A planar temperature field reconstruction method for composite material curing process

Abstract

This invention discloses a planar temperature field reconstruction method for the curing process of composite materials. The method includes: obtaining transient non-uniform temperature field information of the composite material plate during the curing process through numerical simulation; analyzing the planar temperature field distribution law along the thickness direction of the composite material plate at the temperature peak moment; extracting the coordinates of feature points in the planar temperature field based on this law; collecting measured temperature information of the feature points of the composite material plate during the curing process; and reconstructing the planar temperature field of the composite material plate during the curing process based on the measured temperature information of the feature points using spline interpolation. The beneficial effects of this invention are: by reconstructing the measured temperature information obtained from monitoring using spline interpolation, this invention achieves the reconstruction of the planar temperature field under sparse monitoring samples, while improving the accuracy and efficiency of temperature field reconstruction.

Description

Technical Field

[0001] This invention relates to temperature field reconstruction technology, specifically to a planar temperature field reconstruction method for the curing process of composite materials. Background Technology

[0002] Carbon fiber composites possess advantages such as light weight, high strength, high stiffness, and excellent fatigue resistance, and are widely used in automotive A and B pillars, aircraft doors and wings, and the housings of electromechanical equipment. The curing process of composite materials largely determines the performance of the material after molding. The curing process mainly refers to the process by which the resin changes from a liquid to a solid state and combines with the fibers under the action of a specific temperature. This process involves the coupling of multiple physical fields, such as thermo-chemical fields and stress-strain fields.

[0003] Temperature is a crucial factor to monitor during the curing process of composite materials. Accurate temperature monitoring can effectively improve the molding quality of the composite material and prevent curing deformation or other defects. Currently, fiber Bragg grating (FBG) sensors are commonly used to monitor the temperature during the curing process. FBG sensors offer advantages such as simple structure, resistance to electromagnetic interference, good compatibility with the resin matrix, ease of forming distributed monitoring networks, and embedded detection, making them effective for monitoring temperature data during the composite material curing process.

[0004] However, in practical applications, due to the inherent limitations of curing devices such as autoclaves, the limited number of channels in fiber optic demodulators, and the limited space for sensor placement, it is impossible to use a large number of FBG sensors at the same time to obtain enough point information, thus failing to accurately reflect the planar temperature field information.

[0005] Currently, temperature monitoring during the curing process of carbon fiber composites is achieved by using fiber optic grating sensors to monitor information at specific points, with very little research on monitoring the entire planar temperature field. Furthermore, temperature field reconstruction studies often focus on metals or objects with relatively simple temperature field distributions. However, the presence of nonlinear internal heat sources during the curing process of composite materials leads to a more complex and non-uniform temperature field, resulting in poor accuracy of the temperature fields obtained using existing technologies. Therefore, finding a method to achieve high-precision reconstruction of the planar temperature field during the curing process of carbon fiber composites is a problem that needs to be solved. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of existing technologies by providing a planar temperature field reconstruction method for the curing process of composite materials, aiming to improve the accuracy of temperature field reconstruction.

[0007] The technical solution adopted in this invention is: a planar temperature field reconstruction method for the curing process of composite materials, the method comprising:

[0008] The transient non-uniform temperature field information of the composite material plate curing process is obtained by numerical simulation. The distribution law of the planar temperature field in the thickness direction of the composite material plate at the temperature peak moment is analyzed, and the coordinates of the feature points in the planar temperature field are extracted based on the law.

[0009] Collect measured temperature information at characteristic points of the composite material plate during the curing process;

[0010] Based on the measured temperature information of characteristic points, the planar temperature field of the curing process of composite material plates is reconstructed using spline interpolation.

[0011] According to the above scheme, the planar temperature field along the thickness direction of the composite material plate at the temperature peak moment refers to the planar temperature field along the thickness direction of the composite material plate when the temperature at a point inside the composite material plate reaches its maximum value during the external heating process.

[0012] According to the above scheme, the distribution law of the planar temperature field is as follows: the planar temperature field is uniformly divided into multiple temperature intervals along the thickness direction. There is a temperature change starting point on each temperature interval boundary line parallel to the X-axis. The temperature values ​​of all points on the left boundary line of the temperature change starting point are the same and are the same as the temperature value corresponding to the leftmost point of the boundary line. The temperature values ​​of all points on the right boundary line of the temperature change starting point follow the same decreasing change law.

