New energy lithium battery positive and negative electrode gap detection system and method

Abstract

The invention belongs to the field of nondestructive testing, and particularly relates to a new energy lithium battery positive and negative electrode gap detection system and method. According to the invention, the length of the gap between the positive electrode and the negative electrode of the battery X-ray image can be detected, and the detection line is drawn and the key position is marked by introducing the battery X-ray image. The system combines an image calibration function, converts a pixel distance into an actual physical distance, automatically identifies the position of the positive electrode by using a peak detection technology, and accurately calculates the length of a gap between the positive electrode and the negative electrode. The method is easy and convenient to operate and high in detection precision, the quality detection efficiency in the battery manufacturing process can be greatly improved, errors and working intensity of manual detection are reduced, and reliable technical support is provided for quality control of battery products.

Description

Technical Field

[0001] The present invention belongs to the field of nondestructive testing, and in particular relates to a positive and negative electrode gap detection system and method for new energy lithium batteries. Background Art

[0002] X-ray imaging and industrial CT technology, as important means of modern non-destructive testing, are widely used in industries such as new energy lithium battery manufacturing to obtain high-precision images of the internal structure of products. X-ray imaging (DR imaging) forms a two-dimensional image on the projection surface by penetrating the object through rays, which can quickly show the overall structure inside the battery and is particularly suitable for discovering penetrating defects. Industrial CT technology reconstructs a three-dimensional image of the battery through X-ray projections at multiple angles, thereby showing more detailed structural information inside. These two technologies provide high-quality basic images for subsequent automated testing and quality analysis, so that key details such as defects inside the battery, material uniformity, and the position of the positive and negative electrodes can be clearly presented, providing a reliable basis for further automated testing and analysis.

[0003] In the production of new energy lithium batteries, the gap between the positive and negative electrodes is an important parameter that affects battery performance. Traditional detection methods mainly rely on manual detection or simple optical measuring equipment. Manual detection usually requires operators to perform visual inspections through X-ray images or microscopes. This method is not only inefficient, but also prone to subjective errors due to fatigue or experience differences. Another common detection method is to evaluate the external dimensions of the battery through physical measurement tools such as probes or measuring calipers, but these methods are difficult to accurately measure internal gaps. Some automated equipment can assist in detection through image processing technology, but its accuracy and stability are still limited by image clarity and algorithm capabilities, and cannot cope with interference caused by complex internal structures or material changes. Therefore, traditional gap detection methods have obvious deficiencies in accuracy, efficiency and consistency, and it is difficult to meet the high quality standards in modern battery manufacturing. Summary of the invention

[0004] In order to solve the related problems in the prior art, the present invention proposes a positive and negative electrode gap detection system and method for new energy lithium batteries with overlapping positive and negative electrodes. The present invention can efficiently and accurately realize the automatic detection of the gap length between the positive and negative electrodes of the battery, provide the inspectors with a convenient operation method and reliable detection data, and thus provide strong support for the comprehensive judgment of internal defects of the battery. Through the present invention, the workload of the inspectors will be significantly reduced, while the efficiency and accuracy of the detection will be greatly improved, further improving the quality control level of battery products.

[0005] In the implementation process, the present invention mainly uses peak detection technology to process the pixel points in the battery X-ray image to accurately detect the position of the positive electrode. Since the battery is arranged with overlapping positive and negative poles, there will be a negative pole between the two positive poles. After the number of positive poles is determined, the number of negative poles is also determined accordingly. At the same time, combined with the image calibration information, the system can accurately calculate the actual length of the gap. The image calibration process includes calibration of the width of the positive and negative poles, as well as calibration of the pixel distance in the image, converting the pixel distance into the actual physical distance. Through this comprehensive method, the system can not only accurately identify the key features in the image, but also efficiently provide accurate measurement of the gap length.

[0006] The technical solution of the present invention is:

[0007] The positive and negative electrode gap detection system of new energy lithium battery includes an image import and preprocessing module, an image calibration module, a geometric annotation and editing module, and an image analysis and gap detection module. The image import and preprocessing module is responsible for importing the X-ray image of the battery from an external file and dynamically adapting to the size of the screen. The image calibration module is responsible for the calibration of pixel distance and the calibration of the positive and negative electrode widths. The geometric annotation and editing module provides image drawing, drawing cleanup, zooming and translation functions. The image analysis and gap detection module processes the pixel values ​​on the detection line drawn by the user, marks the positive electrode on the image through peak detection technology, and calculates the gap length in combination with the calibration data.

