Method for quantitatively detecting defect geometry and mechanical property loss of carbon fiber sheets

Abstract

The present invention relates to a method for quantitatively detecting the geometric configuration of defects and mechanical property loss of carbon fiber plates, and belongs to the field of plate monitoring. The steps include: quantitatively producing a series of standard defect samples; thoroughly cleaning the surface of the standard defect samples; fixing the infrared detection device according to the experimental requirements; performing infrared detection on the standard defect samples and retaining the optimal image of the defect; performing image processing on the optimal image of the defect; reproducing the geometric configuration and volume of the defect; establishing the relationship between the tensile strength loss rate and the volume of the defect geometric configuration; and calculating the geometric configuration of the defects and the tensile strength loss rate of the carbon fiber plate to be tested. The standard defect samples used in the present invention are made of the same material as the carbon fiber plate to be tested, which ensures the reliability of the calculation results. The data calculated by the present invention are practical and cost-effective in product monitoring, and have broad application prospects.

Description

Technical Field

[0001] The present invention relates to the field of plate monitoring, and in particular to a method for quantitatively detecting geometric configuration defects and mechanical property loss of carbon fiber plates. Background Art

[0002] Carbon fiber composite sheets are an advanced material with superior properties such as high specific strength and high-temperature resistance. They are widely used in high-speed trains, aerospace, and other fields. However, during their production and use, a certain number of defects are inevitable. If these defects are not discovered and corrected promptly, the consequences can be extremely serious. Therefore, inspection of carbon fiber composite sheets is extremely necessary. Currently, domestic and international inspection methods for carbon fiber sheets include ultrasonic testing, eddy current testing, radiographic testing, and infrared testing. Among these inspection methods, infrared testing is widely used across various industries due to its non-contact nature and large inspection area. While infrared testing has made significant progress in qualitative research on defects in carbon fiber composite sheets, quantitative research on defects is relatively limited. Harbin Institute of Technology has used the phase lock-in method to detect defects in composite materials, demonstrating that infrared phase lock-in testing can quickly detect large-area defects, internal defects, and multi-layer defects. Professor Tang Qingju of Harbin Institute of Technology has discovered that using Markov principal component analysis to reconstruct image sequences can improve image quality and defect detection capabilities. However, there is currently no mature research method for the relationship between the defect geometry of carbon fiber composite sheets and the loss rate of mechanical properties of the sheets, especially a method for quantitatively detecting the defect geometry and mechanical property loss of carbon fiber sheets. Summary of the Invention

[0003] The present invention aims to provide a method for quantitatively detecting the geometric configuration of defects and mechanical property loss in carbon fiber sheet materials. This method addresses the existing issues of low image signal-to-noise ratio, difficulty in quantitatively detecting defect geometry, and unclear relationship between defect geometry and mechanical property loss in sheet materials. The standard defect specimen used in the present invention is made of the same material as the carbon fiber sheet material being tested, ensuring the reliability of the calculation results. The data obtained by the present invention is practical and cost-effective for product monitoring, with broad application prospects.

[0004] The above-mentioned purpose of the present invention is achieved through the following technical solutions:

[0005] A method for quantitatively detecting defective geometric configurations and mechanical property loss in carbon fiber sheets comprises the following steps:

[0006] Step (1), quantitatively preparing a series of standard defect specimens: impact tests are sequentially performed on a series of carbon fiber plates of the same material and thickness as the carbon fiber plate to be tested; each carbon fiber plate has only one impact defect, and the impact energy received by each carbon fiber plate is different; this series of carbon fiber plates with different impact defects are regarded as standard defect specimens;

[0007] Step (2): thoroughly clean the surface of the standard defect sample to ensure that there is no interference from debris during the subsequent infrared thermal imaging process;

[0008] Step (3), adjusting the position and distance between the infrared thermal imager, the halogen lamp and the standard defect sample, and setting the flash frequency and power of the halogen lamp, the object reflectivity and the reflection temperature of the infrared thermal imager to meet the experimental requirements;

[0009] Step (4), using a halogen lamp to perform thermal excitation on each standard defect sample, and simultaneously using an infrared thermal imager to take infrared thermal images and collect data;