[0013] According to the above scheme, a fiber optic grating monitoring system is used to obtain the measured temperature information of characteristic points of the composite material board during the curing process.

[0014] According to the above scheme, the fiber optic grating monitoring system includes a composite material plate, an autoclave, a fiber optic grating sensor, a coupler, a spectrometer, and a broadband light source.

[0015] The composite material plate is placed in a thermostatic jar, and the fiber optic grating sensor is mounted on the composite material plate. The grating area of ​​the fiber optic grating sensor corresponds to the feature point of the composite material plate.

[0016] The fiber optic grating sensor extends through a pre-drilled hole in the autoclave and is connected to a coupler outside the autoclave. The coupler is connected to a spectrometer and a broadband light source, respectively.

[0017] According to the above scheme, based on the measured temperature information of characteristic points, the method for reconstructing the planar temperature field of the composite material curing process using spline interpolation is as follows:

[0018] Step 1) Input the measured temperature information of the feature points within the reconstructed planar temperature field;

[0019] Step 2) Determine the starting point of temperature change at each boundary line;

[0020] Step 3) Based on the measured temperature information of the feature points, calculate the temperature values ​​of the leftmost and rightmost points of each boundary line in the plane temperature field.

[0021] Step 4) Obtain the temperature change curve to the left of the starting point of each boundary temperature change;

[0022] Step 5) Obtain the temperature change curve to the right of the starting point of temperature change at each boundary line;

[0023] Step 6) Draw a thermal map of the composite material plate based on the temperature change curves of each boundary line, thus completing the planar temperature field reconstruction during the curing process of the composite material.

[0024] According to the above scheme, the specific method of step 1) is as follows: take the lower left corner of the plane temperature field in the thickness direction of the composite material plate at the temperature peak obtained by numerical simulation as the origin, the long side as the X-axis direction and the short side as the Y-axis direction, discretize the plane temperature field into several points, and input the coordinates of the feature points and the measured temperature information corresponding to the feature points obtained in step 2.

[0025] According to the above scheme, the method for determining the starting point of temperature change at each boundary line is as follows: through numerical simulation, the interval of the X coordinate value of the starting point of temperature change at each boundary line of the plane temperature field is obtained, which is used as the range of coordinate values ​​of the temperature change point set during reconstruction; the starting point of temperature change is generated by a uniformly distributed random number function in MATLAB software.

[0026] According to the above scheme, step 3) is as follows: Select the starting point of temperature change on a certain boundary line as the feature point. The measured temperature value corresponding to the feature point is also the temperature value corresponding to the leftmost point on the boundary line. After determining the temperature values ​​of the leftmost points of several boundary lines, use spline interpolation to solve for the temperature values ​​of the leftmost points on other boundary lines. Select the point with the minimum temperature on a certain boundary line as the feature point. This feature point is also the rightmost point on the boundary line. After determining the temperature values ​​of the rightmost points of several boundary lines, use spline interpolation to solve for the temperature values ​​of the rightmost points on other boundary lines.

[0027] According to the above scheme, the method to obtain the temperature change curve to the left of the starting point of temperature change on each boundary line is as follows: extend the temperature value corresponding to the leftmost point on each boundary line of the plane temperature field to the starting point of temperature change in the positive X-axis direction. That is, the temperature values ​​of all points to the left of the starting point of temperature change on the same boundary line are the same and consistent with the temperature value corresponding to the point x=0 on the boundary line. Then, draw the temperature change curve to the left of the starting point of temperature change on each boundary line.

[0028] The method for obtaining the temperature change curve to the right of the starting point of temperature change at each boundary line is as follows: based on the temperature values ​​of the starting point and the rightmost point of temperature change at each boundary line, the temperature values ​​of the points to the right of the starting point of temperature change at each boundary line are calculated using spline interpolation, and then the temperature change curve to the right of the starting point of temperature change at each boundary line is drawn.

[0029] The beneficial effects of this invention are as follows: This invention obtains the coordinates of characteristic points by analyzing the temperature change law during the curing process of composite materials through numerical simulation; and detects the measured temperature values ​​of characteristic points during the curing process of composite materials. The measured temperature information obtained by monitoring is reconstructed by spline interpolation method, realizing the reconstruction of the planar temperature field under sparse monitoring samples. At the same time, it improves the accuracy and efficiency of temperature field reconstruction, reduces damage to composite materials, and solves the problem that the current monitoring samples for temperature information are too few to accurately reflect the planar temperature field information. Attached Figure Description

[0030] Figure 1 This is a flowchart illustrating a specific embodiment of the present invention.