[0008] (1) Image import and preprocessing module

[0009] The image import and preprocessing module is responsible for importing X-ray images of batteries from an external file system and making necessary adjustments to ensure that the images can be correctly displayed in the system and are suitable for subsequent analysis. The module first reads the image file, decodes it and converts it into a format that the system can process. The module then performs adaptive proportional scaling of the image, adjusts the image to a size suitable for display, and ensures that the aspect ratio of the image remains unchanged to avoid image distortion. This process not only ensures high-quality display of the image, but also provides a clear view for more accurate subsequent operations. With these functions, the image import and preprocessing module lays a solid foundation for subsequent gap detection and analysis, ensuring the accuracy and availability of image data.

[0010] (2) Image calibration module

[0011] The image calibration module plays a key role in the positive and negative electrode gap detection system of new energy lithium batteries, and is mainly used to improve the accuracy and reliability of detection. The module calibrates the width of the positive and negative electrodes and the pixel distance. In the battery production process, the width of the positive and negative electrodes is a fixed value that has been determined. The true width of the positive and negative electrodes (in millimeters) is manually entered for calibration. In addition, the calibration line segment is drawn, and the true length of the corresponding pixel distance (in millimeters) is entered. The module generates a scaling factor based on this input information for subsequent detection calculations. This process not only ensures the accuracy of the gap length measurement, but also provides a reliable data basis for the system by accurately calibrating the known positive and negative electrode widths, further improving the overall detection efficiency and the credibility of the results.

[0012] (3) Geometry annotation and editing module

[0013] The geometric annotation and editing module is an important part of the positive and negative gap detection system of new energy lithium batteries, providing image annotation and editing functions. This module is responsible for drawing calibration lines, detection lines, and adding and deleting positive pole marking points on the image processed by the image import and preprocessing module. Drawing calibration lines is used for pixel distance calibration; drawing detection lines is used to detect the positive pole position; adding and deleting positive pole marking points is used to fine-tune the position of the positive pole marking points to ensure the accuracy of detection and to respond to the special needs of users more flexibly. In addition, the geometric annotation and editing module can quickly delete unnecessary marking lines and detection points on the lines through the clearing function to keep the image neat. The module also supports proportional scaling of images to ensure the accuracy of annotation information and facilitate more detailed viewing of images. Through these functions, the geometric annotation and editing module provides a flexible operating platform for subsequent image analysis and gap detection, improving the efficiency and accuracy of detection work.

[0014] (4) Image analysis and gap detection module

[0015] The image analysis and gap detection module is the core component of the positive and negative electrode gap detection system of new energy lithium batteries. It is responsible for in-depth analysis of the detection line to realize the automatic measurement of the gap length of the positive and negative electrodes. In the CT image of the battery, the positive electrode usually appears white. This is because the density of the positive electrode material is higher and it can absorb X-rays more strongly, resulting in a highlight area in the image. Relatively speaking, the negative electrode has a lower density and a weaker ability to absorb X-rays, so it appears gray in the image. The background, on the other hand, appears black because there is no substantial material and it hardly absorbs X-rays. This contrasting color difference helps to clearly distinguish the positive and negative electrodes of the battery and their surroundings in the CT image. Since the grayscale value of the positive electrode is higher, the sharp peak that is more obvious in the pixel curve corresponds to the positive electrode. The module first uses peak detection technology to process the pixel values ​​in the detection line and identify significant peaks, so as to accurately locate the position of the positive electrode and mark the key marking points at the positive electrode position on the image. Subsequently, the module combines the scaling factor obtained by calibrating the pixel distance and the input positive and negative electrode width calibration data to accurately calculate the gap length between the positive and negative electrodes. The realization of this series of functions not only improves the accuracy and efficiency of detection, but also provides an important basis for the comprehensive evaluation of internal defects in batteries.

[0016] Beneficial effects of the present invention:

[0017] (1) Improve detection accuracy: By adopting peak detection technology and image calibration, the system can accurately identify the positive electrode position and accurately calculate the gap length, thereby significantly improving the accuracy of the detection results.

[0018] (2) Systematic process: The present invention adopts a clear operation process, including reading the map, calibration, marking, adding and deleting marking points and gap distance calculation, so that the whole detection process is clear and organized.

[0019] (3) Reduce manual burden: The system's automation function greatly reduces the operator's work pressure, reduces subjective errors caused by fatigue or experience differences, and ensures the consistency and reliability of detection. Inspectors can add or delete marking points at any time according to actual needs. This flexibility can further improve the pertinence and effectiveness of detection. After selecting the marking points, the system can quickly calculate the gap distance, reducing the time and error of traditional manual calculations and improving detection efficiency.

