Magneto-optical imaging detection system, adaptive excitation and defect quantification method

Abstract

The present invention belongs to the technical field of oil and gas equipment detection, and particularly relates to a magneto-optical imaging detection system, an adaptive excitation, and a defect quantification method. The magnetic circuit module of the magneto-optical imaging detection system has a more efficient excitation intensity design and a smaller lift-off of the magneto-optical thin film, so it has a stronger surface and buried depth defect detection sensitivity; its optical imaging module has a higher integration degree, and the formed packaging structure of the magneto-optical imaging detection system is more miniaturized. The magneto-optical imaging detection system includes: a scanning probe, a light source controller, an industrial personal computer, a DC power supply, and a power amplifier; the scanning probe includes a magnetic circuit module and an optical imaging module; the magnetic circuit module is composed of a coil, a manganese-zinc ferrite, a magnetic shielding layer, and a magneto-optical sensor; the optical imaging module is composed of a camera, a polarized light source, and a polarizer. Among them, the coil is wound around the periphery of the manganese-zinc ferrite and is connected to the DC power supply and the power amplifier; the magnetic shielding layer is arranged outside the magneto-optical sensor.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas equipment detection, and particularly relates to a magneto-optical imaging detection system, an adaptive excitation, and a defect quantification method. Background Art

[0002] Ferromagnetic materials are widely used in the oil and gas equipment field due to their high strength, low cost and other characteristics, such as oil pipelines and oil and gas storage tanks. It should be noted that during the service process of such oil and gas equipment, affected by factors such as pressure, temperature, stress concentration, and electrochemical corrosion, cracks, corrosion pits and other defects are likely to occur on the surface and inside of its materials; if it deteriorates further, major safety accidents will be caused. Therefore, in order to ensure the safe operation of oil and gas equipment and eliminate potential safety hazards, it is crucial to detect it. Non-destructive testing technology can conduct safety inspections on oil and gas equipment without damaging its structure and provide a basis for material performance diagnosis, which is of great significance for ensuring oil and gas safety.

[0003] Existing non-destructive testing technologies at least include the following several types: eddy current testing, ultrasonic testing, magnetic particle testing, ray testing, etc. Among them, the visualization degrees of eddy current and ultrasonic testing technologies are relatively low, and the technical level requirements for operators are relatively high; although the visualization degrees of magnetic particle and ray testing are relatively high, their detection efficiency is relatively low, and the detection sensitivity to surface defects is relatively low. Magneto-optical imaging technology, as a non-destructive testing method that couples the "magnetic-optical" dual physical fields, has attracted the key attention of those skilled in the art because of its high visualization, high detection efficiency, high sensitivity and other characteristics for internal and external defects of materials.

[0004] For example: The patent number CN117554469A "A metal defect detection device and method based on magneto-optical imaging method" invented by Liu Haibin et al. of Beijing University of Technology invented a ferromagnetic material defect detection device based on alternating current excitation, which realized high-visualization detection of external defects, but its excitation method restricted the detection ability of internal defects, and the device integration degree was low, making it difficult to detect efficiently. The patent number CN118169223A "A pipeline defect magnetic flux leakage detection device based on magneto-optical imaging" invented by Hu Fabin of Chengdu Youyida Technology Co., Ltd. invented a pipeline defect detection device with coil excitation, but the excitation device had poor adjustability, making it difficult to balance the detection sensitivity of internal and external defects, and the imaging effect was uncontrollable, making it difficult to quantify.

[0005] In summary, the applicant found that the existing magneto-optical imaging technology still has limitations in terms of difficult to balance the detection of internal and external defects, difficult to control the excitation intensity, and difficult to quantify the defect detection results, and cannot meet the requirements of those skilled in the art for high visualization, high detection efficiency, and high sensitivity of internal and external defects. Summary of the Invention

[0006] The present invention provides a magneto - optical imaging detection system, an adaptive excitation and defect quantification method. The magnetic circuit module of the magneto - optical imaging detection system is designed with more efficient excitation intensity and smaller lift - off of the magneto - optical thin film, so it has stronger surface and buried - depth defect detection sensitivity; its optical imaging module has higher integration, and the formed packaging structure of the magneto - optical imaging detection system is more miniaturized.

