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

Abstract

The invention belongs to the technical field of oil and gas equipment detection, and particularly relates to a magneto-optical imaging detection system and a self-adaptive excitation and defect quantification method. The magnetic circuit module of the magneto-optical imaging detection system is designed to be more efficient in excitation intensity, and the lift-off of the magneto-optical film is smaller, so that the magneto-optical imaging detection system has higher surface and burial depth defect detection sensitivity; the integration level of the optical imaging module is higher, and the formed packaging structure of the magneto-optical imaging detection system is smaller. The magneto-optical imaging detection system comprises a scanning probe, a light source controller, an industrial control all-in-one machine, a direct-current power supply and a power amplifier, the scanning probe comprises 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 polaroid. Wherein the coil is wound on the periphery of the manganese zinc ferrite and is connected with the direct-current power supply and the power amplifier; the magnetic shielding layer is arranged on the outer side of the magneto-optical sensor.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and gas equipment detection, and in particular 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 field of oil and gas equipment, such as oil pipelines and oil and gas storage tanks, due to their high strength and low cost. It is worth noting that during the service of such oil and gas equipment, due to the influence of pressure, temperature, stress concentration, electrochemical corrosion and other factors, cracks, corrosion pits and other defects are prone to occur on the surface and inside of the material; if further deterioration occurs, it will cause major safety accidents. Therefore, in order to ensure the safe operation of oil and gas equipment and eliminate potential safety hazards, it is very important to detect it. Non-destructive testing technology can conduct safety inspections on oil and gas equipment without damaging its structure, providing a basis for material performance diagnosis, which is of great significance to ensure oil and gas safety.

[0003] The existing non-destructive testing technologies include at least the following: eddy current testing, ultrasonic testing, magnetic particle testing, and radiographic testing. Among them, eddy current and ultrasonic testing technologies have a low degree of visualization and require high technical skills of operators; although magnetic particle and radiographic testing have a high degree of visualization, their detection efficiency is relatively low, and the detection sensitivity of surface defects is low. Magneto-optical imaging technology, as a non-destructive testing method that couples the "magnetic-optical" dual physical fields, has attracted the attention of technical personnel in this field because of its high visualization of internal and external defects of materials, high detection efficiency, and high sensitivity.

[0004] For example, Liu Haibin and others from Beijing University of Technology invented a ferromagnetic material defect detection device based on AC excitation with patent number CN117554469A, "A metal defect detection device and method based on magneto-optical imaging", which achieved highly visualized detection of external defects, but its excitation method restricted the detection capability of internal defects, and the device had low integration and was difficult to detect efficiently. Hu Fabin from Chengdu Youyida Technology Co., Ltd. invented a pipeline defect detection device with coil excitation with patent number CN118169223A, "A pipeline defect leakage detection device based on magneto-optical imaging", which invented a pipeline defect detection device with coil excitation, but the excitation device had poor adjustability, making it difficult to take into account the detection sensitivity of internal and external defects, and the imaging effect was uncontrollable and difficult to quantify.

[0005] In summary, the applicant found that the existing magneto-optical imaging technology still has limitations such as difficulty in balancing internal and external defect detection, difficulty in controlling the excitation intensity, and difficulty in quantifying defect detection results. It cannot meet the technical personnel's needs 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 a defect quantification method. The magnetic circuit module design of the magneto-optical imaging detection system has a more efficient excitation intensity and a smaller magneto-optical film lift-off, thereby having a stronger sensitivity for detecting surface and buried depth defects; the optical imaging module has a higher degree of integration, and the packaging structure of the magneto-optical imaging detection system formed is more miniaturized.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions: The magneto-optical imaging detection system includes: a scanning probe, a light source controller, an industrial control integrated machine, 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; 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 all-in-one computer data to upload the collected optical signal so as to process the optical signal to form magneto-optical image data.

[0008] Preferably, 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.

[0009] On the other hand, the present invention further provides an adaptive excitation method, which is based on the above-mentioned magneto-optical imaging detection system and includes 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: (1); 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, and B is the grayscale matrix of each pixel point obtained by solving the defect-free magneto-optical image with the best detection effect; is the arithmetic mean of the matrix, 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: (2); In formula (2), is the maximum grayscale value in the grayscale function, is the minimum grayscale value in the grayscale function; Step S103: adaptively adjusting the excitation intensity of the magneto-optical imaging detection system.

