A composite material detection system, control method, device and medium thereof

Abstract

The application relates to the technical field of material detection, and discloses a composite material detection system, a control method, equipment and a medium, which comprise a detector module, an X-ray source, a transverse adjusting mechanism, a longitudinal adjusting mechanism, a fine adjustment mechanism and a control unit; the detector module, the X-ray source, the transverse adjusting mechanism, the longitudinal adjusting mechanism and the fine adjustment mechanism are electrically connected with the control unit; a composite material layer to be detected is arranged between the detector module and the X-ray source; the X-ray source is connected with the fine adjustment mechanism; and the fine adjustment mechanism is used for adjusting the emitting position and the emitting angle of the X-ray source. The application can guarantee the detection effect of the detector module, improve the detection accuracy, and further meet the real-time detection of defects of the composite material in the automatic layering process, and solve the problems of insufficient adaptability and inability to accurately identify defects in the prior art.

Description

Technical Field

[0001] This application relates to the field of materials testing technology, and in particular to a composite material detection system and its control method, equipment and medium. Background Technology

[0002] With the increasing demand for lightweight, high-strength materials in high-performance structural fields such as aerospace, automotive, and energy, various types of composite materials, including carbon fiber, have gained widespread application due to their superior performance. However, during the automated layup process of composite materials, internal defects such as porosity, delamination, and fiber misalignment often occur, which may affect the mechanical properties, structural stability, and safety of the final product.

[0003] While existing detection systems (such as ultrasonic testing and infrared testing) can inspect the interior of composite materials, their detection performance is relatively poor. During automated layup, the number of layers in the composite material continuously accumulates, and due to its complex structure, existing detection systems cannot accurately detect changes in the composite material layers and its own complex structure during automated layup, leading to inaccurate test results. Therefore, existing detection systems suffer from insufficient adaptability to automated layup processes and are unable to accurately identify defects. Summary of the Invention

[0004] This application provides a composite material detection system and its control method, equipment and medium to solve one or more technical problems existing in the prior art, and at least provide a beneficial option or create conditions.

[0005] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0006] According to one aspect of the embodiments of this application, a composite material detection system is provided, the composite material detection system comprising: a detector module, an X-ray source, a lateral adjustment mechanism, a longitudinal adjustment mechanism, a fine-tuning mechanism, and a control unit; the detector module, the X-ray source, the lateral adjustment mechanism, the longitudinal adjustment mechanism, and the fine-tuning mechanism are all electrically connected to the control unit;

[0007] A composite material layer to be detected is disposed between the detector module and the X-ray source. The X-ray source is connected to the fine-tuning mechanism, which is used to adjust the emission position and emission angle of the X-ray source.

[0008] The fine-tuning mechanism is mounted on the lateral adjustment mechanism and is slidably connected to the lateral adjustment mechanism; the longitudinal adjustment mechanism includes a guide rail and a support frame, the lateral adjustment mechanism is fixed on the support frame and is perpendicular to the support frame; the bottom of the support frame is mounted on the guide rail and is slidably connected to the guide rail.

[0009] The planar position and angle of the detector module are adjusted by the control unit, and the plane of the detector module is always perpendicular to the emission direction of the X-ray source.

[0010] During the detection of the composite material layer, the emission position and emission angle of the X-ray source are continuously adjusted so that each area of ​​the composite material layer is transmitted by the X-ray source, forming a transmission signal; the detector module detects the transmission signal, forms a transmission image signal, and sends the transmission image signal to the control unit.

[0011] In one embodiment of this application, based on the foregoing scheme, the composite material detection system further includes a worktable, the worktable including a base, a first rotating shaft, a first rotatable telescopic rod, a drive mechanism, and a second rotating shaft; the first rotating shaft is disposed on the base and rotatably connected to the first rotatable telescopic rod; the first rotatable telescopic rod is connected to the drive mechanism and the second rotating shaft respectively, and the second rotating shaft is connected to the detector module.

[0012] In one embodiment of this application, based on the foregoing scheme, the detector module includes a support plate and a detection sensor. The detection sensor is fixed on the support plate, and the support plate is rotatably connected to the second rotating shaft. The planar position and planar angle of the support plate are adjusted by the second rotating shaft. The first rotatable telescopic rod is extended and retracted by the drive mechanism and / or rotated on the first rotating shaft by the first rotatable telescopic rod to adjust the position and angle of the second rotating shaft, so that the plane of the detection sensor on the support plate remains perpendicular to the emission direction of the X-ray source.