[0007] To solve the above - mentioned technical problems, the present invention adopts the following technical solutions:

[0008] A magneto - optical imaging detection system, comprising: a scanning probe, a light source controller, an industrial personal computer, a DC power supply, and a power amplifier;

[0009] The scanning probe includes a magnetic circuit module and an optical imaging module; the magnetic circuit module is composed of a coil, manganese - zinc ferrite, a magnetic shielding layer, and a magneto - optical sensor; the optical imaging module is composed of a camera, a polarized light source, and a polarizer;

[0010] Among them, the coil is wound around the periphery of the manganese - zinc ferrite and is connected to the DC power supply and the power amplifier to generate an excitation magnetic field; the magnetic shielding layer is arranged outside the magneto - optical sensor to prevent the background magnetic field from entering and interfering with the leakage magnetic field required by the magneto - optical sensor;

[0011] The camera and the polarized light source are arranged at the same central axis position of the magneto - optical sensor; the polarizer is arranged between the camera and the polarized light source, and the transmission axis of the polarizer forms a specific angle with the polarization direction of the polarized light in the polarized light source; among them, the polarized light source is used to provide linearly polarized light for the optical imaging module; the camera is data - connected to the industrial personal computer and is used to upload the collected optical signal so as to process the optical signal to form magneto - optical image data.

[0012] More preferably, it further includes: a fixed base, a scanning - probe housing, and a magneto - optical sensor holder;

[0013] Among them, the fixed base is provided with an installation groove, and steel - ball rollers are arranged under the fixed base; the scanning - probe housing is arranged on the periphery of the scanning probe to protect each structural unit in the scanning probe; the magneto - optical sensor holder cooperates with the magneto - optical sensor to adjust the lift - off distance between the magneto - optical sensor and the specimen to be detected.

[0014] On the other hand, the present invention also provides an adaptive excitation method. The adaptive excitation method is based on the above - mentioned magneto - optical imaging detection system and includes the following steps:

[0015] Step S101: Extract the defect magneto - optical image with the best detection effect and the defect - free magneto - optical image with the best detection effect, and calculate the optimal difference between the defect magneto - optical image with the best detection effect and the defect - free magneto - optical image with the best detection effect;

[0016] Among them, the optimal difference C between the defect magneto-optical image with the best detection effect and the defect-free magneto-optical image with the best detection effect satisfies:

[0017] (1);

[0018] In formula (1), A is the gray-scale matrix of each pixel point obtained by solving based on the defect magneto-optical image with the best detection effect, and B is the gray-scale matrix of each pixel point obtained by solving based on the defect-free magneto-optical image with the best detection effect; is to calculate the arithmetic mean of the matrix, and R is the number of pixels in the feature region;

[0019] Step S102: Extract the gray-scale values of each pixel point in the middle row of the magneto-optical image in actual detection, draw a two-dimensional gray-scale map, and construct a gray-scale function; calculate the actual number of differences K in the gray-scale function;

[0020] Among them, the actual number of differences K in the gray-scale function satisfies:

[0021] (2);

[0022] In formula (2), is the maximum gray-scale value in the gray-scale function, is the minimum gray-scale value in the gray-scale function;

[0023] Step S103: Perform adaptive adjustment on the excitation intensity of the magneto-optical imaging detection system.

[0024] More preferably, the process of performing adaptive adjustment on the excitation intensity of the magneto-optical imaging detection system in step S103 can be specifically described as:

[0025] When K < C, it is determined that the excitation intensity is too small, and the value of the excitation current of the magneto-optical imaging detection system needs to be increased;

[0026] When K > C and the extreme value of the gray-scale function is not unique, it is determined that the excitation intensity is too large, and the value of the excitation current of the magneto-optical imaging detection system needs to be decreased;

[0027] When K > C and the extreme value of the gray-scale function is unique, it is determined that the excitation intensity is the best.