[0010] Preferably, 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.

[0011] On the other hand, the present invention further provides a defect quantification method, which is based on the above-mentioned magneto-optical imaging detection system and is characterized in that it includes the following steps: Step S201: performing image processing on the magneto-optical image acquired by the magneto-optical imaging detection system; Step S202: calibrating 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, 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 is solved; Based on the results obtained by edge detection and the correspondence 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.

[0012] Preferably, the process of performing image processing on the magneto-optical image acquired by the magneto-optical imaging detection system in step S201 can be specifically described as follows: Step S2011: using Gaussian filtering method to filter the magneto-optical image collected by the magneto-optical imaging detection system; Step S2012: Use gray threshold segmentation method, according to the threshold The grayscale values ​​of all pixels in the magneto-optical image are divided into two categories: those above the threshold and those below the threshold; Step S2013: performing morphological processing on the magneto-optical image after the grayscale threshold segmentation processing in step S2012; Step S2014: morphologically process the magneto-optical image after step S2013. Algorithmic edge detection.

[0013] Preferably, the weights of the Gaussian filtering method satisfy: (3); In formula (3), is the Gaussian coefficient, Represents the pixel coordinates on the acquired magneto-optical image.

[0014] Preferably, the process of performing morphological processing on the magneto-optical image after the grayscale threshold segmentation processing in step S2012 in step S2013 can be specifically described as follows: Performing an erosion operation on the magneto-optical image after the grayscale threshold segmentation process in step S2012 to eliminate the elongated areas in the magneto-optical image that are not related to the defects; Then a closing operation is performed, that is, a dilation operation is performed first and then an erosion operation is performed, so as to fill the small holes in the defective area of ​​the magneto-optical image and smooth the boundary of the magneto-optical image.

[0015] Preferably, in 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: (4); in, is the internal parameter of the camera (14), and are the scale factors of the two-dimensional pixel coordinates in the x and y directions of the sampled image, is the coordinate of the center point of the image captured in the camera coordinate system, is the two-dimensional pixel coordinate of the sampled image, is the coordinate of the space point in the camera coordinate system.

[0016] The present invention provides a magneto-optical imaging detection system, adaptive excitation and defect quantification method, wherein the magneto-optical imaging detection system includes a scanning probe, a light source controller, an industrial control integrated machine, 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: performing parameter calibration on 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.

[0017] The magneto-optical imaging detection system, adaptive excitation and defect quantification method having the above structural features and the above step features have at least the following technical advantages compared to the prior art: (1) The magneto-optical imaging detection system provided by the present invention has a more efficient excitation intensity of the magnetic circuit module 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 degree of integration, and the packaging structure of the magneto-optical imaging detection system formed is more miniaturized; (2) The adaptive excitation method provided by the present invention can realize adaptive adjustment of the excitation intensity of the magneto-optical imaging detection system, and its detection efficiency is higher; (3) The defect quantification method provided by the present invention has a more accurate defect contour quantification result, which can effectively improve the detection capability of the magneto-optical imaging detection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the following drawings: Figure 1 A schematic diagram of the structure of the magneto-optical imaging detection system provided by the present invention; Figure 2 It is a schematic diagram of the structure of the scanning probe; Figure 3 A schematic flow chart of the adaptive excitation method provided by the present invention; Figure 4a It is a two-dimensional grayscale schematic diagram when the excitation intensity is too large; Figure 4b It is a two-dimensional grayscale schematic diagram when the excitation intensity is moderate; Figure 4c It is a two-dimensional grayscale schematic diagram of the excitation intensity being too small; Figure 5 A schematic diagram of the process flow of the defect quantification method provided by the present invention.

[0019] Figure numerals: 1. scanning probe; 2. light source controller; 3. industrial control integrated machine; 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 clamp; 110. fixed base; 111. steel ball roller. DETAILED DESCRIPTION

[0020] The present invention provides a magneto-optical imaging detection system, an adaptive excitation and a defect quantification method. The magnetic circuit module design of the magneto-optical imaging detection system has a more efficient excitation intensity and a smaller magneto-optical film lift-off, thereby having a stronger sensitivity for detecting surface and buried depth defects; the optical imaging module has a higher degree of integration, and the packaging structure of the magneto-optical imaging detection system formed is more miniaturized.