[0010] Step (5), selecting the optimal defect image from a series of infrared thermal images based on the feature image, and performing noise reduction, image enhancement, and threshold segmentation processing on the optimal defect image;

[0011] Step (6): extracting the spatial data required to construct the defect geometry from the processed optimal defect image, reproducing the defect geometry using Tecplot software, and calculating the defect volume;

[0012] Step (7), after all standard defect samples are subjected to infrared detection and their respective defect geometric configurations are calculated, tensile tests are performed in sequence to measure their tensile strength loss rates, and the relationship between the tensile strength loss rate and the defect geometric configuration volume K=f(V) is established;

[0013] Step (8), calculate the defect geometry and mechanical property loss of the carbon fiber plate to be tested: use a halogen lamp to thermally excite the carbon fiber plate to be tested, and simultaneously use an infrared thermal imager to take infrared thermal images and collect data, and obtain the defect geometry and tensile strength loss rate according to steps (5) to (7).

[0014] The impact test described in step (1) is completed using a double-guide rail drop hammer device, which generates different impact energies by controlling the total mass of the drop hammer loading.

[0015] The specific algorithm for performing noise reduction, image enhancement, and threshold segmentation on the defect optimal image described in step (5) is: when performing noise reduction and enhancement on the defect optimal image, contrast enhancement, pseudo color enhancement, or wavelet algorithm is used; when performing threshold segmentation on the image after noise reduction and enhancement, watershed segmentation method, Otsu algorithm, or Triangle algorithm is used.

[0016] In the relationship K=f(V) established in step (7), the tensile strength loss rate is defined as 0% when the carbon fiber plate is defect-free, and the difference between the tensile strength of the defect-free carbon fiber plate and the tensile strength of the defective carbon fiber plate divided by the tensile strength of the defect-free carbon fiber plate is defined as the loss rate K. K is K1, K2, K3, ..., K obtained by calculating the volumes of different defective geometric configurations in sequence. n The value of .

[0017] Another object of the present invention is to provide a dual-guide rail drop hammer device, which is composed of a static support 1, an impact hammer body 2, a pulley 3, a punch 4, a weight 5, a sample fixing platform 6, a guide rail 7, and a fixing nut 8. The impact hammer body 2, the punch 4, the weight 5, and the pulley 3 constitute the impact hammer body 2. The guide rail 7 is fixed to the inner side of the static support 1, and the pulley 3 slides on the guide rail 7. The impact hammer body 2 and the weight 5 are fixed to the supporting beam via a screw and a fixing nut 8. The two ends of the supporting beam are respectively connected to the pulley 3 axis. Before the impact test begins, the first carbon fiber plate to be tested is fixed on the sample fixing platform 6, and then the impact hammer body 2 is lifted to the highest point and allowed to fall freely. The gravitational potential energy of the impact hammer body 2 is converted into kinetic energy, and the punch 4 of the impact hammer body 2 collides with the plate to be tested, resulting in impact damage. After removing the first carbon fiber sheet to be tested, secure the second carbon fiber sheet to the specimen fixture 6. A weight of 0.1 kg is secured directly above the impact hammer 2. The impact hammer 2 is then lifted to its highest point and allowed to fall freely. The gravitational potential energy of the impact hammer 2 is converted into kinetic energy, and the punch 4 of the impact hammer 2 collides with the sheet to be tested, causing impact damage. After removing the second carbon fiber sheet to be tested, secure the third carbon fiber sheet to the specimen fixture 6. A weight of 0.2 kg is secured directly above the impact hammer 2. The impact hammer 2 is then lifted to its highest point and allowed to fall freely. The gravitational potential energy of the impact hammer 2 is converted into kinetic energy, and the punch 4 of the impact hammer 2 collides with the sheet to be tested, causing impact damage. Similarly, impact tests are conducted on 20 3K carbon fiber sheets. The 3K carbon fiber sheets that have completed the impact test serve as standard defect specimens.

[0018] Compared with the prior art, the present invention has the following advantages:

[0019] 1. The standard defect sample and the carbon fiber plate to be tested are made of the same material, so that the heat transfer characteristics of the standard defect sample are completely consistent with those of the carbon fiber plate to be tested. This can ensure that the data is reliable when performing infrared testing and tensile performance testing on the carbon fiber plate to be tested.

