Defect detection method and device, storage medium and electronic device

Abstract

The present disclosure relates to the field of material detection, and particularly relates to a defect detection method and device, a storage medium and an electronic device. The defect detection method comprises: acquiring a defect detection parameter and a thermal radiation reference image of a ceramic matrix composite material to be detected, wherein the defect detection parameter comprises an infrared detection power; performing infrared detection on the ceramic matrix composite material to be detected based on the defect detection parameter to obtain a thermal radiation detection image of the ceramic matrix composite material to be detected; and determining a defect detection result of the ceramic matrix composite material to be detected according to the thermal radiation reference image and the thermal radiation detection image. Through the method, the defect detection period is greatly shortened, the accuracy and timeliness of defect detection are fundamentally improved, and strong technical support is provided for quality control and performance optimization of the ceramic matrix composite material.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of material detection, and particularly relates to a defect detection method and device, a storage medium and an electronic device. BACKGROUND

[0002] Ceramic matrix composites have gained widespread acclaim in various fields due to their outstanding high specific strength, excellent high-temperature performance, strong oxidation resistance, and low density. In particular, in the field of cutting-edge technology such as aerospace, their application has reached an unprecedented depth and breadth. China has successfully developed and mastered the preparation technology of ceramic matrix composites for large and complex components, marking a major breakthrough in the field of material science.

[0003] However, despite the significant progress in technology, the preparation process of ceramic matrix composites still faces challenges such as complexity and long duration, which directly leads to the occurrence of macroscopic defects such as pores and delamination in the microstructure of the material, as well as uneven distribution of pores, which are key difficulties in accurately assessing and controlling the internal quality of the material.

[0004] Therefore, further optimizing the preparation process, reducing defects, and improving the overall performance of the material have become important directions for current research and practice. SUMMARY

[0005] The main purpose of the present disclosure is to provide a defect detection method, device, storage medium and electronic device, which aims to solve the technical problems of poor accuracy and timeliness of defect detection for ceramic matrix composites in the prior art.

[0006] To achieve the above-mentioned purpose, the present disclosure provides a defect detection method, comprising:

[0007] obtaining defect detection parameters and a thermal radiation reference image of a ceramic matrix composite to be detected, the defect detection parameters including infrared detection power;

[0008] based on the defect detection parameters, performing infrared detection on the ceramic matrix composite to be detected to obtain a thermal radiation detection image of the ceramic matrix composite to be detected;

[0009] determining a defect detection result of the ceramic matrix composite to be detected according to the thermal radiation reference image and the thermal radiation detection image.

[0010] Optionally, the obtaining of the defect detection parameters and the thermal radiation reference image of the ceramic matrix composite to be detected comprises:

[0011] obtaining a contrast test block of the ceramic matrix composite to be detected, the contrast test block being used to simulate material defects of the ceramic matrix composite;

[0012] determine an infrared detection device for infrared detection of the ceramic matrix composite material to be detected;

[0013] based on the contrast test block, the sensitivity of the infrared detection device is verified, and the verified infrared detection device is obtained, the power of the verified infrared detection device meets the power condition of the ceramic matrix composite material to be detected, and the power condition is determined based on the heat absorption capacity of the ceramic matrix composite material to be detected;

[0014] by the verified infrared detection device, the contrast test block is subjected to infrared detection, and the defect detection parameters and the thermal radiation reference image are obtained.

[0015] Optionally, the power of the verified infrared detection device is greater than or equal to 4000W.

[0016] Optionally, the contrast test block of the ceramic matrix composite material to be detected comprises:

[0017] Obtain the material information of the ceramic matrix composite material to be detected, the material information including the structure data, material data and manufacturing method data of the ceramic matrix composite material to be detected;

[0018] Obtain the defect information of the ceramic matrix composite material to be detected, the defect information including the defect position and defect quantity corresponding to the possible defects of the ceramic matrix composite material to be detected;

[0019] Obtain the preset blind hole information, the blind hole information including a plurality of blind hole sizes;

[0020] According to the material information, the defect information and the blind hole information, a flat bottom hole method is used to prepare the contrast test block.

[0021] Optionally, the defect detection result of the ceramic matrix composite material to be detected is determined according to the thermal radiation reference image and the thermal radiation detection image, comprising:

[0022] According to the thermal radiation reference image and the thermal radiation detection image, the defect area of the ceramic matrix composite material to be detected is determined, and the color of the defect area is consistent with the defect color in the thermal radiation reference image;

[0023] According to the thermal radiation detection image, the uniformity evaluation of the ceramic matrix composite material to be detected is obtained, and the uniformity evaluation result is obtained;

[0024] According to the defect area and the uniformity evaluation result, the defect detection result of the ceramic matrix composite material to be detected is determined.

[0025] Optionally, the determining the defect region of the ceramic matrix composite material to be detected according to the thermal radiation reference image and the thermal radiation detection image comprises:

[0026] comparing the thermal radiation reference image and the thermal radiation detection image to obtain a comparison result image;

[0027] performing color enhancement processing on the comparison result image to obtain an enhanced comparison result image;

[0028] determining defect position information and defect size information of the ceramic matrix composite material to be detected based on the enhanced comparison result image;

[0029] determining the defect region according to the defect position information and the defect size information.

