Tension adjusting method and system of automatic battery paper pasting machine based on machine vision

Abstract

The invention discloses a tension adjusting method and system for an automatic battery paper pasting machine based on machine vision, and the method comprises the following steps: collecting a battery image in real time through a machine vision system, and analyzing the type, size and appearance characteristics of a battery; analyzing the surface state of the battery through a machine vision system, and judging whether the surface of the battery has stains and scratches or not; transmitting the identified battery type, size and sticker state information to a control system; the control system calculates and outputs adjusting parameters according to the type, the size and the sticker state of the battery; according to the adjusting parameters, the position of a winding shaft of a winding mechanism of the automatic paper pasting machine for the battery is automatically adjusted; the paper pasting effect is monitored in real time through a machine vision system; by combining machine vision and an automatic adjusting technology, accurate control over the pulling force of the automatic paper pasting machine for the battery is achieved, and therefore the technical problems that the pulling force is uneven, paper pasting is poor due to battery surface defects, paper pasting effect monitoring is insufficient, and adaptability to different battery specifications is poor are solved.

Description

Technical Field

[0001] The invention relates to a tension adjustment method and system of an automatic battery sticker machine based on machine vision. Background Art

[0002] In the modern battery production process, the quality of the sticker on the battery surface directly affects the appearance and reliability of the product. As one of the key equipment in the battery production line, the automatic sticker machine has the main function of accurately adhering the sticker to the battery surface. However, the existing automatic sticker technology still faces some technical difficulties in practical application, which affects the stability of the sticker process and the quality of the final product.

[0003] Traditional automatic sticker machines usually rely on fixed parameter settings or manual adjustments to control the tension of stickers. This method has certain instability because factors such as battery type, size, surface condition and sticker material may affect the tension requirement. If the tension control is not precise, it may cause quality problems such as wrinkles, bubbles, looseness or incomplete sticker adhesion. Therefore, how to accurately adjust the tension according to the specific characteristics of the battery to ensure the consistency and high quality of the sticker process has become a difficulty in battery production.

[0004] There may be various defects on the surface of the battery, such as stains, scratches, oil stains, etc. If these defects are not identified in time, the sticker will not adhere properly, or even if it is successfully attached, the sticker effect may be poor due to uneven surface, affecting the appearance and quality of the final product. Traditional automatic sticker machines usually rely on manual inspection or lack real-time surface detection systems in this regard, and cannot effectively identify defects on the battery surface, resulting in defective products during the sticker process.

[0005] During the battery sticker process, the state and quality of the sticker will be affected by many factors, such as temperature, humidity, changes in sticker material, etc. Traditional sticker machines often lack the ability to monitor the state of stickers in real time, so they cannot make timely adjustments when wrinkles, bubbles, or misalignment appear on stickers. Once sticker quality problems occur, they can often only be inspected and reworked after production is completed, which not only increases production costs, but may also cause large batches of defective products to enter the market, reducing the overall quality of the product.

[0006] During the battery production process, the types and sizes of batteries vary greatly, and batteries of different specifications have different requirements for the tension and fitting accuracy of stickers. Traditional automatic sticker machines usually operate based on fixed set values ​​and cannot automatically adjust according to the requirements of different battery specifications. This practice not only reduces production efficiency, but may also lead to inconsistent quality of different types of battery stickers, which cannot meet the requirements of high-precision production. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention provides a tension adjustment method and system for an automatic battery sticker machine based on machine vision. By combining machine vision with automatic adjustment technology, precise control of the tension of the automatic battery sticker machine is achieved, thereby solving technical problems such as uneven tension, poor stickers caused by battery surface defects, insufficient monitoring of sticker effects, and poor adaptability to different battery specifications. The stability and production efficiency of the battery sticker process are improved, and the high consistency and high precision of the battery appearance quality are ensured.

[0008] The technical solution adopted by the present invention to solve its technical problem is:

[0009] A tension adjustment method for a battery automatic sticker machine based on machine vision, comprising the following steps:

[0010] The machine vision system collects battery images in real time, analyzes the type, size and appearance of the battery, and identifies the type and specification of the battery;

[0011] The machine vision system is used to analyze the surface condition of the battery to determine whether there are stains or scratches on the battery surface, and to detect the condition of the sticker, including whether the sticker is correctly pasted and whether there are wrinkles or bubbles.

[0012] Transmit the identified battery type, size, and sticker status information to the control system;

[0013] The control system calculates and outputs adjustment parameters based on the battery type, size and sticker status;

[0014] According to the adjustment parameters, the reel position of the reel mechanism of the battery automatic sticker machine is automatically adjusted to adjust the sticker tension;

[0015] The sticker effect is monitored in real time through the machine vision system. If the sticker is found not to meet the quality standards, the position of the reel is adjusted.

[0016] Preferably, the method of collecting battery images in real time through a machine vision system, analyzing the type, size and appearance characteristics of the battery, and identifying the type and specification of the battery is as follows:

[0017] Use a high-definition industrial camera to photograph the battery and obtain the battery image;

[0018] Use the median filter algorithm to remove noise from the collected battery images;

[0019] Performing contrast enhancement on the acquired battery images;

[0020] The battery image is processed using an edge detection algorithm to extract the edge features of the battery.

