A real-time defect detection and quality control method for composite material automatic wire placement

Abstract

The present invention proposes a real-time detection and quality control method for composite material automatic wire laying defects, which detects and identifies wire laying defects in real time during the composite material automatic wire laying process, and obtains the type and size of the defects in real time; according to the type and size of the defects, the variable S of the degree of reduction of the mechanical properties of the composite material formed workpiece caused by the defects is accumulated, and when S reaches a threshold value S max When the laying is stopped, the laid structure of the composite material forming workpiece is repaired and the wire laying process parameters are adjusted until the laying is completed, wherein the repaired defects are no longer used for the accumulation of the variable S. The present invention controls the quality of the composite material part processing process according to the degree of reduction in the mechanical properties of the parts, and realizes closed-loop control from defect detection to quality control.

Description

Technical Field

[0001] The present invention relates to the technical field of composite material ply defect detection and ply quality control, and in particular to a composite material automatic wire laying defect real-time detection and quality control method, and the classification numbers thereof include B29C70 / 38, G01N21 / 88 and G01B11 / 24. Background Art

[0002] Carbon fiber reinforced resin-based composite materials have played an important role in the development of modern aviation technology and are frequently used in the structure of modern aircraft. Compared with traditional aluminum alloy materials, carbon fiber reinforced resin-based composite materials have higher specific strength and specific modulus, excellent corrosion resistance and fatigue performance. Automatic fiber placement technology can manufacture parts with complex shapes and curved surfaces. It has the advantages of automation and high efficiency and is an advanced manufacturing process for composite components. The fiber placement head of the automatic fiber placement machine lays prepreg narrow strips as units. During the fiber placement process, each narrow strip can be independently allocated and cut, and the fiber placement head can move in three dimensions, providing a high degree of flexibility for manufacturing.

[0003] Since automatic wire placement technology is very complex and difficult to control, defects such as gaps and wrinkles are prone to occur during the manufacturing process. Automatic wire placement defects directly affect the various properties of composite parts. How to detect and identify automatic wire placement defects in real time, and then achieve quality control of workpieces to reduce the defective rate, is a key issue facing the development of automatic wire placement technology.

[0004] In response to this problem, Boeing, Schmitt and EI in the United States have used image acquisition and processing systems to implement online detection methods for ply quality based on ply surface images, and have developed relatively mature products. Nanjing University of Aeronautics and Astronautics, China Aviation Manufacturing Technology Research Institute and other institutions have also studied high-quality acquisition, image preprocessing, image segmentation and defect recognition of composite ply images based on image processing technology, and achieved real-time detection of composite laying defects. For example, Chinese patent publication number CN113176265A discloses an on-machine detection system and method for automatic composite wire laying overlap and gap defects, and Chinese patent publication number CN113848182A discloses an online detection system and method for composite ply quality. Summary of the invention

[0005] The technical problems to be solved by the present invention are:

[0006] Existing online detection methods for composite material ply quality or defects are all aimed at ply defect identification, with the focus on how to accurately identify defects and defect types, without considering the quality control of composite material parts in the actual production process, that is, the existing technologies do not consider how to deal with defects after they are identified. Due to the complexity of the automatic wire laying process, if the wire laying is stopped once a defect is found during the online detection process, the wire laying will inevitably lead to high processing costs if the defective ply is torn off and then re-laid, which is necessary. Therefore, it is necessary to design a corresponding quality control strategy after the defect is identified, so as to avoid the scrapping of parts due to unacceptable defects after manufacturing, and reduce the additional costs caused by repeated rework due to a few defects during the wire laying process.

[0007] The technical solution of the present invention:

[0008] In order to solve the above technical problems, the present invention proposes a real-time detection and quality control method for automatic wire placing defects of composite materials, which performs real-time detection and identification of wire placing defects during the automatic wire placing process of composite materials. The focus is on measuring and analyzing the characteristic parameters of wire placing defects such as length, angle, and volume through a neural network model. In combination with the defect types, the weights of different defect characteristics corresponding to different mechanical performance requirements are clarified, so that the degree of reduction of the mechanical properties of parts by defects can be accurately judged, and the quality of the composite parts processing process can be controlled according to the degree of reduction of the mechanical properties of parts, thereby realizing closed-loop control from defect detection to quality control.