[0030] Optionally, the uniformity evaluation of the ceramic matrix composite material to be detected according to the thermal radiation detection image comprises:

[0031] performing gray scale processing on the thermal radiation detection image to obtain a thermal radiation detection gray scale image;

[0032] statistically analyzing the distribution of each pixel point in the thermal radiation detection gray scale image to obtain a distribution histogram;

[0033] converting the data in the distribution histogram into a pixel point distribution matrix, and calculating a statistical quantity of the pixel point distribution matrix, the statistical quantity comprising a standard deviation, an average, and a coefficient of variation;

[0034] performing uniformity evaluation of the ceramic matrix composite material to be detected according to the statistical quantity to obtain the uniformity evaluation result.

[0035] In addition, to achieve the above-mentioned purposes, the present disclosure further provides a defect detection device, which comprises:

[0036] an acquisition module configured to acquire defect detection parameters of a ceramic matrix composite material to be detected and a thermal radiation reference image, the defect detection parameters comprising an infrared detection power;

[0037] a detection module configured to perform infrared detection on the ceramic matrix composite material to be detected based on the defect detection parameters to obtain a thermal radiation detection image of the ceramic matrix composite material to be detected;

[0038] a determination module configured to determine a defect detection result of the ceramic matrix composite material to be detected according to the thermal radiation reference image and the thermal radiation detection image.

[0039] In addition, to achieve the above object, the present disclosure further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and a processor executes the computer program to implement the above method.

[0040] In addition, to achieve the above object, the present disclosure further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above method.

[0041] In addition, to achieve the above object, the present disclosure further provides a computer program product, which, when executed by a processor, implements the above method.

[0042] The defect detection method, device, storage medium and electronic device provided by the embodiments of the present disclosure first acquire the defect detection parameters of the ceramic matrix composite to be detected and a thermal radiation reference image, wherein the defect detection parameters include an infrared detection power. Then, based on the defect detection parameters, the ceramic matrix composite to be detected is subjected to infrared detection to obtain a thermal radiation detection image of the ceramic matrix composite to be detected. Finally, according to the thermal radiation reference image and the thermal radiation detection image, a defect detection result of the ceramic matrix composite to be detected is determined. In this way, by using infrared detection technology, the ceramic matrix composite can be detected non-contactingly and non-destructively, and by comparing and analyzing the thermal radiation detection image and the thermal radiation reference image, the temperature abnormal area in the material, i.e., the potential defect position, can be identified. Not only the detection accuracy and efficiency are improved, but also the possibility of human misjudgment is greatly reduced. The accuracy and timeliness of defect detection are fundamentally improved, and strong technical support is provided for quality control and performance optimization of the ceramic matrix composite. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor on the basis of the drawings shown.

[0044] Figure 1 The device structure schematic diagram of the hardware running environment related to the embodiments of the present disclosure;

[0045] Figure 2 The flowchart of the defect detection method related to the embodiments of the present disclosure;

[0046] Figure 3 The design drawing of the contrast test block related to the embodiments of the present disclosure;

[0047] Figure 4 A thermal radiation detection image related to an embodiment of the present disclosure;

[0048] Figure 5 A structural block diagram of a defect detection device related to an embodiment of the present disclosure.

[0049] The implementation, functional features and advantages of the present disclosure will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present disclosure.

[0051] Referring to FIG. 1, Figure 1 A device structure schematic diagram of a hardware running environment related to an embodiment of the present disclosure.

[0052] Generally, the device comprises at least one processor 301, a memory 302, and a defect detection program stored in the memory 302 and executable on the processor 301, the defect detection program being configured to implement the steps of the defect detection method as described above.

[0053] The processor 301 can include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 301 can be implemented in at least one of a hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), a PLA (Programmable Logic Array). The processor 301 can also include a main processor and a coprocessor, the main processor being a processor for processing data in an awake state, also known as a CPU (Central Processing Unit), and the coprocessor being a low-power processor for processing data in a standby state. In some embodiments, the processor 301 can be integrated with a GPU (Graphics Processing Unit) that is responsible for rendering and drawing the content required to be displayed by the display screen. The processor 301 can also include an AI (Artificial Intelligence) processor for processing the operation of the defect detection method, so that the defect detection method model can be autonomously trained and learned to improve efficiency and accuracy.

[0054] The memory 302 can include one or more storage media, which can be non-transitory. The memory 302 can also include a high-speed random access memory, and a non-volatile memory such as one or more disk storage devices, flash storage devices. In some embodiments, the non-transitory storage medium in the memory 302 is used to store at least one instruction for being executed by the processor 301 to implement the defect detection method provided by the method embodiment in the present disclosure.

