Composite laminated plate impact delamination damage layer-by-layer reconstruction method and device based on ultrasonic c-scan results, and medium

Abstract

The application discloses a composite laminate impact delamination damage layer-by-layer reconstruction method and device based on an ultrasonic C-scan result, and a medium, and relates to the technical field of composite laminate impact damage. The method determines the interfaces between layers of a to-be-tested composite laminate and a reference time of flight, clusters ultrasonic C-scan time-of-flight data, determines the average time of flight of each response cluster obtained through clustering, thereby determining a damage-free area and an observable delamination damage area of each interface between layers, determining an area classification result of each interface between layers according to the damage-free area and the observable delamination damage area, taking the area classification result and layer information as input, predicting a damage area in a blocked area by using a blocked area layer-by-layer reconstruction model, and fusing the observable delamination damage area and the predicted damage area to obtain a complete delamination damage distribution result of each interface between layers. The application can accurately reconstruct the delamination damage distribution of each interface between layers inside a composite laminate after impact.

Description

Technical Field

[0001] This application relates to the field of impact damage technology for composite laminates, and in particular to a method, equipment, and medium for layer-by-layer reconstruction of impact delamination damage in composite laminates based on ultrasonic C-scan results. Background Technology

[0002] Composite laminates, due to their advantages such as high specific strength, high specific stiffness, and strong design flexibility, have been widely used in aerospace, transportation, and high-end equipment. During service or maintenance, these structures are susceptible to low-velocity impact loads such as tool drops, hail impacts, and foreign object impacts, leading to damage within the material, including matrix cracking, delamination, and localized fiber breakage. Delamination damage, located within the material, is highly concealed but significantly weakens the structure's compressive residual strength and load-bearing capacity; therefore, accurate detection and characterization of this damage are of great importance.

[0003] Currently, non-destructive testing methods for impact damage in composite laminates mainly include ultrasonic testing, X-ray CT, and infrared thermography. Among these, ultrasonic testing, especially ultrasonic C-scanning, has become one of the most commonly used methods for detecting impact damage in composite materials due to its sensitivity to interlaminar delamination damage, high detection efficiency, and strong engineering applicability. Ultrasonic C-scanning records the echo amplitude, flight time, or energy attenuation information of ultrasonic waves at different scanning positions to form a two-dimensional planar image of the damaged area, which can intuitively reflect the approximate location and extent of the damage.

[0004] However, ultrasound C-scan results are essentially two-dimensional projection representations. Delamination damage at different interlayer interfaces will be superimposed in the scan results, thus usually only reflecting the overall damage projection range and making it difficult to directly distinguish which specific interlayer interface has delamination. At the same time, when there is delamination or other damage in the shallow layer, the shallow layer damage will preferentially reflect, scatter, or attenuate the incident ultrasound waves, making it difficult to reliably obtain effective echo information from the deep interface. Therefore, ultrasound C-scan results often only show shallow layer damage and fail to reflect the true damage state of the deep interface, i.e., there is a significant acoustic obstruction problem.

[0005] In contrast, methods such as X-ray CT can obtain damage distribution information in the thickness direction with high accuracy, but these methods are usually expensive, have low detection efficiency, and have high requirements for component size and detection conditions, making them difficult to apply to rapid engineering inspection of large composite component components.

[0006] Therefore, accurately reconstructing the delamination damage distribution at the interlayer interfaces within a composite laminate after impact, based solely on ultrasonic C-scan results, is a pressing technical problem in this field. Solving this problem is crucial for accurate assessment of structural residual strength, damage tolerance design, maintenance decision-making, and ensuring structural service safety. Summary of the Invention

[0007] The purpose of this application is to provide a method, equipment, and medium for reconstructing layer-by-layer delamination damage of composite laminates based on ultrasonic C-scan results, which can accurately reconstruct the delamination damage distribution of the interfaces between the layers inside the composite laminate after impact.

[0008] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a method for layer-by-layer reconstruction of impact delamination damage in composite laminates based on ultrasonic C-scan results, including: Time-of-flight data of the composite laminate under test after impact were obtained by ultrasonic C-scan. Determine the interlayer interfaces and reference flight times of each interlayer interface of the composite laminate under test; The flight time data is clustered, and the average flight time of each response cluster is determined. Based on the average flight time of each response cluster and the baseline flight time of each interlayer interface, the undamaged region and the observable layered damage region of each interlayer interface are determined. Based on the undamaged area and the observable layered damage area at each interlayer interface, the region classification result of each interlayer interface is determined; the region classification result includes observable layered damage area, undamaged area, and occluded area; Using the region classification results and the layup information of the composite laminate to be tested as input, the model is reconstructed layer by layer in the shading region to predict the damage area of ​​each interlayer interface in the shading region. By fusing the observable layered damage regions and the predicted damage regions within the occlusion regions at each interlayer interface, a complete layered damage distribution result for each interlayer interface is obtained.

[0009] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to implement the above-described method for layer-by-layer reconstruction of impact delamination damage in composite laminates based on ultrasonic C-scan results.

[0010] Thirdly, this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for reconstructing layer-by-layer impact delamination damage of composite laminates based on ultrasonic C-scan results.

