Method, apparatus and system for automatic identification of self-healing region of metallized film capacitor, and application thereof

Abstract

Provided in the embodiments of the present application are a method, apparatus and system for automatic identification of a self-healing region of a metallized film capacitor, and the application thereof. The system comprises an automatic sample replacement unit, which is used for placing or automatically replacing a capacitor metallized film; a CCD image acquisition unit, which is used for capturing image information of the capacitor metallized film; and a data processing unit, which is used for processing the image information, so as to realize automatic identification of a self-healing region of the capacitor metallized film.

Description

A method, device, system, and application for automatic identification of self-healing regions in metallized film capacitors.

[0001] Cross-references to related applications

[0002] This application is based on and claims priority to Chinese Patent Application No. 202411557958.0, filed on November 4, 2024, entitled “Automatic Identification Method, Apparatus, System and Application of Self-Healing Region of Metallized Film Capacitor”, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to, but is not limited to, the field of power capacitor technology, and in particular to an automatic identification system and method for self-healing areas of metallized film capacitors. Background Technology

[0004] DC-Link capacitors are characterized by their small size, large capacitance, high voltage withstand capability, high current withstand capability, low loss, excellent temperature performance, high energy density, and good safety and reliability. The self-healing capacitors on the DC side bridge arm of the converter valve hall in converter stations serve as voltage supports and DC filters. They are crucial components for maintaining the stable operation of the entire transmission system, ensuring good coordination, and guaranteeing transmission quality. Based on current research both domestically and internationally, damage to metallized film capacitors is primarily caused by continuous self-healing on the metallized film. Therefore, understanding the mechanism and parameters of self-healing is of great significance for designing capacitors to improve their lifespan, reduce enterprise costs, and enhance the stability of power system transmission.

[0005] The self-healing process of metallized films is complex, involving both physical changes and chemical reactions. It can be summarized as follows: the dielectric film breaks down, creating a current path; the metal electrodes near the breakdown point evaporate due to heat generated by the current; the breakdown point is isolated; the discharge arc is extinguished; and insulation is restored. When a localized breakdown occurs in the dielectric film, a current path is created at the breakdown point, and external energy is injected into the breakdown point, forming a discharge circuit. The area of ​​the electrode removed around the breakdown point is the self-healing area, typically on the order of square millimeters. Therefore, the capacitance loss caused by a single self-healing is very small, generally in the pF range. However, multiple self-healing events may occur during each charge-discharge cycle of the capacitor, and the number of self-healing events per charge-discharge cycle gradually increases with the aging of the dielectric film. This cumulative effect of multiple self-healing events leads to a significant decrease in capacitance. When the actual capacitance falls below 95% of the rated capacitance, the capacitor fails.

[0006] Therefore, it is imperative to study a self-healing identification system and scheme for capacitor metallized films. Summary of the Invention

[0007] To overcome the aforementioned problems, this application proposes an automatic identification system and method for self-healing regions of metallized film capacitors. The system includes an automatic sample changing unit for placing or automatically replacing the metallized film of the capacitor; a CCD image acquisition unit for capturing image information of the metallized film; and a data processing unit for processing the image information to achieve automatic identification of the self-healing regions of the metallized film. The system acquires information from different locations on the metallized film sample, thus providing sufficient data for accurate analysis of self-healing region parameters. Its automatic identification and analysis process reduces the influence of human factors, improves the reliability and consistency of the detection, and thus completes this application.

[0008] Specifically, the purpose of this application is to provide the following:

[0009] In a first aspect, an automatic identification system for self-healing regions of metallized film capacitors is provided, the system comprising:

[0010] An automatic sample changing unit is used to place or automatically replace the metallized film of capacitors;

[0011] The CCD image acquisition unit is used to capture image information of the metallized film of the capacitor.

[0012] The data processing unit processes image information to enable automatic identification of the self-healing areas of the capacitor metallization film.

[0013] In some embodiments, the data processing unit is connected to the CCD image acquisition unit.

[0014] In some embodiments, the CCD image acquisition unit is located above the automatic sampling unit.

[0015] In some embodiments, the automatic sample changing unit includes:

[0016] The drive wheel is used to drive the movement and sample changing of the metallized film in the capacitor;

[0017] The driven wheel assists the driving wheel in moving and changing the metallized film of the capacitor.