[0031] Figure 2 This is a schematic diagram of the fiber Bragg grating monitoring system.

[0032] Figure 3 This is a schematic diagram of the composite material plate and the location of the planar temperature field in this embodiment.

[0033] Figure 4 This is a schematic diagram of the characteristic points in the planar temperature field in this embodiment.

[0034] Figure 5 This is a planar temperature field distribution cloud map along the thickness direction at the peak temperature moment during the curing process of the composite material obtained by numerical simulation in this embodiment.

[0035] Figure 6 The planar temperature field distribution cloud map was reconstructed for this embodiment.

[0036] Figure 7 This is a contour map showing the difference between the planar temperature field obtained from numerical simulation and the reconstructed planar temperature field in this embodiment.

[0037] Figure 3 In China: 1. Broadband light source; 2. Coupler; 3. Fiber Bragg grating sensor; 4. Fiber Bragg grating sensor grating area; 5. Composite material; 6. Autoclave; 7. Reserved hole; 8. Spectrometer. Detailed Implementation

[0038] To better understand the present invention, it will be further described below with reference to the accompanying drawings and specific embodiments.

[0039] like Figure 1 The method shown is a planar temperature field reconstruction method for the curing process of composite materials, specifically a planar temperature field reconstruction method for the curing process of carbon fiber composite materials. The method includes the following steps:

[0040] Step 1: Provide a composite material plate and obtain the transient non-uniform temperature field information of the composite material plate curing process through numerical simulation. Analyze the distribution law of the planar temperature field in the thickness direction of the composite material plate at the temperature peak moment. Based on this law, extract the coordinates of the feature points in the planar temperature field (that is, the planar temperature field in the thickness direction of the composite material plate at the temperature peak moment).

[0041] Step 2: Establish a fiber Bragg grating monitoring system for measuring temperature distribution. Place the fiber Bragg grating sensors of the monitoring system on the corresponding feature points of the composite material board and collect the measured temperature information of the feature points of the composite material board during the curing process.

[0042] Step 3: Based on the temperature field distribution law in the thickness direction at the temperature peak moment during the curing process of the composite material plate and the measured temperature information of the characteristic points, the planar temperature field of the curing process of the composite material plate is reconstructed using Matlab software based on spline interpolation.

[0043] The composite material plate is placed entirely into an autoclave for curing. Due to the symmetry of the plate, this invention focuses only on half of the plate's length and reconstructs the temperature field at the center plane of this half-plate's width. Figure 3 As shown. In this invention, the composite material plates mentioned in the temperature field reconstruction process all refer to a 1 / 2 plate model. Combining the heat-conduction model and the curing kinetics model, numerical simulations are performed on the curing process of the composite material plates to obtain a planar temperature field cloud map along the thickness direction of the composite material plate at the temperature peak. Specifically, the planar temperature field along the thickness direction of the composite material plate at the temperature peak is the planar temperature field along the thickness direction of the composite material plate when the temperature at a point inside the composite material plate reaches its maximum value during external heating. The X-direction of the planar temperature field corresponds to the length direction of the composite material plate, and the Y-direction corresponds to the thickness direction of the composite material plate.

[0044] Analysis of the planar temperature field cloud map reveals the distribution pattern of the planar temperature field: the planar temperature field is uniformly divided into multiple temperature intervals along the thickness direction. Each temperature interval boundary line parallel to the X-axis has a special point, namely the starting point of temperature change. On the left side of the boundary line at the starting point of temperature change, the temperature values ​​of all points are the same, and are the same as the temperature value corresponding to the point x=0 on the boundary line (i.e., the leftmost point of the boundary line). On the right side of the boundary line at the starting point of temperature change, the temperature values ​​of all points follow the same decreasing trend.

[0045] In step one of this invention, the point corresponding to the maximum temperature on the dividing line is the starting point of temperature change, and the rightmost point on the dividing line is the point corresponding to the minimum temperature on the line. The number of feature points is no less than six. Some feature points are selected from the points corresponding to the maximum temperature on the dividing line (i.e., the starting point of temperature change is selected as feature points), and some feature points are selected from the points corresponding to the minimum temperature on the dividing line. The coordinates of each feature point are then determined.