[0055] In some embodiments, the terminal can also optionally include a communication interface 303 and at least one peripheral device. The processor 301, the memory 302, and the communication interface 303 can be connected through a bus or a signal line. Each peripheral device can be connected to the communication interface 303 through a bus, a signal line, or a circuit board. Specifically, the peripheral device includes at least one of a radio frequency circuit 304, a display screen 305, and a power supply 306.

[0056] The communication interface 303 can be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 301 and the memory 302. In some embodiments, the processor 301, the memory 302 and the communication interface 303 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 301, the memory 302 and the communication interface 303 can be implemented on a separate chip or circuit board, and the present embodiment does not limit this.

[0057] The radio frequency circuit 304 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 304 communicates with a communication network and other communication devices through electromagnetic signals. The radio frequency circuit 304 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the radio frequency circuit 304 includes an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and the like. The radio frequency circuit 304 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: a metropolitan area network, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 304 can also include NFC (Near Field Communication) related circuit, and the present disclosure does not limit this.

[0058] The display screen 305 is configured to display a UI (User Interface). The UI can include graphics, text, icons, video, and any combination thereof. When the display screen 305 is a touch display screen, the display screen 305 is further configured to capture touch signals on or above the surface of the display screen 305. The touch signals can be input to the processor 301 as control signals for processing. In this case, the display screen 305 can also be configured to provide virtual buttons and / or virtual keyboard, also known as soft buttons and / or soft keyboard. In some embodiments, the display screen 305 can be one, front panel of the electronic device; in other embodiments, the display screen 305 can be at least two, respectively arranged on different surfaces of the electronic device or in a folding design; in yet other embodiments, the display screen 305 can be a flexible display screen, arranged on a curved surface or a folding surface of the electronic device. Even, the display screen 305 can also be arranged in an irregular shape other than a rectangle, i.e., a notched screen. The display screen 305 can be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), etc.

[0059] The power supply 306 is configured to supply power to various components in the electronic device. The power supply 306 can be AC power, DC power, disposable battery or rechargeable battery. When the power supply 306 includes a rechargeable battery, the rechargeable battery can support wired charging or wireless charging. The rechargeable battery can also be configured to support fast charging technology. Those skilled in the art can understand that Figure 1 The structure shown in the figure does not constitute a limitation on the device, and can include more or fewer components than shown, or combine certain components, or different arrangement of components.

[0060] In addition, the embodiments of the present disclosure also propose a storage medium, wherein the storage medium stores a defect detection program, and the defect detection program is executed by a processor to implement the steps of the defect detection method described above. Therefore, no further description will be given here. In addition, the description of the beneficial effects of using the same method will not be given further. For technical details of the storage medium embodiments involved in the present disclosure, please refer to the description of the method embodiments of the present disclosure. For example, the program instructions can be deployed to be executed on one device, or on multiple devices located in one place, or on multiple devices distributed in multiple places and interconnected through a communication network.

[0061] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The above-mentioned program can be stored in a storage medium. When the program is executed, it can include the processes of the above-mentioned embodiment methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), or the like.

[0062] In recent years, the internal quality problem of ceramic matrix composites has become increasingly prominent, becoming a new challenge faced by the industry. In view of this emerging problem and the new detection needs it brings, there is currently a lack of mature and standardized detection means in the field.

[0063] In the related art, the non-destructive testing of resin matrix composites relies mainly on ultrasonic and X-ray technologies. However, the unique acoustic properties of ceramic matrix composites, namely high attenuation and anisotropy, severely limit the penetration ability of ultrasonic waves, making it difficult to accurately capture internal information. On the other hand, although X-ray detection can effectively identify volumetric defects, it is not sensitive enough to area defects such as delamination, which is particularly critical in ceramic matrix composites.

[0064] Therefore, the present disclosure proposes a defect detection method, device, storage medium and electronic equipment. Based on high-power infrared technology, the internal quality of ceramic matrix composites is detected, aiming to overcome the limitations of existing technologies and achieve accurate monitoring of the internal quality of ceramic matrix composites.

[0065] Reference Figure 2 , Figure 2 A flowchart of a defect detection method according to an embodiment of the present disclosure is shown in FIG. 1. The method includes the following steps:

[0066] Step S11: Obtain the defect detection parameters and thermal radiation reference image of the ceramic matrix composite to be detected. The defect detection parameters include the infrared detection power.

[0067] Step S12: Based on the defect detection parameters, perform infrared detection on the ceramic matrix composite to be detected to obtain the thermal radiation detection image of the ceramic matrix composite to be detected.

[0068] Step S13: Determine the defect detection result of the ceramic matrix composite to be detected according to the thermal radiation reference image and the thermal radiation detection image.