[0011] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a method, device, and medium for layer-by-layer reconstruction of impact delamination damage in composite laminates based on ultrasonic C-scan results. By establishing the interlayer interfaces and their reference times of flight for each layer of the composite laminate under test, and combining the clustering results of the time-of-flight data, the ultrasonic response is assigned to specific interlayer interfaces. Addressing the problem of shallow delamination obscuring deep echoes, the regions on each interlayer interface are divided into observable delamination damage areas, undamaged areas, and obscured areas. Then, using the observable delamination damage areas, layup information, and the layer-by-layer reconstruction model of the obscured areas, the delamination damage in the obscured areas, which cannot be directly observed by ultrasound, is predicted and recovered layer by layer. Finally, the complete delamination damage distribution results of each interlayer interface of the composite laminate under test are obtained. Therefore, this application can more effectively distinguish damage information at different interlayer interfaces and recover the deep delamination damage results in areas that are difficult to observe directly, improving the accuracy of the delamination damage distribution of the internal interlayer interfaces of the composite laminate after impact. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A simplified flowchart illustrating a method for reconstructing layer-by-layer impact delamination damage in composite laminates based on ultrasonic C-scan results, provided for embodiments of this application; Figure 2 A more detailed flowchart illustrating a method for reconstructing layer-by-layer impact delamination damage in composite laminates based on ultrasonic C-scan results, provided for embodiments of this application; Figure 3 This is a schematic diagram of the reconstructed distribution results provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0014] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0015] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0016] Terminology Explanation: Composite laminate: refers to a plate-like structure formed by stacking and curing multiple layers of unidirectional fiber-reinforced composite materials in a predetermined layup sequence. The fibers in each layup have different orientations to meet the load-bearing requirements of the structure in different directions.

[0017] Low-velocity impact: refers to the impact loading process in which an impactor acts on the surface of a composite laminate at a relatively low velocity. This process usually does not lead to penetration, but it is prone to causing internal damage such as matrix cracking, interlaminar delamination, and localized fiber breakage.

[0018] Impact delamination damage: refers to the separation, debonding, or extended interlaminar damage that occurs at the interface between adjacent plies of a composite laminate under impact load.

[0019] Ultrasonic C-scan: refers to a method of recording the echo amplitude, flight time or energy attenuation information of ultrasonic waves after they propagate inside the test piece, and performing two-dimensional imaging according to the planar scanning position.

[0020] Time of Flight (TOF): refers to the time it takes for an ultrasonic wave to travel from emission to reception of a specific echo signal, used to reflect the thickness direction location of the reflecting interface or damage.

[0021] Layer-by-layer reconstruction: Based on the detection results, layup information and constraint rules, the layer-by-layer delamination damage on the interlayer interfaces in the thickness direction of the laminate is restored layer by layer to obtain the damage distribution results of each interface.

[0022] Acoustic blockage: This refers to the phenomenon that during ultrasound detection, shallow damage preferentially reflects, scatters, or attenuates ultrasound waves, making it impossible to reliably obtain effective echo information from deep interfaces. As a result, ultrasound C-scan results usually only show shallow damage and fail to reflect the true state of deep damage.

[0023] Existing ultrasonic testing methods for impact damage in composite laminates include: Existing technology 1: A method for evaluating the overall area of ​​debonding or delamination defects in composite materials based on ultrasonic C-scan results.

[0024] This method primarily utilizes ultrasonic C-scan results to identify and assess the overall projection range and area of ​​debonding or delamination defects within composite materials. A representative example is Chinese patent application CN104931585A, entitled "Method for Area Assessment of Debonding Defects in Composite Materials Using Ultrasonic C-Scan." This method generally includes the following steps: S1: Perform ultrasonic C-scan testing on the composite material specimen to be tested: Use ultrasonic testing equipment to scan the specimen, obtain echo information at each scanning position, and form the corresponding C-scan image.

[0025] S2: Constructing standard reference images required for defect identification: Based on the structural dimensions of the test piece or the preset defect state, establish simulated debonding images or standard images for comparative analysis, and count the total number of pixels in the standard images.

[0026] S3: Identify abnormal defect areas in C-scan images: Based on grayscale differences, echo anomalies, or amplitude changes in the scanned images, extract suspected debonding or delamination defect areas and count the number of pixels in the defect areas.

[0027] S4: Calculate the defect ratio and overall area: Calculate the overall area of ​​the debonding or delamination defect based on the ratio between the number of pixels in the defect area and the total number of pixels in the standard image.

[0028] S5: Output overall defect assessment results: Use the obtained defect area as the basis for assessing the degree of internal damage of the composite material.

[0029] This method can identify and assess the overall projection range of defects inside composite materials, but its output mainly shows the overall area of ​​the two-dimensional projection layer, making it difficult to further distinguish the layered damage distribution at different interlayer interfaces.

[0030] Existing technology 2: Automatic identification of interface debonding and C-scan imaging method based on ultrasonic echo characteristics and neural network.

[0031] This method mainly utilizes ultrasonic echo signal characteristics and a neural network model to automatically identify debonding defects at the interface of layered structures and generate two-dimensional C-scan imaging results. A representative example is Chinese Patent Publication No. CN114755301A, entitled "Automatic Identification and C-scan Imaging Method and System for Bond Quality of Layered Structure Interfaces." This method generally includes the following steps: S1: Acquire ultrasonic echo signals at the interface of the layered structure: Perform ultrasonic testing on the artificial defect sample and the structure under test to obtain the original echo data at different interfaces.

[0032] S2: Preprocessing and feature extraction of the original echo signal: Filtering, envelope extraction and time-domain parameter calculation are performed on the acquired ultrasonic signal to extract feature parameters that can be used to identify debonding defects.

[0033] S3: Construct and train a neural network model: Use calibration data from artificial defective samples to train the neural network, enabling the model to recognize interface debonding.

[0034] S4: Input the signal to be tested into the trained model for identification: classify and judge the echo signal of the area to be detected, and identify whether there is a debonding defect.

[0035] S5: Output two-dimensional C-scan imaging results: A two-dimensional C-scan image is formed based on the identification results of each detection position, which is used to characterize the planar distribution of interface debonding defects.

[0036] This method can improve the automation of interface debonding identification, but its results are still mainly two-dimensional C-scan images, and it cannot further realize the layer-by-layer reconstruction of impact debonding damage of composite laminates at different interlayer interfaces.

[0037] Existing technology 3: A three-dimensional reconstruction method for internal damage of composite materials based on CT slice images.