[0020] 2. The present invention adopts noise reduction, image enhancement, threshold segmentation and other processes when processing the optimal defect image, so that the quality of the image is guaranteed, thereby ensuring high accuracy when the defect geometric configuration is subsequently reproduced.

[0021] 3. This invention prepares a series of standard defect specimens with sufficient data, making the relationship between the tensile strength loss rate of carbon fiber sheets and the volume of the defect geometry, K = f(V), highly reliable. This enables rapid monitoring of carbon fiber sheets and has broad prospects for practical application. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings described herein are used to provide further understanding of the present invention and constitute a part of this application. The illustrative examples of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0023] Figure 1 It is a schematic diagram of the three-dimensional structure of the double-guide rail drop hammer device of the present invention;

[0024] Figure 2 It is a schematic top view of the structure of the dual-guide rail drop hammer device of the present invention;

[0025] Figure 3 This is a schematic diagram of the front view of the double-guide rail drop hammer device of the present invention (without weights);

[0026] Figure 4 This is a schematic diagram of the front view of the double-guide rail drop hammer device of the present invention (with a weight added);

[0027] Figure 5 This is a schematic diagram of the front view structure of the dual-guide rail drop hammer device of the present invention (with two weights added).

[0028] In the figure: 1. Static support; 2. Impact hammer; 3. Pulley; 4. Punch; 5. Weight; 6. Sample fixing table; 7. Guide rail; 8. Fixing nut. DETAILED DESCRIPTION

[0029] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0030] The method of the present invention for quantitatively detecting the geometric configuration of defects and mechanical property loss of carbon fiber plates comprises the following steps:

[0031] Step (1), quantitatively preparing a series of standard defect specimens: impact tests are performed on a series of carbon fiber plates of the same material and thickness as the carbon fiber plate to be tested; each carbon fiber plate has only one impact defect, and the impact energy received by each carbon fiber plate is different; this series of carbon fiber plates with different impact defects are regarded as standard defect specimens.

[0032] Step (2): clean the surface of the standard defect sample thoroughly to ensure that there is no interference from debris during the subsequent infrared thermal imaging process.

[0033] Step (3): adjust the position and distance between the infrared thermal imager, the halogen lamp and the standard defect sample, and set the flash frequency and power of the halogen lamp, the object reflectivity of the infrared thermal imager, the reflected temperature and other related parameters to meet the experimental requirements.

[0034] Step (4): thermally excite each standard defect sample using a halogen lamp, and simultaneously use an infrared thermal imager to capture infrared thermal images and collect data.

[0035] Step (5) selects the optimal defect image from a series of infrared thermal images based on the feature image, and performs noise reduction, image enhancement, and threshold segmentation processing on it.

[0036] Step (6) extracts the spatial data required to construct the defect geometry from the processed optimal defect image, reproduces the defect geometry using Tecplot software, and calculates the defect volume.

[0037] Step (7): After all standard defective specimens are subjected to infrared detection and their respective defect geometric configurations are calculated, tensile tests are performed in sequence to measure their tensile strength loss rate, and the relationship between the tensile strength loss rate and the defect geometric configuration volume K=f(V) is established.

[0038] Step (8) calculates the defect geometry and mechanical property loss of the carbon fiber plate to be tested; uses a halogen lamp to thermally excite the carbon fiber plate to be tested, and simultaneously uses an infrared thermal imager to take infrared thermal images and collect data, and obtains the defect geometry and tensile strength loss rate according to steps (5) to (7).

[0039] Preferably, the impact test in step (1) is performed using a double-guide rail drop hammer device, which has different impact energies by controlling the total mass of the drop hammer loading.

[0040] Preferably, the specific algorithms for performing noise reduction, image enhancement, and threshold segmentation on the defect optimal image in step (5) are: contrast enhancement, pseudo color enhancement, or wavelet algorithm is used when performing noise reduction and enhancement on the defect optimal image; and watershed segmentation method, Otsu algorithm, or Triangle algorithm is used when performing threshold segmentation on the image after noise reduction and enhancement.