[0021] The present invention provides a magneto-optical imaging detection system, such as Figure 1 As shown, it includes: a scanning probe 1, a light source controller 2, an industrial control integrated machine 3, a DC power supply 4 and a power amplifier 5. Further, as Figure 2 As shown, the scanning probe 1 also includes a magnetic circuit module and an optical imaging module. 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.

[0022] Specifically, the coil 12 is wound around the periphery of the manganese-zinc ferrite 13 and is 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 on the outside of 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 light transmission axis of the polarizer 16 is at a specific angle to the polarization direction of the polarized light in the polarized light source 15. Among them, the polarized light source 15 is used to provide linear polarized light for the optical imaging module. The camera 14 is connected to the industrial control all-in-one machine 3 for uploading the collected optical signal so as to process the optical signal to form magneto-optical image data.

[0023] In addition, as a more preferred embodiment, Figure 2As shown, the magneto-optical imaging detection system also includes: a fixed base 110, a scanning probe housing 11, and a magneto-optical sensor clamp 19. Among them, a mounting groove is provided on the fixed base 110, and a steel ball roller 111 is provided under the fixed base 110. The scanning probe housing 11 is provided on the periphery of the scanning probe 1 to protect the various structural units in the scanning probe 1. The magneto-optical sensor clamp 19 cooperates with the magneto-optical sensor 18 to adjust the lifting distance between the magneto-optical sensor 18 and the sample to be inspected.

[0024] In order to facilitate those skilled in the art to understand this application, Figure 1 , 2 , further providing the following specific embodiment. Among them, the specific parameters of each structural unit in the magneto-optical imaging detection system can be referred to as: The distance between the manganese zinc ferrite 13 and the bottom of the steel ball roller 111 is 0.5 mm; the distance between the magneto-optical sensor 18 and the bottom of the steel ball roller 111 is 0.1 mm; the overall size of the scanning probe 1 is 150 mm long, 70 mm wide, and 70 mm high. In addition, the magneto-optical sensor 18 uses yttrium iron garnet film, and the magnetic field response range is 0.0625 mT to 2.5 mT, thereby ensuring the high sensitivity of the magneto-optical imaging detection system. The camera 14 uses 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, thereby ensuring 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 selected on the test piece to be detected, and this is used as an example to introduce the implementation process of the present invention.

[0025] The assembly, magneto-optical imaging and detection process of the magneto-optical imaging detection system can be specifically referred to as follows: First, select the 0.5 mm enameled wire required by the coil 12 specifications according to the defect size and the detection working conditions, and wind it on the manganese-zinc ferrite 13; then place the manganese-zinc ferrite 13, the polarized light source 15 and the magneto-optical sensor holder 19 into the installation groove reserved by the fixed base 110; then place the magneto-optical sensor 18 into the cavity of the magneto-optical sensor holder 19, and wrap it on all 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 steel ball roller 111 is fixedly connected to the fixed base 110, so that 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 integrated machine 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 integrated machine 3 respectively.

[0026] The working process of the magneto-optical imaging and excitation of the assembled magneto-optical imaging detection system can be described as follows: (1) Magnetic circuit: When current is passed through the coil 12, a magnetic field is generated, which is then conducted through the manganese-zinc ferrite 13 to excite the specimen. The excitation magnetic field flows through the defect area to generate a leakage magnetic field, which then returns to the coil 12 through the manganese-zinc ferrite 13, forming a closed magnetic induction loop; (2) Optical path: 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. It undergoes magneto-optical rotation effect after passing through the leakage magnetic field, and its vibration direction is deflected, and then it is reflected by the reflective film at the bottom of the magneto-optical sensor 18. It is then transmitted through the semi-transparent and semi-reflective mirror, extinguished by the polarizer 16, and finally enters the camera 14 to obtain a magneto-optical image after photoelectric conversion.

[0027] On the other hand, the present invention also provides an adaptive excitation method, such as Figure 3 As shown, the following steps are included: 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: (1); 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, and B is the grayscale matrix of each pixel point obtained by solving 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 area.

[0028] 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: (2); In formula (2), is the maximum grayscale value in the grayscale function, is the minimum grayscale value in the grayscale function.

[0029] Step S103: adaptively adjusting the excitation intensity of the magneto-optical imaging detection system.