[0021] Preferably, the method of analyzing the surface state of the battery by a machine vision system, determining whether there are stains or scratches on the battery surface, and detecting the state of the sticker, including whether the sticker is correctly pasted, and whether there are wrinkles or bubbles, is as follows:

[0022] Use image segmentation algorithms to extract the battery surface area from the background;

[0023] Defect detection of battery surface areas, identifying and marking stains, scratches and other defects by comparing and analyzing the battery surface with preset standard images;

[0024] The state of the sticker on the battery surface is analyzed by morphological processing methods to detect whether there are wrinkles or bubbles;

[0025] Use template matching or feature point matching algorithms to determine whether the sticker is correctly pasted and confirm the consistency of the sticker position with the preset position.

[0026] Preferably, the method of transmitting the identified battery type, size, and sticker status information to the control system is:

[0027] Connecting the recognition result to the control system through a data interface, wherein the data interface is a serial communication interface, an Ethernet interface or a wireless communication interface;

[0028] Format the identified battery type, size and sticker status information to generate a standardized data packet to ensure the correctness and integrity of information transmission;

[0029] The formatted information is transmitted to the control system in real time via the data interface;

[0030] Use data encryption technology during transmission.

[0031] Preferably, the control system calculates and outputs the adjustment parameters according to the type, size and sticker status of the battery:

[0032] Based on the battery type information, a preset regulation model is selected, the regulation model including parameter ranges related to different battery types;

[0033] According to the battery size information, adjust the parameter range in the adjustment model to ensure that the adjustment parameters match the battery size;

[0034] Use sticker status information to modify the adjustment model and optimize the adjustment parameters to compensate for the impact of sticker defects;

[0035] The control system adjusts the key parameters in the battery production or packaging process, including pressure, temperature, bonding force or bonding speed, according to the adjusted model output adjustment parameters;

[0036] The calculated adjustment parameters are fed back to the control system.

[0037] As a preferred method, according to the adjustment parameters, the reeling shaft position of the reeling mechanism of the battery automatic sticker machine is automatically adjusted to adjust the sticker tension as follows:

[0038] The control system generates a corresponding reel position control signal based on the calculated adjustment parameters, and there is a preset relationship between the control signal and the sticker tension;

[0039] After receiving the control signal, the reeling mechanism drives the reeling shaft to adjust its position, and changes the position of the reeling shaft to change the tension of the sticker;

[0040] According to the size of the battery and the state of the sticker, the position of the reel is adjusted in real time to ensure that the tension of the sticker on the battery surface remains within the optimized range;

[0041] A sensor is set in the feedback control system of the sticker machine to monitor the tension state of the sticker, compare the actual tension with the target tension, and further adjust the position of the reel to accurately control the tension;

[0042] The control system continuously monitors changes in battery type, size and sticker status, automatically updates adjustment parameters and adjusts the reel position through control signals to ensure that the tension during each sticker application always meets the set standards.

[0043] As a preferred method, the sticker effect is monitored in real time by a machine vision system. If it is found that the sticker does not meet the quality standards, the method for adjusting the position of the reel is as follows:

[0044] The machine vision system acquires the battery surface image in real time, performs quality inspection on the sticker effect, and identifies defects on the sticker surface, such as wrinkles, bubbles, and deviations;

[0045] Compare and analyze sticker defects detected in real time with preset quality standards to determine whether the stickers meet quality requirements;

[0046] If it is detected that the sticker does not meet the quality standards, the control system immediately generates an adjustment signal to instruct the reel shaft position of the reeling mechanism to be adjusted;

[0047] The control system adjusts the reel position or the tension setting of the sticker according to the type and severity of the sticker defect;

[0048] The adjustment process is optimized through closed-loop feedback control, and after each adjustment, the sticker effect is verified again through the machine vision system;

[0049] After the sticker quality reaches the standard, the system returns to normal operation and continues to sticker the next batch of batteries.

[0050] Another technical problem to be solved by the present invention is to provide a tension adjustment system for a battery automatic sticker machine based on machine vision, comprising:

[0051] A machine vision system is used to collect battery images in real time and analyze the type, size, appearance characteristics and surface condition of the battery through image processing;

[0052] The machine vision system can identify the type and specification of the battery, determine whether there are stains or scratches on the battery surface, and detect the status of the sticker, including whether the sticker is correctly pasted and whether there are wrinkles or bubbles;

[0053] A control system connected to the machine vision system, configured to receive information about battery type, size, and sticker status, and calculate and output adjustment parameters based on the information;

[0054] A reeling mechanism, used to automatically adjust the position of the reeling shaft according to the adjustment parameters, thereby adjusting the tension of the sticker;

[0055] The real-time monitoring module works in conjunction with the machine vision system to monitor the sticker effect in real time and adjust the position of the reel when it is detected that the sticker does not meet the quality standards.

[0056] Another technical problem to be solved by the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, a tension adjustment method for an automatic battery sticker machine based on machine vision as described above is implemented.

[0057] Another technical problem to be solved by the present invention is to provide a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the tension adjustment method of the automatic battery sticker machine based on machine vision as described in any of the above is implemented.