[0041] Preferably, in the relationship between the tensile strength loss rate and the volume of the defective geometric configuration established in step (7), the tensile strength loss rate is defined as 0% when the carbon fiber plate is defect-free, and the difference between the tensile strength of the defect-free carbon fiber plate and the tensile strength of the defective carbon fiber plate divided by the tensile strength of the defect-free carbon fiber plate is defined as the loss rate K. ， K is K1, K2, K3, ..., K obtained by sequentially calculating the data of different standard samples. n The value of .

[0042] See also Figures 1 to 5 As shown, the dual-guide rail drop hammer device of the present invention is composed of a static support 1, an impact hammer body 2, a pulley 3, a punch 4, a weight 5, a sample fixing platform 6, a guide rail 7, and a fixing nut 8. The impact hammer body 2, the punch 4, the weight 5, and the pulley 3 constitute the impact hammer body 2. The guide rail 7 is fixed to the inner side of the static support 1, and the pulley 3 slides on the guide rail 7. The impact hammer body 2 and the weight 5 are fixed to the supporting beam by a screw and a fixing nut 8. The two ends of the supporting beam are respectively connected to the pulley 3 axis. Before the impact test begins, the first carbon fiber plate to be tested is fixed on the sample fixing platform 6, and then the impact hammer body 2 is lifted to the highest point and allowed to fall freely. The gravitational potential energy of the impact hammer body 2 is converted into kinetic energy. The punch 4 of the impact hammer body 2 collides with the plate to be tested, resulting in impact damage. After removing the first carbon fiber sheet to be tested, secure the second carbon fiber sheet to the specimen fixture 6. A weight of 0.1 kg is secured directly above the impact hammer 2. The impact hammer 2 is then lifted to its highest point and allowed to fall freely. The gravitational potential energy of the impact hammer 2 is converted into kinetic energy, and the punch 4 of the impact hammer 2 collides with the sheet to be tested, causing impact damage. After removing the second carbon fiber sheet to be tested, secure the third carbon fiber sheet to the specimen fixture 6. A weight of 0.2 kg is secured directly above the impact hammer 2. The impact hammer 2 is then lifted to its highest point and allowed to fall freely. The gravitational potential energy of the impact hammer 2 is converted into kinetic energy, and the punch 4 of the impact hammer 2 collides with the sheet to be tested, causing impact damage. Similarly, impact tests are conducted on 20 3K carbon fiber sheets. The 3K carbon fiber sheets that have completed the impact test serve as standard defect specimens.

[0043] Example:

[0044] A method for detecting the geometric configuration of defects and the loss rate of tensile properties of carbon fiber plates, comprising the following steps:

[0045] Step (1), quantitatively preparing a series of standard defect specimens: impact tests are performed on a series of carbon fiber plates of the same material and thickness as the carbon fiber plate to be tested; each carbon fiber plate has only one impact defect, and the impact energy received by each carbon fiber plate is different; this series of carbon fiber plates with different impact defects are regarded as standard defect specimens.

[0046] In this embodiment, a 3K carbon fiber plate is selected to prepare the standard defect sample, and the material of the carbon fiber plate to be tested is also 3K carbon fiber.

[0047] First, the common defects of 3K carbon fiber plates during the production and use stages are analyzed to determine the geometric configuration, volume size and other information of common defects.

[0048] Secondly, a dual-rail drop hammer device was used to conduct impact tests on 20 3K carbon fiber plates with a side length of 50mm and a thickness of 2mm. Each plate was subjected to a different impact force, thereby preparing 20 standard defect specimens with defects of different sizes. The different impact forces described in this process are achieved by controlling the overall mass of the impact hammer of the dual-rail drop hammer device. The impact part of the impact hammer is a circular area with a diameter of 50mm, and the punch is a cylinder with a diameter of 5mm. The surface of the punch is perpendicular to the surface of the 3K carbon fiber plate. The original mass of the entire impact hammer is 2kg, and the drop height of the impact hammer is 50cm each time. The impact energy is adjusted by controlling the mass of the weight loaded above the impact hammer.

