Non-uniform strain field reconstruction method and system in composite material curing process

Abstract

The invention discloses a non-uniform strain field reconstruction method and system in a composite material curing process, and the method comprises the steps: building a sensor monitoring system for measuring strain distribution, collecting a strain distribution signal, and obtaining an actual reflection spectrum as a standard reflection spectrum through conversion; a strain distribution curve is generated by using a Matlab algorithm toolbox, and a corresponding reflection spectrum is obtained through calculation; a reconstruction method is adopted to operate the strain distribution curve, so that the corresponding reflection spectrum gradually approaches the standard reflection spectrum; according to the method and the system provided by the invention, the monitoring precision and the monitoring efficiency of the distribution condition of the non-uniform strain field in the curing process of the composite material are improved, and the monitoring accuracy and the monitoring efficiency of the distribution condition of the non-uniform strain field in the curing process of the composite material are improved. The monitoring cost is reduced, meanwhile, damage to the composite material caused by monitoring is reduced, and the method has great value for design and application of the composite material.

Description

Technical Field

[0001] The present invention relates to the field of strain distribution reconstruction applied to fiber grating sensors, and in particular to a method and system for reconstructing non-uniform strain in a composite material curing process based on a differential evolution algorithm. Background Art

[0002] Advanced composite materials have the characteristics of light weight, high specific modulus and specific strength, good designability and fatigue resistance, and are widely used in fields such as aerospace and shipbuilding. Advanced composite materials can also achieve integrated molding. In actual production and manufacturing, due to factors such as mismatched thermal expansion coefficients of various materials, curing shrinkage strain, and mold-part interaction, curing deformation and residual stress that affect the molding effect are generated in the parts. Higher residual stresses can cause molding defects such as separation between composite laminates and matrix fracture. After cooling and demolding, the internal stress in the part that balances external loads and mold constraints is released, causing the part to rebound or warp, resulting in poor molding quality and reduced performance. In severe cases, it will exceed the assembly tolerance range, resulting in assembly failure or part scrapping. Therefore, it is very important to monitor the curing process of composite materials, especially the strain size.

[0003] Fiber Bragg Grating (FBG) sensors offer excellent properties, including compact size, sensitive response, strong resistance to electromagnetic interference, and good compatibility with fiber-composite materials. They can be embedded between carbon fiber composite plies like fibers, with minimal impact on the composite structure itself. Furthermore, they enable "one-fiber, multiple-point" measurement, leading to their increasing application in monitoring composite curing processes. However, when the strain detected by an FBG sensor is non-uniform, the grating chirps, resulting in not only peak shifts but also peak broadening and height reduction, reducing measurement accuracy. In severe cases, peak splitting can occur, leading to multiple peaks and making FBG sensing experiments impossible. To avoid this phenomenon, the current solution is to replace the sensor with a shorter grating length, but this results in a smaller monitoring range, lower detection efficiency, and increased monitoring costs.

[0004] Currently, strain monitoring during the composite material curing process is performed by analyzing the reflection spectrum to determine the changed Bragg wavelength. The wavelength before and after the change—known as wavelength drift—is then compared. The strain distribution is then determined based on the functional relationship between the wavelength drift and external disturbances. However, this approach has very limited applications. Furthermore, this traditional wavelength drift measurement method can only measure the average strain of the sensing area, which inevitably loses information about the strain gradient of the non-uniform strain field during the curing process. The strain distribution preserves the strain gradient information of the strain field and reflects the most realistic strain field characteristics of the composite material curing process. The strain distribution can more accurately and intuitively reflect the strain field during the composite material curing process and more precisely characterize the area where deformation occurs. Therefore, finding a high-precision monitoring method and system for the non-uniform strain distribution during the composite material curing process is a current challenge. To address these issues, the following proposes a solution. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for reconstructing a non-uniform strain field during the curing process of a composite material, which has the advantage of improving the monitoring accuracy of the distribution of the non-uniform strain field during the curing process of the composite material.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions:

[0007] A method and system for reconstructing a non-uniform strain field during a composite material curing process, comprising the following steps:

[0008] The first step is to establish a sensor monitoring system for measuring strain distribution. The strain distribution signal is collected by the sensor monitoring system and converted into the actual reflection spectrum under the action of non-uniform strain during the curing process of the composite material. The actual reflection spectrum is used as the standard reflection spectrum.