[0038] This method primarily utilizes X-ray CT to acquire slice images at different depths within the composite material, and then reconstructs the internal damaged structure through image processing and 3D modeling. A representative scheme is found in Chinese Patent Publication No. CN114419284A, entitled "A 3D Reconstruction Modeling Method for Fiber-Reinforced Composite Materials Based on CT Slice Images." This method generally includes the following steps: S1: Perform X-ray CT scans on the composite material specimen: obtain CT slice images of different thickness locations inside the specimen.

[0039] S2: Preprocessing of CT slice images: including grayscale conversion, denoising, enhancement and binarization to improve the identifiability of internal lesion areas.

[0040] S3: Identify damage contours in each slice: Segment abnormal regions in the image and extract their boundary contour information.

[0041] S4: Register and overlay the slice results of each layer: Match and stack the damage contours of each slice according to the thickness direction.

[0042] S5: Complete the three-dimensional reconstruction of internal damage: Establish a three-dimensional geometric model of internal damage of composite materials based on the results of multi-layer slicing.

[0043] This method can obtain relatively complete thickness-direction damage information, but its implementation relies on X-ray CT rather than solely on ultrasound C-scan results, resulting in high equipment costs and limited engineering applicability.

[0044] The main drawback of the existing technology is that, based solely on the results of ultrasonic C-scans, it is impossible to accurately obtain the layer-by-layer delamination damage distribution at the interfaces between the layers inside the composite laminate after impact.

[0045] The reason for this is that existing ultrasound C-scan-based detection methods primarily utilize information such as echo amplitude, time of flight, or energy attenuation to construct two-dimensional planar images, and characterize damage through anomaly region identification, area statistics, or two-dimensional imaging results. Since these methods are essentially based on two-dimensional projection information, layered damage at different interlayer interfaces will superimpose in the same planar result. Therefore, they typically only reflect the overall projected damage range, making it difficult to distinguish which specific interlayer interface experienced layered damage. In other words, because the input representation of existing methods is a two-dimensional projection result, their output results usually only remain at the level of overall projected damage, and cannot directly obtain the layer-by-layer interface damage distribution.

[0046] Furthermore, when there is delamination or other damage in the shallow layers of the laminate, the shallow damage will preferentially reflect, scatter, or attenuate ultrasonic waves, making it difficult to reliably obtain effective echo information from the deeper interfaces. Due to acoustic obstruction, existing technologies not only cannot distinguish the damage superposition relationship between different interfaces, but also cannot effectively observe deep damage that is obscured by shallow damage, thus further exacerbating the difficulty of identifying layer-by-layer delamination damage.

[0047] Furthermore, existing methods for obtaining thickness-direction damage information typically rely on imaging techniques such as X-ray CT. While these methods can provide relatively complete three-dimensional or layered damage information, they are costly, inefficient, and require sophisticated equipment, making them less suitable for large composite material components or on-site engineering inspections. Therefore, although existing technologies can improve the characterization of internal damage to some extent, they often depend on high-cost equipment such as CT scanners, making it difficult to balance detection accuracy with engineering applicability.

[0048] In summary, the shortcomings of existing technologies can be categorized into the following aspects: 1. Based solely on ultrasonic C-scan results, it is impossible to accurately obtain the layer-by-layer delamination damage distribution at the interfaces between different layers within the composite laminate. (This is the most significant drawback.) 2. Since ultrasound C-scan is essentially a two-dimensional projection characterization, layered damage at different interlayer interfaces is prone to superimpose, making it difficult to determine the specific damage layer.

[0049] 3. Because shallow damage acoustically blocks deep echoes, the damage state of deep interfaces is difficult to identify reliably.

[0050] 4. Existing methods for obtaining thickness-direction damage information mostly rely on equipment such as X-ray CT, which are costly, inefficient, and have limited applicability in engineering applications.

[0051] To address the above drawbacks, in an exemplary embodiment, such as Figure 1As shown, a method for reconstructing layer-by-layer impact delamination damage of composite laminates based on ultrasonic C-scan results is provided. This method is executed by a computer device, specifically by a computer device such as a terminal or server alone, or by a terminal and server together. In the embodiments of this application, the method includes the following steps 101 to 107.

[0052] Step 101: Obtain the time-of-flight data of the composite laminate under test after impact by ultrasonic C-scan.

[0053] Step 102: Determine the interlayer interfaces of the composite laminate to be tested and the reference flight time of each interlayer interface.

[0054] Step 103: Cluster the flight time data and determine the average flight time of each response cluster obtained by clustering.

[0055] Step 104: Determine the undamaged region and the observable layered damage region of each interlayer interface based on the average flight time of each response cluster and the baseline flight time of each interlayer interface.

[0056] Step 105: Determine the region classification results of each interlayer interface based on the undamaged area and the observable layered damage area of ​​each interlayer interface; the region classification results include observable layered damage area, undamaged area and occluded area.

[0057] Step 106: Using the region classification results and the layup information of the composite laminate to be tested as input, the model is reconstructed layer by layer using the shading region to predict the damage area of ​​each interlayer interface within the shading region.

[0058] Step 107: Merge the observable layered damage areas and the predicted damage areas within the occlusion areas of each interlayer interface to obtain the complete layered damage distribution results of each interlayer interface.

[0059] By implementing steps 101 to 107 above, without relying on X-ray CT layer-by-layer imaging, the problems of existing technologies that can only obtain two-dimensional projection damage information, have difficulty distinguishing layered damage at different interlayer interfaces, and are easily affected by acoustic shielding are overcome. Layer-by-layer reconstruction of layered damage at each interlayer interface of composite laminate is achieved, thereby providing a more accurate basis for fine characterization of impact damage, analysis of compression failure mechanisms, assessment of structural residual strength, and maintenance decision-making.