[0069] By the above technical solution, first, the defect detection parameters of the ceramic matrix composite to be detected and the thermal radiation reference image are obtained, wherein the defect detection parameters include the infrared detection power. Then, based on the defect detection parameters, the ceramic matrix composite to be detected is subjected to infrared detection to obtain a thermal radiation detection image of the ceramic matrix composite to be detected. Finally, according to the thermal radiation reference image and the thermal radiation detection image, the defect detection result of the ceramic matrix composite to be detected is determined. In this way, by using the infrared detection technology, the ceramic matrix composite can be detected non-contact and non-destructively, and by comparing and analyzing the thermal radiation detection image and the thermal radiation reference image, the temperature abnormal area in the material, i.e. the potential defect position, can be identified. Not only the detection accuracy and efficiency are improved, but also the possibility of human error is greatly reduced. The accuracy and timeliness of defect detection are fundamentally improved, providing strong technical support for quality control and performance optimization of ceramic matrix composites.

[0070] Further, the technical effects of the above technical solution not only lie in the accuracy and reliability of the detection result, but also lie in the rapidity and automation degree of the detection process, providing strong support for the quality control and safety guarantee of ceramic matrix composites. At the same time, the above technical solution not only fills the gap in the field of internal quality detection of ceramic matrix composites, but also provides strong technical support for promoting the progress of related industry technology and improving the quality control level.

[0071] In a possible manner, the defect detection parameters of the ceramic matrix composite to be detected and the thermal radiation reference image are obtained, comprising:

[0072] A contrast test block of the ceramic matrix composite to be detected is obtained, and the contrast test block is used to simulate material defects of the ceramic matrix composite;

[0073] An infrared detection device for infrared detection of the ceramic matrix composite to be detected is determined;

[0074] The sensitivity of the infrared detection device is verified based on the contrast test block to obtain a verified infrared detection device, and the power of the verified infrared detection device meets the power condition of the ceramic matrix composite to be detected, wherein the power condition is determined based on the heat absorption capacity of the ceramic matrix composite to be detected;

[0075] The contrast test block is subjected to infrared detection by the verified infrared detection device to obtain the defect detection parameters and the thermal radiation reference image.

[0076] It should be understood that the main purpose of the sensitivity check is to ensure that the infrared detection equipment can accurately and clearly identify the artificial defects in the contrast test block, so as to verify whether the detection capability of the equipment meets the detection requirements. The defect detection parameter refers to a series of technical parameters set during the sensitivity check process of the infrared detection equipment to ensure that the equipment can accurately identify the artificial defects in the contrast test block. These parameters are crucial to the accuracy and reliability of the detection results. Specifically, the defect detection parameter can include the power, frame frequency, excitation time, scanning mode, detection distance and other related parameters of the infrared detection equipment. The embodiments of the present disclosure do not limit this.

[0077] For example, first, an infrared detection equipment can be selected, whose power preliminarily meets the basic requirements of the detection of the ceramic matrix composite to be detected. In order to optimize resource utilization and ensure the accuracy of the detection results, the infrared detection equipment can be further checked for sensitivity by using the contrast test block. Through the contrast test block, the ceramic matrix composite under different defect states can be simulated, so as to evaluate the defect detection capability of the infrared detection equipment under different conditions. Based on the test results of the contrast test block, the optimal working power of the infrared detection equipment can be further refined and determined to ensure that potential defects inside the material can be effectively detected during the detection process, and unnecessary energy waste can be avoided.

[0078] Specifically, in order to ensure that the infrared detection equipment can accurately adapt to the characteristics of the ceramic matrix composite to be detected, a sensitivity test block with matching or similar characteristics to the infrared detection equipment can be selected for checking. Among them, the sensitivity test block is internally provided with defects of known size, depth and distribution to simulate various types of flaws that may occur in real materials, so as to further compare.

[0079] During the checking process, the known characteristics of the sensitivity test block can be used as a standard reference for comparison and analysis with the detection results of the infrared detection equipment. Through this process, the performance of the equipment in detecting specific types of defects, including its sensitivity, accuracy and stability, can be evaluated in depth. Based on the checking results of the sensitivity test block, the defect detection parameters of the infrared detection equipment can be further refined and adjusted. In this way, through repeated testing and comparison, the defect detection is continuously iteratively optimized, and the best defect detection combination that meets the detection requirements can be found.

[0080] Then, the sensitivity test block is detected using the adjusted parameters, and the detection results are observed and recorded. It is ensured that the equipment can clearly and accurately identify the defect position, shape and size in the contrast test block. If the equipment can meet the detection requirements, i.e. it can clearly identify the defects in the sensitivity test block, the checking is completed. The defect detection parameters after the checking are recorded, and the infrared detection equipment and the defect detection parameters after the checking are used to detect the contrast test block, and a thermal radiation reference image is obtained.

[0081] In a possible manner, the power of the infrared detection device after inspection is greater than or equal to 4000 W.

[0082] For example, by using the above method, the power of the infrared detection device after inspection is ensured to meet the power condition of the ceramic matrix composite to be detected based on the heat absorption capacity of the ceramic matrix composite to be detected. Specifically, it can be determined that the power of the infrared detection device after inspection is greater than or equal to 4000 W, that is, an infrared detection device with a power of 4000 W can be used for defect detection.