[0009] In the second step, a set of strain distribution curves were randomly generated using the Matlab algorithm toolbox, and the strain distribution curves were numerically calculated using the improved transfer matrix method to obtain a corresponding set of reflection spectra;

[0010] In the third step, the strain distribution curve is operated using a reconstruction method so that the reflection spectrum corresponding to the strain distribution curve gradually approaches the standard reflection spectrum; as the calculated reflection spectrum changes, the strain distribution curve also changes accordingly with the reflection spectrum, and the actual strain field distribution corresponding to the actual reflection spectrum of the sensor monitoring area can be obtained.

[0011] Preferably, the improved transfer matrix method described in the second step is an improved transfer matrix method obtained by improving the transfer matrix method by combining the high accuracy of the Runge-Kutta method in calculating non-uniform strain and the fast calculation speed of the transfer matrix method.

[0012] Preferably, the reconstruction method in the third step is specifically a non-uniform strain segmented reconstruction method, comprising the following steps:

[0013] Estimate the number of segments and segment intervals based on the simulated strain distribution;

[0014] The standard reflection spectrum is used, and a differential evolution algorithm is used to segmentally reconstruct the strain distribution of the sensor sensing area by taking the specified error between the standard reflection spectrum and the reflection spectrum corresponding to the arbitrarily generated strain distribution curve as the objective function.

[0015] The beneficial effects of the present invention are:

[0016] 1. The present invention proposes a method and system for reconstructing the non-uniform strain field during the curing process of a composite material. At present, the strain measurement during the curing process of a composite material is only performed by analyzing the reflection spectrum, determining the Bragg wavelength after the change, and comparing the wavelength before and after the change, that is, the wavelength drift method is used to obtain the average strain value of the fiber Bragg grating sensor monitoring area. This method of using the average strain value to represent the strain magnitude of the monitoring area is bound to lose the strain gradient information of the strain field. The method and system for reconstructing the non-uniform strain field during the curing process of a composite material provided by the present invention can effectively solve the above-mentioned problem. The strain information obtained by monitoring is reconstructed and processed by the differential evolution algorithm to obtain a more accurate strain distribution. The method and system of the present invention improve the monitoring accuracy of the distribution of the non-uniform strain field during the curing process of the composite material, which is of great value to the deformation research of the composite material curing process and the optimization of the curing process parameters.

[0017] 2. During the curing process of the composite material, it is subjected to unbalanced thermal strain and after curing and molding, it is cooled from high temperature to room temperature. The additional thermoelastic strain generated by the mutual constraint between the optical fiber, carbon fiber and resin matrix caused by the different thermal expansion coefficients of the three causes the occurrence of multi-peak phenomenon. The current response method is to replace the sensor with a shorter grid length. This method will cause the measurement efficiency to become lower. More sensors are needed to monitor the same composite material plate, and the cost of monitoring will also increase. At the same time, the introduction of more sensors will also increase the damage to the composite material itself. The method and system for reconstructing the non-uniform strain field in the curing process of the composite material provided by the present invention can effectively solve the above problems. The strain information obtained by monitoring is reconstructed and processed by an intelligent algorithm, which improves the monitoring accuracy while increasing the monitoring efficiency, reducing the detection cost, and reducing the damage to the composite material.