[0018] In some embodiments, the automatic sample changing unit further includes a microcontroller area for fixing a stepper motor drive element, the fixed stepper motor drive element being used for power supply.

[0019] In some embodiments, the automatic sample changing unit further includes a surface light source area for placing a surface light source, which provides a light source.

[0020] In some embodiments, the automatic sample changing unit further includes a controller area for placing a controller for controlling the operation of the automatic sample changing unit.

[0021] In some embodiments, the CCD image acquisition unit is preferably a CCD camera.

[0022] In some embodiments, the data processing unit uses mathematical morphology-based image recognition to achieve contour recognition and automatic segmentation of the self-healing region.

[0023] Secondly, a method for automatically identifying self-healing regions of capacitor metallization films according to the system described in the first aspect, the method comprising:

[0024] Step 1: Place or automatically replace the metallization film on the capacitor;

[0025] Step 2: Capture image information of the capacitor metallization film;

[0026] Step 3: Process the image information to achieve automatic identification of the self-healing area of ​​the capacitor metallization film.

[0027] The beneficial effects of this application include:

[0028] (1) The system provided in this application acquires information from different locations of the capacitor metallized film sample, thereby providing sufficient data for accurate analysis of the parameters of the self-healing region; the system achieves automatic sample changing and autonomous detection of sample information through an automatic sample changing unit; and provides solutions for different demanders through a CCD image acquisition unit and a data processing unit.

[0029] (2) The system provided in this application realizes high-speed and efficient automatic sample replacement, autonomous detection, damage identification, and data analysis. Based on artificial intelligence algorithms of image recognition and machine learning, it realizes data analysis of self-healing areas, generates detection reports with one click, and obtains comprehensive and accurate analysis data, providing an efficient solution for liberating manpower in enterprises and research institutes.

[0030] (3) The automatic identification method for self-healing regions of capacitor metallized film provided in this application accurately identifies self-healing regions based on mathematical morphology image recognition. This not only improves the identification accuracy, but also reduces the influence of human factors in the automatic identification and analysis process, thereby improving the reliability and consistency of detection. Attached Figure Description

[0031] Various other advantages and benefits of this application will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0032] In the attached diagram:

[0033] Figure 1 shows a schematic diagram of the automatic identification system for self-healing areas of capacitor metallized film according to this application.

[0034] Figure 2 shows a schematic diagram of the automatic sampling unit structure of this application;

[0035] Figure 3 shows the image information acquired by the area array CCD camera in Embodiment 1;

[0036] Figure 4 shows the image information acquired in Example 1 converted to grayscale;

[0037] Figure 5 shows the edge information of the self-healing point of the capacitor metallization film in Example 1;

[0038] Figure 6 shows the area distribution of the self-healing region in Example 1;

[0039] Figure 7 shows a statistical diagram of the self-healing region area in Example 1;

[0040] Among them, 1-automatic sample changing unit; 11-supporting microcontroller area; 12-drive wheel; 13-driven wheel; 14-surface light source area; 15-controller area; 16-support plate; 17-support frame; 18-base plate fixing plate; 19-concave groove; 2-CCD image acquisition unit; 3-data processing unit; 4-acquisition support frame. Detailed Implementation

[0041] Specific embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While specific embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0042] It should be noted that certain terms are used in the specification and claims to refer to specific components. Those skilled in the art will understand that different terms may be used to refer to the same component. This specification and claims do not distinguish components based on differences in terminology, but rather on differences in function. The terms "comprising" or "including" used throughout the specification and claims are open-ended and should be interpreted as "comprising but not limited to." The following descriptions in the specification are preferred embodiments for carrying out this application; however, these descriptions are for the purpose of understanding the general principles of the specification and are not intended to limit the scope of this application. The scope of protection of this application shall be determined by the appended claims.

[0043] In the description of this application, it should be noted that the terms "upper," "lower," "inner," "outer," "front," and "rear," etc., indicate the orientation or positional relationship based on the orientation or positional relationship in the working state of this application, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. In addition, the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0044] To facilitate understanding of the embodiments of this application, the following will provide further explanation and description with reference to the accompanying drawings and specific embodiments, and the accompanying drawings do not constitute a limitation on the embodiments of this application.

