Defect detection method and device, storage medium and electronic equipment

Abstract

The invention relates to the field of material detection, in particular to a defect detection method and device, a storage medium and electronic equipment. The defect detection method comprises the following steps: acquiring defect detection parameters and a thermal radiation reference image of a to-be-detected ceramic-based composite material, wherein the defect detection parameters comprise infrared detection power; based on the defect detection parameters, performing infrared detection on the to-be-detected ceramic-based composite material to obtain a thermal radiation detection image of the to-be-detected ceramic-based composite material; and determining a defect detection result of the to-be-detected ceramic-based composite material according to the thermal radiation reference image and the thermal radiation detection image. By means of the method, the defect detection period is greatly shortened, the accuracy and timeliness of defect detection are fundamentally improved, and powerful technical support is provided for quality control and performance optimization of the ceramic-based composite material.

Description

Technical Field

[0001] The present disclosure relates to the field of material detection, and in particular to a defect detection method, device, storage medium and electronic equipment. Background Art

[0002] Ceramic matrix composites, with their remarkable characteristics such as high specific strength, excellent high temperature resistance, strong antioxidant ability and low density, have won wide acclaim in many fields, especially in cutting-edge science and technology fields such as aerospace, where their application has reached unprecedented depth and breadth. my country has successfully independently developed and mastered the preparation technology of ceramic matrix composites for large and complex components. This achievement marks a major breakthrough in my country's field of materials science.

[0003] However, despite significant technological advances, the preparation process of ceramic-based composites still faces the challenges of complexity and time-consuming, which directly leads to the occurrence of macroscopic defects such as holes and delamination in the microstructure of the material, as well as uneven pore distribution. These problems have become the key difficulties in accurately evaluating and controlling the internal quality of the material.

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

[0005] The main purpose of the present disclosure is to provide a defect detection method, device, storage medium and electronic device, aiming to solve the technical problems of poor accuracy and timeliness in defect detection of ceramic-based composite materials in the prior art.

[0006] To achieve the above objectives, the present disclosure proposes a defect detection method, comprising:

[0007] Acquire defect detection parameters and thermal radiation reference images of the ceramic matrix composite material to be detected, wherein the defect detection parameters include infrared detection power;

[0008] Based on the defect detection parameters, infrared detection is performed on the ceramic-based composite material to be detected to obtain a thermal radiation detection image of the ceramic-based composite material to be detected;

[0009] A defect detection result of the ceramic-based composite material to be detected is determined according to the thermal radiation reference image and the thermal radiation detection image.

[0010] Optionally, the step of obtaining defect detection parameters and thermal radiation reference images of the ceramic matrix composite material to be detected includes:

[0011] Obtaining a comparison test block of the ceramic-based composite material to be tested, wherein the comparison test block is used to simulate material defects of the ceramic-based composite material;

[0012] Determining infrared detection equipment for performing infrared detection on the ceramic-based composite material to be detected;

[0013] Based on the comparison test block, the infrared detection device is subjected to sensitivity calibration to obtain the infrared detection device after the calibration, wherein the power of the infrared detection device after the calibration satisfies the power condition of the ceramic-based composite material to be detected, and the power condition is determined based on the heat absorption capacity of the ceramic-based composite material to be detected;

[0014] The infrared detection device after the inspection is used to perform infrared detection on the comparison test block to obtain the defect detection parameters and thermal radiation reference image.

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

[0016] Optionally, obtaining a comparison test block of the ceramic-based composite material to be tested includes:

[0017] Acquiring material information of the ceramic-based composite material to be detected, wherein the material information includes structural data, material data and manufacturing method data of the ceramic-based composite material to be detected;

[0018] Acquiring defect information of the ceramic-based composite material to be detected, wherein the defect information includes defect positions and defect quantities corresponding to defects that may exist in the ceramic-based composite material to be detected;

[0019] Acquire preset blind hole information, wherein the blind hole information includes multiple blind hole sizes;

[0020] According to the material information, the defect information and the blind hole information, the comparison test block is prepared by adopting a flat bottom hole method to obtain the comparison test block.

