displacement of its adjacent pixels, is the absolute value of the displacement gradient between two points; The pixel area is a sliding window, and all displacement gradient values ​​in each window are calculated Standard deviation , which represents the fluctuation intensity of the local deformation field; and the global displacement gradient standard deviation (obtained by calculating the entire deformation field) for comparison, when Mark as abnormal window ( The threshold is set based on the statistical principles of normal distribution. Consecutive abnormal windows are detected in the spatial domain. If three or more abnormal windows appear continuously along the normal or tangential direction of the material surface, a displacement discontinuity region is determined, triggering elastic modulus optimization. By introducing a uniformity index and a closed-loop feedback mechanism, this technical solution transforms the entire decoupling process from an open-loop, one-way calculation process to an intelligent system capable of self-assessment and self-correction. This system can identify and trigger corrections to core physical model parameters, fundamentally improving the robustness of the entire in-situ monitoring system and the reliability of the final measurement results.

[0045] Optionally, the optimizing the elastic modulus parameter in the material mechanical parameters includes: According to the objective of minimizing the standard deviation of the displacement gradient, the elastic modulus parameters are inversely calculated to generate the optimized elastic modulus parameters; The theoretical thermal stress distribution is recalculated using the optimized elastic modulus parameters to generate new interference deformation data.

[0046] Specifically, in order to achieve the optimization of the elastic modulus parameters, this method converts the detected real thermal expansion deformation field inhomogeneity problem into an inverse optimization problem with the goal of minimizing the standard deviation of the displacement gradient. This process is triggered when the real thermal expansion deformation field is detected to have a displacement discontinuity region. Its core is to iteratively adjust the elastic modulus parameters until the theoretical calculation and experimental observation are physically optimally matched. First, establish an objective function with the elastic modulus as the independent variable, and the value of this function is the standard deviation of the displacement gradient of the real thermal expansion deformation field. The optimization process can be expressed as seeking an optimal elastic modulus , so that the objective function Minimum, the formula is: , In this optimization problem, is the elastic modulus parameter to be optimized; is the objective function; Indicates taking the parameters that make the function reach the minimum value; is the standard deviation operator; is the spatial gradient operator; is the full-field deformation data measured experimentally; is the current dynamic correction coefficient; Represents the interference deformation data, which is the elastic modulus function, since the calculation of theoretical thermal stress and mechanical strain depends on The optimization process is implemented through an iterative loop. In each iteration, the system selects a trial elastic modulus parameter, re-executes the complete forward calculation from calculating the theoretical thermal stress to generating the interference deformation data. Then, the interference deformation data is used for decoupling to obtain a temporary real thermal expansion deformation field, and the standard deviation of its displacement gradient is calculated. According to the standard deviation value, the optimization algorithm, such as gradient descent method or particle swarm optimization algorithm, will give the next better trial elastic modulus parameter. This loop is repeated until the standard deviation of the displacement gradient converges to a minimum value or is lower than the set tolerance, at which time the obtained elastic modulus parameter is the optimized elastic modulus parameter. After obtaining the optimized parameter, the system will use the parameter value to fixedly recalculate the theoretical thermal stress distribution, and finally generate a new set of interference deformation data with higher accuracy for subsequent real-time decoupling monitoring. The technical solution introduces a reverse calculation and optimization mechanism, giving the entire monitoring system the ability of self-calibration and model correction. When simple dynamic coefficient adjustment is not enough to eliminate decoupling errors, this method can go deep into the root of the physical model and identify and optimize the core material mechanics parameters. This not only solves the systematic errors caused by inaccurate elastic modulus, but also enables the entire method to adapt to unknown or temperature-varying material properties.