[0058] The beneficial effects of the present invention are:

[0059] By collecting and analyzing the image data of the battery in real time, the pulling force of the sticker machine is automatically adjusted so that the pulling force of the sticker is always consistent with the specifications and surface characteristics of the battery, thus avoiding the inconsistency caused by manual settings; the machine vision system analyzes the surface status of the battery in real time, which can effectively detect defects on the battery surface and make corresponding adjustments to ensure the quality of the sticker.

[0060] By continuously monitoring the sticker effect through the machine vision system, it is possible to detect in real time that the sticker does not meet the quality standards (such as wrinkles, bubbles, misalignment, etc.), and adjust the position of the reel in time to ensure that the sticker quality always meets the requirements; by using the machine vision system to automatically identify the type, size and specification of the battery, and transmit it to the control system, it automatically calculates and adjusts the tension according to different battery requirements, which can greatly improve adaptability and ensure the stability of sticker quality for different batteries. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a flow chart of a tension adjustment method of an automatic battery sticker machine based on machine vision of the present invention;

[0062] Figure 2 It is a structural schematic diagram of a tension adjustment system of an automatic battery sticker machine based on machine vision of the present invention. Specific implementation methods

[0064] The principles and features of the present invention are described below, and the examples are only used to explain the present invention and are not used to limit the scope of the present invention. The present invention is described more specifically by way of example in the following paragraphs. According to the following description and claims, the advantages and features of the present invention will become clearer.

[0065] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items. Example

[0066] See also Figure 1 As shown, a tension adjustment method of a battery automatic sticker machine based on machine vision includes the following steps:

[0067] The machine vision system collects battery images in real time, analyzes the type, size and appearance of the battery, and identifies the type and specification of the battery;

[0068] The machine vision system is used to analyze the surface condition of the battery to determine whether there are stains or scratches on the battery surface, and to detect the condition of the sticker, including whether the sticker is correctly pasted and whether there are wrinkles or bubbles.

[0069] Transmit the identified battery type, size, and sticker status information to the control system;

[0070] The control system calculates and outputs adjustment parameters based on the battery type, size and sticker status;

[0071] According to the adjustment parameters, the reel position of the reel mechanism of the battery automatic sticker machine is automatically adjusted to adjust the sticker tension;

[0072] The sticker effect is monitored in real time through the machine vision system. If the sticker is found not to meet the quality standards, the position of the reel is adjusted.

[0073] By analyzing the type, size, appearance characteristics and surface condition of the battery in real time, the machine vision system can accurately determine the specific characteristics of the battery and the quality of the sticker. By automatically adjusting the position of the reel, the tension control is more precise, ensuring that the sticker is uniform, wrinkle-free and bubble-free, significantly improving the quality and consistency of the battery sticker; this solution uses machine vision to collect and analyze the type and size of the battery in real time, and can support batteries of various specifications and types. In the traditional manual adjustment process, batteries of different specifications require human intervention, while the automatic identification and control system based on machine vision can automatically adjust the tension according to the specific situation of the battery, avoiding errors and inconsistencies caused by manual operation, thereby improving production efficiency and flexibility.

[0074] This method combines real-time image recognition with a feedback control mechanism to monitor the sticker effect in real time. If the sticker has problems such as wrinkles, bubbles or deviations, the system will automatically adjust the position of the reel to avoid the production of defective products and reduce rework and scrap rates. This function greatly improves the automation level of the production line, reduces human intervention, and improves production efficiency; through machine vision and automated control systems, it reduces dependence on manual operations. Traditional methods usually require manual surface inspection of the battery or manual adjustment of machine parameters when problems arise. The automated system can self-adjust and optimize, greatly reducing errors caused by human factors and further ensuring product quality.

[0075] This solution makes the production process more intelligent, combining technologies such as image processing, machine learning, and feedback control to enhance the adaptive ability of the production line. The machine vision system can not only detect the status of batteries and stickers in real time, but also automatically adjust equipment parameters according to the characteristics of different batteries and the quality of stickers, making the entire production process more accurate and flexible, in line with the development trend of modern intelligent manufacturing; by accurately controlling the tension of stickers, it can ensure that the tension in each sticker process reaches the optimal state, thereby avoiding the waste of sticker materials (such as uneven stickers, tearing, etc.). At the same time, the number of unqualified products is reduced, the cost of rework and scrap is reduced, and the production cost is further optimized.

[0076] Through the precise monitoring of each battery by the machine vision system, combined with the automatic adjustment of the tension, the sticker effect can always be kept highly consistent during the production process. This is especially critical for products with high requirements for battery appearance quality and important brand image. The appearance quality and reliability of the final product will be greatly improved; improving the appearance quality, production efficiency and consistency of battery products will help improve the market competitiveness of products. Higher quality sticker effects mean better user experience, and the reliability and aesthetics of the product can better meet consumer and industry standards, increase market recognition and customer satisfaction.

[0077] The method of collecting battery images in real time through the machine vision system, analyzing the type, size and appearance characteristics of the battery, and identifying the type and specification of the battery is as follows:

[0078] Use a high-definition industrial camera to photograph the battery and obtain the battery image;

[0079] Use the median filter algorithm to remove noise from the collected battery images;

[0080] Performing contrast enhancement on the acquired battery images;

[0081] The battery image is processed using an edge detection algorithm to extract the edge features of the battery.