[0060] Figure 2 This application illustrates a more detailed process of the method. Figure 3This is a schematic diagram of the reconstructed distribution results. The method in this application reconstructs the layered damage distribution of interlayer interfaces within a composite laminate by preprocessing the raw ultrasonic C-scan data, allocating interlayer interfaces, identifying occlusion regions, and reconstructing occlusion regions based on machine learning. The following refers to... Figure 2 and Figure 3 The method described in this application will be explained in detail.

[0061] In another exemplary embodiment of this application, step 101 involves acquiring raw ultrasound C-scan TOF data and preprocessing it to improve the accuracy of subsequent inter-slice interface assignment. Step 101 can be replaced by steps 201 to 207.

[0062] Step 201: Determine the scanning method based on the accessibility of both sides of the composite laminate being tested; the scanning method includes single-sided ultrasonic C-scan and double-sided ultrasonic C-scan.

[0063] When the component is accessible from both sides, a two-sided ultrasonic C-scan is used; when the component is accessible from only one side, a single-sided ultrasonic C-scan is used.

[0064] Step 202: When the scanning method is single-sided ultrasonic C-scan, obtain the original time-of-flight data of one side of the composite material laminate to be tested after impact.

[0065] Ultrasonic C-scan testing was performed on the impact-exposed composite laminate to obtain raw time-of-flight data for each planar position within the scanned area. Specifically, for each scan position... Corresponding to a TOF value When layered damage exists at this location, the TOF value reflects the depth information corresponding to the layered damage, providing a basis for subsequent layered damage layer determination.

[0066] When a single-sided scan is used, a single-sided ultrasound C-scan TOF image is obtained, denoted as . Its corresponding matrix expression is: ; in, Indicates the first under frontal scanning conditions line, number The TOF value corresponding to the column sampling position. and These represent the number of sampling points in the scanning area in the two planar directions, respectively.

[0067] Step 203: Preprocess the raw flight time data of one side to obtain the preprocessed flight time data of one side, and use it as the flight time data of the composite laminate to be tested after impact.

[0068] First, the TOF image is cropped according to the sample boundary to extract the effective detection area of ​​the laminate, while removing the background outside the laminate and invalid scanning areas; second, using... Median filtering is used to initially correct abnormal TOF points, and then neighborhood mean interpolation is used to fill in local missing points. Then, small-scale Gaussian filtering is used to smooth the image slightly to suppress random noise and preserve damage boundary information.

[0069] Step 204: When the scanning method is double-sided ultrasonic C-scan, obtain the original time-of-flight data of the front and back sides of the composite laminate to be tested after impact.

[0070] Step 205: Perform planar registration on the original flight time data of the front and back sides to obtain the registered flight time data of the front and back sides.

[0071] When using double-sided scanning, ultrasonic C-scan TOF images of the front and back sides of the laminate are obtained separately. The TOF images of the front and back sides are then registered in a plane to establish a one-to-one correspondence in a unified coordinate system. The registered front and back TOF images are denoted as follows: and Its corresponding matrix expression is: .

[0072] Step 206: Preprocess the flight time data of the registered front and back sides to obtain preprocessed flight time data of the front and back sides.

[0073] In addition to median filtering, neighborhood mean interpolation, and Gaussian smoothing, preprocessing methods such as mean filtering, bilateral filtering, wavelet denoising, morphological processing, outlier removal, and interpolation reconstruction can also be used. Any method that can achieve effective region extraction, noise suppression, outlier correction, and missing information completion is applicable to this application.

[0074] Step 207: Correct the inconsistent data in the flight time data of the front and back sides after preprocessing, obtain the final flight time data of the front and back sides, and use it as the flight time data of the composite material laminate to be tested after impact.

[0075] For double-sided scanning, the TOF images of the front and back sides are further examined for corresponding positional differences, and areas with obvious inconsistencies are corrected.

[0076] In another exemplary embodiment of this application, step 102 described above may be replaced by steps 301 to 302.

[0077] Step 301: Determine the interlayer interfaces inside the composite laminate under test based on the number of plies and the thickness of each ply.

[0078] Assume the laminate has a total of If the ply is layered, then the number of layers between adjacent layers is [missing information]. The interfaces between layers are denoted as follows: ; Among them, the Interlayer Interface Indicates the first Layer and First Interface between layers.

[0079] Step 302: Under the condition of scanning the composite laminate under test from the front, use the formula The reference flight time of each interlayer interface under frontal scanning conditions was obtained.

[0080] In the formula, For the frontal scan condition, the first Reference flight time of each interlayer interface The equivalent propagation velocity of ultrasound in the composite laminate under test is given. For the first The depth of the interface between each layer from the front surface , For the first Layer thickness.

[0081] Step 303: Under the condition of reverse scanning of the composite laminate to be tested, use the formula The reference flight time of each interlayer interface under reverse scanning conditions is obtained.

[0082] In the formula, For the reverse scanning condition, the first The baseline flight time of each candidate interlayer interface The total thickness of the composite laminate to be tested is given.

[0083] Step 304: Using the formula Determine the reference flight time corresponding to the back wall echo of the non-destructive region under frontal or reverse scanning conditions.

[0084] In the formula, This is the reference time of flight for the backwall echo of the non-destructive region under frontal scanning conditions. This is the reference flight time corresponding to the back wall echo of the non-destructive region under reverse scanning conditions.

[0085] In another exemplary embodiment of this application, step 103 described above may be replaced by steps 401 to 404.

[0086] Step 401: Establish feature vectors for each plane position on the composite material laminate to be tested; the feature vectors include the coordinates of each plane position and the time-of-flight data of each plane position.

[0087] A feature vector is constructed for each pixel within the obtained effective detection region. For any pixel... Construct its feature vector: ; in, This indicates the TOF value corresponding to that pixel. and This indicates the coordinates of the pixel's position in the plane.

[0088] Step 402: Normalize the feature vector to obtain a normalized feature vector.

[0089] To reduce the impact of different units on subsequent clustering results, the above feature vectors are normalized: ; in, and These are the weighting coefficients.