[0009] The present invention specifically comprises the following steps:

[0010] Step 1: During the automatic wire laying process of the composite material, the wire laying defects in the composite material forming workpiece are detected in real time, and the types and sizes of the defects are obtained in real time;

[0011] Step 2: Accumulate the variable S of the reduction degree of mechanical properties of composite material molded workpieces caused by defects. When S reaches the threshold S max When , stop the placement, repair the laid structure of the composite material forming workpiece and adjust the wire laying process parameters, and then return to step 1 until the placement is completed; the repaired defects are no longer used for the accumulation of variable S.

[0012] Furthermore, in step 1, during the automatic wire laying process of the composite material, the wire laying head of the automatic wire laying machine drives the data acquisition device to collect real-time surface contour data of the composite material molded workpiece ply, and after pre-processing the surface contour data of the composite material molded workpiece ply, it is input into the trained neural network model, and according to the output of the neural network model, it is determined whether there are defects in the current ply and the type and size of the defects.

[0013] Furthermore, in step 2, the variable S is calculated according to the formula

[0014]

[0015] Calculated, where is the weight factor of the defect at the ith location, is the volume percentage of the defect-affected area at the i-th location, and n represents the number of defects in the currently laid structure that participate in the accumulation of variable S.

[0016] Furthermore, the weight factor According to the formula

[0017]

[0018] Determine, among which is the weight factor of the defect type at the i-th defect, is the weight factor of the defect direction angle at the i-th location; the direction angle is the angle between the index direction of the mechanical property and the ply direction where the defect is located.

[0019] Furthermore, the volume ratio According to the formula

[0020]

[0021] Determine, among which is the area of ​​the i-th defect, is the thickness of a single layer, is the theoretical total volume of the composite workpiece.

[0022] Furthermore, the mechanical properties include longitudinal tensile strength, longitudinal compressive strength, transverse tensile strength, transverse compressive strength, and in-plane shear strength; for the longitudinal tensile strength and longitudinal compressive strength, their index directions are consistent with the main directions of the composite material molded workpiece; for the transverse tensile strength and transverse compressive strength, their index directions are perpendicular to the main directions of the composite material molded workpiece, and for the in-plane shear strength, their index directions are consistent with the main directions of the composite material molded workpiece.

[0023] Furthermore, the types of defects include gaps, overlaps, torsion, wrinkles, bridges, and foreign matter.

[0024] Furthermore, when the required mechanical properties are longitudinal tensile strength and transverse tensile strength, the weight factor corresponding to the defect type is for:

[0025]

[0026] For longitudinal tensile strength, the weight factor corresponding to the defect orientation angle is for:

[0027]

[0028] For transverse tensile strength, the weight factor corresponding to the defect orientation angle is for:

[0029]

[0030] When the required mechanical properties are longitudinal compressive strength and transverse compressive strength, the weight factor corresponding to the defect type is for:

[0031]

[0032] For longitudinal compressive strength, the weight factor corresponding to the defect orientation angle is for:

[0033]

[0034] For transverse compressive strength, the weight factor corresponding to the defect orientation angle is for:

[0035]

[0036] When the required mechanical property is in-plane shear strength, the weight factor corresponding to the defect type is for:

[0037]

[0038] For in-plane shear strength, the weight factor corresponding to the defect orientation angle is for:

[0039]

[0040] Furthermore, when a composite material forming workpiece needs to examine multiple mechanical properties at the same time, the thresholds of each mechanical property are set respectively, and the cumulative variables of the reduction degree corresponding to each mechanical property are calculated respectively. Only when the cumulative variables of the reduction degree corresponding to each mechanical property are less than their respective thresholds, the ply laying will continue.

[0041] Furthermore, the weight factor According to the formula

[0042]

[0043] Get, where is the magnification factor. If the first The coverage area of ​​the defect does not overlap with the coverage area of ​​the defect in the previous layer, then ,otherwise , where when the ply angles of two adjacent plies are different, , when the ply angles of two adjacent plies are the same, .