[0082] High-definition industrial cameras can provide high-resolution images to ensure clear capture of battery details, especially for complex battery appearance features such as printing, labels, scratches, etc.; the median filtering algorithm can effectively remove noise in the image (such as image blur or interference caused by environmental factors) to ensure more accurate subsequent processing; the edge detection algorithm can extract battery contours and features, help identify key information such as the shape and size of the battery, and provide high-precision size and type discrimination.

[0083] By using contrast enhancement during image acquisition, the details of the battery surface (such as battery edges, logos, dimensions, etc.) can be displayed more clearly, providing clearer features for subsequent algorithm processing, allowing the machine vision system to identify battery types and specifications more quickly and accurately; since the battery image is subjected to noise removal, contrast enhancement and edge extraction processing, the system can maintain good recognition effects even in the case of lighting changes, background interference or stains on the battery surface, thereby improving the adaptability and robustness of the system.

[0084] The entire image processing process is automated, avoiding errors and inconsistencies caused by manual operations, ensuring the accuracy of each inspection, reducing the impact of human factors on battery identification results, and improving the automation level of the production line. By acquiring and processing images in real time through machine vision, the type and size information of the battery can be instantly fed back, making it easier for subsequent control systems to make adjustments based on the identification results, such as automatically selecting suitable stickers, adjusting production parameters, etc., to improve production efficiency.

[0085] Use a high-definition industrial camera or camera array to photograph the battery. The camera resolution needs to be high enough to ensure that the detailed information of the battery, such as size, printed logo, defects, etc., can be captured; arrange appropriate lighting conditions to ensure that the battery surface is evenly illuminated to avoid shadows or light spots affecting the image quality. Ring light sources or background light sources can be used to improve the clarity of the image.

[0086] Apply the median filter algorithm to the collected original image. Median filtering is a common image smoothing technique that effectively removes salt and pepper noise in the image by replacing the value of each pixel with the median of its neighboring pixels. This step is particularly important for images with poor clarity, as it can effectively reduce the impact of external interference (such as dust, stains, etc.) on subsequent processing.

[0087] Use contrast enhancement techniques (such as histogram equalization, stretching transformation, etc.) to improve the visibility of areas of interest in battery images (such as battery edges, text, logos, etc.). This will help subsequent edge detection algorithms more easily identify the shape and size of the battery; by enhancing the image contrast, the edges and key features of the battery will be more obvious, especially in the case of uneven lighting, enhancing the contrast can effectively improve the details of the image.

[0088] Apply edge detection algorithms (such as Canny edge detection, Sobel operator, etc.), which can detect edge features in the image, especially the outline and boundary of the battery; through edge detection, the outline information of the battery can be accurately extracted to provide a basis for subsequent size calculation and battery type identification; edge information can also help determine the shape of the battery (such as round, rectangular, etc.), thereby assisting in the classification of battery types.

[0089] After extracting edge information, the battery type is identified through image matching, template matching or machine learning algorithms (such as convolutional neural network CNN). Based on the size, appearance, edge features and other information of the battery, the system can automatically classify different types of batteries; based on the size, shape and edge features of the battery, combined with the pre-set specification library, the machine vision system can determine the specifications and type of the battery, and thus sort the battery into the corresponding production process or packaging process.

[0090] Once the battery type, specifications and appearance characteristics are identified, the relevant information will be transmitted to the control system or quality monitoring system of the production line through industrial communication protocols (such as Ethernet / IP, Modbus, etc.); the control system can adjust the production process or parameters of the automation equipment (such as adjusting the tension or production speed of the sticker machine) based on this information to ensure the efficient operation of the production line.

[0091] The method of analyzing the battery surface condition through the machine vision system to determine whether there are stains and scratches on the battery surface, and to detect the status of the sticker, including whether the sticker is correctly pasted, whether there are wrinkles or bubbles, is as follows:

[0092] Use image segmentation algorithms to extract the battery surface area from the background;

[0093] Defect detection of battery surface areas, identifying and marking stains, scratches and other defects by comparing and analyzing the battery surface with preset standard images;

[0094] The state of the sticker on the battery surface is analyzed by morphological processing methods to detect whether there are wrinkles or bubbles;

[0095] Use template matching or feature point matching algorithms to determine whether the sticker is correctly pasted and confirm the consistency of the sticker position with the preset position.

[0096] Through automated processing, the machine vision system can quickly and accurately detect defects on the battery surface and the status of stickers, avoiding errors and work fatigue caused by manual inspection. Through image segmentation, defect detection and feature matching, it can accurately identify tiny defects such as stains and scratches, as well as wrinkles and bubbles on stickers, ensuring the high quality of battery products.

[0097] The machine vision system follows the same standards and algorithms in each inspection to ensure the uniformity and consistency of quality control and reduce the deviation of human judgment; by real-time monitoring of the battery surface status, the system can provide feedback as soon as defects occur, adjust the production process or product processing in time, and prevent defective products from flowing into subsequent links.

[0098] Reduce the need for manual quality inspection, reduce labor costs, and reduce the error rate of manual operation; the system can process a large number of battery images in a short time, provide fast feedback, improve production efficiency, and avoid unnecessary delays in the production process.

[0099] Through the standardized testing process, we ensure that the surface quality of all produced batteries meets the specified requirements, ensure product consistency and enhance brand reputation; the system can automatically record the test data of each battery, which is convenient for subsequent quality tracking and problem analysis. If a battery defect is found, it can be traced back to a specific production batch, which is convenient for quality management and improvement.