[0049] Finally, impact tests were performed on 20 3K carbon fiber plates in sequence. When impacting the first plate, no weight was loaded on the impact hammer, the mass of the entire impact hammer was 2kg, and the impact hammer dropped from a height of 50cm. When impacting the second plate, a 0.1kg weight was loaded on the impact hammer, the mass of the entire impact hammer was 2.1kg, and the impact hammer dropped from a height of 50cm. When impacting the third plate, a 0.2kg weight was loaded on the impact hammer, the mass of the entire impact hammer was 2.2kg, and the impact hammer dropped from a height of 50cm. Similarly, impact tests were performed on 20 3K carbon fiber plates, and the 3K carbon fiber plates that completed the impact were the standard defect specimens.

[0050] Step (2): clean the surface of the standard defect sample thoroughly to ensure that there is no interference from debris during the subsequent infrared thermal imaging process.

[0051] Step (3): adjust the position and distance between the infrared thermal imager, the halogen lamp and the standard defect sample, and set the flash frequency and power of the halogen lamp, the object reflectivity of the infrared thermal imager, the reflected temperature and other related parameters to meet the experimental requirements.

[0052] Assemble the infrared detection system and place the infrared thermal imager in a suitable position so that the entire carbon fiber plate to be tested can be detected by the infrared thermal imager; place the halogen lamp in a suitable position so that the entire carbon fiber plate to be tested can be evenly heated. The power and pulse heating frequency of the halogen lamp can be adjusted according to the experimental requirements.

[0053] In this embodiment, a FILRA655sc thermal imager is used to perform infrared detection on 20 standard defect samples. The acquisition frequency is set to 100 Hz, the acquisition time is set to 10 to 20 seconds, and the distance between the thermal imager and the standard defect sample is set to 400 to 500 mm. The power of the halogen lamp is set to 20 KJ, and the distance between the halogen lamp and the standard defect sample is set to 400 to 500 mm.

[0054] Step (4): thermally stimulate each standard defect sample using a halogen lamp, and simultaneously use an infrared thermal imager to capture infrared thermal images and collect data.

[0055] The basic principle of infrared testing is to actively apply a preset, controllable thermal stimulus to the object under test. If defects are present inside and on the surface of the object, the surface temperature distribution will differ. Infrared thermal imagers can continuously observe changes in the surface temperature field of the object under test and collect and record the data. After analyzing and processing the captured infrared thermal images, not only can qualitative and rapid defects be detected, but also quantitative and precise defects can be detected.

[0056] Step (5) selects the optimal defect image from a series of infrared thermal images based on the feature image, and performs noise reduction, image enhancement, and threshold segmentation processing on it.

[0057] Among the many factors that influence defect dimensional accuracy, temperature resolution in infrared inspection systems is a crucial one. Background noise introduced by environmental and other factors can degrade infrared image quality and, consequently, reduce defect resolution. The optimal defect visualization time is related to the material's thermal diffusivity and defect depth. The deeper the defect, the lower the thermal diffusivity, and the later the optimal defect visualization time occurs. Infrared thermal images captured at the optimal defect visualization time have the most distinct defect features, making them considered optimal defect images.

[0058] In this embodiment, when infrared testing is performed on a standard defect sample according to the detailed parameters set in step (3), an image sequence corresponding to each infrared thermal image is also generated during the process of collecting infrared thermal images. Feature extraction is performed on each infrared thermal image to obtain a feature-extracted image. The optimal defect image can be determined based on the maximum temperature difference value in the feature-extracted image. Because each infrared thermal image has a corresponding image sequence, the optimal defect image can be accurately saved from a large number of infrared thermal images.

[0059] To improve the quality of the optimal defect image, the selected optimal defect image is subjected to noise reduction, image enhancement, and threshold segmentation. Contrast enhancement, pseudo-color enhancement, or wavelet algorithms are used for noise reduction and enhancement of the optimal defect image. Threshold segmentation of the noise-reduced and enhanced image is performed using the watershed segmentation method, Otsu algorithm, or Triangle algorithm.

[0060] Step (6) extracts the spatial data required to construct the defect geometry from the processed optimal defect image, reproduces the defect geometry using Tecplot software, and calculates the defect volume.

[0061] First, the spatial data required to construct the defect geometry is extracted from the processed optimal defect image. This step can be achieved by reading the optimal defect image with an industrial computer. The generated spatial data can be saved in a specific format according to individual needs.