[0028] On the other hand, the present invention also provides a defect quantification method. The defect quantification method is based on the above-mentioned magneto-optical imaging detection system, and is characterized in that it includes the following steps:

[0029] Step S201: Perform image processing on the magneto-optical image collected by the magneto-optical imaging detection system;

[0030] Step S202: Calibrate the parameters of the camera in the magneto-optical imaging detection system;

[0031] According to the relative position between the camera and the magneto-optical sensor in the magneto-optical imaging detection system, the corresponding relationship between the spatial points on the upper surface of the magneto-optical sensor in the camera coordinate system and the pixel points in the magneto-optical image is solved;

[0032] Based on the result obtained by edge detection and combined with the corresponding relationship between the spatial points on the upper surface of the magneto-optical sensor in the camera coordinate system and the pixel points in the magneto-optical image, the contour size of the defect is quantified.

[0033] More preferably, the process of image processing on the magneto-optical image collected by the magneto-optical imaging detection system in step S201 can be specifically described as:

[0034] Step S2011: Use the Gaussian filtering method to perform filtering processing on the magneto-optical image collected by the magneto-optical imaging detection system;

[0035] Step S2012: Use the gray threshold segmentation method. According to the threshold Divide the gray values of all pixel points in the magneto-optical image into two categories: those higher than the threshold and those lower than the threshold;

[0036] Step S2013: Perform morphological processing on the magneto-optical image after the gray threshold segmentation processing in step S2012;

[0037] Step S2014: Perform Algorithm edge detection on the magneto-optical image after the morphological processing in step S2013.

[0038] More preferably, the weight of the Gaussian filtering method satisfies:

[0039] (3);

[0040] In formula (3), is the Gaussian coefficient, represents the pixel point coordinates on the collected magneto-optical image.

[0041] More preferably, the process of performing morphological processing on the magneto-optical image after the gray threshold segmentation processing in step S2013 can be specifically described as:

[0042] Perform erosion operation on the magneto-optical image after the gray threshold segmentation processing in step S2012 to eliminate the slender regions irrelevant to the defect in the magneto-optical image;

[0043] Then perform a closing operation, that is, first perform a dilation operation and then an erosion operation, so as to fill the small holes in the defect region of the magneto-optical image and smooth the boundary of the magneto-optical image.

[0044] More preferably, during the process of calibrating the parameters of the camera in the magneto-optical imaging detection system in step S202, the imaging model of the camera satisfies:

[0045] (4);

[0046] Among them, is the internal parameter of the camera (14), and are the scale factors in the x and y directions of the two-dimensional pixel coordinates of the acquired image respectively, is the center point coordinate of the acquired image in the camera coordinate system, is the two-dimensional pixel coordinate of the acquired image, is the coordinate of the spatial point in the camera coordinate system.

[0047] The present invention provides a magneto-optical imaging detection system, an adaptive excitation and defect quantification method. Among them, the magneto-optical imaging detection system includes a scanning probe, a light source controller, an industrial control all-in-one computer, a DC power supply, and a power amplifier. The scanning probe includes a magnetic circuit module and an optical imaging module. The magnetic circuit module is further composed of a coil, a manganese-zinc ferrite, a magnetic shielding layer, and a magneto-optical sensor; the optical imaging module is further composed of a camera, a polarized light source, and a polarizer. The defect quantification method includes the following steps: step S201: performing image processing on the magneto-optical image collected by the magneto-optical imaging detection system; step S202: calibrating the parameters of the camera in the magneto-optical imaging detection system; according to the relative position between the camera and the magneto-optical sensor in the magneto-optical imaging detection system, solving the corresponding relationship between the spatial point on the upper surface of the magneto-optical sensor in the camera coordinate system and the pixel point in the magneto-optical image; quantifying the contour size of the defect.