[0030] Preferably, 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.

[0031] For example, assuming that the defect magneto-optical image with the best detection effect and the defect-free magneto-optical image with the best detection effect are referenced, the optimal difference is solved as ; And further calculate the actual difference number in the grayscale function is At this time, K<C, then it is necessary to increase the excitation current value of the magneto-optical imaging detection system (for example, choose to increase the power of the magneto-optical imaging detection system). times). After another judgment, it is found that K>C, but the extreme value of the grayscale function is not unique. At this time, it is necessary to reduce the excitation current value of the magneto-optical imaging detection system (for example, choose to slightly reduce the power of the magneto-optical imaging detection system). The above operation is repeated until K>C and the extreme value of the grayscale function is unique, then the excitation intensity is determined to be optimal. Figure 4a-4c As shown, Figure 4a It is a two-dimensional grayscale image when the excitation intensity is too large; Figure 4b It is a two-dimensional grayscale image when the excitation intensity is moderate; Figure 4c It is a two-dimensional grayscale image when the excitation intensity is too small.

[0032] At this point, the magneto-optical imaging detection system has completed the adaptive excitation process. Then, the defect quantification process of the magneto-optical imaging detection system is continued.

[0033] In another aspect, the present invention also provides a defect quantification method, such as Figure 5 As shown, the following steps are included: Step S201: performing image processing on the magneto-optical image acquired by the magneto-optical imaging detection system.

[0034] Among them, as a more preferred embodiment of the present invention, the process of performing image processing on the magneto-optical image acquired by the magneto-optical imaging detection system in step S201 can be specifically described as follows: Step S2011: using Gaussian filtering method to filter the magneto-optical image collected by the magneto-optical imaging detection system; Step S2012: Use gray threshold segmentation method, according to the threshold The grayscale values ​​of all pixels in the magneto-optical image are divided into two categories: those above the threshold and those below the threshold; Step S2013: performing morphological processing on the magneto-optical image after the grayscale threshold segmentation processing in step S2012; Step S2014: morphologically process the magneto-optical image after step S2013. Algorithmic edge detection.

[0035] Furthermore, the weights of the Gaussian filter satisfy: (3); In formula (3), is the Gaussian coefficient, Represents the pixel coordinates on the acquired magneto-optical image.

[0036] In addition, preferably, the process of performing morphological processing on the magneto-optical image after the grayscale threshold segmentation processing in step S2012 in step S2013 can be specifically described as follows: Performing an erosion operation on the magneto-optical image after the grayscale threshold segmentation process in step S2012 to eliminate the elongated areas in the magneto-optical image that are not related to the defects; Then a closing operation is performed, that is, a dilation operation is performed first and then an erosion operation is performed, so as to fill the small holes in the defective area of ​​the magneto-optical image and smooth the boundary of the magneto-optical image.

[0037] Step S202: calibrating 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, 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 is solved; Based on the results obtained by edge detection and the correspondence 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.

[0038] Among them, as a more preferred implementation of the present invention, in 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: (4); in, is the internal parameter of the camera (14), and are the scale factors of the two-dimensional pixel coordinates in the x and y directions of the sampled image, is the coordinate of the center point of the image captured in the camera coordinate system, is the two-dimensional pixel coordinate of the sampled image, is the coordinate of the space point in the camera coordinate system For example, the magneto-optical image is first filtered using the Gaussian filter method, and then the grayscale threshold segmentation of the magneto-optical image is performed: the magneto-optical image after Gaussian filtering is used as the original image, and the grayscale threshold is determined according to the grayscale value of the background magnetic field. , and perform image segmentation. Subsequently, the segmented magneto-optical image is morphologically processed: a closing operation is performed to fill the small holes in the defect area and smoothly connect the adjacent areas to improve the quality of the defect image. The algorithm performs edge detection on the magneto-optical image and accurately detects the edges of defects by identifying points with obvious brightness changes in the digital image to obtain defect contour information.

[0039] Then use the Zhang Zhengyou calibration method to calibrate the camera parameters, and the obtained internal parameter matrix is Further, according to the relative position of the camera and the magneto-optical sensor in the structural design, we can calculate , substituted into the above formula, the relative relationship between the spatial point on the upper surface of the magneto-optical sensor and the pixel point in the image in the camera coordinate system can be solved, and finally the defect contour size is 5.22mm long and 0.31mm wide. After comparison, it can be found that the defect contour size obtained by calculation is consistent with the actual defect contour size, which proves that the defect quantification method provided by the present invention is reliable and accurate in its quantification process.