[0044] Beneficial effects:

[0045] The present invention proposes a method for real-time detection and quality control of defects in automatic wire placement of composite materials. During the process of automatic wire placement of composite materials, wire placement defects are detected and identified in real time. The characteristic parameters of wire placement defects, such as length, angle, area, volume, etc., are measured and analyzed mainly through a neural network model. In combination with the types of defects, the weights of different defect characteristics corresponding to different mechanical property requirements are clarified, so that the degree of reduction of the mechanical properties of parts by defects can be accurately judged, and the quality of the composite material part processing process can be controlled according to the degree of reduction of the mechanical properties of parts, thereby realizing closed-loop control from defect detection to quality control. Through this method, when the influence of automatic wire placement defects on mechanical properties reaches a threshold, wire placement can be automatically performed and technical personnel can be prompted to perform maintenance and process adjustments, thereby avoiding the situation where the workpiece is scrapped due to unacceptable defects after manufacturing, thereby reducing material costs and maintenance costs.

[0046] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0048] Figure 1 It is a flow chart of the composite material automatic wire placement defect detection and quality control method.

[0049] Figure 2 This is a schematic diagram of the position of the laser profile sensor and the wire laying head.

[0050] Figure 3 It is a schematic diagram of gap, overlap, torsion, wrinkle, foreign matter and bridge. DETAILED DESCRIPTION

[0051] Embodiments of the present invention are described in detail below. The embodiments are exemplary and intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0052] The present embodiment proposes a method for real-time detection and quality control of defects in automatic wire placement of composite materials. During the automatic wire placement process of composite materials, the wire placement defects in the composite molded workpiece are detected in real time based on a convolutional neural network model, and the types (gaps, overlaps, torsion, wrinkles, foreign matter, bridging) and sizes of the defects are acquired in real time. The variable S of the degree of reduction in the mechanical properties of the composite molded workpiece caused by the defects is monitored and accumulated. When the performance reduction degree reaches a threshold, the placement is stopped, the laid structure of the composite molded workpiece is repaired, and the wire placement process parameters are adjusted, thereby realizing a closed loop from defect detection to quality control.

[0053] In terms of hardware, an automatic wire laying defect detection system is adopted, which includes an automatic wire laying machine, a data acquisition device, a defect detection device, and a display device; the automatic wire laying machine is a prior art, and its structure and function are not described in detail. The automatic wire laying machine is equipped with a programmable logic controller, which is electrically connected to the data acquisition device, and the triggering of the data acquisition device is controlled by the programmable logic controller; the automatic wire laying machine is connected to the data acquisition device, and the data acquisition device is controlled by the programmable logic controller; the data acquisition device is installed at the wire laying head position of the automatic wire laying machine and is fixedly connected to the wire laying head. The relative position of the data acquisition device and the wire laying head part of the automatic wire laying machine is referenced Figure 2 The wire laying head carries the data acquisition device and moves to collect the surface contour data of the current composite material forming workpiece while laying; the data acquisition device adopts a line laser contour sensor, and the repetition accuracy of the line laser contour sensor in the height direction is 0.5um, and the measuring distance is 52.5mm~93.5mm; the defect detection device is connected with the data acquisition device, the automatic wire laying machine and the display device, which includes a computer device; the display device is connected with the defect detection device, which includes a display.

[0054] Before starting placement, the data acquisition device is calibrated first: adjust the relative position of the data acquisition device and the wire placement head until the following conditions are met: the field of view of the data acquisition device is perpendicular to the tangent of the placement path; the normal vector of the data acquisition device is parallel to the measured surface; the distance between the data acquisition device and the measured surface is within the range of 52.5mm~93.5mm.

[0055] After the calibration is completed, the programmable logic controller carried by the automatic wire placing machine sends a signal to control the triggering of the data acquisition device; during the movement of the wire placing head of the automatic wire placing machine, the wire placing head moves with the data acquisition device, and the data acquisition device obtains the surface contour data of the current composite material forming workpiece in real time and transmits it to the defect detection device.