[0048] The magneto-optical imaging detection system, adaptive excitation and defect quantification method with the above structural features and the above step features, compared with the prior art, at least has the following technical advantages:

[0049] (1). The magnetic circuit module of the magneto-optical imaging detection system provided by the present invention has a more efficient excitation intensity design and a smaller magneto-optical film lift-off, so it has a stronger surface and buried depth defect detection sensitivity; its optical imaging module has a higher integration degree, and the formed magneto-optical imaging detection system packaging structure is more miniaturized;

[0050] (2). The adaptive excitation method provided by the present invention can realize the adaptive adjustment of the excitation intensity of the magneto-optical imaging detection system, and its detection efficiency is higher;

[0051] (3). The defect quantification method provided by the present invention has a more accurate defect contour quantification result, which can effectively improve the detection ability of the magneto-optical imaging detection system. Description of the Drawings

[0052] This attached drawing is used to provide a further understanding of the present invention, and constitutes a part of the specification. It is used together with the embodiments of the present invention to explain the present invention, and does not constitute a limitation to the present invention. In the following attached drawings:

[0053] Figure 1 is a schematic structural diagram of the magneto-optical imaging detection system provided by the present invention;

[0054] Figure 2 is a schematic structural diagram of the scanning probe;

[0055] Figure 3 is a schematic flow diagram of the adaptive excitation method provided by the present invention;

[0056] Figure 4a is a two-dimensional gray-scale diagram when the excitation intensity is too high;

[0057] Figure 4b is a two-dimensional gray-scale diagram when the excitation intensity is moderate;

[0058] Figure 4c is a two-dimensional gray-scale diagram when the excitation intensity is too low;

[0059] Figure 5 is a schematic flow diagram of the defect quantification method provided by the present invention.

[0060] Reference numerals: 1, scanning probe; 2, light source controller; 3, industrial personal computer; 4, DC power supply; 5, power amplifier; 11, scanning probe housing; 12, coil; 13, manganese-zinc ferrite; 14, camera; 15, polarized light source; 16, polarizer; 17, magnetic shielding layer; 18, magneto-optical sensor; 19, magneto-optical sensor holder; 110, fixed base; 111, steel ball roller. Detailed implementation manners

[0061] The present invention provides a magneto-optical imaging detection system, an adaptive excitation and a defect quantification method. The magnetic circuit module of the magneto-optical imaging detection system designs the excitation intensity more efficiently, and the lift-off of the magneto-optical thin film is smaller, so it has stronger surface and buried defect detection sensitivity; its optical imaging module has higher integration, and the formed magneto-optical imaging detection system packaging structure is more miniaturized.

[0062] The present invention provides a magneto-optical imaging detection system, as Figure 1 shown, including: a scanning probe 1, a light source controller 2, an industrial personal computer 3, a DC power supply 4, and a power amplifier 5. Further, as Figure 2As shown, the scanning probe 1 further includes a magnetic circuit module and an optical imaging module. Among them, the magnetic circuit module is composed of a coil 12, a manganese-zinc ferrite 13, a magnetic shielding layer 17, and a magneto-optical sensor 18; the optical imaging module is composed of a camera 14, a polarized light source 15, and a polarizer 16.

[0063] Specifically, the coil 12 is wound around the periphery of the manganese-zinc ferrite 13 and connected to the DC power supply 4 and the power amplifier 5 to generate an excitation magnetic field. The magnetic shielding layer 17 is arranged outside the magneto-optical sensor 18 to prevent the background magnetic field from entering and interfering with the leakage magnetic field required by the magneto-optical sensor 18. The camera 14 and the polarized light source 15 are arranged at the same central axis position of the magneto-optical sensor 18. The polarizer 16 is arranged between the camera 14 and the polarized light source 15, and the transmission axis of the polarizer 16 forms a specific angle with the polarization direction of the polarized light in the polarized light source 15. Among them, the polarized light source 15 is used to provide linearly polarized light for the optical imaging module. The camera 14 is connected to the industrial control computer 3 for uploading the collected optical signal so as to process the optical signal to form magneto-optical image data.