[0046] In step two of the present invention, the fiber optic grating monitoring system includes a composite material plate, an autoclave, a fiber optic grating sensor, a coupler, a spectrometer, and a broadband light source;

[0047] The composite material plate is placed in a thermostatic jar, and the fiber optic grating sensor is mounted on the composite material plate. The grating area of ​​the fiber optic grating sensor corresponds to the feature point of the composite material plate.

[0048] The fiber optic grating sensor extends through a pre-drilled hole in the autoclave and is connected to a coupler outside the autoclave. The coupler is connected to a spectrometer and a broadband light source, respectively.

[0049] In this invention, the curing process of the composite material plate is carried out in an autoclave. A fiber Bragg grating sensor enters the autoclave through a pre-drilled hole and is embedded in the feature points of the composite material plate. The pre-drilled hole is sealed to prevent air leakage. The other end of the fiber Bragg grating sensor is directly connected to the coupler, which is also directly connected to a broadband light source for sensing, measuring, and controlling optical signals. The coupler is also directly connected to a spectrometer to read the temperature data of the composite material plate in real time during the curing process. The temperature data of the feature points of the composite material plate at the peak temperature is obtained using this system as the initial data for reconstructing the planar temperature field.

[0050] In step three of this invention, the spline interpolation method is a cubic spline interpolation method. The specific method for reconstructing the planar temperature field during the composite material curing process is as follows:

[0051] 1) Input the measured temperature information of the feature points in the reconstructed planar temperature field: Take the lower left corner of the planar temperature field along the thickness direction of the composite material plate at the peak temperature obtained by numerical simulation in step one as the origin, the long side as the X-axis direction (corresponding to the length direction of the composite material plate), and the short side as the Y-axis direction (corresponding to the thickness direction of the composite material plate), discretize the planar temperature field into several points, input the coordinates of the feature points and the measured temperature information corresponding to the feature points obtained in step two.

[0052] 2) Determine the starting points of temperature changes at each boundary line: Numerical simulation is used to obtain the interval of the X-coordinate values ​​of the starting points of temperature changes at each boundary line of the planar temperature field, which serves as the range of coordinate values ​​for temperature change points set during reconstruction. Temperature change starting points are generated using a uniformly distributed random number function in MATLAB software. Specifically, the first step is to set the range and standard deviation of the mean to ensure that 99.7% of the temperature starting coordinate point data falls within the set range. The second step is to generate random values ​​matching the number of boundary lines, calculate the mean of the current random values, and then shift and scale the mean to approximate the target mean. The third step is to check each random value; if it is greater than the upper limit of the range, it is corrected to the upper limit; if it is less than the lower limit of the range, it is corrected to the lower limit. The fourth step is to use the generated random coordinate values ​​as the starting points of temperature changes for subsequent steps.

[0053] 3) Based on the measured temperature information of the feature points, the temperature values ​​of the leftmost and rightmost points of each boundary line in the plane temperature field are calculated using spline interpolation (specifically cubic spline interpolation): The starting point of temperature change on a certain boundary line is selected as the feature point, and the measured temperature value corresponding to the feature point is also the temperature value corresponding to the leftmost point on that boundary line. After determining the temperature values ​​of the leftmost points of several boundary lines, the spline interpolation method is used to solve for the temperature values ​​of the leftmost points on other boundary lines. The minimum temperature point on a certain boundary line is selected as the feature point, and this feature point is also the rightmost point on that boundary line. After determining the temperature values ​​of the rightmost points of several boundary lines, the spline interpolation method is used to solve for the temperature values ​​of the rightmost points on other boundary lines.

[0054] 4) Obtain the temperature change curve to the left of the starting point of temperature change on each boundary line: Extend the temperature value corresponding to the leftmost point (i.e., the point at x=0) on each boundary line of the plane temperature field to the starting point of temperature change (i.e., the starting point of temperature change generated in step 2) in the positive direction of the X-axis. That is, the temperature values ​​of all points to the left of the starting point of temperature change on the same boundary line are the same and consistent with the temperature value corresponding to the point at x=0 on the boundary line (i.e., the leftmost point). Then draw the temperature change curve to the left of the starting point of temperature change on each boundary line.

[0055] 5) Obtain the temperature change curve to the right of the starting point of temperature change on each boundary line: Based on the temperature values ​​of the starting point and the rightmost point of temperature change on each boundary line, calculate the temperature values ​​of the points to the right of the starting point of temperature change on each boundary line using spline interpolation, and then draw the temperature change curve to the right of the starting point of temperature change on each boundary line.