[0013] In one embodiment of this application, based on the aforementioned scheme, the lateral movement mechanism includes a lateral beam and a sliding unit. The lateral beam is fixed to the support frame and is arranged perpendicularly to the support frame. The sliding unit is slidably connected to the lateral beam and fixedly connected to the fine-tuning mechanism.

[0014] In one embodiment of this application, based on the foregoing scheme, the fine-tuning mechanism includes a second rotatable telescopic rod, a hydraulic drive unit, a horizontal rotation joint, a vertical rotation joint, a vertical connecting shaft, and a rotating connecting rod; the second rotatable telescopic rod is connected to the sliding unit, the hydraulic drive unit, and the horizontal rotation joint respectively; the horizontal rotation joint is rotatably connected to the vertical connecting shaft, and the vertical connecting shaft is rotatably connected to the vertical rotation joint; the rotating connecting rod is rotatably connected to the vertical rotation joint and is connected to the X-ray source.

[0015] According to one aspect of this application, a control method for a composite material detection system is proposed, the method being executed in the aforementioned control unit, the method comprising:

[0016] When the plane of the detector module is perpendicular to the emission direction of the X-ray source, the transmission image signal of the composite material layer acquired by the detector module is received.

[0017] The abnormal information of the composite material layer is determined based on the transmitted image signal;

[0018] Based on the abnormal information, parameter adjustment information for the composite material laying equipment is determined, so that the composite material laying equipment adjusts the laying parameters of the composite material layer according to the parameter adjustment information.

[0019] In one embodiment of this application, based on the foregoing scheme, determining the anomalous information of the composite material layer according to the transmitted image signal includes:

[0020] The composite material layer is divided into grid regions of a preset format based on the transmitted image signal, and the grid regions include multiple grids;

[0021] For each grid, multiple predicted bounding boxes are determined. Based on a preset deep learning algorithm, the position parameters, confidence parameters, and anomaly category probability parameters of each predicted bounding box are obtained. The anomaly information of the grid is determined based on each of the position parameters, the confidence parameters, and the anomaly category probability parameters.

[0022] The abnormal information of the composite material layer is determined based on the abnormal information of each of the grids.

[0023] In one embodiment of this application, based on the foregoing scheme, determining the anomaly information of the grid according to each of the location parameters, the confidence parameter, and the anomaly category probability parameter includes:

[0024] The target position parameter is determined from each of the position parameters according to the preset positioning loss function;

[0025] The target confidence parameter is determined from each of the confidence parameters according to the preset confidence loss function;

[0026] The target anomaly category probability parameter is determined from each of the anomaly category probability parameters according to the preset anomaly category loss function;

[0027] The anomaly information of the grid is determined based on the target location parameter, the target confidence parameter, and the target anomaly category probability parameter.

[0028] According to one aspect of the embodiments of this application, a computer-readable storage medium is provided that stores a computer program thereon, the computer program including executable instructions that, when executed by a processor, implement the method described in the above embodiments.

[0029] According to one aspect of the embodiments of this application, an electronic device is provided, including: one or more processors; and a memory for storing executable instructions of the processors, which, when executed by the one or more processors, cause the one or more processors to perform the method as described in the above embodiments.

[0030] The beneficial effects of this application are as follows: The control unit can control the lateral adjustment mechanism, longitudinal adjustment mechanism, and fine-tuning mechanism to achieve omnidirectional movement of the X-ray source, enabling the X-ray source to quickly reach the required position. The fine-tuning mechanism can also quickly adjust the required emission angle of the X-ray source, thus forming a cooperative relationship with the detector module. This allows the X-rays emitted by the source to penetrate the composite material layer and be detected by the detector module, forming a transmission image signal. The control unit can analyze the received transmission image signal to determine whether defects have occurred in the composite material layer, and the type and location of the defects. During the continuous automatic layup of the composite material, the volume of the composite material layer increases with the accumulation of layers. At this time, the emission position and angle of the X-ray source can be adaptively adjusted by controlling the lateral adjustment mechanism, longitudinal adjustment mechanism, and fine-tuning mechanism. Simultaneously, the detector module is kept perpendicular to the emission direction of the X-ray source, ensuring the detection effect of the detector module and improving the accuracy of detection. This satisfies the requirement for real-time detection of defects in the composite material during automatic layup, solving the problems of insufficient adaptability and inaccurate defect identification in existing technologies. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly explained below. Obviously, the described drawings are only a part of the embodiments of this application, and not all of them. Those skilled in the art can obtain other design schemes and drawings based on these drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of the overall composite material detection system according to an embodiment of this application;