[0090] Step 403: Cluster the normalized feature vectors of all planar locations to obtain multiple response clusters.

[0091] Cluster analysis is performed on the normalized feature vectors to group pixels with similar Time-of-Flight (TOF) values ​​and continuous spatial locations into the same response cluster. K-means clustering is preferred, but Gaussian mixture model clustering, hierarchical clustering, density clustering, fuzzy clustering, or other unsupervised clustering methods can also be used. Let the clustering result be... There are several response clusters, denoted as follows: .

[0092] This step enables the clustering of pixels in a TOF image.

[0093] Step 404: Determine the average flight time of each response cluster based on the normalized feature vector of the planar position within each response cluster.

[0094] For the Response clusters Calculate the average TOF value corresponding to its cluster center: ; in, Indicates the first The number of pixels contained in a response cluster.

[0095] In another exemplary embodiment of this application, step 104 above involves assigning the clustering results to different interlayer interfaces: assigning each response cluster to the class whose TOF value is closest to its cluster center. Step 104 can be replaced by steps 501 to 505.

[0096] Step 501: Determine the reference flight time corresponding to the back wall echo of the non-destructive region.

[0097] Step 502: Calculate the difference between the average flight time of each response cluster and the reference flight time corresponding to the backwall echo of the undamaged region and the reference flight time of each interlayer interface.

[0098] Step 503: If the difference between the average flight time of the response cluster and the reference flight time corresponding to the back wall echo of the lossless region is the smallest, then the response cluster is determined to be a lossless region.

[0099] Step 504: If the difference between the average flight time of the response cluster and the reference flight time of the interlayer interface is the smallest, then the response cluster is determined as the observable layered damage region of the corresponding interlayer interface, thereby obtaining the initial layered damage allocation result of each interlayer interface.

[0100] It should be noted that multiple response clusters can be assigned to the same candidate interlayer interface, multiple response clusters can also belong to the lossless region at the same time, and some candidate interlayer interfaces may not have corresponding response clusters.

[0101] Step 505: Remove abnormal noise regions from the initial layered damage allocation results of each interlayer interface, and correct the spatially isolated regions in the initial layered damage allocation results to obtain the final observable layered damage regions of each interlayer interface.

[0102] To improve the rationality of the inter-layer interface allocation results, the initial inter-layer interface allocation results are revised. Let the interface be allocated to the... The first candidate inter-layer interface A connected region is denoted as Its pixel count is denoted as The average flight time is denoted as The centroid coordinates are as follows Let the total number of pixels in all identified damaged areas be... , No. The baseline TOF for each candidate interlayer interface is The back wall echo reference TOF is Corrections are made for small areas and spatially isolated areas.

[0103] (1) Judgment and correction of areas with excessively small area When connected regions If the following condition is met, the region is determined to be too small: ; in, The absolute area threshold is preferably 9 to 16 pixels. Regions determined to be too small are marked as abnormal noise regions and removed.

[0104] (2) Determination and correction of spatially isolated regions For connected regions Perform morphological expansion to construct its neighborhood annular region. Let the percentage of pixels with the same number within the annular region be . The centroid distance between the nearest connected regions with the same number is A region is considered to be spatially isolated when the following condition is met: ; in, The neighborhood support threshold is preferably 0.1 to 0.3; The spatial isolation distance threshold is preferably 3 to 10 pixels.

[0105] For areas determined to be spatially isolated, the following rules apply: if their average TOF is similar to that of an adjacent inter-layer interface... If the reference TOF is closer and the numbering has the highest proportion within the neighboring annulus, then the region will be renumbered. If it is spatially isolated, but the distance to the nearest region with the same number is less than the preset connection threshold, it will be merged with the nearest region with the same number through morphological connection or region merging. If it has both the characteristics of being too small in area and spatially isolated, it will be preferentially removed as noise.

[0106] Therefore, the correction process for spatially isolated regions can be summarized as follows: Under frontal scanning conditions, based on the formula... Determine the number of the interlayer interface corresponding to each response cluster; under reverse scanning conditions, according to the formula Determine the number of the interlayer interface corresponding to each response cluster; construct the neighborhood ring region of each connected region formed by the response clusters in the initial hierarchical damage allocation result; when the connected region and the neighborhood ring region satisfy... When the connected region is determined to be a spatially isolated region, if the average flight time of the spatially isolated region is different from the interlayer interface number... The difference in the baseline flight time is the smallest, and the number is... If the pixel proportion is highest within the neighboring ring region, then the spatially isolated region is renumbered. If the centroid distance between a connected region and the nearest region with the same number is less than a preset connection threshold, the connected region and the nearest region with the same number are merged through morphological connection or region merging.

[0107] in, For numbering, For the first The average flight time of each response cluster The reference flight time is the time of flight of the back wall echo of the non-destructive region under frontal scanning conditions, and the reference flight time of each interlayer interface. The reference flight time is the time of flight of the back wall echo of the non-destructive region under reverse scanning conditions, and the reference flight time of each interlayer interface.

[0108] In some implementations, threshold segmentation, template matching, or supervised learning classification methods can be directly used to assign pixels to candidate interlayer interfaces.

[0109] In another exemplary embodiment of this application, after the above processing, observable layer damage allocation results of the undamaged region and each candidate interlayer interface are obtained. The undamaged region is denoted as... The observable layered damage region at each candidate interlayer interface is denoted as... . This indicates that under the current TOF information, it can be directly assigned to the [number]th [unit]. Layered damage areas at interlayer interfaces.

[0110] Based on the obtained lossless region and observable delamination damage areas at the interfaces between layers. For each candidate interlayer interface, a known damaged region (observable layered damaged region), a known undamaged region (referred to as the undamaged region), and an occluded region are constructed. For the first... The known damaged area of ​​each interlayer interface is defined as: .