[0047] Based on the same inventive concept, as shown in Figure 5 The present application also provides a temperature difference-deformation decoupling system for in-situ monitoring of thermal expansion coefficient, which comprises: A synchronous acquisition module is configured to acquire high spatial resolution temperature distribution data of a surface or a key area of a measured material, and to synchronously acquire full-field deformation data of the surface of the measured material, thereby generating a temperature-deformation multi-source data set; A temperature field reconstruction module is configured to perform three-dimensional reconstruction on the high spatial resolution temperature distribution data, thereby generating dynamic temperature field data; An interference deformation module is configured to calculate theoretical thermal stress caused by uneven temperature distribution based on the dynamic temperature field data and material mechanics parameters, thereby generating interference deformation data; A real-time decoupling module is configured to perform real-time decoupling operation on the full-field deformation data by using the interference deformation data, thereby introducing a dynamic correction coefficient to obtain a real thermal expansion deformation field; A thermal expansion coefficient calculation module is configured to calculate a thermal expansion coefficient based on the real thermal expansion deformation field and temperature change trend data extracted from the dynamic temperature field data; A cooperative optimization module is configured to monitor a uniformity index of the real thermal expansion deformation field, to determine whether the uniformity index exceeds a preset threshold, and to adjust the dynamic correction coefficient and the material mechanics parameters online.

[0048] In order to verify the effectiveness and superiority of the temperature difference-deformation decoupling method for in-situ monitoring of thermal expansion coefficient proposed in this invention, an in-situ monitoring experiment was conducted in a temperature-controlled thermal test chamber using an aerospace-grade high-temperature alloy plate specimen as the test object. The specimen size is In the experiment, one end of the specimen was locally heated to create a typical non-uniform temperature distribution and complex thermal stress field inside the specimen.

[0049] In this embodiment, the synchronous acquisition module uses a high-resolution fast scanning infrared thermal imager and a binocular digital image correlation ( ) system. The infrared thermal imager continuously captures the specimen surface at a frequency of 50 Hz, generating high-spatial-resolution temperature distribution data. The system simultaneously captures random speckle patterns pre-prepared on the specimen surface, generating full-field deformation data. An external synchronization trigger ensures strict temporal alignment of data acquisition between the two systems, forming a temperature-deformation multi-source dataset.

[0050] The temperature field reconstruction module first establishes three-dimensional geometric information that is completely consistent with the specimen, and uses the collected surface temperature data as boundary conditions. By solving the unsteady-state heat conduction equation, it generates dynamic temperature field data inside the entire specimen that evolves over time.

[0051] The interference deformation module is based on the dynamic temperature field data and uses the initial mechanical parameters (elastic modulus , Poisson's ratio ), the theoretical thermal stress caused by uneven temperature distribution was calculated using finite element analysis software, and the initial interference deformation data was generated through further integration processing.

[0052] In the initial stage of the experiment, the real-time decoupling module uses a dynamic correction coefficient with an initial value of 1.0 , the interference deformation data is subtracted from the full-field deformation data to obtain the preliminary true thermal expansion deformation field. However, the collaborative optimization module monitors that the uniformity index (displacement gradient standard deviation) of the deformation field is , significantly higher than The preset threshold was exceeded, and local discontinuities were found in the deformation field. This indicates that there is a deviation between the initial mechanical parameters and the actual conditions of the material at the current high temperature.

[0053] Accordingly, the synergistic optimization module triggers the optimization program of the elastic modulus parameter. With the minimization of the displacement gradient standard deviation of the real thermal expansion deformation field as the goal, the system iteratively adjusts the elastic modulus parameter through reverse calculation. After several iterations, the system determines the optimal elastic modulus as 195 GPa, and simultaneously optimizes the dynamic correction coefficient to 1.29. The interference deformation data is regenerated using the optimized parameters and decoupled, and the uniformity index of the final real thermal expansion deformation field is reduced to , which is much lower than the threshold value, and the discontinuous area in the field disappears.

[0054] Finally, the thermal expansion coefficient calculation module calculates the thermal expansion coefficient values in different temperature intervals based on the highly uniform real thermal expansion deformation field and the corresponding dynamic temperature field data. To verify the effect of the present application, the measurement results of the present application are compared with those of the traditional measurement method (i.e., without decoupling, directly calculating with total deformation and average temperature) and the standard reference value of the material.