[0064] In addition, as a more preferred embodiment, as Figure 2 shown, the magneto-optical imaging detection system further includes: a fixed base 110, a scanning probe housing 11, and a magneto-optical sensor holder 19. Among them, the fixed base 110 is provided with an installation groove, and the fixed base 110 is provided with steel ball rollers 111 below. The scanning probe housing 11 is arranged outside the scanning probe 1 to protect each structural unit in the scanning probe 1. The magneto-optical sensor holder 19 cooperates with the magneto-optical sensor 18 to adjust the lift-off distance between the magneto-optical sensor 18 and the specimen to be inspected.

[0065] To facilitate those skilled in the art to understand the present application, in combination with the attached Figure 1 、 2 , a specific embodiment is further provided as follows. Among them, the specific parameters of each structural unit in the magneto-optical imaging detection system can be referred to as:

[0066] The distance from the manganese-zinc ferrite 13 to the bottom of the steel ball roller 111 is 0.5 mm; the distance from the magneto-optical sensor 18 to the bottom of the steel ball roller 111 is 0.1 mm; the overall size of the scanning probe 1 is 150 mm in length, 70 mm in width, and 70 mm in height. In addition, the magneto-optical sensor 18 is made of yttrium iron garnet film, and the magnetic field response range is 0.0625 mT to 2.5 mT, so as to ensure the high-sensitivity flaw detection of the magneto-optical imaging detection system. The camera 14 is a high-resolution camera with a resolution of 640×360 pixels, a pixel size of 3×3 μm, and an overall size of 8×8×5 mm, so as to ensure the high-quality imaging of the magneto-optical imaging detection system. Finally, a long strip defect with a length of 5 mm, a width of 0.3 mm, and a depth of 3 mm is set on the specimen to be detected, and the implementation process of the present invention is introduced by taking this as an example.

[0067] Among them, for the assembly, magneto-optical imaging, and detection processes of the magneto-optical imaging detection system, the following can be specifically referred to: First, select the 0.5 mm enameled wire required for the coil 12 specifications according to the defect size and detection working conditions, and wind it around the manganese-zinc ferrite 13; then place the manganese-zinc ferrite 13, polarized light source 15, and magneto-optical sensor holder 19 into the installation groove reserved in the fixed base 110; next, place the magneto-optical sensor 18 into the cavity of the magneto-optical sensor holder 19, and wrap it on all four sides with the magnetic shielding layer 17; then place the polarizer 16 between the camera 14 and the polarized light source 15, and finally complete the installation of the scanning probe 1 and the fixed connection between the steel ball roller 111 and the fixed base 110. Thus, the assembly of the scanning probe 1 is completed. Next, connect the coil 12 to the output end of the power amplifier 5, connect the DC power supply 4 to the input end of the power amplifier 5, and connect the DC power supply 4 and the power amplifier 5 to the industrial control computer 3 respectively; connect the polarized light source 15 to the light source controller 2, and connect the camera 14 and the light source controller 2 to the industrial control computer 3 respectively.

[0068] For the magneto-optical imaging detection system after assembly, the working process of its excitation and magneto-optical imaging can be described as follows:

[0069] (1) Magnetic circuit part: After passing a current through the coil 12, a magnetic field is generated and conducted through the manganese-zinc ferrite 13 to excite the test piece. The excitation magnetic field flows through the defect area to generate a leakage magnetic field, and then returns to the coil 12 through the manganese-zinc ferrite 13 again to form a closed magnetic induction loop;

[0070] (2) Optical path part: Linearly polarized light is generated by the polarized light source 15 and enters the magneto-optical sensor 18 after being reflected by the semi-transparent and semi-reflective mirror in the polarized light source 15; after passing through the leakage magnetic field, the magneto-optical rotation effect occurs, and its vibration direction deflects, and then is reflected by the reflection film at the bottom of the magneto-optical sensor 18; after passing through the semi-transparent and semi-reflective mirror again and being transmitted, it is extinguished through the polarizer 16, and finally enters the camera 14 to obtain a magneto-optical image through photoelectric conversion.