[0045] On one hand, according to the automatic identification system for self-healing regions of a metallized film capacitor provided in this application, as shown in Figure 1, the system includes:

[0046] Automatic sample changing unit 1, which is used to place or automatically replace the metallized film of capacitors;

[0047] CCD image acquisition unit 2 is used to capture image information of capacitor metallization film;

[0048] The data processing unit 3 is used to process image information to achieve automatic identification of the self-healing area of ​​the capacitor metallization film.

[0049] In this application, the data processing unit 3 is connected to the CCD image acquisition unit 2, and the CCD image acquisition unit 2 is located above the automatic sampling unit 1.

[0050] According to this application, as shown in Figure 2, the automatic sampling unit includes:

[0051] The microcontroller area 11 is used to fix a stepper motor drive element, which is used for power supply;

[0052] The drive wheel 12 is used to drive the movement and sample changing of the metallized film in the capacitor.

[0053] Driven wheel 13 is used to assist drive wheel 12 in moving and changing the metallized film of capacitor;

[0054] A surface light source area 14 is used to place a surface light source, which is used to provide a light source;

[0055] Controller area 15, which is used to house a controller for controlling the operation of the automatic sample changing unit;

[0056] Support plate 16, which is used to fix drive wheel 12 and driven wheel 13, and provides surface light source area 14 and controller area 15;

[0057] Support frame 17, which is used to fix CCD image acquisition unit 2;

[0058] The base plate fixing plate 18 is used to support the microcontroller area 11, the driving wheel 12, the driven wheel 13, the surface light source area 14, the controller area 15, the support plate 16, and the support frame 17.

[0059] In one embodiment, the base plate fixing plate 18 is provided with concave grooves 19, preferably two concave grooves 19, which are symmetrically, parallel and of equal length arranged on the left and right sides of the base plate fixing plate 18; the concave grooves 19 are used to fix the support plates 16, that is, preferably two support plates 16, which are engaged in the grooves of the concave grooves 19.

[0060] Furthermore, the support plate 16 is provided with holes for fixing the driving wheel 12 and the driven wheel 13. The driving wheel 12 and the driven wheel 13 are respectively located at both ends of the support plate 16.

[0061] According to this application, preferably, there are two drive wheels 12, which are arranged vertically and parallel to each other at one end of the support plate 16; preferably, there are two driven wheels 13, which are arranged vertically and parallel to each other at the other end of the support plate 16 and are at the same horizontal position as the two drive wheels 12. The drive wheels 12 and driven wheels 13 drive the metallized film of the capacitor to move by rotation, thereby realizing sample replacement.

[0062] In use, the capacitor metallized film is sandwiched between the upper and lower wheels of the driving wheel 12 and the upper and lower wheels of the driven wheel 13.

[0063] In this application, a surface light source area 14 and a controller area 15 are provided between the concave grooves 19. The surface light source area 14 and the controller area 15 are both located between the driving wheel 12 and the driven wheel 13. That is to say, the support plates 16 are provided with the driving wheel 12, the surface light source area 14, the controller area 15 and the driven wheel 13 from left to right.

[0064] In this application, the support frame 17 is fixedly installed on the left side of the drive wheel 12, that is, at the end away from the surface light source area 14. The position of the support frame 17 where the CCD image acquisition unit 2 is placed is higher than the height of the surface light source, the drive wheel 12, and the driven wheel 13.

[0065] In this application, a microcontroller area 11 is provided on the outside of the support plate 16, that is, on the outside of the concave groove 19.

[0066] In use, the capacitor metallized film is fixed between the upper and lower wheels of the driving wheel 12 and the driven wheel 13. The driving wheel 12 rotates to drive the capacitor metallized film to move. The surface light source is placed in the surface light source area 14, the controller is placed in the controller area 15, and the CCD image acquisition unit 2 is placed at 17.

[0067] In this application, the fixed stepper motor drive element includes a microcontroller and a stepper motor driver. By controlling the driving speed of the stepper motor drive element through the microcontroller, the rotational speed of the drive wheel 12 can be controlled, thereby regulating the replacement speed of the capacitor metallization film to achieve automatic sample changing.