[0083] Of course, other manners can also be used to determine the power of the infrared detection device after inspection based on the heat absorption capacity of the ceramic matrix composite to be detected, as long as the power of the infrared detection device after inspection meets the power condition of the ceramic matrix composite to be detected, which is not limited in the embodiments of the present disclosure.

[0084] In a possible manner, the contrast test block of the ceramic matrix composite to be detected is obtained, including:

[0085] The material information of the ceramic matrix composite to be detected is obtained, and the material information includes structure data, material data and manufacturing method data of the ceramic matrix composite to be detected.

[0086] The defect information of the ceramic matrix composite to be detected is obtained, and the defect information includes defect positions and defect quantities corresponding to possible defects of the ceramic matrix composite to be detected.

[0087] The preset blind hole information is obtained, and the blind hole information includes a plurality of blind hole sizes.

[0088] According to the material information, the defect information and the blind hole information, a flat-bottom hole method is used to prepare the contrast test block.

[0089] For example, the structure, material and manufacturing of the contrast test block should be the same as the ceramic matrix composite to be detected. For example, if the ceramic matrix composite to be detected is a plane structure made by the CVI (chemical vapor deposition) + PIP (impregnation and pyrolysis) method, the test block should also be prepared by the CVI + PIP method to eliminate the influence of structural differences on the detection result.

[0090] In addition, the comparison test block includes artificial defects, which can be precisely machined into the block using a flat-bottomed hole method to simulate the actual morphology of macroscopic defects in the ceramic matrix composite material being tested. The location, shape, and size of these defects are determined based on the defect information analysis results of the ceramic matrix composite material being tested, ensuring the realism of the simulation. Then, based on preset blind hole information, blind holes of different sizes can be machined into the comparison test block to meet the needs of different detection sensitivities. At the same time, the possibility of increasing the blind hole size in the future is reserved to adapt to changes in technology development and detection requirements.

[0091] Specifically, Figure 3 This is a design drawing of a comparative test block involved in an embodiment of this disclosure. For example... Figure 3 As shown, based on current technological levels and actual testing needs, and considering the common defect levels that need to be detected during internal quality testing of ceramic matrix composite materials, the blind hole information in this disclosure can be preset to include various blind hole sizes such as φ3mm, φ6mm, and φ9mm, and depth dimensions can include 0.4mm, 2mm, and 3.6mm to cover different levels of detection sensitivity. The selection of these sizes can comprehensively simulate the defects of ceramic matrix composite materials and characterize the defect detection capability of the testing system, ensuring that it can accurately identify and quantify the defects of ceramic matrix composite materials under various conditions. Of course, the corresponding blind hole information can also be preset based on the macroscopic defects of the ceramic matrix composite material to be tested in actual applications and the defect values ​​that the system can detect; this disclosure does not specifically limit this.

[0092] This technical solution targets ceramic matrix composites, preparing highly consistent and representative comparative test blocks, providing strong support for the internal quality inspection of ceramic matrix composites. With continuous technological advancements and increasingly diverse testing needs, parameters such as blind hole size in this solution will be continuously optimized and expanded to adapt to a wider range of testing scenarios and requirements.

[0093] In possible ways, the defect detection results of the ceramic matrix composite material to be inspected are determined based on thermal radiation reference images and thermal radiation detection images, including:

[0094] Based on the thermal radiation reference image and the thermal radiation detection image, the defect area of ​​the ceramic matrix composite material to be tested is determined, and the color of the defect area is consistent with the defect color in the thermal radiation reference image.

[0095] Based on the thermal radiation detection images, the uniformity of the ceramic matrix composite material under test is evaluated, and the uniformity evaluation results are obtained.

[0096] Based on the evaluation results of defect area and uniformity, the defect detection results of the ceramic matrix composite material to be tested are determined.

[0097] For example, the thermal radiation reference image is acquired on the same or similar material in a defect-free or known defect state, which can be used as a contrast benchmark. Therefore, by comparing the thermal radiation detection image with the thermal radiation reference image, the defect area of the ceramic matrix composite to be detected can be determined.

[0098] In addition, in the thermal radiation detection image, in addition to focusing on the defect area, the overall analysis of the thermal radiation distribution of the entire material can also be performed, that is, the uniformity of the thermal radiation on the surface or inside of the material is evaluated. Specifically, the temperature difference, temperature gradient or standard deviation of the thermal radiation intensity of different regions in the image can be calculated, and then according to the preset uniformity standard or threshold, it can be judged whether the uniformity of the ceramic matrix composite to be detected meets the requirements.

[0099] In a possible manner, the defect area of the ceramic matrix composite to be detected is determined according to the thermal radiation reference image and the thermal radiation detection image, comprising:

[0100] Comparing the thermal radiation reference image and the thermal radiation detection image, a comparison result image is obtained;

[0101] Performing color enhancement processing on the comparison result image to obtain an enhanced comparison result image;

[0102] Based on the enhanced comparison result image, the defect position information and the defect size information of the ceramic matrix composite to be detected are determined;

[0103] According to the defect position information and the defect size information, the defect area is determined.