[0111] This application considers region classification under single-sided scanning conditions and region classification under double-sided scanning conditions, so the above step 105 can be replaced by the following steps 601 to 602.

[0112] Step 601: Under single-sided scanning conditions, if the planar position Determined as the first The observable delamination damage area at each interlayer interface, then the planar location The regional classification at the interfaces between each layer satisfies: ; ; ; in, Indicates the first Observable delamination damage areas at interlayer interfaces Indicates the first Undamaged areas at interlayer interfaces Indicates the first The occlusion area of ​​the interface between layers; Each planar location within the non-destructive region is defined as an undamaged region at each interlayer interface, forming the region classification result for each interlayer interface under single-sided scanning conditions; that is... .

[0113] Step 602: Under double-sided scanning conditions, set the planar position. The corresponding interlayer interface number in the frontal scan is The corresponding interlayer interface number in the reverse scan is Then we have: .

[0114] when At that time, located and The interlayer interface numbered between layers is defined as the occlusion area, and the planar position located on the outer side and assigned to the undamaged area is defined as the undamaged area; the outer side refers to... and Interlayer interfaces outside of the formed consecutively numbered areas.

[0115] For example: when When the two layers are in contact, the interlayer interface is defined as the occlusion region, that is: .

[0116] The location on the outer side and assigned to the back wall echo class is defined as the known undamaged area, i.e.: .

[0117] when At that time, there were: .serial number The interlayer interfaces other than those are defined as undamaged areas.

[0118] Therefore, for the first The interface between layers is used to obtain the region classification results: .

[0119] The output of this step is a region classification map of the interfaces between each candidate layer, which provides input for subsequent reconstruction of occluded regions.

[0120] In another exemplary embodiment of this application, based on the obtained region classification results of each interlayer interface, the shading region is reconstructed layer by layer to obtain the complete delamination damage distribution of each interlayer interface of the composite laminate, specifically including the following steps: ① Constructing model input The region classification results of each interlayer interface obtained in step S4 are stacked by channel to form the input tensor: ; in, , and These represent the encoding results for known damaged areas, known undamaged areas, and occluded areas, respectively. Simultaneously, the laminate layup information is encoded into a layup input tensor. This includes information on the ply angles of each layer.

[0121] For those with A laminated slab with multiple layers, wherein the ply angles of each layer are as follows: Then the plying information can be represented as a feature vector. And further extended to ply input tensors. .

[0122] Ultimately, the input to the machine learning model is represented as .

[0123] ② Establish and train a layer-by-layer reconstruction model of the occluded region. Constructing a layer-by-layer reconstruction model of occlusion regions based on U-Net The model comprises three parts: an encoder, a decoder, and skip connections between them. The encoder performs layer-by-layer downsampling feature extraction on the input region classification results and layered information to obtain damage feature representations at different scales. The decoder performs layer-by-layer upsampling recovery on the encoded deep features to reconstruct the hierarchical damage spatial distribution within the occluded region. Skip connections directly pass features of the corresponding scale from the encoder to the decoder to preserve damage boundaries, local shape, and spatial location information, thereby improving the fineness and accuracy of the occluded region reconstruction results.

[0124] The model is trained using region classification results and layer information as input, and the actual layer damage distribution at each interlayer interface as training labels. The training labels are denoted as: ; in, Indicates the first The true delamination damage labels of the interlayer interfaces. For the model input Its output is represented as: ; in, ; Indicates the first The predicted damage results or damage probability distribution of each interlayer interface. The machine learning model can be trained based on simulation data, experimental data, or a mixture of simulation and experimental data.

[0125] ③ Reconstruct the occluded area layer by layer. The trained machine learning model is used to predict the occlusion areas at the interfaces between layers. For the first... Interlayer interfaces can be accessed via thresholds. right Binarization is performed to obtain the first... Reconstruction results of damaged areas at interlayer interfaces within the occluded region: .

[0126] ④ Integrate known regions with reconstruction results The known damaged area is fused with the obtained occlusion area reconstruction result to obtain the first... Complete layered damage distribution results at each interlayer interface : .

[0127] ⑤ Output the final layer-by-layer damage reconstruction results After the above processing, the complete delamination damage distribution results of each candidate interlayer interface of the composite laminate are obtained, denoted as: .

[0128] Therefore, the final output result is the complete delamination damage distribution result of each interlayer interface of the composite laminate. This allows for the reconstruction of the layer-by-layer damage distribution within the composite laminate from the results of two-dimensional ultrasonic C-scan.

[0129] The machine learning model used in the layer-by-layer reconstruction model of occlusion regions is not necessarily limited to U-Net. It can also employ fully convolutional networks (FCNs), encoder-decoder networks, residual networks, Transformer networks, diffusion models, or a combination of traditional machine learning models and image reconstruction algorithms to predict occlusion regions. The training data is also not limited to the current combination of simulation and experimental data; it can also be trained using pure simulation data, pure experimental data, or a hybrid augmented dataset of both.

[0130] The key points of this application are: 1. Overall technical approach for reconstructing layer-by-layer impact delamination damage of composite laminates based on ultrasonic C-scan results: This application does not only characterize the overall damage projection range obtained by ultrasonic C-scan, but further transforms the ultrasonic time-of-flight information into the layer-by-layer delamination damage distribution results of each interlayer interface.

[0131] 2. Interlayer interface allocation method based on candidate interlayer interface benchmark TOF and cluster analysis: This application establishes benchmark TOF corresponding to candidate interlayer interfaces and back wall echoes, and combines the TOF response clustering results to realize the corresponding allocation of ultrasonic response to specific interlayer interfaces.

[0132] 3. Layer-by-layer region classification method for acoustic occlusion effect: This application addresses the problem of shallow layer occlusion of deep echoes by classifying the regions on the interface between layers into known damaged regions, known undamaged regions, and occluded regions, providing a basis for subsequent layer-by-layer reconstruction.