[0033] Figure 2 This is a top-view perspective view of a composite material detection system according to an embodiment of this application;

[0034] Figure 3 This is a schematic diagram of the workbench and detector module according to an embodiment of this application;

[0035] Figure 4 This is an overall structural diagram of the fine-tuning mechanism shown in the embodiments of this application;

[0036] Figure 5 This is a schematic diagram illustrating the rotation direction of a horizontal rotary joint according to an embodiment of this application;

[0037] Figure 6 This is a schematic diagram illustrating the rotation direction of a vertical rotating joint according to an embodiment of this application;

[0038] Figure 7 This is a diagram illustrating the connection relationship between the guide rail and the support frame according to an embodiment of this application;

[0039] Figure 8 This is a flowchart illustrating a control method for a composite material detection system according to an embodiment of this application;

[0040] Figure 9 This is a schematic diagram of the system structure of an electronic device according to an embodiment of this application.

[0041] Figure Labels

[0042] X-ray source 1, detector module 2, detection sensor 21, support plate 22, lateral adjustment mechanism 3, lateral beam 31, sliding unit 32, longitudinal adjustment mechanism 4, control unit 5, composite material layer 6, worktable 7, base 71, first rotating shaft 72, first rotatable telescopic rod 73, drive mechanism 74, second rotating shaft 75, fine adjustment mechanism 8, second rotatable telescopic rod 81, hydraulic drive unit 82, horizontal rotating joint 83, vertical rotating joint 84, vertical connecting shaft 85, rotating connecting rod 86. Detailed Implementation

[0043] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this application will be more complete and comprehensive, and will fully convey the concept of the exemplary embodiments to those skilled in the art.

[0044] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0045] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller node devices.

[0046] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0047] It should be noted that "multiple" in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0048] The following is a detailed description of the vortex-induced vibration suppression system proposed in the embodiments of this application:

[0049] like Figure 1 As shown, Figure 1 This is a schematic diagram of the overall composite material detection system according to an embodiment of this application. The composite material detection system includes a detector module 2, an X-ray source 1, a lateral adjustment mechanism 3, a longitudinal adjustment mechanism 4, a fine-tuning mechanism 8, and a control unit 5; the detector module 2, X-ray source 1, lateral adjustment mechanism 3, longitudinal adjustment mechanism 4, and fine-tuning mechanism 8 are all electrically connected to the control unit 5.

[0050] A composite material layer 6 to be detected is provided between the detector module 2 and the X-ray source 1. The X-ray source 1 is connected to the fine-tuning mechanism 8, which is used to adjust the emission position and emission angle of the X-ray source 1.

[0051] The fine-tuning mechanism 8 is mounted on the lateral adjustment mechanism 3 and is slidably connected to the lateral adjustment mechanism 3; the longitudinal adjustment mechanism 4 includes a guide rail and a support frame, the lateral adjustment mechanism 3 is fixed on the support frame and is perpendicular to the support frame; the bottom of the support frame is mounted on the guide rail and is slidably connected to the guide rail;

[0052] The planar position and angle of the detector module 2 are adjusted by the control unit 5, and the plane of the detector module 2 is always perpendicular to the emission direction of the X-ray source 1.

[0053] During the detection of the composite material layer 6, the emission position and emission angle of the X-ray source 1 are continuously adjusted so that each area of ​​the composite material layer 6 is transmitted by the X-ray source 1, forming a transmission signal; and the detector module 2 detects the transmission signal, forms a transmission image signal, and sends the transmission image signal to the control unit 5.

[0054] Specifically, such as Figure 2 As shown, Figure 2 That is, a top-down view of the composite material detection system. Figure 2 The Y-axis direction is the direction of the guide rail of the longitudinal adjustment mechanism 4. The entire composite material detection system can be moved in the Y-axis direction by sliding the support frame on the guide rail. Then, the fine-tuning mechanism 8 can move along the X-axis on the lateral adjustment mechanism 3. It should be noted that the plane formed by the X-axis and Y-axis is a horizontal plane, or a plane parallel to the horizontal plane. Figure 7 This is a diagram showing the connection relationship between the guide rail and the support frame.