[0020] (4) Comprehensive evaluation capability: Through accurate measurement and analysis of gap length, the system provides strong support for the comprehensive evaluation of internal defects in batteries, helping manufacturers better manage and control product quality.

[0021] (5) Easy to operate: The system has a user-friendly interface and a modular design that enables inspectors to easily import, annotate, calibrate, and analyze images, improving the inspectors’ operating experience.

[0022] (6) Wide applicability: The present invention is not only applicable to the new energy lithium battery industry, but can also be extended to other fields that require non-destructive testing and quality assessment, and has good application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of the process of the positive and negative electrode gap detection system of the new energy lithium battery of the present invention;

[0024] Figure 2 It is a schematic diagram of the positive electrode detection process.

[0025] Figure 3 This is the X-ray image of the battery after importing.

[0026] Figure 4 Draw a schematic diagram of the calibration line.

[0027] Figure 5 It is a schematic diagram of the positive electrode detection results. DETAILED DESCRIPTION

[0028] The specific implementation of the present invention is further described below in conjunction with the accompanying drawings and technical solutions.

[0029] The method for detecting gaps between positive and negative electrodes of a new energy lithium battery of the present invention has the following process: Figure 1 As shown, the specific detection steps are as follows:

[0030] Step 1: Read the image, import the X-ray image and pre-process it

[0031] In the new energy lithium battery positive and negative electrode gap detection system, the image import and preprocessing module is responsible for reading and processing the X-ray image of the battery. This step first selects the X-ray image file and loads it into the detection system. The image read by the image import and preprocessing module is displayed in a way that adapts to the screen size to ensure that the image can be viewed easily. The module uses adaptive scaling technology to dynamically adjust the display ratio of the image in the interface according to its actual size, thereby optimizing the inspection experience.

[0032] Step 2: Perform image calibration to determine the true size

[0033] In the positive and negative gap detection system of new energy lithium batteries, the calibration step aims to determine the physical distance corresponding to the pixel distance in the image by inputting the known real size. In this stage, the system interacts with the interface. The geometric annotation and editing module draws the detection line and inputs the length of the pixel distance of the line corresponding to the actual physical world in millimeters. This process involves drawing the calibration line and providing the real length information to calculate the proportional relationship between the pixel and the actual size. By converting the pixel distance in the image to the real distance, the system can achieve high-precision measurement. The calibration process also includes the calibration of the positive and negative electrode widths. The actual widths of the positive and negative electrodes that have been measured in the production process are directly input through the image calibration module in the interactive interface for calibration. The entire calibration process provides a reliable basis for the subsequent gap length calculation, enabling the system to accurately evaluate the gap situation inside the battery.

[0034] Step 3: Draw the test line, adjust the marking point, and complete the positive electrode detection

[0035] The geometry annotation and editing module is used to draw the detection line on the imported X-ray image to measure the gap length. After drawing, the detection system will save the starting and ending coordinates of the line segment and provide the necessary data basis for the subsequent analysis steps.

[0036] like Figure 2 As shown, during the detection process, the image analysis and gap detection module first uses the bilinear interpolation method to extract the pixel points on the detection line drawn by the inspector, and then smoothes the pixel curve through a filter.

[0037] Bilinear interpolation is an algorithm used to estimate intermediate values ​​in two-dimensional space and is often used in image processing. When a given target point is located at non-integer coordinates of four adjacent pixels, bilinear interpolation calculates the pixel value of the target point using the values ​​of these four known points. Its implementation process is divided into two steps:

[0038] (1) Horizontal interpolation: First, in the horizontal direction, use linear interpolation to calculate the pixel values ​​of the left and right positions of the target point in the upper and lower rows where the target point is located. The interpolation formula is:

[0039] R1=(x2-x)·f(x1,y1)+(x-x1)·f(x2,y1)

[0040] R2=(x2-x)·f(x1,y2)+(x-x1)·f(x2,y2)

[0041] Among them, f(x1,y1), f(x2,y1), f(x1,y2), and f(x2,y2) represent the values ​​of four adjacent pixels respectively, and R1 and R2 are the interpolation results of the upper and lower rows.

[0042] (2) Vertical interpolation: Then, in the vertical direction, the same linear interpolation formula is used to calculate the final pixel value of the target point through R1 and R2:

[0043] f(x,y)=(y2-y)·R1+(y-y1)·R2

[0044] Through the above two steps, bilinear interpolation can smoothly estimate the pixel value of the target position.