[0056] The defect detection device has a data preprocessing module, a pretrained neural network model and a quality control module. The data preprocessing module preprocesses the surface contour data of the current composite material forming workpiece layer acquired in real time by the data acquisition device, including converting the surface contour data in the form of a three-dimensional point cloud into a two-dimensional grayscale image representing the depth, and normalizing and denoising the image. The preprocessed data is input into the pretrained neural network model to determine whether there are defects and the type and size of the defects, thereby completing the positioning, classification and size measurement tasks of common defects (gaps, overlaps, twists, wrinkles, foreign bodies, bridges). The neural network model input is a two-dimensional grayscale image, and the algorithm output is a two-dimensional pseudo-color image and the feature information of each defect. The neural network model is a prior art and will not be repeated. The output two-dimensional pseudo-color image and the feature information of each defect are transmitted to the display device and stored. The display device displays the feature information of each defect in real time. The feature information includes: the number of various defects, the type of each defect, the layer where each defect is located, the plane coordinates of the location of the center point of each defect, the maximum length and width of each defect, and the area of ​​each defect.

[0057] The quality control module accumulates the variable S of the reduction degree of mechanical properties of composite material formed workpieces caused by defects according to the characteristic information of each defect. When S reaches the set threshold S max When the defect detection device sends a stop command to the automatic fiber placement machine, the automatic fiber placement machine stops laying, and prompts the technician to repair the laid structure of the composite material forming workpiece and adjust the fiber placement process parameters, such as roller pressure, prepreg heating temperature, and laying speed, so as to achieve a closed loop from defect detection to quality control; after repair and adjustment, the automatic fiber placement machine continues to lay until the laying is completed, and the repaired defects are no longer used for the accumulation of variable S. The threshold S max According to different mechanical properties, it is determined through experiments, that is, different mechanical performance requirements have their own corresponding thresholds S max .

[0058] The core content of the present invention is to accumulate the variable S of the degree of reduction of the mechanical properties of the composite material molded workpiece caused by the defects according to the characteristic information of each defect. The existing technology mainly focuses on judging whether there are defects and the types of defects in the composite material laying process, and does not consider how to deal with the defects after they are identified.

[0059] The present invention takes the volume proportion of the defect-affected area as a benchmark, combines the defect weight factor, and accumulates the variable S of the degree of reduction of the mechanical properties of the composite material formed workpiece caused by the defect. First, different types of defects have different effects on the mechanical properties, so the defect type weight factor is the main component of the defect weight factor; but due to the characteristics of carbon fiber laminate composite materials, the same defect type has a very different effect on the mechanical properties under different direction angles, so the defect weight factor comprehensively considers the effects of the defect type and the defect direction angle, and uses the product of the defect type weight factor and the defect direction angle weight factor to characterize the defect weight factor. Through experiments and simulation calculations, the present invention determines the effects of defects such as gaps, overlaps, torsion, wrinkles, bridges, foreign bodies, etc. on typical mechanical properties such as longitudinal tensile strength, longitudinal compressive strength, transverse tensile strength, transverse compressive strength, and in-plane shear strength. With a 10% decrease in mechanical properties as the maximum acceptable limit, the defect type weight factor and the defect direction angle weight factor corresponding to different mechanical properties are calculated, thereby realizing a quantitative evaluation of the degree of reduction of the mechanical properties of composite material formed workpieces caused by defects.

[0060] The specific process of quantitative evaluation is as follows:

[0061] After obtaining the characteristic information of the defect, according to the formula

[0062]

[0063] The variable S of the reduction degree of mechanical properties of composite material formed workpieces caused by defects is obtained by cumulative calculation, which is a dimensionless quantity; is the weight factor of the defect at the ith location, a dimensionless quantity, is the volume percentage of the defect-affected area at the ith location, which is a dimensionless quantity, and n represents the number of defects participating in the accumulation of variable S in the currently laid structure.

[0064] Volume ratio According to the formula

[0065]

[0066] Determine, among which is the area of ​​the defect at the i-th location, obtained according to the output of the neural network model, is the thickness of a single layer, is the theoretical total volume of the composite workpiece.