[0055] Furthermore, after the X-ray source 1 can be adjusted along the X-axis and Y-axis directions of the horizontal plane, the fine-tuning mechanism 8 can also adjust the position in the Z-axis direction (the normal axis perpendicular to the horizontal plane). At the same time, the emission angle of the X-ray source 1 can be adjusted by the fine-tuning mechanism 8. The emission angle has two dimensions of adjustment. The first dimension is rotation along the horizontal plane, with an adjustable angle of 360°. The second dimension is rotation along the Z-axis, where the angle can also be adjusted arbitrarily. Thus, the fine-tuning mechanism 8 can achieve all-round angle adjustment. Together with the horizontal adjustment mechanism 3, the vertical adjustment mechanism 4, and the fine-tuning mechanism 8 that can adjust the position in the Z-axis direction, the emission position and emission angle of the X-ray source 1 can be arbitrarily adjusted.

[0056] Furthermore, during the detection of the composite material layer 6, as the composite material in the composite material layer 6 is continuously laid, the volume and structure of the composite material layer 6 are also constantly changing. At this time, the emission position and emission angle of the X-ray source 1 are continuously adjusted so that the emission direction of the X-ray source 1 is always perpendicular to the plane of the detector module 2. At the same time, by adjusting the emission position of the X-ray source 1, a suitable distance is maintained between the X-ray source 1 and the composite material layer 6, ensuring that the X-ray source 1 has a good transmission effect on the composite material layer. As a result, the transmission image signal acquired by the detector module 2 has high accuracy, and the parameters such as resolution and clarity also meet the requirements of good performance parameters.

[0057] In one embodiment of this application, the composite material detection system further includes a worktable 7, which includes a base 71, a first rotating shaft 72, a first rotatable telescopic rod 73, a drive mechanism 74, and a second rotating shaft 75. The first rotating shaft 72 is disposed on the base 71 and is rotatably connected to the first rotatable telescopic rod 73. The first rotatable telescopic rod 73 is connected to the drive mechanism 74 and the second rotating shaft 75, respectively, and the second rotating shaft 75 is connected to the detector module 2.

[0058] Specifically, a schematic diagram of the workbench 7 and the detector module 2 can be shown as follows: Figure 3 As shown, the first rotating shaft 72 is mounted on the base 71 and is slidably connected to the base 71. This means the position of the detector module 2 can be adjusted by sliding the first rotating shaft 72 on the upper surface of the base 71. The first rotatable telescopic rod 73 can rotate both around the first rotating shaft 72 and around the second rotating shaft 75, which is connected to the detector module 2. The length of the first rotatable telescopic rod 73 can be extended or retracted by the drive mechanism 74, thereby adjusting the position of the second rotating shaft 75, and thus the position of the detector module 2. When the detector module 2 is far from the composite material layer 6, it can be brought closer to the composite material layer 6 by extending the first rotatable telescopic rod 73, resulting in more accurate and better-quality transmission image signals received by the detector module 2. The drive mechanism 74 can specifically be a drive compression cylinder.

[0059] In one embodiment of this application, the detector module 2 includes a support plate 22 and a detection sensor 21. The detection sensor 21 is fixed on the support plate 22, and the support plate 22 is rotatably connected to the second rotating shaft 75. The planar position and planar angle of the support plate 22 are adjusted by the second rotating shaft 75. The first rotatable telescopic rod 73 is extended and retracted by the drive mechanism 74 and / or rotated on the first rotating shaft 72 by the first rotatable telescopic rod 73 to adjust the position and angle of the second rotating shaft 75, so that the plane of the detection sensor 21 on the support plate 22 remains perpendicular to the emission direction of the X-ray source 1.

[0060] Specifically, the detection sensor 21 is fixed to the support plate 22, which is rotatably connected to the second rotating shaft 75. Therefore, the position of the detection sensor 21 can be adjusted simply by rotating the second rotating shaft 75 and extending / retracting the first rotatable telescopic rod 73. The planar position of the support plate 22 needs to maintain an appropriate distance from the composite material layer 6, neither too far nor too close. At the same time, the planar angle of the support plate 22 (that is, the planar angle of the detector) needs to be parallel to the composite material layer 6. In this way, the detection effect is good. Therefore, the planar position and planar angle of the support plate 22 are adjusted by the second rotating shaft 75, and the first rotatable telescopic rod 73 is extended / retracted by the drive mechanism 74 and / or rotated on the first rotating shaft 72 by the first rotatable telescopic rod 73 to adjust the position and angle of the second rotating shaft 75, so that the plane of the detection sensor 21 on the support plate 22 is perpendicular to the emission direction of the X-ray source 1.