[0021] Optionally, determining the defect detection result of the ceramic-based composite material to be detected according to the thermal radiation reference image and the thermal radiation detection image includes:

[0022] Determining a defect region of the ceramic-based composite material to be inspected according to the thermal radiation reference image and the thermal radiation detection image, wherein a color of the defect region is consistent with a defect color in the thermal radiation reference image;

[0023] According to the thermal radiation detection image, a uniformity evaluation is performed on the ceramic-based composite material to be detected to obtain a uniformity evaluation result;

[0024] The defect detection result of the ceramic-based composite material to be detected is determined according to the defect area and the uniformity evaluation result.

[0025] Optionally, determining the defect area of ​​the ceramic-based composite material to be inspected according to the thermal radiation reference image and the thermal radiation detection image includes:

[0026] Comparing the thermal radiation reference image with the thermal radiation detection image to obtain a comparison result image;

[0027] Performing color enhancement processing on the comparison result graph to obtain an enhanced comparison result graph;

[0028] Based on the enhanced comparison result diagram, determining defect position information and defect size information of the ceramic-based composite material to be inspected;

[0029] The defect area is determined according to the defect position information and the defect size information.

[0030] Optionally, the performing uniformity evaluation on the ceramic-based composite material to be tested according to the thermal radiation detection image to obtain a uniformity evaluation result includes:

[0031] Performing grayscale processing on the thermal radiation detection image to obtain a thermal radiation detection grayscale image;

[0032] Counting the distribution of each pixel in the thermal radiation detection grayscale image to obtain a distribution histogram;

[0033] Converting the data in the distribution histogram into a pixel distribution matrix, and calculating the statistics of the pixel distribution matrix, wherein the statistics include a standard deviation, a mean, and a coefficient of variation;

[0034] According to the statistical quantity, the uniformity of the ceramic-based composite material to be tested is evaluated to obtain the uniformity evaluation result.

[0035] In addition, to achieve the above-mentioned purpose, the present disclosure also provides a defect detection device, the defect detection device comprising:

[0036] An acquisition module, used to acquire defect detection parameters and thermal radiation reference images of the ceramic matrix composite material to be detected, wherein the defect detection parameters include infrared detection power;

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

[0038] A determination module is used to determine the defect detection result of the ceramic-based 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 objectives, the present disclosure also provides a computer-readable storage medium, on which a computer program is stored, and a processor executes the computer program to implement the above method.

[0040] In addition, to achieve the above-mentioned purpose, the present disclosure also provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-mentioned method.

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

[0042] The defect detection method, device, storage medium and electronic device proposed in the embodiments of the present disclosure first obtain the defect detection parameters and thermal radiation reference image of the ceramic-based composite material to be detected, wherein the defect detection parameters include infrared detection power. Then, based on the defect detection parameters, infrared detection is performed on the ceramic-based composite material to be detected to obtain a thermal radiation detection image of the ceramic-based composite material to be detected. Finally, the defect detection result of the ceramic-based composite material to be detected is determined based on the thermal radiation reference image and the thermal radiation detection image. In this way, by using infrared detection technology, non-contact and non-destructive detection of ceramic-based composite materials can be performed. By comparing and analyzing the thermal radiation detection image with the thermal radiation reference image, the temperature abnormality area inside the material, that is, the potential defect location, can be identified. Not only the accuracy and efficiency of detection are improved, but also the possibility of human misjudgment 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-based composite materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0044] Figure 1 A schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present disclosure;

[0045] Figure 2 A schematic diagram of a defect detection method according to an embodiment of the present disclosure;

[0046] Figure 3 A design diagram of a comparison test block involved in the embodiment of the present disclosure;

[0047] Figure 4 A thermal radiation detection image involved in the embodiment of the present disclosure;

[0048] Figure 5 It is a structural block diagram of a defect detection device involved in the embodiment of the present disclosure.

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

[0050] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions 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 ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0051] Refer to image 1. Figure 1 The figure is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present disclosure.

[0052] Typically, the device includes: at least one processor 301, a memory 302, and a defect detection program stored in the memory 302 and executable on the processor 301, wherein the defect detection program is configured to implement the steps of the defect detection method described above.

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

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

[0055] In some embodiments, the terminal may further optionally include: a communication interface 303 and at least one peripheral device. The processor 301, the memory 302 and the communication interface 303 may be connected via a bus or a signal line. Each peripheral device may be connected to the communication interface 303 via 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 may 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 may be implemented on a separate chip or circuit board, which is not limited in this embodiment.