[0100] Use a high-definition industrial camera to capture images of the battery surface to ensure that sufficient details are captured. The position and angle of the camera should be optimized to ensure complete visualization of the battery surface area; to avoid the impact of lighting changes on image quality, a ring light source or evenly distributed backlighting can be used to ensure that the battery surface is evenly illuminated to reduce shadows and reflections.

[0101] Use image segmentation algorithms (such as thresholding, K-means clustering, semantic segmentation based on deep learning, etc.) to extract the battery surface area from the original image. The battery area can be segmented by color, texture or shape features to distinguish it from the background; the accuracy of segmentation is crucial to ensure that only the battery surface area is extracted to avoid background interference.

[0102] The extracted battery surface area is compared with a preset standard image (which can be a defect-free battery image), and a difference detection algorithm (such as image difference, structural similarity index (SSIM), etc.) is used to identify stains, scratches, dents and other defects on the battery surface. During the comparative analysis process, different algorithms are needed to identify different types of defects. For example, stains and scratches may have different texture or color features, so specific image processing algorithms (such as edge detection, texture analysis, etc.) can be used to identify them separately.

[0103] The battery surface is processed by morphological operations (such as dilation, corrosion, opening operation, closing operation, etc.) to highlight and analyze the surface structure. These operations are very effective in detecting irregular shapes such as wrinkles, bubbles, folds, etc. on stickers; wrinkles or bubbles on stickers can be judged by detecting the morphological changes in local areas. Morphological operations can effectively highlight these defective areas and facilitate further analysis.

[0104] Use template matching or feature point matching algorithms (such as SIFT, ORB, SURF, etc.) to detect whether the sticker is correctly pasted. Template matching will compare with the preset standard sticker pattern to check whether the position, size and rotation angle of the sticker on the battery meet the requirements; if the sticker pasting position or angle deviates, the system will automatically mark it as unqualified and provide timely feedback to the production line.

[0105] The system will mark the detected defects and generate a report. These marks can be visual, such as marking the location of the defect in the image, or generating a text report listing the type and location of the defect; the defect information will be transmitted to the production line control system through a data interface (such as PLC, MES, etc.), automatically adjusting production parameters or performing rework operations. For example, if bubbles are found in the sticker, the system can trigger an automatic correction program or manual intervention.

[0106] The system can record the test results of each battery, including the defect type, location, and whether it passed the test. These data can be stored in the database for subsequent query, analysis, or traceability; if unqualified batteries are detected, the system can automatically mark and prevent them from continuing to enter the production process to prevent defective products from entering the market.

[0107] The method of transmitting the identified battery type, size, and sticker status information to the control system is as follows:

[0108] Connecting the recognition result to the control system through a data interface, wherein the data interface is a serial communication interface, an Ethernet interface or a wireless communication interface;

[0109] Format the identified battery type, size and sticker status information to generate a standardized data packet to ensure the correctness and integrity of information transmission;

[0110] The formatted information is transmitted to the control system in real time via the data interface;

[0111] Use data encryption technology during transmission.

[0112] By transmitting the recognition results to the control system in real time, it is possible to immediately respond to the needs of the production line or adjust the production process to ensure the continuity and efficiency of production; the system can automatically adjust the equipment settings based on the transmitted data, avoid manual intervention, reduce errors, and improve the automation level of the production line.

[0113] Through formatting, the data is packaged into standardized data packets to ensure the integrity and correctness of the data. This can avoid the problem of inconsistent data formats between different devices or systems; by using different types of data interfaces (serial communication, Ethernet interface, wireless interface), the solution can adapt to a variety of different control systems and production environments, improving the flexibility and scalability of the system.

[0114] Data encryption technology is used to protect the transmitted data, ensuring that it is not tampered with or leaked during transmission, thereby improving the security and reliability of data transmission. This is especially important for applications in industrial automation systems that require high data security; formatted data packets can use technologies such as checksums to ensure the correctness of data transmission and avoid data loss or damage.

[0115] All battery information is centrally transmitted to the control system, which facilitates the monitoring and management of the production process. The control system can view the status data of each battery in real time, so as to make more accurate judgments and decisions; through the collected data, the control system can perform historical data analysis, trend prediction and fault diagnosis, and further optimize the production process and quality control.

[0116] The control system can automatically adjust the parameters on the production line based on the real-time transmitted battery information, such as adjusting the sticker pasting position, sticker material, or production speed, to ensure that each battery meets the quality standards; through automated data transmission and processing, it reduces manual intervention, avoids omissions and errors in manual inspections, and improves the stability and consistency of the production line.

[0117] In the battery surface recognition system, the machine vision system will collect information such as battery type, size, sticker status, etc. Usually, the vision system will convert this information into a digital format for subsequent processing; the recognition results (such as battery type, size, sticker status) will be formatted through a specific algorithm. Data formatting can use common data exchange formats (such as JSON, XML, CSV, etc.) to organize this information into standardized data packets to ensure consistency of data structure and ease of parsing.

[0118] A packet can contain the following fields:

[0119] Battery ID

[0120] Battery Type

[0121] Battery size (such as length, width, height)

[0122] The sticker condition (such as whether it is pasted correctly, whether there are bubbles or wrinkles, etc.)