[0133] 4. A method for layer-by-layer reconstruction of occluded regions by combining region coding, ply information and machine learning models: This application uses known region information, ply structure information and machine learning models to predict and restore layer-by-layer damage in occluded regions that cannot be directly observed by ultrasound.

[0134] 5. A unified reconstruction method compatible with single-sided and double-sided scanning: This application can acquire and process data according to different detection conditions of single-sided or double-sided accessibility of components, and realize layer-by-layer damage reconstruction under a unified framework.

[0135] 6. Layer-by-layer characterization method for outputting complete delamination damage results at each interlayer interface: The final result obtained in this application is the complete delamination damage distribution result at each interlayer interface of the composite laminate, which can be used for subsequent damage visualization, area statistics and mechanical analysis.

[0136] The advantages of this application are as follows: 1. This application enables layer-by-layer reconstruction of impact delamination damage in composite laminates based solely on ultrasonic C-scan results: Existing technologies, based solely on ultrasonic C-scan results, typically only obtain a two-dimensional projection range of the damage, making it difficult to accurately characterize the layer-by-layer delamination damage distribution at the interlayer interfaces within the composite laminate. This application, through preprocessing, interlayer interface allocation, region classification, and layer-by-layer reconstruction of ultrasonic C-scan time-of-flight information, extends the ultrasonic detection results from two-dimensional projection damage characterization to layer-by-layer delamination damage characterization in the thickness direction. Therefore, it enables layer-by-layer reconstruction of delamination damage at the interlayer interfaces of composite laminates without relying on other high-cost three-dimensional imaging methods.

[0137] 2. This application can reduce the impact of damage superposition at different interlayer interfaces and acoustic obstruction on damage identification results, thereby improving the completeness and accuracy of layer-by-layer damage characterization: Since existing ultrasonic C-scan methods are essentially based on two-dimensional projection analysis, layered damage at different interlayer interfaces easily superimposes in the same planar result. Simultaneously, shallow damage can obstruct deep echoes, making it difficult to determine specific damage layers and reliably identify deep damage. This application establishes a candidate interlayer interface benchmark Time-of-Flight (TOF) and combines it with cluster analysis to allocate interlayer interfaces. Furthermore, it divides the regions on each interlayer interface into known damaged areas, known undamaged areas, and obstructed areas, and reconstructs the obstructed areas layer by layer. Therefore, it can more effectively distinguish damage information at different interlayer interfaces and recover some deep layered damage results that are difficult to observe directly, thereby improving the completeness and accuracy of damage identification.

[0138] 3. This application, while maintaining damage characterization capabilities, possesses superior engineering applicability and application value: Existing technologies for obtaining thickness-direction damage information often rely on equipment such as X-ray CT. While these methods can provide relatively complete three-dimensional damage information, they suffer from high detection costs, low efficiency, stringent equipment requirements, and poor applicability in engineering settings. This application, based on ultrasonic C-scan results, achieves layer-by-layer damage reconstruction without relying on X-ray CT layer-by-layer imaging. This not only reduces dependence on high-cost detection equipment but also outputs complete layered damage distribution results at the interfaces between layers. This can be further used for fine characterization of impact damage, analysis of compression failure mechanisms, assessment of structural residual strength, and maintenance decision-making, thus possessing high engineering application value.

[0139] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 4As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores the complete delamination damage distribution results of each interlayer interface. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a layer-by-layer reconstruction method for impact delamination damage in composite laminates based on ultrasonic C-scan results.

[0140] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer equipment to which the present application is applied. Specific computer equipment may include, for example, [the following is a list of possible additional structures]. Figure 4 The embodiments show more or fewer components, combinations of certain components, or different component arrangements. In one exemplary embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, which the processor executes to implement the steps in the above-described method embodiments.

[0141] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0142] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0143] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0144] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0145] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0146] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0147] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for reconstructing impact delamination damage of a composite laminate based on ultrasonic C-scan results, characterized in that, include: Time-of-flight data of the composite laminate under test after impact were obtained by ultrasonic C-scan. Determine the interlayer interfaces and reference flight times of each interlayer interface of the composite laminate under test; The flight time data is clustered, and the average flight time of each response cluster is determined. Based on the average flight time of each response cluster and the baseline flight time of each interlayer interface, the undamaged region and the observable layered damage region of each interlayer interface are determined. Based on the undamaged area and the observable layered damage area at each interlayer interface, the region classification result of each interlayer interface is determined; the region classification result includes observable layered damage area, undamaged area, and occluded area; Using the region classification results and the layup information of the composite laminate to be tested as input, the model is reconstructed layer by layer in the shading region to predict the damage area of ​​each interlayer interface in the shading region. By fusing the observable layered damage regions and the predicted damage regions within the occlusion regions at each interlayer interface, a complete layered damage distribution result for each interlayer interface is obtained.

2. The method according to claim 1, wherein, Ultrasonic C-scan was used to acquire time-of-flight data of the composite laminate after impact, including: The scanning method is determined based on the accessibility of both sides of the composite laminate being tested; the scanning method includes single-sided ultrasonic C-scan and double-sided ultrasonic C-scan. When the scanning method uses single-sided ultrasonic C-scan, the original time-of-flight data of one side of the composite laminate under test after impact are obtained. The original flight time data of one side is preprocessed to obtain the preprocessed flight time data of one side, which is then used as the flight time data of the composite laminate to be tested after impact. When the scanning method uses double-sided ultrasonic C-scan, the original time-of-flight data of the front and back sides of the composite laminate under test after impact are obtained. Planar registration is performed on the original flight time data of the front and back sides to obtain the registered flight time data of the front and back sides; The flight time data of the registered front and back sides are preprocessed to obtain preprocessed flight time data of the front and back sides; The inconsistencies in the flight time data of the front and back sides after preprocessing are corrected to obtain the final flight time data of the front and back sides, which is then used as the flight time data of the composite laminate to be tested after impact.