[0045] Next, the system uses the derivative method to find the peak of the pixel curve and marks the found peak (the position corresponding to the positive pole) with a dot on the image.

[0046] The core idea of ​​the derivative method for finding wave crests is to identify the local maximum (i.e. wave crest) in the curve by calculating the first-order and second-order derivatives. Mathematically, the first-order derivative reflects the change in the slope of the curve. When the first-order derivative changes from positive to negative, it indicates that the curve has passed a local maximum (wave crest). At the same time, the second-order derivative is used to confirm the concavity of the point. When the second-order derivative is negative, the curve is concave downward, further confirming that the point is a wave crest.

[0047] In the implementation process, the first and second order derivatives are first approximated by calculating the difference between adjacent points. Then, in order to eliminate noise, the derivatives are smoothed by applying Gaussian filtering. Finally, the location of the peak is determined by checking the positive and negative changes of the first order derivative and the sign of the second order derivative. In addition, the significance (the difference between the peak height and the baseline) is also used to screen out the truly meaningful peaks.

[0048] The entire process simplifies the testing steps, ensuring that inspectors can efficiently and accurately complete the measurement of the gap length between the positive and negative poles of the battery.

[0049] In addition, in the new energy lithium battery positive and negative electrode gap detection system, the function of adding and deleting marking points allows the inspector to add or delete marking points on the image and adjust the position of the marking points according to the detection requirements. By adjusting the marking points, the accuracy of the positive electrode position marking can be guaranteed. This series of functions improves the visual management of important features by inspectors and enhances the flexibility of the system, making the detection process more efficient and accurate.

[0050] Step 4: Select points and calculate gaps

[0051] In the battery production process, the positive and negative electrodes are arranged alternately. Therefore, in the detection process, it is only necessary to accurately identify the position of the positive electrode and obtain the correspondence between the pixels in the image and the actual physical size through image calibration to calculate the gap length between the positive and negative electrodes. In the image analysis and gap detection module, the inspector can select the line segment he needs for gap calculation by selecting two marked points as the starting point and the end point. After that, the detection system will use the formula Automatically calculate the average spacing between the positive and negative electrodes on the line segment. x is the length of the selected line segment, which is based on the calibration information of the image and converts the pixel distance into the actual physical distance (mm); m and n are the end point and starting point numbers respectively; a and b are the calibrated positive and negative electrode widths (mm) respectively. This interactive point selection method, combined with precise calibration calculation, enables inspectors to quickly and accurately obtain the gap length between the positive and negative electrodes of the battery, thereby providing data support for further quality analysis and judgment.

[0052] The following is an example of a wound battery. The specific steps are as follows:

[0053] Step 1: Read the image, import the battery X-ray image and perform preprocessing. Figure 3 , is the read picture, the black part is the background, the white part is the positive pole, and the gray part is the negative pole.

[0054] Step 2: Perform image calibration to determine the true size. Figure 4 , draw the calibration line segment. Then enter the real physical distance corresponding to the calibration line segment to get the scaling ratio for subsequent calculations; then enter the real width of the positive and negative electrodes to complete all calibrations.

[0055] Step 3: Draw the test line, adjust the marking points, and complete the positive electrode test. Figure 5 , which is the result of automatic detection after drawing the detection line. The points on the detection line are the visualization results of positive electrode detection, and the marked points mark the position of the positive electrode.

[0056] Step 4: Select points and calculate the gap. Take the first and last marked points as the starting and ending points as an example: the actual distance x between the two points is calculated to be 96mm through the scaling factor obtained by the previous calibration, m is the end point number 28, n is the starting point number 1, a is the calibrated positive electrode width 2mm, b is the calibrated negative electrode width 1mm, according to The calculated average gap is 0.556 mm.