[0018] 3. The non-uniform strain reconstruction method for the composite material curing process involved in the present invention is a segmented reconstruction method. The segmented reconstruction has the following advantages: on the one hand, the segmented reconstruction method can describe the curve more accurately; on the other hand, it can reduce the function order corresponding to the strain distribution curve, reduce the number of parameters to be optimized, and improve the optimization efficiency and accuracy of the program. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic flow chart of the method for reconstructing the non-uniform strain field during the curing process of the composite material in the present invention.

[0020] Figure 2 It is a schematic diagram of the specific process of the non-uniform strain field reconstruction algorithm in the composite material curing process of the present invention.

[0021] Figure 3 Schematic diagram corresponding to an embodiment of a sensor system for measuring strain distribution during the curing process of a composite material in the present invention.

[0022] Figure 4 It is a schematic diagram of the segmented reconstruction transmission characteristics of the non-uniform strain field during the curing process of the composite material in the present invention.

[0023] Figure 5 It is a comparison chart of the iterative curve results of the segmented reconstruction in the present invention and the traditional non-segmented reconstruction results.

[0024] Figure 6 This is a comparison diagram of the reflectance spectrum results of the segmented reconstruction in the present invention and the traditional non-segmented reconstruction results.

[0025] Figure 7 It is a comparison diagram of the strain curve results of the segmented reconstruction in the present invention and the traditional non-segmented reconstruction results.

[0026] like Figure 3 As shown: 1. Broadband light source; 2. Coupler; 3. Fiber Bragg grating sensor; 4. Composite material; 5. Autoclave; 6. Reserved hole; 7. Spectrum analyzer; 8. Computer. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0028] The purpose of the present invention is to provide a method and system for reconstructing the non-uniform strain field during the curing process of a composite material, which can improve the monitoring accuracy and efficiency of the strain field distribution during the curing process of the composite material, reduce the monitoring cost, and at the same time reduce the damage caused to the composite material by monitoring. It has great value for the design and application of composite materials and meets the quality requirements of composite material component products.

[0029] In order to make the above-mentioned objects and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0030] Example

[0031] like Figure 1 As shown, a method for reconstructing a non-uniform strain field during the curing process of a composite material specifically includes:

[0032] Step 101: Establishing a sensor monitoring system for measuring strain distribution, collecting strain distribution signals through the sensor monitoring system, converting them into an actual reflection spectrum under the action of non-uniform strain during the curing process of the composite material, and using the actual reflection spectrum as a standard reflection spectrum;

[0033] Step 101 specifically includes:

[0034] like Figure 3 As shown, the sensor system for measuring strain distribution includes a broadband light source, a coupler, a fiber Bragg grating sensor, a composite material, a spectrum analyzer, and a computer.

[0035] The hot pressing curing process of this embodiment is carried out in an autoclave, and multiple measured points can be set up to monitor the strain distribution of multiple points of the composite material during the curing process. The grating area of ​​the fiber optic Bragg grating sensor enters the autoclave through the reserved hole on the autoclave and is buried in the measured point of the composite material, and then the reserved hole is sealed with a sealing strip. The other end of the fiber optic Bragg grating sensor is directly connected to the coupler; the coupler is also directly connected to a broadband light source at the same time for transmitting optical signals; the coupler is also directly connected to a spectrometer at the same time for reading the strain information of the composite material in real time during the curing process and converting the strain signal obtained into a reflection spectrum; the spectrometer is directly connected to the computer for subsequent reconstruction of the strain distribution through an intelligent algorithm.

[0036] The working principle of the sensor system for measuring strain distribution is as follows: a broadband light source generates an optical signal, which is transmitted to the fiber Bragg grating sensor through a coupler. After reflection from the grating area, the reflected optical signal is transferred to the spectrum analyzer through a coupler to convert it into a reflection spectrum corresponding to the strain distribution. Finally, the reflection spectrum is connected to a computer and reconstructed through an intelligent algorithm to obtain the corresponding strain distribution curve.