[0062] Secondly, the generated spatial data is refined and processed. This step adopts different processing methods depending on the characteristics of the processing object. When the amount of generated spatial data is too large, it needs to be properly screened and deleted, which can reduce the amount of data required for the reconstruction of the defect geometry. However, in the process of data screening and deletion, the original information should be retained as much as possible to ensure that useful information is not lost. When the distribution of reconstructed data is too sparse and thus affects the reconstruction effect of the defect geometry, the data used for reconstruction needs to be interpolated. It should be noted that in the original data for reconstructing the defect geometry, each data does not have a direction, but the direction of each data is used when reconstructing the defect geometry. Therefore, the direction of each data needs to be calculated before reconstructing the defect geometry.

[0063] Next, choose a method for reconstructing the defect geometry. There are currently two distinct approaches to reconstructing three-dimensional space: volume rendering and surface rendering. When it comes to quantitative defect reconstruction, surface rendering is more appropriate.

[0064] Finally, the defect geometry is reconstructed and output. Tecplot, developed by Amtecg, offers superior performance and can effectively process a variety of data structures. Inputting data into Tecplot allows for reconstruction and output of the defect geometry.

[0065] Step (7): After all standard defective specimens are subjected to infrared detection and their respective defect geometric configurations are calculated, tensile tests are performed in sequence to measure their tensile strength loss rate, and the relationship between the tensile strength loss rate and the defect geometric configuration volume K=f(V) is established.

[0066] In the established relationship between the tensile strength loss rate and the volume of the defective geometric configuration, K=f(V), the tensile strength loss rate is defined as 0% when the carbon fiber plate is defect-free, and the difference between the tensile strength of the defect-free carbon fiber plate and the tensile strength of the defective carbon fiber plate divided by the tensile strength of the defect-free carbon fiber plate is defined as the tensile strength loss rate K. In this embodiment, the defect geometric configuration volumes and the corresponding tensile strength loss rates of 20 standard defective specimens are substituted into K=f(V) to obtain K1, K2, K3, ..., K n , K1, K2, K3, ..., K n The value fitting generates the relationship curve K=f(V).

[0067] Step (8): Calculate the defect geometry and mechanical property loss of the carbon fiber plate to be tested.

[0068] According to step (3), the experimental platform is assembled and the experimental parameters are set. The carbon fiber plate to be tested is subjected to infrared detection, infrared thermal images are taken and data is collected. According to steps (5) and (6), the geometric configuration of the defect can be reconstructed and output, and the volume of the defect is calculated. The data is input into step (7) to fit and generate the relationship curve K=f(V), and the loss rate of the tensile strength of the carbon fiber plate to be tested can be calculated.

[0069] The present invention has established a complete detection system. Through quantitative detection of standard defective samples, the relationship K=f(V) between the tensile strength loss rate of carbon fiber plates and the volume of the defect geometric configuration is established, which realizes the rapid monitoring of carbon fiber plates and has broad prospects for practical application.

[0070] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements to the present invention are intended to fall within the scope of protection of the present invention.

Claims

1. A method for quantitatively detecting geometric configuration defects and mechanical property loss in carbon fiber sheets, characterized by: The steps include: Step (1), quantitatively preparing a series of standard defect specimens: impact tests are sequentially performed on a series of carbon fiber plates of the same material and thickness as the carbon fiber plate to be tested; each carbon fiber plate has only one impact defect, and the impact energy received by each carbon fiber plate is different; this series of carbon fiber plates with different impact defects are regarded as standard defect specimens; Step (2): thoroughly clean the surface of the standard defect sample to ensure that there is no interference from debris during the subsequent infrared thermal imaging process; Step (3), adjusting the position and distance between the infrared thermal imager, the halogen lamp and the standard defect sample, and setting the flash frequency and power of the halogen lamp, the object reflectivity and the reflection temperature of the infrared thermal imager to meet the experimental requirements; Step (4), using a halogen lamp to perform thermal excitation on each standard defect sample, and simultaneously using an infrared thermal imager to take infrared thermal images and collect data; Step (5), selecting the optimal defect image from a series of infrared thermal images based on the feature image, and performing noise reduction, image enhancement, and threshold segmentation processing on the optimal defect image; Step (6): extracting the spatial data required to construct the defect geometry from the processed optimal defect image, reproducing the defect geometry using Tecplot software, and calculating the defect volume; Step (7), after all standard defect samples are subjected to infrared detection and their respective defect geometric configurations are calculated, tensile tests are performed in sequence to measure their tensile strength loss rates, and the relationship between the tensile strength loss rate and the defect geometric configuration volume K=f(V) is established; Step (8), calculate the defect geometry and mechanical property loss of the carbon fiber plate to be tested: use a halogen lamp to thermally excite the carbon fiber plate to be tested, and simultaneously use an infrared thermal imager to take infrared thermal images and collect data, and obtain the defect geometry and tensile strength loss rate according to steps (5) to (7).