[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 the 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 user 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 may also include circuits related to NFC (Near Field Communication), which is not limited in the present disclosure.

[0058] The display screen 305 is used to display the UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 305 is a touch display screen, the display screen 305 also has the ability to collect touch signals on the surface or above the surface of the display screen 305. The touch signal can be input to the processor 301 as a control signal for processing. At this time, the display screen 305 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the display screen 305 can be one, the 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 some 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 set to a non-rectangular irregular shape, that is, a special-shaped screen. The display screen 305 can be made of materials such as LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode, organic light-emitting diode).

[0059] The power supply 306 is used to power various components in the electronic device. The power supply 306 can be AC ​​power, DC power, a disposable battery, or a 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 used to support fast charging technology. Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation of the device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0060] In addition, an embodiment of the present disclosure further proposes a storage medium, on which a defect detection program is stored, and when the defect detection program is executed by a processor, the steps of the defect detection method described above are implemented. Therefore, it will not be repeated here. In addition, the description of the beneficial effects of adopting the same method will not be repeated. For technical details not disclosed in the storage medium embodiment involved in the present disclosure, please refer to the description of the method embodiment of the present disclosure. As an example, program instructions can be deployed to be executed on one device, or on multiple devices located at one location, or on multiple devices distributed at multiple locations and interconnected by a communication network.

[0061] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the above-mentioned program can be stored in a storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the above-mentioned storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0062] In recent years, the internal quality issues of ceramic matrix composites have become increasingly prominent and have become a new challenge facing the industry. In view of this emerging problem and the new testing requirements it brings, there is currently a lack of mature and standardized testing methods in the field.

[0063] In related technologies, nondestructive testing of resin-based composite materials mostly relies on ultrasound and X-ray technology, but the unique acoustic properties of ceramic-based composite materials, namely high attenuation and anisotropy, severely limit the penetration of ultrasound, making it difficult to accurately capture its internal information. On the other hand, although X-ray testing can effectively identify volume defects, it is not sensitive enough to area defects such as delamination, which is particularly critical in ceramic-based composite materials.

[0064] In view of this, the present disclosure proposes a defect detection method, device, storage medium and electronic device. The internal quality of ceramic matrix composite materials is detected based on high-power infrared technology, aiming to overcome the limitations of the existing technology and achieve accurate monitoring of the internal quality of ceramic matrix composite materials.

[0065] Reference Figure 2 , Figure 2 The present invention is a flowchart of a defect detection method according to an embodiment of the present invention, which includes the following steps:

[0066] Step S11: acquiring defect detection parameters and a thermal radiation reference image of the ceramic matrix composite material to be detected, wherein the defect detection parameters include infrared detection power.

[0067] Step S12: Based on the defect detection parameters, infrared detection is performed on the ceramic matrix composite material to be detected, so as to obtain a thermal radiation detection image of the ceramic matrix composite material to be detected.

[0068] Step S13: determining the 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.

[0069] Through the above technical scheme, the defect detection parameters and thermal radiation reference images of the ceramic-based composite material to be detected are first obtained, wherein the defect detection parameters include infrared detection power. Then, based on the defect detection parameters, infrared detection is performed on the ceramic-based composite material to be detected to obtain a thermal radiation detection image of the ceramic-based composite material to be detected. Finally, the defect detection result of the ceramic-based composite material to be detected is determined according to the thermal radiation reference image and the thermal radiation detection image. In this way, by using infrared detection technology, non-contact and non-destructive detection of ceramic-based composite materials can be performed. By comparing and analyzing the thermal radiation detection image with the thermal radiation reference image, the abnormal temperature area inside the material, that is, the potential defect location, can be identified. Not only the accuracy and efficiency of detection are improved, but also the possibility of human misjudgment is greatly reduced. It fundamentally improves the accuracy and timeliness of defect detection, and provides strong technical support for quality control and performance optimization of ceramic-based composite materials.

[0070] Furthermore, the technical effect of the above technical solution is not only reflected in the accuracy and reliability of the test results, but also in the rapidity and automation of the test process, which provides strong support for the quality control and safety of ceramic matrix composite materials. At the same time, the above technical solution not only fills the gap in the field of internal quality inspection of ceramic matrix composite materials, but also provides strong technical support for promoting technological progress and quality control level of related industries.