[0067] Weight Factor According to the formula

[0068]

[0069] Determine, among which is the weight factor of the defect type at the i-th defect, which is a dimensionless quantity determined by experiments and numerical simulation methods. is the weight factor of the defect direction angle at the i-th position, which is a dimensionless quantity determined by experiments and numerical simulation methods; the direction angle is the angle between the index direction of the mechanical property and the ply direction of the ply where the defect is located. For longitudinal tensile strength and longitudinal compressive strength, the index direction is consistent with the main direction of the composite material molded workpiece; for transverse tensile strength and transverse compressive strength, the index direction is perpendicular to the main direction of the composite material molded workpiece, and for in-plane shear strength, the index direction is consistent with the main direction of the composite material molded workpiece.

[0070] Taking a 10% decrease in mechanical properties as the maximum acceptable limit, the defect type weight factors and defect direction angle weight factors corresponding to different mechanical properties are calculated as follows:

[0071] When the required mechanical properties are longitudinal tensile strength and transverse tensile strength, the weight factor corresponding to the defect type is for:

[0072]

[0073] For longitudinal tensile strength, the weight factor corresponding to the defect orientation angle is for:

[0074]

[0075] For transverse tensile strength, the weight factor corresponding to the defect orientation angle is for:

[0076]

[0077] When the required mechanical properties are longitudinal compressive strength and transverse compressive strength, the weight factor corresponding to the defect type is for:

[0078]

[0079] For longitudinal compressive strength, the weight factor corresponding to the defect orientation angle is for:

[0080]

[0081] For transverse compressive strength, the weight factor corresponding to the defect orientation angle is for:

[0082]

[0083] When the required mechanical property is in-plane shear strength, the weight factor corresponding to the defect type is for:

[0084]

[0085] For in-plane shear strength, the weight factor corresponding to the defect orientation angle is for:

[0086]

[0087] In this embodiment, a certain type of aircraft fuselage composite panel is considered, the stress state is mainly in-plane shear force, and the ply sequence is [45 / 0 / 45 / 0 / -452 / 0 / -45 / 90 / 45] S ; Prepreg single layer thickness 0.12mm; Mainly examine the in-plane shear strength performance and set the threshold Set to 1. Through real-time detection, there are two defects that are currently involved in the accumulation of mechanical property reduction:

[0088] Defect No. 1: Type is gap, direction angle is 0°, calculated volume percentage ;

[0089] Defect No. 2: Type is overlap, direction angle is 90°, calculated volume percentage .

[0090] According to the above defect type weight factor and defect direction angle weight factor, the defect type weight factor of the first defect is obtained. is 144.387, the defect direction angle weight factor is 0.028, so ; Defect type weight factor for the second defect is 399.84, the defect direction angle weight factor is 1, so .

[0091] Then the current

[0092]

[0093] Therefore, the shear mechanical properties within the current structural surface meet the requirements and laying can continue.

[0094] When the laying process continues, the third defect is detected: the type is wrinkles, the direction angle is 0°, and the calculated volume percentage , the defect type weight factor corresponding to the third defect is 84, the defect direction angle weight factor is 1, so ; then the current

[0095]

[0096] Obviously, the cumulative in-plane shear performance loss of the current aircraft fuselage composite wall panel structure has exceeded the set threshold, and it is necessary to stop laying, repair the laid structure and adjust the wire laying process parameters before continuing laying. For example, here several layers affected by wrinkle defects are torn off, and the process parameters that are strongly related to wrinkle defects such as laying temperature and laying pressure are adjusted, and the layers are re-laid.

[0097] In addition, when the workpiece structure needs to examine multiple mechanical properties at the same time, the thresholds of each mechanical property are set respectively, and the cumulative variables of the reduction degree corresponding to each mechanical property are calculated respectively. Only when the cumulative variables of the reduction degree corresponding to each mechanical property are less than their respective thresholds, the plying will continue.