[0061] In one embodiment of this application, the lateral movement mechanism includes a lateral beam 31 and a sliding unit 32. The lateral beam 31 is fixed to the support frame and is arranged perpendicular to the support frame. The sliding unit 32 is slidably connected to the lateral beam 31 and fixedly connected to the fine-tuning mechanism 8.

[0062] Specifically, the transverse beam 31 is fixed to the support frame, which can be arranged perpendicularly to the transverse beam 31. This allows for adjustment of the X-ray source 1 in two horizontal directions, namely, laterally and longitudinally. The sliding unit 32 is slidably connected to the transverse beam 31, meaning the fine-tuning mechanism 8 can be fixed to the sliding unit 32. The emission position of the X-ray source 1 is adjusted by connecting the sliding unit 32 to the transverse beam 31.

[0063] In one embodiment of this application, the fine-tuning mechanism 8 includes a second rotatable telescopic rod 81, a hydraulic drive unit 82, a horizontal rotation joint 83, a vertical rotation joint 84, a vertical connecting shaft 85, and a rotating connecting rod 86; the second rotatable telescopic rod 81 is connected to the sliding unit 32, the hydraulic drive unit 82, and the horizontal rotation joint 83 respectively; the horizontal rotation joint 83 is rotatably connected to the vertical connecting shaft 85, and the vertical connecting shaft 85 is rotatably connected to the vertical rotation joint 84; the rotating connecting rod 86 is rotatably connected to the vertical rotation joint 84 and is connected to the X-ray source 1.

[0064] Specifically, refer to Figure 4 As shown, Figure 4 The diagram shows the overall structure of the fine-tuning mechanism 8, including a schematic diagram of the rotation direction of the horizontal rotating joint 83. Figure 5 As shown, a schematic diagram of the vertical rotation joint 84 is as follows: Figure 6 As shown, the rotation direction of the horizontal rotating joint 83 and the rotation direction of the vertical rotating joint 84 are in two different planes. Therefore, the rotation direction of the X-ray source 1 can be rotated in all directions, meaning the emission angle of the X-ray source 1 can be adjusted in all directions, greatly improving the adjustability of the emission angle of the X-ray source 1. The height of the horizontal rotating joint 83 can also be adjusted by driving the second rotatable telescopic rod 81 through the hydraulic drive unit 82. Changes in the height of the horizontal rotating joint 83 will inevitably lead to changes in the height of the vertical rotating joint 84, thereby adjusting the height of the X-ray source 1.

[0065] In summary, the composite material detection system proposed in this application can achieve large-scale positional adjustments through the lateral adjustment mechanism 3 and the longitudinal adjustment mechanism 4, enabling significant positional adjustments. The fine-tuning mechanism 8 allows for minor adjustments to the emission position and emission interface of the X-ray source 1. This allows the X-ray source 1 to quickly reach the desired position for transmission through the composite material layer 6. Simultaneously, the worktable 7 below the detector module 2 coordinates with the transmission of the X-ray source 1, resulting in excellent transmission image signals. The control unit 5 can then analyze these high-quality transmission image signals to identify defect parameters in the composite material layer 6, such as the location and type of defects (e.g., delamination, bubbles, fiber misalignment). The composite material detection system can automatically adjust the X-ray energy and emission angle emitted by the X-ray source 1 according to the material thickness and number of layers, ensuring uniform penetration of each composite material layer and obtaining high-quality layered imaging. Through the deep learning algorithm built into the control unit 5, the control unit 5 can automatically identify various defects in carbon fiber composite materials, such as delamination, pores, and fiber misalignment, and perform real-time classification and recording, generating accurate information on defect location, shape, and size. The system can work in conjunction with the composite material laying equipment to automatically adjust parameters such as layup pressure and speed according to the severity of defects, thereby reducing the occurrence of subsequent defects and ensuring the overall quality of automatic composite material layup.

[0066] According to one aspect of the embodiments of this application, a control method for a composite material detection system is provided, the method being executed in the control unit of the aforementioned composite material detection system. Figure 8 This is a flowchart of the control method for the composite material detection system proposed in this application, including steps S1-S3, which are described in detail below:

[0067] In step S1, with the plane of the detector module perpendicular to the emission direction of the X-ray source, the transmission image signal of the composite material layer acquired by the detector module is received.