[0040] The present invention provides a magneto-optical imaging detection system, adaptive excitation and defect quantification method, wherein the magneto-optical imaging detection system includes a scanning probe, a light source controller, an industrial control integrated machine, 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: performing parameter calibration on 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.

[0041] The magneto-optical imaging detection system, adaptive excitation and defect quantification method having the above structural features and the above step features have at least the following technical advantages compared to the prior art: (1) The magneto-optical imaging detection system provided by the present invention has a more efficient excitation intensity of the magnetic circuit module 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 degree of integration, and the packaging structure of the magneto-optical imaging detection system formed is more miniaturized; (2) The adaptive excitation method provided by the present invention can realize adaptive adjustment of the excitation intensity of the magneto-optical imaging detection system, and its detection efficiency is higher; (3) The defect quantification method provided by the present invention has a more accurate defect contour quantification result, which can effectively improve the detection capability of the magneto-optical imaging detection system.

[0042] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. Magneto-optical imaging detection system, characterized in that: Includes: scanning probe, light source controller, industrial control all-in-one computer, DC power supply and 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; 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 all-in-one computer data to upload the collected optical signal so as to process the optical signal to form magneto-optical image data.

2. The magneto-optical imaging detection system according to claim 1, characterized in that: 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.

3. An adaptive excitation method, the adaptive excitation method is based on the magneto-optical imaging detection system according to any one of claims 1 to 2, characterized in that: The steps include: 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: （1）； 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, and B is the grayscale matrix of each pixel point obtained by solving the defect-free magneto-optical image with the best detection effect; is the arithmetic mean of the matrix, 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: （2）； In formula (2), is the maximum grayscale value in the grayscale function, is the minimum grayscale value in the grayscale function; Step S103: adaptively adjusting the excitation intensity of the magneto-optical imaging detection system.

4. The adaptive excitation method according to claim 3, 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.

5. A defect quantification method, the defect quantification method is based on the magneto-optical imaging detection system according to any one of claims 1 to 2, characterized in that: The steps include: Step S201: performing image processing on the magneto-optical image acquired by the magneto-optical imaging detection system; Step S202: calibrating 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, 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 is solved; Based on the results obtained by edge detection and the correspondence 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.

6. The defect quantification method according to claim 5, characterized in that: The process of performing image processing on the magneto-optical image acquired by the magneto-optical imaging detection system in step S201 can be specifically described as follows: Step S2011: using Gaussian filtering method to filter the magneto-optical image collected by the magneto-optical imaging detection system; Step S2012: Use gray threshold segmentation method, according to the threshold The grayscale values ​​of all pixels in the magneto-optical image are divided into two categories: those above the threshold and those below the threshold; Step S2013: performing morphological processing on the magneto-optical image after the grayscale threshold segmentation processing in step S2012; Step S2014: morphologically process the magneto-optical image after step S2013. Algorithmic edge detection.

7. The defect quantification method according to claim 6, characterized in that: The weights of the Gaussian filtering method satisfy: （3）； In formula (3), is the Gaussian coefficient, Represents the pixel coordinates on the acquired magneto-optical image.

8. The defect quantification method according to claim 6, characterized in that: The process of performing morphological processing on the magneto-optical image after the grayscale threshold segmentation processing in step S2012 in step S2013 can be specifically described as follows: Performing an erosion operation on the magneto-optical image after the grayscale threshold segmentation process in step S2012 to eliminate the elongated areas in the magneto-optical image that are not related to the defects; Then a closing operation is performed, that is, a dilation operation is performed first and then an erosion operation is performed, so as to fill the small holes in the defective area of ​​the magneto-optical image and smooth the boundary of the magneto-optical image.

9. The defect quantification method according to claim 5, characterized in that: In 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: （4）； in, is the internal parameter of the camera (14), and are the scale factors of the two-dimensional pixel coordinates in the x and y directions of the sampled image, is the coordinate of the center point of the image captured in the camera coordinate system, is the two-dimensional pixel coordinate of the sampled image, is the coordinate of the space point in the camera coordinate system.

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