[0098] Furthermore, the characteristic information output in the neural network model of the defect detection device includes the plane coordinates of the defect center point, the maximum length and width of each defect, and the area of ​​each defect, and these characteristic information are stored. Therefore, the coverage area of ​​each defect can be obtained, so a judgment basis is added to the quality control module: if the defect coverage area in the current layer overlaps with the defect coverage area in the previous layer, it means that two consecutive layers have defects in similar areas, which is likely to indicate that there is a problem with the wire laying process parameters. Therefore, at this time, regardless of whether the variable S reaches the threshold, the layer laying is stopped and the wire laying process parameters are adjusted. Moreover, since the defect coverage areas of two consecutive layers overlap, the degree of reduction of the mechanical properties by this combined defect is greater than the linear superposition of the degree of reduction of the mechanical properties by the two defects. Therefore, when the variable S is accumulated, the degree of reduction of the mechanical properties by the current layer defect is amplified. Furthermore, the applicant has found through a large number of tests that if the ply angles of two adjacent plies are the same, the magnification factor is 1.5~2, and if the ply angles of two adjacent plies are different, the magnification factor is 1.3~1.7. The value ranges of the magnification factors here may overlap, because under certain mechanical properties, the superimposed effect of defects on the mechanical properties is more affected by the ply angle of two adjacent plies, while under other mechanical properties, the superimposed effect of defects on the mechanical properties is less affected by the ply angle of two adjacent plies.

[0099] The formula is:

[0100]

[0101] is the magnification factor. If the first The coverage area of ​​the defect does not overlap with the coverage area of ​​the defect in the previous layer, then ,otherwise , where when the ply angles of two adjacent plies are different, , when the ply angles of two adjacent plies are the same, .

[0102] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention without departing from the principles and intent of the present invention.

Claims

1. A method for real-time defect detection and quality control of composite material automatic wire placement, characterized in that: The following steps are involved: Step 1: During the automatic wire laying process of the composite material, the wire laying defects in the composite material forming workpiece are detected in real time, and the types and sizes of the defects are obtained in real time; Step 2: Accumulate the variable S of the reduction degree of mechanical properties of composite material molded workpieces caused by defects. When S reaches the threshold S max When the placement is stopped, the laid structure of the composite material forming workpiece is repaired and the wire laying process parameters are adjusted, and then the process returns to step 1 until the placement is completed; the repaired defects are no longer used for the accumulation of the variable S; The variable S is calculated according to the formula Calculated, where is the weight factor of the defect at the ith location, is the volume percentage of the defect-affected area at the i-th location, and n represents the number of defects in the currently laid structure that participate in the accumulation of variable S; Weight Factor According to the formula Determine, among which is the weight factor of the defect type at the i-th defect, is the weight factor of the defect direction angle at the i-th position; the direction angle is the angle between the index direction of the mechanical property and the ply direction where the defect is located; Volume ratio According to the formula Determine, among which is the area of ​​the i-th defect, is the thickness of a single layer, is the theoretical total volume of the composite workpiece.

2. According to claim 1, a composite material automatic wire placement defect real-time detection and quality control method is characterized by: In step 1, during the automatic wire laying process of composite materials, the wire laying head of the automatic wire laying machine drives the data acquisition device to collect real-time surface contour data of the composite material molded workpiece ply. After preprocessing the surface contour data of the composite material molded workpiece ply, it is input into the trained neural network model, and according to the output of the neural network model, it is judged whether there are defects in the current ply and the type and size of the defects.

3. The method for real-time defect detection and quality control of composite material automatic wire placement according to claim 1, characterized in that: The mechanical properties include longitudinal tensile strength, longitudinal compressive strength, transverse tensile strength, transverse compressive strength, and in-plane shear strength; for the longitudinal tensile strength and longitudinal compressive strength, the index direction is consistent with the main direction of the composite material molded workpiece; for the transverse tensile strength and transverse compressive strength, the index direction is perpendicular to the main direction of the composite material molded workpiece, and for the in-plane shear strength, the index direction is consistent with the main direction of the composite material molded workpiece.

4. A composite material automatic wire placement defect real-time detection and quality control method according to claim 3, characterized in that: The defect types include gaps, overlaps, torsion, wrinkles, bridges, and foreign matter.