[0037] In this embodiment, the fiber Bragg grating sensor is selected to have a length of 10 mm, an effective refractive index of 1.45, and a refractive index modulation of 10e. -5 The Bragg wavelength λ0 is 1557nm and the elastic-optical coefficient is 0.26. The composite material adopts 0° ply, and the grating area of ​​the fiber Bragg grating sensor is perpendicular to the fiber direction at 90°.

[0038] Step 102: using the Matlab algorithm toolbox, randomly generating a strain distribution curve, and numerically calculating the strain distribution curve using an improved transfer matrix method to obtain a corresponding reflection spectrum;

[0039] Step 103: The strain distribution curve is operated using a reconstruction method so that the reflection spectrum corresponding to the strain distribution curve gradually approaches the standard reflection spectrum. As the calculated reflection spectrum changes, the strain distribution curve also changes accordingly. Finally, the actual strain field distribution corresponding to the actual reflection spectrum of the sensor monitoring area can be obtained.

[0040] like Figure 2 As shown, step 102 and step 103 are specifically as follows:

[0041] The process of the non-uniform strain field reconstruction algorithm during the composite material curing process includes:

[0042] Step 1: Set relevant parameters in Matlab, including:

[0043] The number of evolutions is set to 3000 in order to control the program to iterate 3000 times;

[0044] The population size is set to 600. The purpose is to ensure that the initial generated function representing the random strain curve and the update function generated by subsequent iterations are composed of these 600 populations;

[0045] The speed boundary value is generally set to 10%-20% of the population threshold, in order to prevent the speed from being too slow and falling into the local optimal solution or to prevent the speed from being too fast and directly skipping the optimal solution;

[0046] The minimum value of each order coefficient of the function is set to 1 and the maximum value is 10. The purpose is to control the parameters to be at the same order of magnitude and achieve better optimization results.

[0047] Step 2: According to the set parameters, randomly generate a function representing the strain distribution curve, initialize the speed, and calculate the fitness corresponding to the current function.

[0048] The fitness refers to the difference between the reflection spectrum corresponding to the current function and the standard reflection spectrum collected by the sensor.

[0049] The algorithm involved in this invention calculates the fitness value through segmentation. It divides the monitoring area (-5, 5) into three segments: (-5, -1.5), (-1.5, 1.5), and (1.5, 5). The reflectivity of these three segments is reconstructed separately, and finally the three segments are combined to calculate the fitness value of the entire curve.

[0050] like Figure 4 As shown in FIG, the segmented reconstruction principle is: the entire FBG sensor is divided into three segments, namely (1, j-1), (j, i), and (i+1, M).

[0051] The optical transmission characteristics from the first segment to the j-1 segment can be expressed as:

[0052]

[0053] F j1 =F j-1 F j-2 …F1;

[0054] The optical transmission characteristics from segment j to segment i can be expressed as:

[0055]

[0056] F ij =F i F i-1 …F j ;

[0057] The optical transmission characteristics from the i+1th segment to the Mth segment can be expressed as:

[0058]

[0059] F Mi+1 =F M F M-1 …F i+1 ;

[0060] The optical transmission characteristics of the three segments mentioned above can be combined to obtain the optical transmission characteristics of the entire segment, which can be expressed as:

[0061]

[0062] The optical transmission characteristics of the entire FBG obtained without segmented reconstruction are expressed as:

[0063] F=F M F M-1 …F1;

[0064] By comparing the optical transmission characteristics obtained by segmented reconstruction and the optical transmission characteristics obtained by unsegmented reconstruction, it can be seen that the matrix does not change before and after segmentation. Therefore, the segmented reconstruction method does not affect the optical transmission characteristics. At the same time, it also improves the accuracy of the description function curve and improves the efficiency and accuracy of the program optimization.

[0065] Step 3: Find the individual optimal fitness value of the current function, that is, find the individual optimum, the purpose of which is to optimize around the individual optimum in the next iterative process;

[0066] Find the global optimal fitness value of the current function, that is, find the global optimum. The purpose is to judge whether the function optimization result is ideal through the global optimal result.