[0068] Specifically, the X-ray source is only turned on to transmit the X-ray image signal to the composite material layer when the plane of the detector module is perpendicular to the emission direction of the X-ray source, that is, after the emission position and emission angle of the X-ray source are adjusted by the various mechanisms of the composite material detection system. At this time, the detector module can detect or acquire the transmission image signal of the composite material layer.

[0069] In step S2, the abnormal information of the composite material layer is determined based on the transmitted image signal.

[0070] In one embodiment of this application, determining the anomalous information of the composite material layer based on the transmitted image signal includes:

[0071] The composite material layer is divided into grid regions of a preset format based on the transmitted image signal, and the grid regions include multiple grids;

[0072] For each grid, multiple predicted bounding boxes are determined. Based on a preset deep learning algorithm, the position parameters, confidence parameters, and anomaly category probability parameters of each predicted bounding box are obtained. The anomaly information of the grid is determined based on each of the position parameters, the confidence parameters, and the anomaly category probability parameters.

[0073] The abnormal information of the composite material layer is determined based on the abnormal information of each of the grids.

[0074] Specifically, the transmission image signal can be a single image detected by the detector module. The transmission image signal corresponds to the transmission image of the composite material layer. Therefore, the composite material layer in the transmission image can be divided into a grid region of a preset format. The preset format can be a grid region of S×S, where S can be any positive integer. The grid region includes multiple grids, each grid corresponding to a specific region of the composite material layer. Each grid is responsible for predicting the target in a specific region.

[0075] The pre-defined deep learning algorithm can be a YOLOv11-based convolutional neural network, which extracts features from the obtained transmission image signal and labels the defect type. Each grid cell predicts multiple bounding boxes. Each bounding box includes three parameters: location parameter, confidence parameter, and anomaly category probability parameter. The location parameter includes: center coordinates. ,width ,high The confidence level parameter is... YOLOv11 predicts a class probability distribution for each bounding box. The anomaly class probability parameter is... , These correspond to the probability distributions for different defect categories (delamination, porosity, fiber misalignment, cracks). The prediction for each bounding box can be expressed as:

[0076] in, These are the coordinates of the bounding box center. It is the width of the bounding box. It is the height of the bounding box. It is a confidence parameter. The probability distributions correspond to different defect categories (delamination, porosity, fiber misalignment, cracks), and the positions and categories of multiple bounding boxes are predicted for each grid.

[0077] In one embodiment of this application, determining the anomaly information of the grid based on each of the location parameters, the confidence parameter, and the anomaly category probability parameter includes:

[0078] The target position parameter is determined from each of the position parameters according to the preset positioning loss function;

[0079] The target confidence parameter is determined from each of the confidence parameters according to the preset confidence loss function;

[0080] The target anomaly category probability parameter is determined from each of the anomaly category probability parameters according to the preset anomaly category loss function;

[0081] The anomaly information of the grid is determined based on the target location parameter, the target confidence parameter, and the target anomaly category probability parameter.

[0082] Specifically, a target bounding box is generated for each grid through regression analysis (anomaly information of the grid can be generated based on the target bounding box), and the coordinate information of the defect area and the defect category of the area can be obtained through the anomaly information of the grid.

[0083] The YOLOv11 loss function consists of several parts, primarily including localization loss, confidence loss, and classification loss. The specific form of the loss function is as follows:

[0084] in This is the localization loss of the bounding box, which measures the difference between the predicted bounding box and the true bounding box, and is usually calculated using the mean squared error (MSE). We can determine the target location parameters in the grid that have the highest predicted probability, which are closest to the true bounding box.

[0085] It is the confidence loss, which measures the difference between the predicted confidence parameter and the true confidence parameter for each bounding box. We can determine the target confidence parameter that has the highest predicted probability in the grid, which is the closest to the true confidence parameter.

[0086] This is the classification loss, which measures the difference between the predicted class and the true class, typically using the cross-entropy loss function. We can determine the target anomaly category probability parameter that has the highest predicted probability in the grid, which is the closest to the true category.

[0087] Furthermore, the target location parameters, target confidence parameters, and target anomaly category probability parameters constitute the anomaly information of the grid. This allows us to determine the location coordinates of the defects, as well as information such as the defect type, shape, and size. This information enables us to subsequently adjust the parameters of the automated layup equipment to avoid the generation of these defects. The anomaly information of the composite material layer is composed of the anomaly information of each individual grid. If a grid does not contain defects, no anomaly information is generated for that grid.