[0071] Among possible ways, the defect detection parameters and thermal radiation reference images of the ceramic matrix composite material to be detected are obtained, including:

[0072] Obtaining a comparison test block of the ceramic matrix composite material to be tested, where the comparison test block is used to simulate material defects of the ceramic matrix composite material;

[0073] Determine the infrared testing equipment used for infrared testing of the ceramic matrix composite material to be tested;

[0074] Based on the comparison test block, the sensitivity of the infrared detection equipment is checked to obtain the infrared detection equipment after the test, and the power of the infrared detection equipment after the test meets the power condition of the ceramic matrix composite material to be tested, and the power condition is determined based on the heat absorption capacity of the ceramic matrix composite material to be tested;

[0075] Through the inspected infrared detection equipment, infrared detection is carried out on the comparison test block to obtain defect detection parameters and thermal radiation reference images.

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

[0077] For example, first, an infrared detection device can be selected, whose power initially meets the basic requirements for the detection of the ceramic-based composite material to be detected. In order to optimize resource utilization and ensure the accuracy of the test results, the sensitivity of the infrared detection device can be further calibrated using a comparison test block. Through the comparison test block, the ceramic-based composite material in different defect states can be simulated, so as to evaluate the defect detection capability of the infrared detection device under different conditions. Based on the test results of the comparison test block, the optimal operating power of the infrared detection equipment can be further refined and determined to ensure that the potential defects inside the material can be effectively detected during the detection process, while avoiding unnecessary energy waste.

[0078] Specifically, in order to ensure that the infrared detection equipment can accurately adapt to the characteristics of the ceramic matrix composite material to be detected, a sensitivity test block that matches or has similar characteristics to the infrared detection equipment can be used for calibration. Among them, the sensitivity test block has built-in defects of known size, depth and distribution to simulate various defects that may appear in real materials for further comparison.

[0079] During the calibration process, the known characteristics of the sensitivity test block can be used as a standard reference to compare and analyze the test results of the infrared detection equipment. Through this process, the performance of the equipment in detecting specific types of defects can be deeply evaluated, including its sensitivity, accuracy and stability. Based on the calibration results of the sensitivity test block, the defect detection parameters of the infrared detection equipment can be finely adjusted. In this way, through repeated experiments and comparisons, and continuous iterative optimization of defect detection, the best defect detection combination that best meets the detection requirements can be found.

[0080] Then, use the adjusted parameters to test the sensitivity test block, observe and record the test results. Ensure that the equipment can clearly and accurately identify the defect location, shape and size in the comparison test block. If the equipment can meet the test requirements, that is, it can clearly identify the defects in the sensitivity test block, the verification is completed. Record the verified defect detection parameters, and use the verified infrared detection equipment and defect detection parameters to perform infrared detection on the comparison test block to obtain a thermal radiation reference image.

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

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

[0083] Of course, other methods may also be used to ensure that the power of the infrared detection equipment after inspection meets the power condition of the ceramic-based composite material to be inspected, and to determine the power of the infrared detection equipment after inspection based on the heat absorption capacity of the ceramic-based composite material to be inspected. The embodiments of the present disclosure are not limited to this.

[0084] Among possible methods, obtaining a comparative test block of the ceramic matrix composite material to be tested includes:

[0085] Acquire material information of the ceramic matrix composite material to be tested, the material information including structural data, material data and manufacturing method data of the ceramic matrix composite material to be tested;

[0086] Obtaining defect information of the ceramic matrix composite material to be inspected, the defect information including defect positions and defect quantities corresponding to defects that may exist in the ceramic matrix composite material to be inspected;

[0087] Obtain preset blind hole information, which includes various blind hole sizes;

[0088] According to the material information, defect information and blind hole information, a flat-bottom hole method was adopted to obtain a comparison test block.

[0089] For example, the structure, material and production of the comparison test block should be the same as those of the ceramic matrix composite material to be tested. For example, if the ceramic matrix composite material to be tested is a planar structure produced by the CVI (chemical vapor deposition) + PIP (impregnation pyrolysis) method, the test block should also be prepared by the CVI + PIP method to eliminate the influence of structural differences on the test results.