[0055] Table 1 Comparison of thermal expansion coefficients (CTE) measured by different methods

[0056] Table 2 Synergistic optimization module online adjustment process data table

[0057] Table 3 Error analysis of measurement results of the present application and standard reference value

[0058] From the data in Tables 1, 2 and 3 above, it can be seen that the method of the present application has significant advantages in dealing with the problem of monitoring the thermal expansion coefficient under a non-uniform temperature field.

[0059] The data comparison in Table 1 clearly shows that the traditional method cannot separate the interference deformation caused by thermal stress, and the deviation of the measurement results from the standard reference value increases with increasing temperature, resulting in serious errors. However, the measurement results obtained by the present application through accurate decoupling and optimization are highly consistent with the standard reference value, proving that the present method can effectively eliminate systematic errors caused by temperature differences.

[0060] Table 2 details the online adjustment process of the synergistic optimization module. As can be seen from the data, by optimizing the elastic modulus and dynamic correction coefficient in reverse with the uniformity of the real thermal expansion deformation field as the goal, the uniformity index of the system converges to an ideal state much lower than the threshold value after a few iterations. This fully demonstrates the strong adaptive ability and model correction ability of the closed-loop feedback mechanism of the present application.

[0061] The error analysis of Table 3 further quantitatively proves the accuracy of the present application. The relative error of the measurement results of the present application is kept within 1% in the whole test temperature range, which meets the requirement of high-precision measurement. This indicates that the real thermal expansion deformation field obtained by the present application can highly reflect the intrinsic physical behavior of the material, thereby ensuring the accuracy and reliability of the finally calculated thermal expansion coefficient.

[0062] It should be noted that the electrical connection between the above-mentioned various units does not necessarily mean the direct connection of the line, and the indirect connection mode can also be applied to the embodiments of the present application as long as the purpose of the present application is achieved. The above-mentioned is only an exemplary embodiment of the present application, and cannot limit the scope of the present application.

[0063] That is, any equivalent changes and modifications made according to the teachings of the present application are still within the scope of the present application. Other embodiments of the present application will be readily apparent to those skilled in the art upon considering the description and the disclosure of the true principles of the present application. The present application is intended to cover any variations, uses or adaptive changes of the present application following the general principles of the present application and including common knowledge or conventional technical means in the art not disclosed by the present application.

Claims

1. A method for decoupling temperature difference and deformation for in-situ monitoring of coefficient of thermal expansion, characterized in that, The method comprises: acquiring high spatial resolution temperature distribution data of a surface or a key area of a measured material, and synchronously collecting full-field deformation data of the surface of the measured material to generate a temperature-deformation multi-source data set; reconstructing the high spatial resolution temperature distribution data in three dimensions to generate dynamic temperature field data; calculating theoretical thermal stress caused by uneven temperature distribution based on the dynamic temperature field data and material mechanics parameters to generate interference deformation data; performing real-time decoupling operation on the full-field deformation data by using the interference deformation data, introducing a dynamic correction coefficient, and obtaining a real thermal expansion deformation field; calculating a thermal expansion coefficient based on the real thermal expansion deformation field and temperature change trend data extracted from the dynamic temperature field data; monitoring uniformity indexes of the real thermal expansion deformation field, judging whether the uniformity indexes exceed a preset threshold, and adjusting the dynamic correction coefficient and the material mechanics parameters online.

2. The method of claim 1, wherein, The generation of the temperature-deformation multi-source data set comprises: measuring the measured material by using a fast scanning infrared thermal imager or a distributed multi-point micro temperature sensor array to generate high spatial resolution temperature distribution data; measuring the surface of the measured material by using a digital image correlation method or a laser speckle interference method to generate full-field deformation data; synchronously integrating the high spatial resolution temperature distribution data and the full-field deformation data to generate a temperature-deformation multi-source data set.