[0056] 6) Draw the thermal map of the composite material plate based on the temperature change curves of each boundary line, which completes the reconstruction of the planar temperature field during the curing process of the composite material, which is essentially the reconstruction of the planar non-uniform temperature field.

[0057] The composite material plate in this invention can specifically be a carbon fiber composite material plate, and the planar temperature field at the peak temperature moment during the curing process of the carbon fiber composite material plate is reconstructed.

[0058] Example

[0059] This embodiment focuses on a carbon fiber composite plate measuring 200mm (length) × 200mm (width) × 5.4mm (thickness). Due to the symmetry of the carbon fiber composite plate, this embodiment uses a half-model along the length of the plate as the research object, and reconstructs the temperature field of the width center plane of this model, as follows. Figure 3 As shown.

[0060] The planar temperature field reconstruction method for the curing process of carbon fiber composite plates is as follows:

[0061] Step 1: Obtain transient non-uniform temperature field information of carbon fiber composite plate curing process through numerical simulation, analyze the planar temperature field distribution law in the thickness direction of carbon fiber composite plate at the temperature peak moment, and extract the coordinates of characteristic points in the temperature field based on the law.

[0062] The planar temperature field distribution map was obtained through numerical simulation. The origin of the temperature field is located at the lower left corner of the plane. The X-axis corresponds to the length direction of the carbon fiber composite plate, and the Y-axis corresponds to the thickness direction of the carbon fiber composite plate. The planar temperature field is divided into multiple temperature ranges, corresponding to multiple boundary lines. Each boundary line has a temperature change start point. The temperature values ​​of all points on the boundary line to the left of the temperature change start point are the same, while the temperature values ​​on the boundary line to the right of the temperature change start point decrease.

[0063] In this embodiment, the planar temperature field of the carbon fiber composite plate corresponds to its cross-section. The planar temperature field is divided into temperature intervals every 0.1 mm along the thickness direction, resulting in a total of 55 temperature interval boundaries. Six feature points, A through F, are selected, with their specific locations as follows: Figure 4 As shown, feature points A and F are located on the boundary line at the frontmost side of the carbon fiber composite plate, feature points E and D are located on the boundary line at the backmost side of the carbon fiber composite plate, and feature points A, E, and F are the starting points of temperature changes on the three boundary lines. Feature points B, C, and D are located at the points with the smallest temperature values ​​on their respective boundary lines, which are also the rightmost points of the boundary lines.

[0064] Step 2: Establish a fiber Bragg grating monitoring system for measuring temperature distribution. Install the fiber Bragg grating sensors of the monitoring system on the six corresponding feature points of the carbon fiber composite board and collect the measured temperature information of the feature points.

[0065] In this embodiment, the number of fiber optic grating sensors can be arranged according to actual needs.

[0066] Step 3: Based on the temperature field distribution law in the thickness direction at the peak temperature of the carbon fiber composite plate during curing and the measured temperature values ​​at characteristic points, the planar non-uniform temperature field of the carbon fiber composite plate curing process is reconstructed using Matlab software and spline interpolation method.

[0067] The specific refactoring method includes the following steps:

[0068] 1) Input the measured temperature information corresponding to the feature points in the plane temperature field. In this embodiment, the coordinates and measured temperature values ​​corresponding to the 6 feature points are as follows: (80,0)-453.84K (meaning that the abscissa of the feature point is 80 and the ordinate is 0, and the temperature at the feature point is 453.84K), (100,0)-453.16K, (66,4.2)-455.91K, (100,4.2)-455.28, (74,5.4)-455.71K, and (100,5.4)-455.14K. Figure 4 The approximate locations of the six feature points are shown in the image.

[0069] 2) Obtain the starting points of temperature changes at each boundary line within the reconstructed planar temperature field. Specifically, through numerical simulation, the X-coordinate values ​​of the starting points of temperature changes at each boundary line of the planar temperature field in this embodiment are within the interval [70, 80]. Therefore, this interval is used as the range of temperature change point coordinates for reconstruction. After obtaining the range of temperature starting coordinates, using MATLAB software, the first step is to set the mean range to 10 and the standard deviation to 10 / 6 (based on the 3σ principle of normal distribution) to ensure that 99.7% of the temperature starting coordinate data fall within the set range. The second step is to generate 55 random values, calculate the mean of the current random values, and then shift and scale the mean to make it close to the target mean of 75 (this can be set according to actual conditions). The third step is to check each random value; if it is greater than the upper limit of 80, it is corrected to the upper limit of 80; if it is less than the lower limit of 70, it is corrected to the lower limit of 70. The fourth step is to use the generated random coordinate values, which are evenly distributed between 70 and 80, as the starting points of temperature changes for subsequent steps.