[0090] In addition, the comparison test block contains artificial defects, and the artificial defects can be accurately machined in the comparison test block by using a flat-bottom hole method to simulate the actual form of the macroscopic defects of the ceramic-based composite material to be tested. Among them, the position, shape and size of these defects are determined based on the defect information analysis results of the ceramic-based composite material to be tested to ensure the authenticity of the simulation. Then, blind holes of different sizes can be machined in the comparison test block according to the preset blind hole information to meet the needs of different detection sensitivities. At the same time, the possibility of increasing the size of the blind holes in the future is reserved to adapt to changes in technological development and detection needs.

[0091] Specifically, Figure 3 : is a design diagram of a comparison test block involved in the embodiment of the present disclosure. Figure 3 As shown, based on the current technical level and actual detection needs, according to the defect levels that are easily detected during the internal quality inspection of the ceramic-based composite material method, the blind hole information in the present disclosure can be preset to include a variety of blind hole sizes such as φ3mm, φ6mm, φ9mm, and the depth size can include 0.4mm, 2mm, 3.6mm to cover different levels of detection sensitivity. The selection of these sizes can fully simulate the defects of ceramic-based composite materials and characterize the defect detection capability of the detection system to ensure that it can accurately identify and quantify the defects of ceramic-based composite materials under various conditions. Of course, the corresponding blind hole information can also be preset according to the macroscopic defects of the ceramic-based composite material to be detected in actual applications and the defect values ​​that can be found by the system, and the embodiments of the present disclosure do not specifically limit this.

[0092] This technical solution prepares highly consistent and representative comparison test blocks for ceramic matrix composites, providing strong support for internal quality inspection of ceramic matrix composites. With the continuous advancement of technology and the increasing diversification of inspection needs, parameters such as blind hole size in this solution will continue to be optimized and expanded to adapt to a wider range of inspection scenarios and needs.

[0093] In a possible manner, determining the 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 includes:

[0094] Determine the defect area of ​​the ceramic matrix composite material to be inspected 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;

[0095] According to the thermal radiation detection image, the uniformity of the ceramic matrix composite material to be detected is evaluated to obtain the uniformity evaluation result;

[0096] The defect detection results of the ceramic matrix composite material to be detected are determined according to the defect area and uniformity evaluation results.

[0097] For example, the thermal radiation reference image is obtained on the same or similar material without defects or with known defects, and can be used as a comparison benchmark. Therefore, by comparing the thermal radiation detection image with the thermal radiation reference image, the defect area of ​​the ceramic matrix composite material to be detected can be determined.

[0098] In addition, in the thermal radiation detection image, in addition to focusing on the defect area, the thermal radiation distribution of the entire material can also be analyzed as a whole, that is, the uniformity of thermal radiation on the surface or inside the material can be evaluated. Specifically, statistical parameters such as temperature differences, temperature gradients, or standard deviations of thermal radiation intensity in different areas of the image can be calculated, and then, according to the preset uniformity standards or thresholds, it can be judged whether the uniformity of the ceramic-based composite material to be tested meets the requirements.

[0099] In a possible manner, determining the defect area of ​​the ceramic matrix composite material to be inspected according to the thermal radiation reference image and the thermal radiation detection image includes:

[0100] Comparing the thermal radiation reference image and the thermal radiation detection image to obtain a comparison result image;

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

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

[0103] Determine the defect area based on the defect location information and defect size information.

[0104] For example, the thermal radiation detection image is compared with the thermal radiation reference image. If an area with a color similar or consistent with that of the artificial defect in the thermal radiation reference image appears in the thermal radiation detection image, it is considered that there is an artificial defect in the area. For example, higher temperatures are displayed in red and lower temperatures are displayed in blue. By identifying these areas with consistent colors and the defect size in the area. Then record the longest distance of the area as X and the shortest distance as Y to identify the size of the defect and obtain the defect size information. Based on the defect location information and defect size information, the defect area in the ceramic-based composite material to be detected can be determined.

[0105] It should be noted that Figure 4 is a thermal radiation detection image involved in the embodiment of the present disclosure, such as Figure 4 As shown, the ceramic matrix composite material to be tested may have one or more defects, and may have one or more defects. Therefore, the defect location information may include one or more defect locations, and the defect size information may also include one or more defect sizes, which is not limited in the embodiments of the present disclosure.