[0104] For example, the thermal radiation detection image is compared with the thermal radiation reference image, if a region similar or consistent in color with the artificial defect color of the thermal radiation reference image appears in the thermal radiation detection image, it is considered that there is an artificial defect in the region. For example, higher temperature is displayed as red and lower temperature is displayed as blue. By identifying these color-consistent regions and the defect size of the region, the longest distance X and the shortest distance Y of the region are recorded to identify the size of the defect, and the defect size information is obtained. According to the defect position information and the defect size information, the defect area in the ceramic matrix composite to be detected can be determined.

[0105] It should be noted that, Figure 4 For a thermal radiation detection image involved in the embodiment of the present disclosure, as Figure 4 As shown in the figure, the ceramic matrix composite to be detected can have one or more defects, and one or more types of defects. Therefore, the defect position information can include one or more defect positions, and the defect size information can also include one or more defect sizes, which are not limited by the embodiment of the present disclosure.

[0106] In a possible manner, the uniformity of the ceramic matrix composite to be detected is evaluated according to the thermal radiation detection image, and a uniformity evaluation result is obtained, including:

[0107] The thermal radiation detection image is subjected to grayscale processing to obtain a thermal radiation detection grayscale image.

[0108] The distribution of each pixel point in the thermal radiation detection grayscale image is counted to obtain a distribution histogram.

[0109] Data in the distribution histogram is converted into a pixel point distribution matrix, and a statistical quantity of the pixel point distribution matrix is calculated, the statistical quantity including a standard deviation, an average, and a coefficient of variation.

[0110] The uniformity of the ceramic matrix composite to be detected is evaluated according to the statistical quantity, and a uniformity evaluation result is obtained.

[0111] For example, the thermal radiation detection image can be subjected to grayscale processing by using a professional image processing software (such as MATLAB) to obtain a thermal radiation detection grayscale image, so as to ensure simplification and standardization of image information and facilitate subsequent statistical analysis. Specifically, the thermal radiation detection image can be converted into a thermal radiation detection grayscale image by using an rgb2gray function, and the grayscale value range is set to 0-255. Of course, the thermal radiation detection image can also be subjected to image processing in other manners to ensure simplification and standardization of image information, and the embodiments of the present disclosure do not limit this.

[0112] Then, the distribution of each pixel point in the grayscale image is counted by using an imhist command to generate a distribution histogram. The histogram directly shows the number distribution of different grayscale level pixel points in the image, and is an important basis for evaluating the uniformity of the image.

[0113] Then, for the convenience of subsequent data processing by using matrix operation, the histogram data can be converted into a matrix form of a*b, that is, a pixel point distribution matrix is obtained. The pixel point distribution matrix can be a single-row matrix of 1*256, and the embodiments of the present disclosure do not limit this.

[0114] Finally, the standard deviation of the matrix data can be calculated by using a built-in function std of MATLAB to determine the dispersion degree of data distribution, and the function can automatically ignore non-numerical items in the data to ensure the accuracy of calculation. The average of the matrix data is calculated by using a mean function to obtain the average grayscale value of the grayscale image. In order to more accurately evaluate the uniformity of the material, the ratio of the standard deviation to the average, that is, the coefficient of variation, can be further calculated. The coefficient eliminates the influence of the data dimension and can more objectively reflect the relative change degree between data.

[0115] Therefore, the uniformity of the ceramic matrix composite to be detected can be evaluated according to the statistical quantity, and a uniformity evaluation result is obtained. In the present disclosure, the uniformity of the ceramic matrix composite to be detected can be quantitatively evaluated according to the calculated coefficient of variation. A low coefficient of variation indicates that the internal temperature (or thermal radiation) distribution of the ceramic matrix composite to be detected is relatively uniform, while a high coefficient of variation indicates that the ceramic matrix composite to be detected may have local defects or non-uniformity. The greater the coefficient of variation, the worse the uniformity of the ceramic matrix composite to be detected.

[0116] The defect detection method provided by the present disclosure can not only accurately identify the subtle defects inside the ceramic matrix composite, but also accurately locate the size and position of the defects. In this way, while ensuring the quality of the material, the application boundary of the non-destructive testing technology is also greatly widened.

[0117] For a sample with a standard size of 200mm*200mm, the method provided by the present disclosure can realize comprehensive and in-depth scanning of the internal macroscopic defects of the sample in 20 minutes, and simultaneously complete the comprehensive evaluation of the uniformity of the material. Compared with the traditional method, this efficient detection process not only greatly shortens the defect detection period, but also fundamentally improves the accuracy and timeliness of defect detection, providing strong technical support for the quality control and performance optimization of ceramic matrix composites.

[0118] Reference Figure 5 , Figure 5 A structural block diagram of a defect detection device involved in an embodiment scheme of the present disclosure is based on the same inventive concept as the foregoing embodiment, and the device comprises:

[0119] The acquisition module 10 is configured to acquire a defect detection parameter and a thermal radiation reference image of a ceramic matrix composite to be detected, wherein the defect detection parameter comprises an infrared detection power.