[0123] Test results (e.g. qualified or not, defect location, etc.)

[0124] Select the appropriate data interface according to the requirements of the control system:

[0125] Serial communication interfaces (such as RS-232 and RS-485) are suitable for some traditional industrial equipment. They have a short communication distance but stable transmission. Ethernet interfaces (such as TCP / IP) are suitable for systems that require high bandwidth, long-distance transmission, and connection with multiple devices. They can provide higher transmission speed and flexibility. Wireless communication interfaces (such as Wi-Fi, Bluetooth, Zigbee, etc.) are suitable for flexible wiring occasions and are particularly suitable for applications in modern smart factories or mobile devices. Interface protocol design: Select one or more suitable communication protocols (such as Modbus, MQTT, RESTful API, etc.) to ensure that data exchange between devices complies with standards and that information transmission can be carried out smoothly.

[0126] To ensure the security of data during transmission, encryption technology is used to encrypt data, including:

[0127] SSL / TLS protocol: used to encrypt communications when transmitting data over the network.

[0128] Symmetric encryption algorithm (such as AES): used to encrypt and decrypt transmitted data packets to ensure the privacy of information.

[0129] Hash verification: A hash algorithm (such as SHA-256) is used to generate a unique identifier for data to ensure the integrity of data transmission and prevent data from being tampered with during transmission.

[0130] Authentication: Establish an authentication mechanism between the control system and the visual system to ensure that only authorized devices and systems can transmit and receive data, avoiding unauthorized data access.

[0131] Transport layer security: VPN (virtual private network) or dedicated network is used during the actual transmission process to ensure the security of the data transmission path.

[0132] After the information is formatted and encrypted, the data stream is transmitted to the control system in real time through the selected data interface. This can be transmitted using a communication protocol stack, which is responsible for handling the packaging, sending, receiving and unpacking of data packets; the control system receives and processes the data stream in real time, updates the parameters on the production line in real time, and promptly detects potential production problems. For different types of batteries, the control system can make corresponding adjustments (such as adjusting the sticker position or battery size); the data received by the control system can be stored in a database for subsequent query and analysis. Each battery in the production process will correspond to a unique record for traceability, reporting and quality management; based on the real-time transmitted data, the control system can make automatic adjustments according to preset parameters and standards. For example, when the system detects an abnormality in a certain type of battery size or sticker status, it can trigger an alarm or automatically adjust the production equipment (such as correcting the sticker position or changing the sticker material).

[0133] The control system calculates and outputs the adjustment parameters according to the type, size and sticker status of the battery:

[0134] Based on the battery type information, a preset regulation model is selected, the regulation model including parameter ranges related to different battery types;

[0135] According to the battery size information, adjust the parameter range in the adjustment model to ensure that the adjustment parameters match the battery size;

[0136] Use sticker status information to modify the adjustment model and optimize the adjustment parameters to compensate for the impact of sticker defects;

[0137] The control system adjusts the key parameters in the battery production or packaging process, including pressure, temperature, bonding force or bonding speed, according to the adjusted model output adjustment parameters;

[0138] The calculated adjustment parameters are fed back to the control system.

[0139] By automatically adjusting key parameters in the production or packaging process (such as pressure, temperature, bonding force, bonding speed) according to the battery type, size and sticker status, manual intervention and human errors can be reduced; parameters are dynamically adjusted according to the specific information of each battery to ensure that the requirements of each battery in the production process are met, thereby avoiding excessive or insufficient adjustments and improving production accuracy.

[0140] The sticker status information is used to correct the adjustment model and compensate for the impact of sticker defects. This is crucial for dealing with incomplete stickers, bubbles, wrinkles or poor positions, and can ensure high-quality sticker bonding and avoid battery appearance or functional problems caused by sticker defects; dynamically adjust the parameters in the adjustment model based on the battery size information to ensure that each battery of different sizes obtains the appropriate production parameters, thereby optimizing the production process, ensuring that the final battery product meets the specification requirements, and improving the overall quality.

[0141] By accurately calculating the adjustment parameters and providing real-time feedback to the control system, defective products caused by improper parameter settings can be effectively avoided, thereby reducing the scrap rate and reducing waste in the production process; automatic adjustment of parameters makes the production process more flexible and can quickly adapt to the needs of different battery types and sizes, avoiding time loss from repeated debugging and improving production efficiency.

[0142] The solution supports fast switching of different battery types. The production line can select the appropriate adjustment model according to the battery type, thereby ensuring that each type of battery is properly adjusted during the production process to meet different production needs. Through real-time feedback and correction of adjustment parameters, the solution can flexibly respond to changes that may occur during the production process (such as equipment status, production speed, etc.), thereby improving the robustness and adaptability of the production system.

[0143] According to the adjustment parameters, the method of automatically adjusting the reel position of the reel mechanism of the battery automatic sticker machine to adjust the sticker tension is as follows:

[0144] The control system generates a corresponding reel position control signal based on the calculated adjustment parameters, and there is a preset relationship between the control signal and the sticker tension;

[0145] After receiving the control signal, the reeling mechanism drives the reeling shaft to adjust its position, and changes the position of the reeling shaft to change the tension of the sticker;

[0146] According to the size of the battery and the state of the sticker, the position of the reel is adjusted in real time to ensure that the tension of the sticker on the battery surface remains within the optimized range;

[0147] A sensor is set in the feedback control system of the sticker machine to monitor the tension state of the sticker, compare the actual tension with the target tension, and further adjust the position of the reel to accurately control the tension;

[0148] The control system continuously monitors changes in battery type, size and sticker status, automatically updates adjustment parameters and adjusts the reel position through control signals to ensure that the tension during each sticker application always meets the set standards.