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

[0107] Performing grayscale processing on the thermal radiation detection image to obtain a thermal radiation detection grayscale image;

[0108] Count the distribution of each pixel in the thermal radiation detection grayscale image to obtain a distribution histogram;

[0109] Convert the data in the distribution histogram into a pixel distribution matrix, and calculate the statistics of the pixel distribution matrix, including the standard deviation, mean and coefficient of variation;

[0110] According to the statistical quantity, the uniformity of the ceramic matrix composite material to be tested is evaluated to obtain the uniformity evaluation result.

[0111] For example, the thermal radiation detection image can be grayed out by professional image processing software (such as MATLAB) to obtain a thermal radiation detection grayscale image to ensure the simplification and standardization of image information and facilitate subsequent statistical analysis. Specifically, the rgb2gray function can be used to convert the thermal radiation detection image into a thermal radiation detection grayscale image, and the grayscale value range is set to 0-255. Of course, other methods can also be used to process the thermal radiation detection image to ensure the simplification and standardization of image information, which is not limited in the embodiments of the present disclosure.

[0112] Next, use the imhist command to count the distribution of each pixel in the grayscale image and generate a distribution histogram. This histogram intuitively shows the number distribution of pixels of different gray levels in the image, which is an important basis for evaluating image uniformity.

[0113] Then, in order to facilitate subsequent data processing using matrix operations, the histogram data can be converted into a*b matrix form, that is, a pixel distribution matrix is ​​obtained. The pixel distribution matrix can be a single-row matrix of 1*256, which is not limited in the embodiment of the present disclosure.

[0114] Finally, the standard deviation of the matrix data can be calculated using MATLAB's built-in function std to determine the degree of discreteness of the data distribution. This function can automatically ignore non-numerical items in the data to ensure the accuracy of the calculation. And the mean function is used to calculate the mean of the matrix data 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 mean can be further calculated, that is, the coefficient of variation can be obtained. This coefficient eliminates the influence of the data dimension and can more objectively reflect the relative degree of change between the data.

[0115] In this way, the uniformity of the ceramic-based composite material to be tested can be evaluated according to the statistical quantity to obtain the uniformity evaluation result. In the present disclosure, the uniformity of the ceramic-based composite material to be tested can be quantitatively evaluated according to the calculated coefficient of variation. A low coefficient of variation indicates that the temperature (or thermal radiation) distribution inside the ceramic-based composite material to be tested is relatively uniform, while a high coefficient of variation indicates that the ceramic-based composite material to be tested may have local defects or inhomogeneities, and the larger the coefficient of variation, the worse the uniformity of the ceramic-based composite material to be tested.

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

[0117] For samples with a standard size of 200mm*200mm, the method provided by this disclosure can achieve a comprehensive and in-depth scan of the macroscopic defects inside the sample in 20 minutes, and simultaneously complete a comprehensive evaluation of the uniformity of the material. Compared with traditional methods, this high-efficiency detection process not only greatly shortens the defect detection cycle, but also fundamentally improves the accuracy and timeliness of defect detection, providing strong technical support for the quality control and performance optimization of ceramic-based composite materials.

[0118] Reference Figure 5 , Figure 5 This is a structural block diagram of a defect detection device involved in an embodiment of the present disclosure. Based on the same inventive concept as the above embodiment, the device includes:

[0119] An acquisition module 10 is used to acquire defect detection parameters and a thermal radiation reference image of the ceramic matrix composite material to be detected, wherein the defect detection parameters include infrared detection power;

[0120] A detection module 20, configured to perform infrared detection on the ceramic-based composite material to be detected based on the defect detection parameters, and obtain a thermal radiation detection image of the ceramic-based composite material to be detected;

[0121] The determination module 30 is used to determine the 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.

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

[0123] Obtaining a comparison test block of the ceramic-based composite material to be tested, wherein the comparison test block is used to simulate material defects of the ceramic-based composite material;

[0124] Determining infrared detection equipment for performing infrared detection on the ceramic-based composite material to be detected;

[0125] Based on the comparison test block, the infrared detection device is subjected to sensitivity calibration to obtain the infrared detection device after the calibration, wherein the power of the infrared detection device after the calibration satisfies the power condition of the ceramic-based composite material to be detected, and the power condition is determined based on the heat absorption capacity of the ceramic-based composite material to be detected;

[0126] The infrared detection device after the inspection is used to perform infrared detection on the comparison test block to obtain the defect detection parameters and thermal radiation reference image.