[0070] 3) Based on the temperature information of the feature points, the temperature values ​​of the leftmost and rightmost points of each boundary line in the planar temperature field are calculated using spline interpolation. As shown in Figure 4, the starting point of temperature change on the boundary line in the original numerical simulation temperature field is selected as the feature point, and the measured temperature value corresponding to the feature point is also the temperature value corresponding to the leftmost point on that boundary line. After determining the temperature values ​​of the leftmost points of the three boundary lines, spline interpolation is used to solve for the temperature values ​​of the leftmost points on other boundary lines. When the point with the minimum temperature on the boundary line is selected as the feature point, the measured temperature of that feature point is also the temperature of the rightmost point on that boundary line. After determining the temperature values ​​of the rightmost points of the three boundary lines, spline interpolation is used to solve for the temperature values ​​of the rightmost points on other boundary lines.

[0071] 4) Extend the temperature value corresponding to the leftmost point (i.e. the point at x=0) on each boundary line of the plane temperature field to the positive X-axis direction to obtain the starting point of temperature change in step 2), and draw the temperature change curve to the left of the starting point of temperature change on each boundary line.

[0072] 5) Obtain the temperature change curve to the right of the starting point of temperature change on each boundary line: Based on the temperature values ​​of the starting point of temperature change on each boundary line (randomly generated point 2) and the rightmost point, calculate the temperature values ​​of the points to the right of the starting point of temperature change on each boundary line using spline interpolation, and then draw the temperature change curve to the right of the starting point of temperature change on each boundary line.

[0073] 6) Based on the temperature change curves of each boundary line, draw a thermal map to complete the reconstruction of the planar non-uniform temperature field of the carbon fiber composite curing process.

[0074] In this embodiment, both the spline interpolation method and the method for obtaining the starting points of temperature changes at each boundary line within the reconstructed plane temperature field are mature methods and can be implemented in Matlab software. (Comparison) Figure 5 and Figure 6 As can be seen, this embodiment has very high reconstruction accuracy.

[0075] like Figure 7 As shown, the temperature value at each point obtained from the numerical simulation is used as the standard value. The temperature value at each point reconstructed using the cubic spline interpolation method is then compared with the standard value using the difference method. Figure 7 The diagram displays the temperature difference cloud map for all points in the plane. The temperature scales of 0.1, 0.2, and 0.3 indicate the magnitude of the temperature difference in Kelvin (K). The difference cloud map also reflects the small error of the reconstructed result. Table 1 shows the temperature values ​​obtained through numerical simulation and reconstruction for several points in this embodiment. Comparative analysis shows that the reconstruction method described in this invention has small error and high accuracy.

[0076] Table 1. Temperature values ​​obtained from numerical simulation and temperature values ​​obtained from reconstruction.

[0077]

[0078] The contents not described in detail in this specification are existing technologies known to those skilled in the art.

[0079] Finally, it should be noted that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. However, any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for reconstructing the planar temperature field during the curing process of a composite material, characterized in that, The method includes: The transient non-uniform temperature field information of the composite material plate curing process is obtained by numerical simulation. The distribution law of the planar temperature field in the thickness direction of the composite material plate at the temperature peak moment is analyzed, and the coordinates of the feature points in the planar temperature field are extracted based on the law. Collect measured temperature information at characteristic points of the composite material plate during the curing process; Based on the measured temperature information of characteristic points, the planar temperature field of the curing process of composite material plates is reconstructed using spline interpolation. The distribution law of the planar temperature field is as follows: the planar temperature field is uniformly divided into multiple temperature intervals along the thickness direction. There is a temperature change starting point on each temperature interval boundary line parallel to the X-axis. The temperature values ​​of all points on the boundary line to the left of the temperature change starting point are the same and are the same as the temperature value corresponding to the leftmost point of the boundary line. The temperature values ​​of all points on the boundary line to the right of the temperature change starting point follow the same decreasing change law.