3. The method of claim 2, wherein the method further comprises, The generation of the dynamic temperature field data comprises: establishing three-dimensional geometric information of the measured material, and taking the high spatial resolution temperature distribution data as a boundary condition to generate three-dimensional boundary temperature data; solving a non-steady-state heat conduction equation inside the material based on the three-dimensional boundary temperature data to generate dynamic temperature field data.

4. The method of claim 3, wherein the method further comprises, The generation of the interference deformation data comprises: calculating a theoretical thermal stress distribution based on the dynamic temperature field data and the material mechanics parameters to generate theoretical thermal stress data; calculating mechanical strain and performing integral processing based on the theoretical thermal stress data to generate interference deformation data.

5. The method of claim 4, wherein the method further comprises, The calculation of mechanical strain and the integral processing comprise: calculating a mechanical strain tensor based on the theoretical thermal stress data by using the elastic modulus and Poisson's ratio of the material according to the linear elastic theory to generate mechanical strain data; performing numerical integration on the mechanical strain data in the three-dimensional geometric domain of the material to generate interference deformation data.

6. The method of claim 4, wherein, The real-time decoupling operation comprises: calculating the interference deformation data and the dynamic correction coefficient to generate corrected interference deformation data; subtracting the corrected interference deformation data from the full-field deformation data to obtain a real thermal expansion deformation field.

7. The method of claim 6, wherein the method further comprises, The calculation of the thermal expansion coefficient comprises: extracting deformation variables of the real thermal expansion deformation field in a target area or key points to generate thermal expansion variable data; extracting overall average temperature changes of the dynamic temperature field data in corresponding areas or key points to generate temperature change trend data; calculating a thermal expansion coefficient based on the thermal expansion variable data and the temperature change trend data according to a definition relationship of the thermal expansion coefficient.

8. The method of claim 7, wherein the method further comprises, The online adjustment of the dynamic correction coefficient and the material mechanics parameters comprises: a displacement gradient standard deviation of the real thermal expansion deformation field is calculated to generate a uniformity index; when the uniformity index exceeds a preset threshold, the dynamic correction coefficient is adjusted to generate an updated dynamic correction coefficient; when a displacement discontinuity region is detected in the real thermal expansion deformation field, an elastic modulus parameter in the material mechanics parameters is optimized.

9. The method of claim 8, wherein the method further comprises, The optimization of the elastic modulus parameter in the material mechanics parameters includes: an elastic modulus parameter is reversely calculated according to a displacement gradient standard deviation minimization target to generate an optimized elastic modulus parameter; the theoretical thermal stress distribution is recalculated by using the optimized elastic modulus parameter to generate new interference deformation data.

10. A temperature difference-deformation decoupling system for in-situ monitoring of thermal expansion coefficient, applied to the in-situ monitoring of thermal expansion coefficient of any one of claims 1-9, characterized in that, The system includes: a synchronous acquisition module configured to acquire high spatial resolution temperature distribution data of a surface or a key region of a measured material and to synchronously acquire full-field deformation data of the surface of the measured material to generate a temperature-deformation multi-source data set; a temperature field reconstruction module configured to perform three-dimensional reconstruction on the high spatial resolution temperature distribution data to generate dynamic temperature field data; an interference deformation module configured to calculate theoretical thermal stress caused by temperature distribution unevenness based on the dynamic temperature field data and material mechanics parameters to generate interference deformation data; a real-time decoupling module configured to perform real-time decoupling operation on the full-field deformation data by using the interference deformation data, to introduce a dynamic correction coefficient, and to obtain a real thermal expansion deformation field; a thermal expansion coefficient calculation module configured to calculate a thermal expansion coefficient based on the real thermal expansion deformation field and temperature variation trend data extracted from the dynamic temperature field data; a collaborative optimization module configured to monitor a uniformity index of the real thermal expansion deformation field, to determine whether the uniformity index exceeds a preset threshold, and to adjust the dynamic correction coefficient and the material mechanics parameters online.

Images