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

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

[0129] Acquiring material information of the ceramic-based composite material to be detected, wherein the material information includes structural data, material data and manufacturing method data of the ceramic-based composite material to be detected;

[0130] Acquiring defect information of the ceramic-based composite material to be detected, wherein the defect information includes defect positions and defect quantities corresponding to defects that may exist in the ceramic-based composite material to be detected;

[0131] Acquire preset blind hole information, wherein the blind hole information includes multiple blind hole sizes;

[0132] According to the material information, the defect information and the blind hole information, the comparison test block is prepared by adopting a flat bottom hole method to obtain the comparison test block.

[0133] Optionally, the determining module 30 is used to:

[0134] Determining a defect region of the ceramic-based composite material to be inspected according to the thermal radiation reference image and the thermal radiation detection image, wherein a color of the defect region is consistent with a defect color in the thermal radiation reference image;

[0135] According to the thermal radiation detection image, a uniformity evaluation is performed on the ceramic-based composite material to be detected to obtain a uniformity evaluation result;

[0136] The defect detection result of the ceramic-based composite material to be detected is determined according to the defect area and the uniformity evaluation result.

[0137] Optionally, the determining module 30 is used to:

[0138] Comparing the thermal radiation reference image with the thermal radiation detection image to obtain a comparison result image;

[0139] Performing color enhancement processing on the comparison result graph to obtain an enhanced comparison result graph;

[0140] Based on the enhanced comparison result diagram, determining defect position information and defect size information of the ceramic-based composite material to be inspected;

[0141] The defect area is determined according to the defect position information and the defect size information.

[0142] Optionally, the determining module 30 is used to:

[0143] Performing grayscale processing on the thermal radiation detection image to obtain a thermal radiation detection grayscale image;

[0144] Counting the distribution of each pixel in the thermal radiation detection grayscale image to obtain a distribution histogram;

[0145] Converting the data in the distribution histogram into a pixel distribution matrix, and calculating the statistics of the pixel distribution matrix, wherein the statistics include a standard deviation, a mean, and a coefficient of variation;

[0146] According to the statistical quantity, the uniformity of the ceramic-based composite material to be tested is evaluated to obtain the uniformity evaluation result.

[0147] It should be noted that, since the steps executed by the device of this embodiment are the same as the steps of the aforementioned method embodiment, its specific implementation method and the technical effects that can be achieved can refer to the aforementioned embodiment and will not be repeated here.

[0148] In addition, in one embodiment, an embodiment of the present disclosure further 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 aforementioned embodiment when executed by the processor.

[0149] In addition, in one embodiment, an embodiment of the present disclosure further provides a computer storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method in the aforementioned embodiment are implemented.

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

[0151] In some embodiments, executable instructions may be in the form of a program, software, software module, script or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may 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] As an example, executable instructions may, but need not, correspond to a file in a file system, may be stored as part of a file that stores other programs or data, such as in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or code portions).

[0153] By way of example, executable instructions may be deployed to be executed on one computing device, or on multiple computing devices located at one site, or on multiple computing devices distributed across multiple sites and interconnected by a communication network.

[0154] It should be noted that, in this article, the terms "include", "may include" or any other variations thereof are intended to cover non-exclusive inclusions, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

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

[0156] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present disclosure, or the part that contributes to the prior art, 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 number of instructions for enabling a multimedia terminal device (which can be a mobile phone, a computer, a television receiver, or a network device, etc.) to execute the methods described in each embodiment of the present disclosure.

[0157] The above descriptions are only optional embodiments of the present disclosure, and are not intended to limit the patent scope of the present disclosure. All equivalent structural transformations made using the contents of the present disclosure and the drawings under the inventive concept of the present disclosure, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present disclosure.

Claims

1. A defect detection method, characterized in that: include: Acquire defect detection parameters and thermal radiation reference images of the ceramic matrix composite material to be detected, wherein the defect detection parameters include infrared detection power; Based on the defect detection parameters, infrared detection is performed on the ceramic-based composite material to be detected to obtain a thermal radiation detection image of the ceramic-based composite material to be detected; A defect detection result of the ceramic-based composite material to be detected is determined according to the thermal radiation reference image and the thermal radiation detection image.