2. The planar temperature field reconstruction method as described in claim 1, characterized in that, The planar temperature field along the thickness direction of the composite material plate at the temperature peak moment refers to the planar temperature field along the thickness direction of the composite material plate when the temperature at a point inside the composite material plate reaches its maximum value during the external heating process.

3. The planar temperature field reconstruction method as described in claim 1, characterized in that, A fiber optic grating monitoring system was used to obtain measured temperature information at characteristic points of the composite material board during the curing process.

4. The planar temperature field reconstruction method as described in claim 3, characterized in that, The fiber Bragg grating monitoring system includes a composite material plate, an autoclave, a fiber Bragg grating sensor, a coupler, a spectrometer, and a broadband light source; The composite material plate is placed in a thermostatic jar, and the fiber optic grating sensor is mounted on the composite material plate. The grating area of ​​the fiber optic grating sensor corresponds to the feature point of the composite material plate. The fiber optic grating sensor extends through a pre-drilled hole in the autoclave and is connected to a coupler outside the autoclave. The coupler is connected to a spectrometer and a broadband light source, respectively.

5. The planar temperature field reconstruction method as described in claim 4, characterized in that, Based on the measured temperature information of characteristic points, the method for reconstructing the planar temperature field of the composite material curing process using spline interpolation is as follows: Step 1) Input the measured temperature information of the feature points within the reconstructed planar temperature field; Step 2) Determine the starting point of temperature change at each boundary line; Step 3) Based on the measured temperature information of the feature points, calculate the temperature values ​​of the leftmost and rightmost points of each boundary line in the plane temperature field. Step 4) Obtain the temperature change curve to the left of the starting point of each boundary line temperature change; Step 5) Obtain the temperature change curve to the right of the starting point of temperature change at each boundary line; Step 6) Draw a thermal map of the composite material plate based on the temperature change curves of each boundary line, thus completing the reconstruction of the planar temperature field during the curing process of the composite material.

6. The planar temperature field reconstruction method as described in claim 5, characterized in that, The specific method for step 1) is as follows: taking the lower left corner of the planar temperature field along the thickness direction of the composite material plate at the temperature peak obtained through numerical simulation as the origin, the long side as the X-axis direction and the short side as the Y-axis direction, the planar temperature field is discretized into several points, and the coordinates of the feature points and the measured temperature information corresponding to the feature points obtained in step 2 are input.

7. The planar temperature field reconstruction method as described in claim 5, characterized in that, The method for determining the starting point of temperature change at each boundary line is as follows: through numerical simulation, the interval of the X coordinate value of the starting point of temperature change at each boundary line of the plane temperature field is obtained, which is used as the range of coordinate values ​​of the temperature change point set during reconstruction; the starting point of temperature change is generated by a uniformly distributed random number function in MATLAB software.

8. The planar temperature field reconstruction method as described in claim 3, characterized in that, Step 3) is as follows: Select the starting point of temperature change on a certain boundary line as the feature point. The measured temperature value corresponding to the feature point is also the temperature value corresponding to the leftmost point on the boundary line. After determining the temperature values ​​of the leftmost points of several boundary lines, use spline interpolation to solve for the temperature values ​​of the leftmost points on other boundary lines. Select the point with the minimum temperature on a certain boundary line as the feature point. This feature point is also the rightmost point on the boundary line. After determining the temperature values ​​of the rightmost points on several boundary lines, use spline interpolation to solve for the temperature values ​​of the rightmost points on other boundary lines.

9. The planar temperature field reconstruction method as described in claim 3, characterized in that, The method to obtain the temperature change curve to the left of the starting point of temperature change on each boundary line is as follows: extend the temperature value corresponding to the leftmost point on each boundary line of the plane temperature field to the starting point of temperature change in the positive X-axis direction. That is, the temperature values ​​of all points to the left of the starting point of temperature change on the same boundary line are the same and consistent with the temperature value corresponding to the point x=0 on the boundary line. Then, draw the temperature change curve to the left of the starting point of temperature change on each boundary line. The method for obtaining the temperature change curve to the right of the starting point of temperature change at each boundary line is as follows: based on the temperature values ​​of the starting point and the rightmost point of temperature change at each boundary line, the temperature values ​​of the points to the right of the starting point of temperature change at each boundary line are calculated using spline interpolation, and then the temperature change curve to the right of the starting point of temperature change at each boundary line is drawn.

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