[0067] Step 4: Perform iterative optimization within the parameter limits set in the first three steps and update relevant data. This includes: speed update, population update, fitness calculation, individual optimal update, and global optimal update.

[0068] Step 5: Repeat the iterative optimization operation of step 4 3000 times according to the constraints of steps 1 to 3. The program ends and a final function is obtained. The reflectance spectrum corresponding to the final function is compared with the standard reflectance spectrum, and the calculation result is accurate.

[0069] This embodiment involves a segmented reconstruction method for a non-uniform strain field during a composite material curing process. This segmented reconstruction method estimates the number of segments and intervals within a whole FBG sensor monitoring area based on the strain distribution, reconstructs the reflectivity of each segment separately, and finally combines these segments to calculate the fitness value of the entire curve. This segmented reconstruction method offers the following advantages over traditional non-segmented reconstruction methods:

[0070] like Figure 5 As shown, it can be seen that the segmented reconstruction method according to the present invention can make the differential evolution algorithm converge to a smaller fitness value compared with the traditional non-segmented reconstruction method;

[0071] like Figure 6 As shown, it can be seen that the spectrum obtained by adopting the segmented reconstruction method according to the present invention can better match the standard spectrum than the spectrum obtained by the traditional non-segmented reconstruction method.

[0072] like Figure 7 As shown, it can be seen that the strain curve result obtained by adopting the segmented reconstruction method according to the present invention can better match the standard strain curve than the strain curve result obtained by the traditional non-segmented reconstruction method.

[0073] The non-uniform strain segmented reconstruction method for a composite material curing process proposed by the present invention can improve the accuracy of non-uniform strain reconstruction and obtain a more accurate strain distribution.

[0074] The present invention and its embodiments have been described above, and the description is not restrictive. What is shown in the accompanying drawings is only one of the embodiments of the present invention, and the actual structure is not limited thereto. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. In short, if a person of ordinary skill in the art is inspired by it, without departing from the purpose of the invention, a structural mode and embodiment similar to the technical solution without creative design should fall within the scope of protection of the present invention.

Claims

1. A method and system for reconstructing non-uniform strain fields during the curing process of composite materials, characterized in that: The following steps are involved: The first step is to establish a sensor monitoring system for measuring strain distribution. The strain distribution signal is collected by the sensor monitoring system and converted into the actual reflection spectrum under the action of non-uniform strain during the curing process of the composite material. The actual reflection spectrum is used as the standard reflection spectrum. In the second step, a set of strain distribution curves were randomly generated using the Matlab algorithm toolbox, and the strain distribution curves were numerically calculated using the improved transfer matrix method to obtain a corresponding set of reflection spectra; In the third step, the strain distribution curve is operated using a reconstruction method so that the reflection spectrum corresponding to the strain distribution curve gradually approaches the standard reflection spectrum; as the calculated reflection spectrum changes, the strain distribution curve also changes accordingly with the reflection spectrum, and the actual strain field distribution corresponding to the actual reflection spectrum of the sensor monitoring area can be obtained.

2. The method and system for reconstructing a non-uniform strain field during the curing process of a composite material according to claim 1, characterized in that: The improved transfer matrix method described in the second step is specifically an improved transfer matrix method obtained by combining the high accuracy of the Runge-Kutta method in calculating non-uniform strain and the fast calculation speed of the transfer matrix method.

3. The method and system for reconstructing a non-uniform strain field during the curing process of a composite material according to claim 1, characterized in that: The reconstruction method in the third step is specifically a non-uniform strain segmented reconstruction method, comprising the following steps: Estimate the number of segments and segment intervals based on the simulated strain distribution; The standard reflection spectrum is used, and a differential evolution algorithm is used to segmentally reconstruct the strain distribution of the sensor sensing area by taking the specified error between the standard reflection spectrum and the reflection spectrum corresponding to the arbitrarily generated strain distribution curve as the objective function.

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