[0149] By automatically adjusting the position of the reel, the tension of the sticker can be accurately controlled so that the sticker can be evenly attached to the battery surface. Reasonable tension can avoid problems such as bubbles, wrinkles, and position deviations on the sticker, thereby improving the appearance and quality of the battery; ensuring that the tension of the sticker on the battery surface remains within the optimal range, avoiding the situation where the sticker is too tight or too loose, further improving the quality of the sticker and enhancing the overall performance and reliability of the battery.

[0150] This method automatically adjusts the position of the reel based on adjustment parameters without frequent human intervention. It can be dynamically adjusted according to the battery size and sticker status, thereby improving the automation level of the production line and reducing the workload and errors of manual operation. The system can monitor and feedback information such as battery size and sticker status in real time, and automatically update the adjustment parameters and adjust the reel position based on this information, so that each sticker process can automatically adapt to the needs of different batteries and avoid human setting errors or omissions.

[0151] By installing sensors to monitor the tension of the sticker and comparing the actual tension with the target tension, any deviation can be discovered in time and corrected by adjusting the position of the reel. This real-time feedback mechanism effectively avoids excessive or insufficient tension, and reduces equipment failure or defective products caused by abnormal sticker tension; by continuously adjusting and monitoring the tension of the sticker, it ensures that the sticker process of each battery meets the requirements, thereby reducing the rate of defective products and improving the product qualification rate.

[0152] The sticker effect is monitored in real time by the machine vision system. If the sticker does not meet the quality standards, the method for adjusting the reel position is as follows:

[0153] The machine vision system acquires the battery surface image in real time, performs quality inspection on the sticker effect, and identifies defects on the sticker surface, such as wrinkles, bubbles, and deviations;

[0154] Compare and analyze sticker defects detected in real time with preset quality standards to determine whether the stickers meet quality requirements;

[0155] If it is detected that the sticker does not meet the quality standards, the control system immediately generates an adjustment signal to instruct the reel shaft position of the reeling mechanism to be adjusted;

[0156] The control system adjusts the reel position or the tension setting of the sticker according to the type and severity of the sticker defect;

[0157] The adjustment process is optimized through closed-loop feedback control, and after each adjustment, the sticker effect is verified again through the machine vision system;

[0158] After the sticker quality reaches the standard, the system returns to normal operation and continues to sticker the next batch of batteries.

[0159] The machine vision system can detect the quality of stickers in real time during each batch of stickers, and find defects such as wrinkles, bubbles, and misalignment. The system responds promptly and adjusts the position of the reel to ensure that the stickers always meet the quality standards and avoid quality fluctuations or unqualified products; through the closed-loop feedback control mechanism, after detecting defects, the system automatically adjusts the reel position or tension setting. After each adjustment, the system verifies again through machine vision to ensure that the quality meets the standards. This automated quality control greatly improves the quality consistency of the product.

[0160] The system reduces the need for manual inspection and manual adjustment of the reel position through automatic detection and adjustment, and reduces the probability of human error. Manual operation may cause quality fluctuations due to fatigue, lack of experience or improper operation, while the automated system can maintain stability continuously and accurately; through automatic detection and adjustment, workers do not need to frequently intervene in the production process, reducing the impact of fatigue and human negligence on product quality.

[0161] When it is detected that the sticker does not meet the standards, the system will respond immediately and adjust the reel position. This instant adjustment can avoid production stagnation or the influx of substandard products, and maximize production efficiency; after each adjustment, the machine vision system will verify again to ensure that the sticker quality of each battery meets the standards, avoiding delays in production time due to negligence in manual inspection.

[0162] See also Figure 2 As shown, a tension adjustment system of a battery automatic sticker machine based on machine vision includes:

[0163] A machine vision system 1, used to collect battery images in real time and analyze the type, size, appearance characteristics and surface condition of the battery through image processing;

[0164] The machine vision system can identify the type and specification of the battery, determine whether there are stains or scratches on the battery surface, and detect the status of the sticker, including whether the sticker is correctly pasted and whether there are wrinkles or bubbles;

[0165] A control system 2, connected to the machine vision system, for receiving information about battery type, size and sticker status, and calculating and outputting adjustment parameters based on the information;

[0166] The reeling mechanism 3 is used to automatically adjust the position of the reeling shaft according to the adjustment parameters, thereby adjusting the tension of the sticker;

[0167] The real-time monitoring module 4 works in conjunction with the machine vision system to monitor the sticker effect in real time and adjust the position of the reel when it is detected that the sticker does not meet the quality standards.

[0168] The machine vision system 1 can collect battery images in real time and detect the status of the sticker, including whether there are defects such as wrinkles, bubbles or deviations. When a sticker that does not meet the quality standards is detected, the control system will automatically adjust the position of the reel and the tension of the sticker based on this information to ensure that the sticker on each battery meets the requirements. This can significantly improve the stability and consistency of the sticker quality and reduce the production of defective products.