[0071] On the other hand, the present invention also provides an adaptive excitation method, as Figure 3 shown, including the following steps:

[0072] Step S101: Extract the defect magneto-optical image with the best detection effect and the defect-free magneto-optical image with the best detection effect, and calculate the optimal difference between the defect magneto-optical image with the best detection effect and the defect-free magneto-optical image with the best detection effect;

[0073] Among them, the optimal difference C between the defect magneto-optical image with the best detection effect and the defect-free magneto-optical image with the best detection effect satisfies:

[0074] (1);

[0075] In formula (1), A is the gray matrix of each pixel point obtained by solving based on the defect magneto-optical image with the best detection effect, and B is the gray matrix of each pixel point obtained by solving based on the defect-free magneto-optical image with the best detection effect; is the arithmetic mean of the matrix, and R is the number of pixels in the feature region.

[0076] Step S102: Extract the gray values of each pixel point at the middle row of the magneto-optical image in the actual detection, draw a two-dimensional gray map, and construct a gray function; calculate the actual number of differences K in the gray function;

[0077] Among them, the actual number of differences K in the gray function satisfies:

[0078] (2);

[0079] In formula (2), is the maximum gray value in the gray function, is the minimum gray value in the gray function.

[0080] Step S103: Perform adaptive adjustment on the excitation intensity of the magneto-optical imaging detection system.

[0081] More preferably, the process of performing adaptive adjustment on the excitation intensity of the magneto-optical imaging detection system in step S103 can be specifically described as:

[0082] When K < C, it is determined that the excitation intensity is too small, and the excitation current value of the magneto-optical imaging detection system needs to be increased;

[0083] When K > C and the extreme value of the gray function is not unique, it is determined that the excitation intensity is too large, and the excitation current value of the magneto-optical imaging detection system needs to be decreased;

[0084] When K > C and the extreme value of the gray function is unique, it is determined that the excitation intensity is optimal.

[0085] For example, assuming that the optimal difference is obtained by referring to the defect magneto-optical image with the best detection effect and the defect-free magneto-optical image with the best detection effect ; and further calculating the actual number of differences in the gray function as . At this time, K < C, then the excitation current value of the magneto-optical imaging detection system needs to be increased (for example, choosing to increase the power of the magneto-optical imaging detection system times). After re-judgment, it is found that K > C, but the extreme value of the gray function is not unique. At this time, the excitation current value of the magneto-optical imaging detection system needs to be decreased (for example, choosing to slightly decrease the power of the magneto-optical imaging detection system Multiple). Repeat the above operations until when K > C and the extreme value of the gray function is unique, then determine that the excitation intensity is the best. As Figures 4a - 4c shown, Figure 4a is the two-dimensional gray scale image when the excitation intensity is too large; Figure 4b is the two-dimensional gray scale image when the excitation intensity is moderate; Figure 4c is the two-dimensional gray scale image when the excitation intensity is too small.

[0086] So far, the magneto-optical imaging detection system has completed the adaptive excitation process. Then, continue to implement the defect quantification process of the magneto-optical imaging detection system.

[0087] On the other hand, the present invention also provides a defect quantification method, as Figure 5 shown, including the following steps:

[0088] Step S201: Perform image processing on the magneto-optical image collected by the magneto-optical imaging detection system.

[0089] Among them, as a more preferred embodiment of the present invention, the process of performing image processing on the magneto-optical image collected by the magneto-optical imaging detection system in step S201 can be specifically described as:

[0090] Step S2011: Use the Gaussian filtering method to perform filtering processing on the magneto-optical image collected by the magneto-optical imaging detection system;

[0091] Step S2012: Use the gray threshold segmentation method to divide the gray values of all pixel points in the magneto-optical image into two categories: those higher than the threshold and those lower than the threshold according to the threshold ;

[0092] Step S2013: Perform morphological processing on the magneto-optical image after the gray threshold segmentation processing in step S2012;

[0093] Step S2014: Perform algorithm edge detection on the magneto-optical image after the morphological processing in step S2013.

[0094] Furthermore, the weight of the Gaussian filtering method satisfies:

[0095] (3);

[0096] In formula (3), is the Gaussian coefficient, represents the pixel point coordinates on the collected magneto-optical image.