5. A composite material automatic wire placement defect real-time detection and quality control method according to claim 4, characterized in that: When the required mechanical properties are longitudinal tensile strength and transverse tensile strength, the weight factor corresponding to the defect type is for: When the defect type is a gap defect: =168; When the defect type is an overlap defect: =210; When the defect type is a torsion defect: =210; When the defect type is a wrinkle defect: =79.968; When the defect type is a bridging defect: =79.968; When the defect type is a foreign body defect: =79.968; For longitudinal tensile strength, the weight factor corresponding to the defect orientation angle is for: When the direction angle is 0° and the defect type is a gap defect: =0.022; When the direction angle is 0° and the defect type is an overlap defect: =0; When the direction angle is 0° and the defect type is a torsion defect: =0; When the direction angle is 0° and the defect type is a wrinkle defect: =1; When the direction angle is 0° and the defect type is a bridging defect: =1; When the direction angle is 0° and the defect type is a foreign body defect: =1; When the direction angle is 90° and the defect type is a gap defect: =0.167; When the direction angle is 90° and the defect type is an overlap defect: =1; When the direction angle is 90° and the defect type is a torsion defect: =1; When the direction angle is 90° and the defect type is a wrinkle defect: =0.5; When the direction angle is 90° and the defect type is a bridging defect: =0.5; When the direction angle is 90° and the defect type is a foreign body defect: =0.5; When the direction angle is ±45° and the defect type is a gap defect: =1; When the direction angle is ±45° and the defect type is an overlap defect: =0.8; When the direction angle is ±45° and the defect type is a torsion defect: =0.8; When the direction angle is ±45° and the defect type is a wrinkle defect: =0.75; When the direction angle is ±45° and the defect type is a bridging defect: =0.75; When the direction angle is ±45° and the defect type is a foreign body defect: =0.75; For transverse tensile strength, the weight factor corresponding to the defect orientation angle is for: When the direction angle is 0° and the defect type is a gap defect: =0.167; When the direction angle is 0° and the defect type is an overlap defect: =1; When the direction angle is 0° and the defect type is a torsion defect: =1; When the direction angle is 0° and the defect type is a wrinkle defect: =0.5; When the direction angle is 0° and the defect type is a bridging defect: =0.5; When the direction angle is 0° and the defect type is a foreign body defect: =0.5; When the direction angle is 90° and the defect type is a gap defect: =0.022; When the direction angle is 90° and the defect type is an overlap defect: =0; When the direction angle is 90° and the defect type is a torsion defect: =0; When the direction angle is 90° and the defect type is a wrinkle defect: =1; When the direction angle is 90° and the defect type is a bridging defect: =1; When the direction angle is 90° and the defect type is a foreign body defect: =1; When the direction angle is ±45° and the defect type is a gap defect: =1; When the direction angle is ±45° and the defect type is an overlap defect: =0.8; When the direction angle is ±45° and the defect type is a torsion defect: =0.8; When the direction angle is ±45° and the defect type is a wrinkle defect: =0.75; When the direction angle is ±45° and the defect type is a bridging defect: =0.75; When the direction angle is ±45° and the defect type is a foreign body defect: =0.75; When the required mechanical properties are longitudinal compressive strength and transverse compressive strength, the weight factor corresponding to the defect type is for: When the defect type is a gap defect: =420; When the defect type is an overlap defect: =349.986; When the defect type is a torsion defect: =349.986; When the defect type is a wrinkle defect: =99.96; When the defect type is a bridging defect: =99.96; When the defect type is a foreign body defect: =99.96; For longitudinal compressive strength, the weight factor corresponding to the defect orientation angle is for: When the direction angle is 0° and the defect type is a gap defect: =0.007; When the direction angle is 0° and the defect type is an overlap defect: =0; When the direction angle is 0° and the defect type is a torsion defect: =0; When the direction angle is 0° and the defect type is a wrinkle defect: =1; When the direction angle is 0° and the defect type is a bridging defect: =1; When the direction angle is 0° and the defect type is a foreign body defect: =1; When the direction angle is 90° and the defect type is a gap defect: =0.333; When the direction angle is 90° and the defect type is an overlap defect: =1; When the direction angle is 90° and the defect type is a torsion defect: =1; When the direction angle is 90° and the defect type is a wrinkle defect: =0.5; When the direction angle is 90° and the defect type is a bridging defect: =0.5; When the direction angle is 90° and the defect type is a foreign body defect: =0.5; When the direction angle is ±45° and the defect type is a gap defect: =1; When the direction angle is ±45° and