[0120] The detection module 20 is configured to perform infrared detection on the ceramic matrix composite to be detected based on the defect detection parameter, and obtain a thermal radiation detection image of the ceramic matrix composite to be detected.

[0121] The determination module 30 is configured to determine a defect detection result of the ceramic matrix composite to be detected according to the thermal radiation reference image and the thermal radiation detection image.

[0122] Optionally, the acquisition module 10 is configured to:

[0123] acquire a contrast test block of the ceramic matrix composite to be detected, wherein the contrast test block is used to simulate material defects of the ceramic matrix composite;

[0124] determine an infrared detection device used for infrared detection on the ceramic matrix composite to be detected.

[0125] Based on the contrast test block, the sensitivity of the infrared detection device is verified, and a verified infrared detection device is obtained. The power of the verified infrared detection device meets the power condition of the ceramic matrix composite material to be detected, and the power condition is determined based on the heat absorption capacity of the ceramic matrix composite material to be detected.

[0126] The contrast test block is subjected to infrared detection by the verified infrared detection device, and the defect detection parameters and the thermal radiation reference image are obtained.

[0127] Optionally, the power of the verified infrared detection device is greater than or equal to 4000W.

[0128] Optionally, the acquisition module 10 is configured to:

[0129] Acquire material information of the ceramic matrix composite material to be detected, the material information including structure data, material data and manufacturing method data of the ceramic matrix composite material to be detected.

[0130] Acquire defect information of the ceramic matrix composite material to be detected, the defect information including defect positions and defect quantities corresponding to possible defects of the ceramic matrix composite material to be detected.

[0131] Acquire preset blind hole information, the blind hole information including a plurality of blind hole sizes.

[0132] According to the material information, the defect information and the blind hole information, a flat-bottom hole method is used to prepare the contrast test block.

[0133] Optionally, the determination module 30 is configured to:

[0134] According to the thermal radiation reference image and the thermal radiation detection image, a defect area of the ceramic matrix composite material to be detected is determined, and the color of the defect area is consistent with the defect color in the thermal radiation reference image.

[0135] According to the thermal radiation detection image, the ceramic matrix composite material to be detected is subjected to uniformity evaluation, and a uniformity evaluation result is obtained.

[0136] According to the defect area and the uniformity evaluation result, a defect detection result of the ceramic matrix composite material to be detected is determined.

[0137] Optionally, the determination module 30 is configured to:

[0138] The thermal radiation reference image and the thermal radiation detection image are compared to obtain a comparison result image.

[0139] The contrast result image is subjected to color enhancement processing to obtain an enhanced contrast result image;

[0140] Based on the enhanced contrast result image, the defect position information and the defect size information of the ceramic matrix composite material to be detected are determined.

[0141] According to the defect position information and the defect size information, the defect region is determined.

[0142] Optionally, the determination module 30 is configured to:

[0143] The thermal radiation detection image is subjected to gray scale processing to obtain a thermal radiation detection gray scale image;

[0144] The distribution of each pixel point in the thermal radiation detection gray scale image is counted to obtain a distribution histogram;

[0145] Data in the distribution histogram is converted into a pixel point distribution matrix, and a statistical quantity of the pixel point distribution matrix is calculated, the statistical quantity including a standard deviation, an average, and a coefficient of variation;

[0146] According to the statistical quantity, the uniformity of the ceramic matrix composite material to be detected is evaluated to obtain a uniformity evaluation result.

[0147] It should be noted that the steps performed by the device of the present embodiment are the same as those of the foregoing method embodiments, and the specific implementation manners and the technical effects that can be achieved are all referable to the foregoing embodiments, which will not be described herein again.

[0148] In addition, in an embodiment, the present embodiment also provides an electronic device, which includes a processor, a memory, and a computer program stored in the memory, and the computer program implements the steps of the method in the foregoing embodiments when executed by the processor.

[0149] In addition, in an embodiment, the present embodiment also provides a computer storage medium, which stores a computer program, and the computer program implements the steps of the method in the foregoing embodiments when executed by a processor.

[0150] In some embodiments, the computer readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disc, or CD-ROM; or various devices including one or any combination of the above memories. The computer can be various computing devices including smart terminals and servers.

[0151] In some embodiments, the executable instructions can take the form of a program, software, software modules, scripts, or code, written in any form of programming language, including compiled or interpreted languages, or declarative or procedural languages; and they can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0152] By way of example, the executable instructions can, but need not, reside in a file system's files, can be stored in a portion of a file that holds other programs or data, e.g., one or more scripts stored in a markup language document, in a single file dedicated to the program in question, or in multiple coordinated files, e.g., files that store one or more modules, sub programs, or portions of code.

[0153] By way of example, the executable instructions can be deployed to be executed on one computer, or on multiple computers of a distributed computing environment, or on multiple computers of a grid computing environment.

[0154] It should be noted that, as used in this document, the terms "includes" or "including" or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that includes a list of elements does not include only those elements recited, but can also include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element preceded by "comprises a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or system that comprises the recited element.