[0097] In addition, preferably, the process of performing morphological processing on the magneto-optical image after the gray threshold segmentation processing in step S2013 can be specifically described as:

[0098] Perform an erosion operation on the magneto-optical image after the grayscale threshold segmentation process in step S2012 to eliminate the slender regions in the magneto-optical image that are irrelevant to the defects;

[0099] Then perform a closing operation, that is, first perform a dilation operation and then an erosion operation, so as to fill the small holes in the defect region of the magneto-optical image and smooth the boundary of the magneto-optical image.

[0100] Step S202: Calibrate the parameters of the camera in the magneto-optical imaging detection system;

[0101] According to the relative position between the camera and the magneto-optical sensor in the magneto-optical imaging detection system, solve the corresponding relationship between the spatial points on the upper surface of the magneto-optical sensor in the camera coordinate system and the pixel points in the magneto-optical image;

[0102] Based on the result obtained by edge detection, combined with the corresponding relationship between the spatial points on the upper surface of the magneto-optical sensor in the camera coordinate system and the pixel points in the magneto-optical image, quantitatively obtain the contour size of the defect.

[0103] Among them, as a relatively preferred embodiment of the present invention, during the process of calibrating the parameters of the camera in the magneto-optical imaging detection system in step S202, the imaging model of the camera satisfies:

[0104] (4);

[0105] Among them, is the internal parameter of the camera (14), and are the scale factors in the x and y directions of the two-dimensional pixel coordinates of the captured image respectively, is the center point coordinate of the captured image in the camera coordinate system, is the two-dimensional pixel coordinate of the captured image, is the coordinate of the spatial point in the camera coordinate system

[0106] For example, first use the Gaussian filtering method to filter the magneto-optical image, and then perform grayscale threshold segmentation of the magneto-optical image: Take the magneto-optical image after Gaussian filtering as the original image, and determine the grayscale threshold as , and perform image segmentation. Subsequently, perform morphological processing on the segmented magneto-optical image: Through a closing operation, fill the small holes in the defect region and smoothly connect the adjacent regions to improve the quality of the defect image. After that, use algorithm to perform edge detection on the magneto-optical image, and accurately detect the edge of the defect by identifying the points with obvious brightness changes in the digital image to obtain the defect contour information.

[0107] Then use, such as Zhang Zhengyou calibration method, to calibrate the parameters of the camera, and the obtained internal parameter matrix is 。Further, according to the relative positions of the camera and the magneto-optical sensor in the structural design, the is calculated and substituted into the above formula to solve the relative relationship between the spatial point on the upper surface of the magneto-optical sensor in the camera coordinate system and the pixel point in the image. Finally, the length of the defect contour size is obtained as 5.22 mm and the width is 0.31 mm. It can be found by comparison that the calculated defect contour size is in good agreement with the actual defect contour size, thus verifying that the quantization process of the defect quantization method provided by the present invention is reliable and accurate.

[0108] The present invention provides a magneto-optical imaging detection system, an adaptive excitation, and a defect quantization method. Among them, the magneto-optical imaging detection system includes a scanning probe, a light source controller, an industrial personal computer, a DC power supply, and a power amplifier. The scanning probe includes a magnetic circuit module and an optical imaging module. The magnetic circuit module is further composed of a coil, manganese-zinc ferrite, a magnetic shielding layer, and a magneto-optical sensor; the optical imaging module is further composed of a camera, a polarized light source, and a polarizer. The defect quantization method includes the following steps: Step S201: Perform image processing on the magneto-optical image collected by the magneto-optical imaging detection system; Step S202: Calibrate the parameters of the camera in the magneto-optical imaging detection system; According to the relative positions between the camera and the magneto-optical sensor in the magneto-optical imaging detection system, solve the corresponding relationship between the spatial point on the upper surface of the magneto-optical sensor in the camera coordinate system and the pixel point in the magneto-optical image; Quantify the contour size of the defect.