2. The method according to claim 1, characterized in that The method of obtaining defect detection parameters and thermal radiation reference images of the ceramic matrix composite material to be detected includes: Obtaining a comparison test block of the ceramic-based composite material to be tested, wherein the comparison test block is used to simulate material defects of the ceramic-based composite material; Determining infrared detection equipment for performing infrared detection on the ceramic-based composite material to be detected; Based on the comparison test block, the infrared detection device is subjected to sensitivity calibration to obtain the infrared detection device after the calibration, wherein the power of the infrared detection device after the calibration satisfies the power condition of the ceramic-based composite material to be detected, and the power condition is determined based on the heat absorption capacity of the ceramic-based composite material to be detected; The infrared detection device after the inspection is used to perform infrared detection on the comparison test block to obtain the defect detection parameters and thermal radiation reference image.

3. The method according to claim 2, characterized in that The power of the infrared detection equipment after inspection is greater than or equal to 4000W.

4. The method according to claim 2, characterized in that: The step of obtaining a comparison test block of the ceramic-based composite material to be tested comprises: Acquiring material information of the ceramic-based composite material to be detected, wherein the material information includes structural data, material data and manufacturing method data of the ceramic-based composite material to be detected; Acquiring defect information of the ceramic-based composite material to be detected, wherein the defect information includes defect positions and defect quantities corresponding to defects that may exist in the ceramic-based composite material to be detected; Acquire preset blind hole information, wherein the blind hole information includes multiple blind hole sizes; According to the material information, the defect information and the blind hole information, the comparison test block is prepared by adopting a flat bottom hole method to obtain the comparison test block.

5. The method according to claim 1, characterized in that The step of determining the defect detection result of the ceramic-based composite material to be detected according to the thermal radiation reference image and the thermal radiation detection image comprises: Determining a defect region of the ceramic-based composite material to be inspected according to the thermal radiation reference image and the thermal radiation detection image, wherein a color of the defect region is consistent with a defect color in the thermal radiation reference image; According to the thermal radiation detection image, a uniformity evaluation is performed on the ceramic-based composite material to be detected to obtain a uniformity evaluation result; The defect detection result of the ceramic-based composite material to be detected is determined according to the defect area and the uniformity evaluation result.

6. The method according to claim 5, characterized in that The step of determining the defect area of ​​the ceramic-based composite material to be inspected according to the thermal radiation reference image and the thermal radiation detection image comprises: Comparing the thermal radiation reference image with the thermal radiation detection image to obtain a comparison result image; Performing color enhancement processing on the comparison result graph to obtain an enhanced comparison result graph; Based on the enhanced comparison result diagram, determining defect position information and defect size information of the ceramic-based composite material to be inspected; The defect area is determined according to the defect position information and the defect size information.

7. The method according to claim 5, characterized in that The step of evaluating the uniformity of the ceramic-based composite material to be tested based on the thermal radiation detection image to obtain a uniformity evaluation result includes: Performing grayscale processing on the thermal radiation detection image to obtain a thermal radiation detection grayscale image; Counting the distribution of each pixel in the thermal radiation detection grayscale image to obtain a distribution histogram; Converting the data in the distribution histogram into a pixel distribution matrix, and calculating the statistics of the pixel distribution matrix, wherein the statistics include a standard deviation, a mean, and a coefficient of variation; According to the statistical quantity, the uniformity of the ceramic-based composite material to be tested is evaluated to obtain the uniformity evaluation result.

8. A defect detection device, characterized in that: include: An acquisition module, used to acquire defect detection parameters and thermal radiation reference images of the ceramic matrix composite material to be detected, wherein the defect detection parameters include infrared detection power; A detection module, configured to perform infrared detection on the ceramic-based composite material to be detected based on the defect detection parameters, and obtain a thermal radiation detection image of the ceramic-based composite material to be detected; A determination module is used to determine the defect detection result of the ceramic-based composite material to be detected according to the thermal radiation reference image and the thermal radiation detection image.

9. 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 according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method according to any one of claims 1 to 7.

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