[0068] Furthermore, the fixed stepper motor drive element also includes a microcontroller-based closed-loop stepper motor. The microcontroller is connected to a stepper motor driver, which in turn is connected to the closed-loop stepper motor. The closed-loop stepper motor powers the automatic sample-changing unit via gear transmission. Specifically, the microcontroller sends pulse signals to the stepper motor driver, which controls the closed-loop stepper motor. The stepper motor then powers the automatic sample-changing unit via gear transmission. More specifically, the microcontroller provides 220V AC power, which is converted to 36V DC power via a DC-DC module to power the stepper motor driver. The 36V DC power is then converted to 5V DC power via the same module to power the closed-loop stepper motor, which in turn powers the automatic sample-changing unit via gear transmission.

[0069] In this application, the CCD image acquisition unit 2 is preferably a CCD camera, and the CCD image acquisition unit 2 is fixed on the acquisition support frame 4.

[0070] Furthermore, the CCD camera converts optical signals into current signals, which are then amplified and converted from analog to digital to achieve image acquisition, storage, transmission, processing, and reproduction. The CCD camera boasts advantages such as small size, light weight, low power consumption, low operating voltage, shock and vibration resistance, stable performance, and long lifespan; high sensitivity, low noise, and a wide dynamic range; fast response speed, self-scanning function, minimal image distortion, and no image retention; and is manufactured using integrated circuit technology, resulting in high pixel integration, precise dimensions, and low commercial production costs.

[0071] In this application, the CCD camera is a linear CCD camera or an area CCD camera, preferably an area CCD camera. A linear CCD camera consists of a series of linear photosensitive elements arranged in one direction, enabling it to capture one-dimensional image information at a high speed, making it more suitable for rapid scanning. An area CCD camera consists of a two-dimensional array of photosensitive elements, capable of capturing the entire two-dimensional image. It typically has a larger photosensitive area and can capture a wider range of image information for comprehensive image analysis.

[0072] In this application, the data processing unit 3 includes:

[0073] The data transmission unit is used to transmit the image information acquired by the CCD image acquisition unit 2 to the data processor.

[0074] The recognition and processing unit is used to identify self-healing regions and extract parameters from image information;

[0075] The analysis and reporting unit is used to output parameters of the self-healing area and generate statistical charts.

[0076] In this application, the data processing unit 3 is based on mathematical morphology image recognition, which can realize contour recognition and automatic segmentation of self-healing regions.

[0077] In this application, the recognition processing unit first converts the image information acquired by the CCD image acquisition unit 2 to grayscale; then, it obtains the edge of the self-healing point of the capacitor metallization film based on the grayscale image; and then, it obtains the parameters of the self-healing region based on the edge of the self-healing point.

[0078] The parameters include length, width, and area. Based on the area, a self-healing region area distribution and a statistical chart of the self-healing region area are obtained. The area proportions are divided into 0-400mm based on the area. 2 400-800mm 2 800-1200mm 2 and 1200mm 2 The above four ranges.

[0079] Furthermore, when obtaining the edge of the self-healing point of the capacitor metallization film from the grayscale image, the process also includes image binarization, image denoising, and contour detection of the grayscale image. The edge of the self-healing point of the capacitor metallization film is obtained based on the contour detection results, and the length, width, and area of ​​the self-healing region are obtained based on the edge of the self-healing point. The area ratio distribution and area statistics of the self-healing region are then calculated based on the area size.

[0080] In this process, image grayscale conversion is used to improve recognition accuracy. The self-healing region, due to electrode loss, appears as a white transparent area under the recognition of the scanning CCD image acquisition unit 2, while the remaining undamaged areas appear as normal colors. In the grayscale image, the pixel information of the self-healing region only contains white grayscale values, while the remaining normal areas contain other values, thus reducing the difficulty of contour segmentation and improving resolution accuracy. Specifically, the three color channels (R, G, B) in the image information pixel channels acquired by the CCD image acquisition unit 2 are converted into a single grayscale value (Y), which is then summed using coefficients, for example, Y = 0.3R + 0.5G + 0.2B.