Claims

1. New energy lithium battery positive and negative electrode gap detection system, characterized by: The new energy lithium battery positive and negative electrode gap detection system includes an image import and preprocessing module, an image calibration module, a geometric annotation and editing module, and an image analysis and gap detection module; the image import and preprocessing module is responsible for importing the X-ray image of the battery from an external file and dynamically adapting to the size of the screen; the image calibration module is responsible for the calibration of the pixel distance and the calibration of the positive and negative electrode widths; the geometric annotation and editing module provides image drawing, drawing cleaning, zooming and translation functions; the image analysis and gap detection module processes the pixel values ​​on the detection line drawn by the user, marks the positive electrode on the image through the peak detection technology, and calculates the gap length in combination with the calibration data; the specific modules are as follows: (1) Image import and preprocessing module The image import and preprocessing module is responsible for importing the X-ray images of the battery from the external file system and making adjustments to ensure that the images can be correctly displayed in the system and are suitable for subsequent analysis. The module first reads the image file, decodes it and converts it into a format that the system can process. Then, the module performs adaptive proportional scaling of the image to adjust the image to a size suitable for display, ensuring that the aspect ratio of the image remains unchanged to avoid image distortion. (2) Image calibration module The image calibration module calibrates the width of the positive and negative electrodes and the pixel distance. In the battery production process, the width of the positive and negative electrodes is a fixed value that has been determined. The actual width of the positive and negative electrodes is manually input for calibration. Then, the calibration line segment is drawn and the actual length of the corresponding pixel distance is input. A scaling factor is generated based on the input information for subsequent detection calculations. (3) Geometry annotation and editing module The geometric annotation and editing module is responsible for drawing calibration lines, detection lines, and adding and deleting positive pole marking points on the image processed by the image import and preprocessing module; drawing calibration lines is used for pixel distance calibration; drawing detection lines is used for detecting the positive pole position; adding and deleting positive pole marking points is used to fine-tune the position of the positive pole marking points to ensure the accuracy of detection and to more flexibly respond to the special needs of users; in addition, the module can quickly delete unnecessary marking lines and detection points on the lines through the clearing function to keep the image neat; the module also supports proportional scaling of images to ensure the accuracy of annotation information and facilitate more detailed image viewing; (4) Image analysis and gap detection module The image analysis and gap detection module is responsible for in-depth analysis of the detection line to achieve automated measurement of the gap length between the positive and negative electrodes. The module first uses peak detection technology to process the pixel values ​​within the detection line and identify significant peaks, thereby accurately locating the position of the positive electrode and marking key marking points at the positive electrode position on the image. Subsequently, the module combines the scaling factor obtained by calibrating the pixel distance and the input positive and negative electrode width calibration data to accurately calculate the gap length between the positive and negative electrodes.

2. A method for detecting gaps between positive and negative electrodes of a new energy lithium battery, using the detection system described in claim 1, characterized in that: The specific detection steps are as follows: Step 1: Read the image, import the X-ray image and pre-process it First, select the X-ray image file and load it into the detection system; the image read by the image import and preprocessing module will be displayed in a way that adapts to the screen size, using adaptive scaling technology to dynamically adjust the display ratio of the image in the interface according to its actual size; Step 2: Perform image calibration to determine the true size The calibration step aims to determine the physical distance corresponding to the pixel distance in the image by inputting the known real size; through the interface and system interaction, the geometric annotation and editing module draws the detection line and inputs the length of the line pixel distance corresponding to the actual physical world; Draw the calibration line and provide the real length information to calculate the proportional relationship between the pixel and the actual size; by converting the pixel distance in the image into the real distance, the system can achieve high-precision measurement; the calibration process also includes the calibration of the positive and negative electrode widths. The actual widths of the positive and negative electrodes that have been measured in the production process are directly input through the image calibration module in the interactive interface for calibration; Step 3: Draw the test line, adjust the marking point, and complete the positive electrode detection Draw the detection line on the imported X-ray image through the geometry annotation and editing module to measure the gap length; after drawing, the detection system will save the starting and ending coordinates of the line segment; During the inspection process, the image analysis and gap detection module first uses the bilinear interpolation method to extract the pixel points on the inspection line drawn by the inspector, and then smoothes the pixel curve through a filter; then, the system uses the derivative method to find the peak of the pixel curve and marks the position corresponding to the found peak, i.e. the positive pole, with a point on the image; Step 4: Select points and calculate gaps In the battery production process, the positive and negative electrodes are arranged alternately. Therefore, in the detection process, it is only necessary to accurately identify the position of the positive electrode and obtain the correspondence between the pixels in the image and the actual physical size through image calibration to calculate the gap length between the positive and negative electrodes. In the image analysis and gap detection module, the inspector selects the line segment he needs for gap calculation, specifically by selecting two marked points as the starting point and the end point respectively. After that, the detection system uses the formula Automatically calculate the average spacing between the positive and negative electrodes on the line segment, where x is the length of the selected line segment. This distance is based on the calibration information of the image and converts the pixel distance into the actual physical distance. m and n are the end point and starting point numbers respectively; a and b are the calibrated positive and negative electrode widths respectively.

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