[0088] Furthermore, in the initial training phase of the deep learning algorithm, regarding dataset processing, a large amount of pre-collected image data of carbon fiber composite materials was used. These images included different types of defects, such as cracks, bubbles, and delamination. Each image was manually labeled to determine the location and type of the defect. The images in the dataset were preprocessed, standardized to a uniform size, and data augmentation operations were performed to improve the model's generalization ability. Data augmentation operations included, but were not limited to, image rotation, translation, cropping, and brightness adjustment. These operations helped improve the model's detection performance under different viewpoints and lighting conditions.

[0089] The YOLOv11 model was trained using a labeled dataset. During training, the model learned the features of various parts of the image and predicted the location and category of defects based on these features. After training, the YOLOv11 model can perform real-time detection on new composite material images, identify defects, and output the location parameters and anomaly category probability parameters (i.e., anomaly information of the mesh). This algorithm is suitable for real-time defect monitoring on carbon fiber composite material production lines and can reduce the errors and missed detection rates of manual inspection.

[0090] In step S3, parameter adjustment information for the composite material laying equipment is determined based on the abnormal information, so that the composite material laying equipment adjusts the laying parameters of the composite material layer according to the parameter adjustment information.

[0091] Specifically, the control unit can also interact with the composite material laying equipment. The abnormal information of the composite material layer generated by the control unit can be sent to the main control unit of the composite material laying equipment, so that the main control unit of the composite material laying equipment can automatically adjust the laying parameters (such as pressure and laying speed) of the composite material laying equipment according to the abnormal information of the composite material layer to reduce the probability of defects in subsequent layers.

[0092] In another aspect, this application also provides a computer-readable storage medium storing a program product capable of implementing the methods provided above in this specification. In some possible implementations, various aspects of this application may also be implemented as a program product comprising program code that, when run on a terminal device, causes the terminal device to perform the steps described in the "Embodiment Methods" section of this specification according to various exemplary embodiments of this application.

[0093] The program product for implementing the above-described method according to the embodiments of this application may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of this application is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0094] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0095] Computer-readable signal media may include data signals propagated as part of a carrier wave in baseband, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0096] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0097] Program code for performing the operations of this application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0098] In another respect, this application also provides an electronic device capable of implementing the above-described method.

[0099] Those skilled in the art will understand that various aspects of this application can be implemented as a system, method, or program product. Therefore, various aspects of this application can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, collectively referred to herein as a "circuit," "module," or "system."

[0100] The following reference Figure 7 To describe an electronic device 400 according to this embodiment of the present application. Figure 7 The electronic device 400 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0101] like Figure 7 As shown, the electronic device 400 is manifested in the form of a general-purpose computing device. The components of the electronic device 400 may include, but are not limited to: at least one processing unit 410, at least one storage unit 420, and a bus 430 connecting different system components (including storage unit 420 and processing unit 410).

[0102] The storage unit stores program code that can be executed by the processing unit 410, causing the processing unit 410 to perform the steps described in the "Embodiment Methods" section above according to various exemplary embodiments of this application.

[0103] Storage unit 420 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 421 and / or cache memory 422, and may further include a read-only memory (ROM) 423.

[0104] Storage unit 420 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of these examples or some combination thereof may include an implementation of a network environment.

[0105] Bus 430 can represent one or more of several types of bus structures, including a memory cell bus or memory cell control node, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0106] Electronic device 400 can also communicate with one or more external devices 1200 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 400, and / or with any device that enables electronic device 400 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 450. Furthermore, electronic device 400 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 460. As shown, network adapter 460 communicates with other modules of electronic device 400 via bus 430. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0107] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this application.

[0108] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this application, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously in multiple modules.