2. The method for quantitatively detecting geometric configuration defects and mechanical property loss of carbon fiber sheet according to claim 1, characterized in that: The impact test described in step (1) is completed using a double-guide rail drop hammer device, which generates different impact energies by controlling the total mass of the drop hammer loading.

3. The method for quantitatively detecting geometric configuration defects and mechanical property loss of carbon fiber sheet according to claim 1, characterized in that: The specific algorithm for performing noise reduction, image enhancement, and threshold segmentation on the defect optimal image described in step (5) is: when performing noise reduction and enhancement on the defect optimal image, contrast enhancement, pseudo color enhancement, or wavelet algorithm is used; when performing threshold segmentation on the image after noise reduction and enhancement, watershed segmentation method, Otsu algorithm, or Triangle algorithm is used.

4. The method for quantitatively detecting geometric configuration defects and mechanical property loss of carbon fiber sheet according to claim 1, characterized in that: In the relationship K=f(V) established in step (7), the tensile strength loss rate is defined as 0% when the carbon fiber plate is defect-free, and the difference between the tensile strength of the defect-free carbon fiber plate and the tensile strength of the defective carbon fiber plate divided by the tensile strength of the defect-free carbon fiber plate is defined as the loss rate K. K is K1, K2, K3, ..., K obtained by calculating the volumes of different defective geometric configurations in sequence. n The value of .

5. A double-guide rail drop hammer device for realizing the method of quantitatively detecting the geometric configuration of defects and mechanical property loss of carbon fiber plates as described in any one of claims 1 to 4, comprising a static support (1), an impact hammer body (2), a pulley (3), a punch (4), a weight (5), a sample fixing table (6), a guide rail (7), and a fixing nut (8), wherein the impact hammer body (2), the punch (4), the weight (5), and the pulley (3) constitute the impact hammer body (2), the guide rail (7) is fixed on the inner side of the static support (1), and the pulley (3) slides on the guide rail (7); the impact hammer body (2) and the weight (5) are fixed on the supporting crossbeam through a screw and a fixing nut (8), and the two ends of the supporting crossbeam are respectively connected to the pulley (3) shaft; before the impact test begins, the first carbon fiber plate to be tested is fixed on the sample fixing table (6), and then the impact hammer body (2) is lifted to the highest point and freely falls, and the gravitational potential energy of the impact hammer body (2) is converted into kinetic energy, and the impact hammer body (2) After the punch (4) of the impact hammer (2) collides with the plate to be tested, impact damage is generated; after the first carbon fiber plate to be tested is taken out, the second carbon fiber plate is fixed on the sample fixing table (6), and a weight of 0.1 kg is fixed on the top of the impact hammer (2), and then the impact hammer (2) is lifted to the highest point and falls freely, and the gravitational potential energy of the impact hammer (2) is converted into kinetic energy, and the punch (4) of the impact hammer (2) collides with the plate to be tested, resulting in impact damage; after the second carbon fiber plate to be tested is taken out, the third carbon fiber plate is fixed on the sample fixing table (6), and a weight of 0.2 kg is fixed on the top of the impact hammer (2), and then the impact hammer (2) is lifted to the highest point and falls freely, and the gravitational potential energy of the impact hammer (2) is converted into kinetic energy, and the punch (4) of the impact hammer (2) collides with the plate to be tested, resulting in impact damage; impact tests are carried out on 20 3K carbon fiber plates, and the 3K carbon fiber plates after the impact are standard defect samples.

Images