3. The method according to claim 1, wherein, Determine the interlayer interfaces and reference flight times of each interlayer interface of the composite laminate under test, including: Based on the number of plies and the thickness of each ply of the composite laminate to be tested, the interlayer interfaces inside the composite laminate to be tested are determined. Under the condition of frontal scanning of the composite laminate under test, the formula is used. The reference flight time of each interlayer interface under frontal scanning conditions is obtained; where, For the frontal scan condition, the first Reference flight time of each interlayer interface The equivalent propagation velocity of ultrasound in the composite laminate under test is given. For the first The depth of the interface between each layer from the front surface , For the first Layer thickness; Under the condition of reverse scanning of the composite laminate under test, the formula is used. The reference flight time of each interlayer interface under reverse scanning conditions is obtained; where, For the reverse scanning condition, the first The baseline flight time of each candidate interlayer interface The total thickness of the composite laminate to be tested; Using formula Determine the reference flight time corresponding to the back wall echo of the non-destructive region under frontal or reverse scanning conditions; where, This is the reference time of flight for the backwall echo of the non-destructive region under frontal scanning conditions. This is the reference flight time corresponding to the back wall echo of the non-destructive region under reverse scanning conditions.

4. The method according to claim 1, wherein, Clustering the flight time data and determining the average flight time for each response cluster obtained from the clustering includes: Establish feature vectors for the plane positions on the composite material laminate to be tested; the feature vectors include the coordinates of each plane position and the time-of-flight data of each plane position; The feature vector is normalized to obtain a normalized feature vector; Clustering the normalized feature vectors of all planar locations yields multiple response clusters; The average flight time of each response cluster is determined based on the normalized eigenvector of the planar position within each response cluster.

5. The method according to claim 1, wherein, Based on the average flight time of each response cluster and the baseline flight time of each interlayer interface, the undamaged region and the observable layered damage regions of each interlayer interface are determined, including: Determine the reference flight time corresponding to the back wall echo of the non-destructive region; Calculate the difference between the average flight time of each response cluster and the reference flight time corresponding to the backwall echo of the undamaged region and the reference flight time of each interlayer interface. If the difference between the average flight time of the response cluster and the reference flight time corresponding to the backwall echo of the undamaged region is the smallest, then the response cluster is determined to be an undamaged region. If the difference between the average flight time of the response cluster and the reference flight time of the interlayer interface is the smallest, the response cluster is determined as the observable layered damage region of the corresponding interlayer interface, thereby obtaining the initial layered damage allocation result of each interlayer interface. Abnormal noise regions in the initial layered damage allocation results of each interlayer interface are removed, and spatially isolated regions in the initial layered damage allocation results are corrected to obtain the final observable layered damage regions of each interlayer interface.

6. The method according to claim 5, wherein, Correcting spatially isolated regions in the initial hierarchical damage assignment results, including: Under frontal scanning conditions, according to the formula Determine the number of the inter-layer interface corresponding to each response cluster; where, For numbering, For the first The average flight time of each response cluster The reference flight time is the time of flight of the back wall echo of the non-destructive region under frontal scanning conditions, and the reference flight time of each interlayer interface. Under the backside scanning condition, the number of the interlayer interface corresponding to each response cluster is determined according to the formula , wherein, is the reference flight time corresponding to the backwall echo of the lossless area under the backside scanning condition and the reference flight time of each interlayer interface. Construct neighborhood ring regions of each connected region formed by the response clusters in the initial hierarchical damage allocation results; When the connected region and the neighboring annular region satisfy When this occurs, the connected region is determined to be a spatially isolated region; among which, This represents the percentage of pixels with the same number as those in the connected region within the neighboring ring area. This represents the centroid distance between the neighboring annular region and the nearest connected region with the same number. The neighborhood support threshold, This is the spatial isolation distance threshold; If the average flight time of an isolated space region is related to the interlayer interface number... The difference in the baseline flight time is the smallest, and the number is... If the pixel proportion is highest within the neighboring ring region, then the spatially isolated region is renumbered. ; If the centroid distance between a connected region and the nearest region with the same number is less than a preset connection threshold, the connected region and the nearest region with the same number are merged through morphological connection or region merging.

7. The method according to claim 1, wherein, Based on the undamaged area and the observable layered damage areas at each interlayer interface, the region classification results for each interlayer interface are determined, including: Under single-sided scanning conditions, if the planar position Determined as the first The observable delamination damage area at each interlayer interface, then the planar location The regional classification at the interfaces between layers satisfies: ； ； ； in, Indicates the first Observable delamination damage areas at interlayer interfaces Indicates the first Undamaged areas at interlayer interfaces Indicates the first The occlusion area of ​​the interface between layers; Each planar position in the non-destructive region is defined as an undamaged region on each interlayer interface, forming the region classification result of each interlayer interface under single-sided scanning conditions; In the case of double-sided scanning, let the plane position In the case of front-side scanning, the corresponding interlayer interface is numbered as In the case of back-side scanning, the corresponding interlayer interface is numbered as ; when At that time, located and The interlayer interface numbered between layers is defined as the occlusion area, and the planar position located on the outer side and assigned to the undamaged area is defined as the undamaged area; the outer side refers to... and Interlayer interfaces outside of the formed consecutively numbered areas; when At that time, number The interlayer interfaces other than those are defined as undamaged areas.

8. The method according to claim 1, wherein, The layer-by-layer reconstruction model of the occluded region is obtained by using a machine learning model, with the region classification results and ply information of each layer interface as input, and the actual layer damage distribution of each layer interface as labels.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes the computer program to implement the layer-by-layer reconstruction method for impact delamination damage of composite laminates based on ultrasonic C-scan results, as described in any one of claims 1-8.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, When executed by a processor, the computer program implements the layer-by-layer reconstruction method for impact delamination damage of composite laminates based on ultrasonic C-scan results, as described in any one of claims 1-8.

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