[0109] It should be understood that this application is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A composite material detection system, characterized in that, The composite material detection system includes: a detector module, an X-ray source, a lateral adjustment mechanism, a longitudinal adjustment mechanism, a fine-tuning mechanism, and a control unit; the detector module, the X-ray source, the lateral adjustment mechanism, the longitudinal adjustment mechanism, and the fine-tuning mechanism are all electrically connected to the control unit; A composite material layer to be detected is disposed between the detector module and the X-ray source. The X-ray source is connected to the fine-tuning mechanism, which is used to adjust the emission position and emission angle of the X-ray source. The fine-tuning mechanism is mounted on the lateral adjustment mechanism and is slidably connected to the lateral adjustment mechanism; the longitudinal adjustment mechanism includes a guide rail and a support frame, the lateral adjustment mechanism is fixed on the support frame and is perpendicular to the support frame; the bottom of the support frame is mounted on the guide rail and is slidably connected to the guide rail. The planar position and angle of the detector module are adjusted by the control unit, and the plane of the detector module is always perpendicular to the emission direction of the X-ray source. During the detection of the composite material layer, the emission position and emission angle of the X-ray source are continuously adjusted so that each area of ​​the composite material layer is transmitted by the X-ray source, forming a transmission signal; the detector module detects the transmission signal, forms a transmission image signal, and sends the transmission image signal to the control unit. The composite material detection system further includes a workbench, which includes a base, a first rotating shaft, a first rotatable telescopic rod, a drive mechanism, and a second rotating shaft. The first rotating shaft is mounted on the base and is rotatably connected to the first rotatable telescopic rod. The first rotatable telescopic rod is connected to the drive mechanism and the second rotating shaft, respectively, and the second rotating shaft is connected to the detector module. The detector module includes a support plate and a detection sensor. The detection sensor is fixed on the support plate, and the support plate is rotatably connected to the second rotating shaft. The planar position and planar angle of the support plate are adjusted by the second rotating shaft. The first rotatable telescopic rod is extended and retracted by the drive mechanism and / or rotated on the first rotating shaft by the first rotatable telescopic rod to adjust the position and angle of the second rotating shaft, so that the plane of the detection sensor on the support plate remains perpendicular to the emission direction of the X-ray source.

2. The composite material detection system according to claim 1, characterized in that, The lateral adjustment mechanism includes a lateral beam and a sliding unit. The lateral beam is fixed to the support frame and is arranged perpendicular to the support frame. The sliding unit is slidably connected to the lateral beam and fixedly connected to the fine-tuning mechanism.

3. The composite material detection system according to claim 2, characterized in that, The fine-tuning mechanism includes a second rotatable telescopic rod, a hydraulic drive unit, a horizontal rotation joint, a vertical rotation joint, a vertical connecting shaft, and a rotating connecting rod. The second rotatable telescopic rod is connected to the sliding unit, the hydraulic drive unit, and the horizontal rotation joint, respectively. The horizontal rotation joint is rotatably connected to the vertical connecting shaft, and the vertical connecting shaft is rotatably connected to the vertical rotation joint. The rotating connecting rod is rotatably connected to the vertical rotation joint and is also connected to the X-ray source.

4. A control method for a composite material detection system, characterized in that, The method is performed on the control unit according to any one of claims 1-3, the method comprising: When the plane of the detector module is perpendicular to the emission direction of the X-ray source, the transmission image signal of the composite material layer acquired by the detector module is received. The abnormal information of the composite material layer is determined based on the transmitted image signal; Based on the abnormal information, parameter adjustment information for the composite material laying equipment is determined, so that the composite material laying equipment adjusts the laying parameters for the composite material layer according to the parameter adjustment information.

5. The control method according to claim 4, characterized in that, The step of determining the abnormal information of the composite material layer based on the transmitted image signal includes: The composite material layer is divided into grid regions of a preset format based on the transmitted image signal, and the grid regions include multiple grids; For each grid, multiple predicted bounding boxes are determined. Based on a preset deep learning algorithm, the position parameters, confidence parameters, and anomaly category probability parameters of each predicted bounding box are obtained. The anomaly information of the grid is determined based on each of the position parameters, the confidence parameters, and the anomaly category probability parameters. The abnormal information of the composite material layer is determined based on the abnormal information of each of the grids.

6. The control method according to claim 5, characterized in that, Determining the anomaly information of the grid based on each of the location parameters, the confidence parameter, and the anomaly category probability parameter includes: The target position parameter is determined from each of the position parameters according to the preset positioning loss function; The target confidence parameter is determined from each of the confidence parameters according to the preset confidence loss function; The target anomaly category probability parameter is determined from each of the anomaly category probability parameters according to the preset anomaly category loss function; The anomaly information of the grid is determined based on the target location parameter, the target confidence parameter, and the target anomaly category probability parameter.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to perform the operations performed by the method as described in any one of claims 4 to 6.

8. An electronic device, characterized in that, The electronic device includes one or more processors and one or more memories, wherein at least one piece of program code is stored in the one or more memories, and the at least one piece of program code is loaded and executed by the one or more processors to perform the operation performed by the method as described in any one of claims 4 to 6.

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