[0081] Image binarization, which transforms a grayscale image into a binary image, is a fundamental method for image segmentation. Specifically, it converts grayscale values ​​greater than a certain threshold into maxima and those less than this threshold into minima. The specific algorithm logic is as follows:

[0082] In the formula, x represents the horizontal coordinate of the pixel; y represents the horizontal and vertical coordinates of the pixel; dst(x,y) represents the binary value of the pixel after binarization; maxval is the set maximum value of the binary value, usually 250 to 255, for example 255; src(x,y) represents the gray value of the pixel in the grayscale image; thresh represents the set threshold, usually 180 to 255, for example 180.

[0083] Image denoising is used to handle interference caused by external environments such as image transmission, thereby improving data accuracy. Here, for subsequent contour processing, an opening operation denoising method is employed. The opening operation is an extension of erosion and dilation algorithms to eliminate background noise points, smooth boundaries without significantly altering volume, and separate adhered targets. The specific algorithm logic is as follows:

[0084] In the formula, A represents the noise reduction region, and B is the template used for the operation. The above formula means that B is first used to erode A, and then B is used to expand A, which completes the opening operation.

[0085] The mathematical logic behind the corrosion mentioned above is as follows:

[0086] Among them (B) z This represents the translation of structuring element B at position z. The result of the erosion operation is the set of all elements z in set A that completely contain structuring element B. This process shrinks the image, eliminating the image's boundary portions, and is often used to remove small, meaningless objects or noise.

[0087] The mathematical logic behind the aforementioned expansion is as follows:

[0088] The result of the dilation operation is the set of all elements z in set A that intersect with structuring element B. This process enlarges the image and is often used to connect adjacent objects or fill in holes inside objects. Contour detection is used to obtain the shape and location information of self-healing regions, i.e., to find the edges of the self-healing points of the capacitor metallization film. Specifically, the `cv2.findContours` function is used to detect contours in the image, and `cv2.drawContours` is used to draw the contours, thus achieving contour detection. A `for` loop is used to iterate through all self-healing regions, and the `cv2.contourArea` function is used to obtain the length, width, and area of ​​each region.

[0089] The process involves traversing all self-healing regions to determine the threshold, and using the print function to store the output results to calculate the area distribution and area statistics of the self-healing regions.

[0090] In one embodiment, the image information acquired by the CCD image acquisition unit 2 is shown in Figure 3; the grayscale image is shown in Figure 4; the grayscale image is denoised, contoured, and segmented, and Figure 5 shows the edge information of the self-healing point of the capacitor metallization film.

[0091] On the other hand, according to the system provided in the first aspect of this application, a method for automatic identification of self-healing regions of capacitor metallization films is provided, the method comprising:

[0092] Step 1: Place or automatically replace the metallization film on the capacitor;

[0093] Step 2: Capture image information of the capacitor metallization film;

[0094] Step 3: Process the image information to achieve automatic identification of the self-healing area of ​​the capacitor metallization film.

[0095] In step 1, the capacitor metallization film is placed or automatically replaced by the automatic sample changing unit 1.

[0096] In step 2, the image information of the capacitor metallization film is captured by the CCD image acquisition unit 2.

[0097] Step 3 preferably includes the following steps:

[0098] Step 3-1: Transmit the captured image information of the capacitor metallization film to the data processor;

[0099] Step 3-2: Identify and extract parameters of the self-healing region from the image information;

[0100] Step 3-3: Output the parameters of the self-healing area and generate statistical charts.

[0101] The following specific examples further illustrate this application; however, these examples are merely exemplary and do not constitute any limitation on the scope of protection of this application.

[0102] Example 1

[0103] As shown in Figures 1 and 2, the capacitor metallization film is placed between the upper and lower wheels of the driving wheel 12 and the driven wheel 13. The surface light source is placed in the surface light source area 14, and the controller is placed in the controller area 15. A CCD camera is used as the CCD image acquisition unit 2. The image information acquired by the CCD camera is shown in Figure 3. The OpenCV2 library in Python is called, and the image information acquired by the CCD image acquisition unit 2 is converted to grayscale using the cv2.cvtColor function. The grayscale image is shown in Figure 4. The thresh is set to 180 and the maxval is set to 255 to binarize the grayscale image. Then, noise is removed by opening operation. The cv2.findContours function is used to detect the contours in the image, and the cv2.drawContours function is used to draw the contours. Figure 5 shows the edge information of the self-healing points of the capacitor metallization film. Figure 5 intuitively presents the self-healing area of ​​the capacitor metallization film. A for loop function is used to traverse all the self-healing areas, and the length, width, and area of ​​each area are obtained by the cv2.contourArea function. Ten regions were randomly selected from Figure 5, and their length, width, and area parameters are shown in Table 1:

[0104] Figure 6 shows the area distribution of the self-healing region, indicating that the area of ​​the self-healing region ranges from 0 to 400 mm. 2 The success rate reached 20%, with the self-healing area ranging from 400 to 800 mm. 2 The percentage is 30%, and the self-healing area is 900–1200 mm². 2 The percentage was 35%, and the self-healing area was 1200 mm. 2 The above accounts for 30%.

[0105] Figure 7 shows a statistical chart of the self-healing region area, which ranges from 0 to 400 mm. 2 The number of self-healing areas is 4, and the area of ​​the self-healing zone is between 400 and 800 mm. 2 The number of self-healing areas is 6, and the area of ​​the self-healing zone is 900-1200 mm. 2 The number is 7, and the self-healing area is 1200mm. 2 The above number is 3.

[0106] The present application has been described in detail above with reference to preferred embodiments and exemplary examples. However, it should be stated that these specific embodiments are merely illustrative explanations of the present application and do not constitute any limitation on the scope of protection of the present application. Various improvements, equivalent substitutions, or modifications can be made to the technical content and implementation methods of the present application without departing from the spirit and scope of protection of the present application, and all such modifications fall within the scope of protection of the present application. The scope of protection of the present application is determined by the appended claims. Industrial applicability

[0107] This application provides an automatic identification system and method for self-healing regions of metallized film capacitors. The system includes an automatic sample changing unit for placing or automatically replacing the metallized film of the capacitor; a CCD image acquisition unit for capturing image information of the metallized film; and a data processing unit for processing the image information to achieve automatic identification of the self-healing regions of the metallized film. The system acquires information from different locations on the metallized film sample, thereby providing sufficient data for accurate analysis of self-healing region parameters. Its automatic identification and analysis process reduces the influence of human factors and improves the reliability and consistency of the detection.

Claims

1. An automatic identification system for self-healing areas of a metallized film capacitor, the system comprising: Automatic sample changing unit (1), which is used to place or automatically replace the metallized film of capacitors; CCD image acquisition unit (2), which is used to capture image information of capacitor metallization film; The data processing unit (3) is used to process image information to achieve automatic identification of the self-healing area of ​​the capacitor metallization film.

2. The system according to claim 1, wherein the data processing unit (3) is connected to the CCD image acquisition unit (2).

3. The system according to claim 1, wherein the CCD image acquisition unit (2) is located above the automatic sampling unit (1).

4. The system according to claim 1, wherein the automatic sample changing unit comprises: The drive wheel (12) is used to drive the movement and sample changing of the metallized film of the capacitor; Driven wheel (13) assists drive wheel (12) in moving and changing the metallized film of capacitor.

5. The system according to claim 4, wherein the automatic sample changing unit further includes a microcontroller area (11) for fixing a stepper motor drive element, the fixed stepper motor drive element being used for power supply.

6. The system according to claim 4, wherein the automatic sample changing unit further includes a surface light source area (14) for placing a surface light source, the surface light source being used to provide a light source.

7. The system according to claim 4, wherein the automatic sample changing unit further includes a controller area (15) for placing a controller for controlling the operation of the automatic sample changing unit.

8. In the system according to claim 1, the CCD image acquisition unit (2) is preferably a CCD camera.

9. According to the system of claim 1, the data processing unit (3) realizes contour recognition and automatic segmentation of the self-healing region based on mathematical morphology image recognition.

10. A method for automatically identifying self-healing regions of capacitor metallization films using the system according to any one of claims 1 to 9, the method comprising: Step 1: Place or automatically replace the metallization film on the capacitor; Step 2: Capture image information of the capacitor metallization film; Step 3: Process the image information to achieve automatic identification of the self-healing area of ​​the capacitor metallization film.

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