[0109] The magneto-optical imaging detection system, adaptive excitation, and defect quantization method having the above structural features and the above step features have at least the following technical advantages compared with the prior art:

[0110] (1) The magnetic circuit module of the magneto-optical imaging detection system provided by the present invention has a more efficient excitation intensity design and a smaller magneto-optical film lift-off, so it has a stronger surface and buried depth defect detection sensitivity; its optical imaging module has a higher integration degree, and the formed magneto-optical imaging detection system packaging structure is more miniaturized;

[0111] (2) The adaptive excitation method provided by the present invention can realize the adaptive adjustment of the excitation intensity of the magneto-optical imaging detection system, and its detection efficiency is higher;

[0112] (3) The defect quantization method provided by the present invention has a more accurate defect contour quantization result, which can effectively improve the detection ability of the magneto-optical imaging detection system.

[0113] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims described above.

Claims

1. An adaptive excitation method, wherein the adaptive excitation method is based on the magneto-optical imaging detection system described below; The magneto-optical imaging detection system comprises: a scanning probe, a light source controller, an industrial control all-in-one computer, a DC power supply and a power amplifier; The scanning probe includes a magnetic circuit module and an optical imaging module; the magnetic circuit module is composed of a coil, a manganese-zinc ferrite, a magnetic shielding layer, and a magneto-optical sensor; the optical imaging module is composed of a camera, a polarized light source, and a polarizer; in, The coil is wound around the periphery of the manganese-zinc ferrite and connected to a DC power supply and a power amplifier to generate an excitation magnetic field; the magnetic shielding layer is arranged outside the magneto-optical sensor to prevent the background magnetic field from entering and interfering with the leakage magnetic field required by the magneto-optical sensor; The camera and the polarized light source are arranged at the same central axis position of the magneto-optical sensor; the polarizer is arranged between the camera and the polarized light source, and the light transmission axis of the polarizer forms a specific angle with the polarization direction of the polarized light in the polarized light source; wherein the polarized light source is used to provide linear polarized light for the optical imaging module; the camera is connected to the industrial control integrated computer data to upload the collected optical signal so as to process the optical signal to form magneto-optical image data; It also includes: a fixed base, a scanning probe housing, and a magneto-optical sensor clamp; Among them, a mounting groove is arranged on the fixed base, and a steel ball roller is arranged under the fixed base; the scanning probe housing is arranged on the periphery of the scanning probe to protect the various structural units in the scanning probe; the magneto-optical sensor clamp cooperates with the magneto-optical sensor to adjust the lifting distance between the magneto-optical sensor and the sample to be inspected; It is characterized by comprising the following steps: Step S101: extracting the defect magneto-optical image with the best detection effect and the non-defect magneto-optical image with the best detection effect, and calculating the optimal difference between the defect magneto-optical image with the best detection effect and the non-defect magneto-optical image with the best detection effect; Among them, the optimal difference C between the defect magneto-optical image with the best detection effect and the defect-free magneto-optical image with the best detection effect satisfies: In formula (1), A is the grayscale matrix of each pixel point obtained by solving the defect magneto-optical image with the best detection effect, B is the grayscale matrix of each pixel point obtained by solving the defect-free magneto-optical image with the best detection effect; avg() is the arithmetic mean of the calculated matrix, and R is the number of pixels in the feature area; Step S102: extracting the grayscale value of each pixel point in the middle row of the magneto-optical image in actual detection, drawing a two-dimensional grayscale map, constructing a grayscale function; and calculating the actual difference number K in the grayscale function; Among them, the actual difference number K in the grayscale function satisfies: In formula (2), G max is the maximum grayscale value in the grayscale function, G min is the minimum grayscale value in the grayscale function; Step S103: adaptively adjusting the excitation intensity of the magneto-optical imaging detection system.

2. The adaptive excitation method according to claim 1, characterized in that: The process of adaptively adjusting the excitation intensity of the magneto-optical imaging detection system in step S103 can be specifically described as follows: When K<C, it is determined that the excitation intensity is too small, and the excitation current value of the magneto-optical imaging detection system needs to be increased; When K>C and the extreme value of the grayscale function is not unique, it is determined that the excitation intensity is too large and the excitation current value of the magneto-optical imaging detection system needs to be reduced; When K>C and the extreme value of the grayscale function is unique, the excitation intensity is determined to be optimal.

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