[0155] The above-mentioned sequence numbers of the embodiments of the present disclosure are only for description, and do not represent advantages or disadvantages of the embodiments.

[0156] Those skilled in the art can clearly understand the above-mentioned embodiment methods by the description of the above embodiments, which can be realized by software and necessary general hardware platforms, of course, can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present disclosure can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, or an optical disk), and includes a plurality of instructions for causing a multimedia terminal device (which can be a mobile phone, a computer, a television receiver, or a network device) to execute the methods described in the various embodiments of the present disclosure.

[0157] The above merely describes optional embodiments of the present disclosure, and does not limit the patent scope of the present disclosure, and any equivalent structural transformation made by using the content of the present disclosure and the drawings, or direct / indirect application in other related technical fields is included in the patent protection scope of the present disclosure.

Claims

1. A defect detection method characterized by, The method comprises the following steps: acquiring defect detection parameters and a thermal radiation reference image of a ceramic matrix composite material to be detected, wherein the defect detection parameters comprise infrared detection power; performing infrared detection on the ceramic matrix composite material to be detected based on the defect detection parameters, to obtain a thermal radiation detection image of the ceramic matrix composite material to be detected; determining a defect area of the ceramic matrix composite material to be detected according to the thermal radiation reference image and the thermal radiation detection image, wherein the color of the defect area is consistent with the defect color in the thermal radiation reference image; performing uniformity evaluation on the ceramic matrix composite material to be detected according to the thermal radiation detection image, to obtain a uniformity evaluation result; determining a defect detection result of the ceramic matrix composite material to be detected according to the defect area and the uniformity evaluation result.

2. The method of claim 1, wherein, The method comprises the following steps: acquiring a contrast test block of the ceramic matrix composite material to be detected, wherein the contrast test block is used to simulate material defects of the ceramic matrix composite material; determining an infrared detection device used for infrared detection on the ceramic matrix composite material to be detected; performing sensitivity verification on the infrared detection device based on the contrast test block, to obtain a verified infrared detection device, wherein the power of the verified infrared detection device meets the power condition of the ceramic matrix composite material to be detected, and the power condition is determined based on the heat absorption capacity of the ceramic matrix composite material to be detected; performing infrared detection on the contrast test block by using the verified infrared detection device, to obtain the defect detection parameters and the thermal radiation reference image.

3. The method of claim 2, wherein, The power of the verified infrared detection device is greater than or equal to 4000 W.

4. The method of claim 2, wherein, The method comprises the following steps: acquiring material information of the ceramic matrix composite material to be detected, wherein the material information comprises structure data, material data and manufacturing method data of the ceramic matrix composite material to be detected; acquiring defect information of the ceramic matrix composite material to be detected, wherein the defect information comprises defect positions and defect quantities corresponding to possible defects of the ceramic matrix composite material to be detected; acquiring preset blind hole information, wherein the blind hole information comprises a plurality of blind hole sizes; preparing the contrast test block in a flat-bottom hole mode according to the material information, the defect information and the blind hole information.

5. The method of claim 1, wherein, The method comprises the following steps: comparing the thermal radiation reference image and the thermal radiation detection image to obtain a comparison result image; performing color enhancement processing on the comparison result image to obtain an enhanced comparison result image; determining defect position information and defect size information of the ceramic matrix composite material to be detected based on the enhanced comparison result image; determining the defect area according to the defect position information and the defect size information.

6. The method of claim 1, wherein, The method comprises the following steps: The thermal radiation detection image is subjected to gray processing to obtain a thermal radiation detection gray image; Distribution of each pixel point in the thermal radiation detection gray image is counted to obtain a distribution histogram; Data in the distribution histogram is converted into a pixel point distribution matrix, and a statistical quantity of the pixel point distribution matrix is calculated, the statistical quantity including a standard deviation, an average number and a coefficient of variation; According to the statistical quantity, the uniformity of the ceramic matrix composite material to be detected is evaluated to obtain the uniformity evaluation result.

7. A defect detection apparatus characterized by comprising: It comprises: An acquisition module is configured to acquire defect detection parameters of a ceramic matrix composite material to be detected and a thermal radiation reference image, the defect detection parameters including an infrared detection power; A detection module is configured to perform infrared detection on the ceramic matrix composite material to be detected based on the defect detection parameters to obtain a thermal radiation detection image of the ceramic matrix composite material to be detected; A determination module is configured to determine a defect area of the ceramic matrix composite material to be detected according to the thermal radiation reference image and the thermal radiation detection image, the color of the defect area being consistent with a defect color in the thermal radiation reference image; According to the thermal radiation detection image, the uniformity of the ceramic matrix composite material to be detected is evaluated to obtain a uniformity evaluation result; According to the defect area and the uniformity evaluation result, a defect detection result of the ceramic matrix composite material to be detected is determined.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the processor executes the computer program to implement the method of any one of claims 1-6.

9. An electronic device, comprising: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the method of any one of claims 1-6.

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