the defect type is an overlap defect: =1; When the direction angle is ±45° and the defect type is a torsion defect: =1; When the direction angle is ±45° and the defect type is a wrinkle defect: =0.75; When the direction angle is ±45° and the defect type is a bridging defect: =0.75; When the direction angle is ±45° and the defect type is a foreign body defect: =0.75; For transverse compressive strength, the weight factor corresponding to the defect orientation angle is for: When the direction angle is 0° and the defect type is a gap defect: =0.333; When the direction angle is 0° and the defect type is an overlap defect: =1; When the direction angle is 0° and the defect type is a torsion defect: =1; When the direction angle is 0° and the defect type is a wrinkle defect: =0.5; When the direction angle is 0° and the defect type is a bridging defect: =0.5; When the direction angle is 0° and the defect type is a foreign body defect: =0.5; When the direction angle is 90° and the defect type is a gap defect: =0.007; When the direction angle is 90° and the defect type is an overlap defect: =0; When the direction angle is 90° and the defect type is a torsion defect: =0; When the direction angle is 90° and the defect type is a wrinkle defect: =1; When the direction angle is 90° and the defect type is a bridging defect: =1; When the direction angle is 90° and the defect type is a foreign body defect: =1; When the direction angle is ±45° and the defect type is a gap defect: =1; When the direction angle is ±45° and the defect type is an overlap defect: =1; When the direction angle is ±45° and the defect type is a torsion defect: =1; When the direction angle is ±45° and the defect type is a wrinkle defect: =0.75; When the direction angle is ±45° and the defect type is a bridging defect: =0.75; When the direction angle is ±45° and the defect type is a foreign body defect: =0.75; When the required mechanical property is in-plane shear strength, the weight factor corresponding to the defect type is for: When the defect type is a gap defect: =144.387; When the defect type is an overlap defect: =399.84; When the defect type is a torsion defect: =116.634; When the defect type is a wrinkle defect: =84; When the defect type is a bridging defect: =84; When the defect type is a foreign body defect: =84; For in-plane shear strength, the weight factor corresponding to the defect orientation angle is for: When the direction angle is 0° and the defect type is a gap defect: =0.028; When the direction angle is 0° and the defect type is an overlap defect: =0.01; When the direction angle is 0° and the defect type is a torsion defect: =0.171; When the direction angle is 0° and the defect type is a wrinkle defect: =1; When the direction angle is 0° and the defect type is a bridging defect: =1; When the direction angle is 0° and the defect type is a foreign body defect: =1; When the direction angle is 90° and the defect type is a gap defect: =0; When the direction angle is 90° and the defect type is an overlap defect: =1; When the direction angle is 90° and the defect type is a torsion defect: =1; When the direction angle is 90° and the defect type is a wrinkle defect: =0.5; When the direction angle is 90° and the defect type is a bridging defect: =0.5; When the direction angle is 90° and the defect type is a foreign body defect: =0.5; When the direction angle is ±45° and the defect type is a gap defect: =1; When the direction angle is ±45° and the defect type is an overlap defect: =0.056; When the direction angle is ±45° and the defect type is a torsion defect: =0.5; When the direction angle is ±45° and the defect type is a wrinkle defect: =0.75; When the direction angle is ±45° and the defect type is a bridging defect: =0.75; When the direction angle is ±45° and the defect type is a foreign body defect: =0.

75.

6. The method for real-time defect detection and quality control of composite material automatic wire placement according to claim 3, characterized in that: When a composite material forming workpiece needs to examine multiple mechanical properties at the same time, the thresholds of each mechanical property are set respectively, and the cumulative variables of the reduction degree corresponding to each mechanical property are calculated respectively. Only when the cumulative variables of the reduction degree corresponding to each mechanical property are less than their respective thresholds, the ply laying will continue.

7. The method for real-time defect detection and quality control of composite material automatic wire placement according to claim 1, characterized in that: Weight Factor According to the formula Get, where is the weight factor of the defect type at the i-th defect, is the weight factor of the defect direction angle at the i-th position; the direction angle is the angle between the index direction of the mechanical property and the ply direction where the defect is located; is the magnification factor. If the first The coverage area of ​​the defect does not overlap with the coverage area of ​​the defect in the previous layer, then ,otherwise , where when the ply angles of two adjacent plies are different, , when the ply angles of two adjacent plies are the same, .

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