[0169] Through the automated collaboration of machine vision and control systems, the system can intelligently calculate and adjust adjustment parameters based on the size, type and surface condition of the battery. This reduces reliance on manual operation and reduces the probability of manual operation errors. Production line workers do not need to intervene frequently, and the system can automatically monitor and adjust the quality of stickers, thereby improving production efficiency and accuracy.

[0170] When the system detects that the sticker does not meet the quality standards, it can quickly adjust the reel position and sticker tension to avoid downtime, waste or rework caused by sticker quality problems. Through this closed-loop control mechanism, the system can optimize the production process in real time, reduce material waste and production downtime, thereby improving overall production efficiency, reducing defective product rates, and ultimately reducing production costs.

[0171] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the tension adjustment method of the automatic battery sticker machine based on machine vision as described above is implemented.

[0172] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the tension adjustment method of the automatic battery sticker machine based on machine vision as described above is implemented.

[0173] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0174] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0175] The above embodiments of the present invention are not intended to limit the protection scope of the present invention, and the implementation modes of the present invention are not limited thereto. All other modifications, replacements or changes made to the above structures of the present invention based on the above contents of the present invention, in accordance with common technical knowledge and customary means in the art, without departing from the above basic technical ideas of the present invention, should fall within the protection scope of the present invention.

Claims

1. A tension adjustment method for a battery automatic sticker machine based on machine vision, characterized in that: The following steps are involved: The machine vision system collects battery images in real time, analyzes the type, size and appearance of the battery, and identifies the type and specification of the battery; The machine vision system is used to analyze the surface condition of the battery to determine whether there are stains or scratches on the battery surface, and to detect the condition of the sticker, including whether the sticker is correctly pasted and whether there are wrinkles or bubbles. Transmit the identified battery type, size, and sticker status information to the control system; The control system calculates and outputs adjustment parameters based on the battery type, size and sticker status; According to the adjustment parameters, the reel position of the reel mechanism of the battery automatic sticker machine is automatically adjusted to adjust the sticker tension; The sticker effect is monitored in real time through the machine vision system. If the sticker is found not to meet the quality standards, the position of the reel is adjusted.

2. The tension adjustment method of the automatic battery sticker machine based on machine vision according to claim 1 is characterized in that: The method of collecting battery images in real time through the machine vision system, analyzing the type, size and appearance characteristics of the battery, and identifying the type and specification of the battery is as follows: Use a high-definition industrial camera to photograph the battery and obtain the battery image; Use the median filter algorithm to remove noise from the collected battery images; Performing contrast enhancement on the acquired battery images; The battery image is processed using an edge detection algorithm to extract the edge features of the battery.

3. The tension adjustment method of the automatic battery sticker machine based on machine vision according to claim 1 is characterized in that: The method of analyzing the battery surface condition through the machine vision system to determine whether there are stains and scratches on the battery surface, and to detect the status of the sticker, including whether the sticker is correctly pasted, whether there are wrinkles or bubbles, is as follows: Use image segmentation algorithms to extract the battery surface area from the background; Defect detection of battery surface areas, identifying and marking stains, scratches and other defects by comparing and analyzing the battery surface with preset standard images; The state of the sticker on the battery surface is analyzed by morphological processing methods to detect whether there are wrinkles or bubbles; Use template matching or feature point matching algorithms to determine whether the sticker is correctly pasted and confirm the consistency of the sticker position with the preset position.

4. The tension adjustment method of the automatic battery sticker machine based on machine vision according to claim 1 is characterized in that: The method of transmitting the identified battery type, size, and sticker status information to the control system is as follows: Connecting the recognition result to the control system through a data interface, wherein the data interface is a serial communication interface, an Ethernet interface or a wireless communication interface; Format the identified battery type, size and sticker status information to generate a standardized data packet to ensure the correctness and integrity of information transmission; The formatted information is transmitted to the control system in real time via the data interface; Use data encryption technology during transmission.

5. The tension adjustment method of the automatic battery sticker machine based on machine vision according to claim 1 is characterized in that: The control system calculates and outputs the adjustment parameters according to the type, size and sticker status of the battery: Based on the battery type information, a preset regulation model is selected, the regulation model including parameter ranges related to different battery types; According to the battery size information, adjust the parameter range in the adjustment model to ensure that the adjustment parameters match the battery size; Use sticker status information to modify the adjustment model and optimize the adjustment parameters to compensate for the impact of sticker defects; The control system adjusts the key parameters in the battery production or packaging process, including pressure, temperature, bonding force or bonding speed, according to the adjusted model output adjustment parameters; The calculated adjustment parameters are fed back to the control system.

6. The tension adjustment method of the automatic battery sticker machine based on machine vision according to claim 1 is characterized in that: According to the adjustment parameters, the method of automatically adjusting the reel position of the reel mechanism of the battery automatic sticker machine to adjust the sticker tension is as follows: The control system generates a corresponding reel position control signal based on the calculated adjustment parameters, and there is a preset relationship between the control signal and the sticker tension; After receiving the control signal, the reeling mechanism drives the reeling shaft to adjust its position, and changes the position of the reeling shaft to change the tension of the sticker; According to the size of the battery and the state of the sticker, the position of the reel is adjusted in real time to ensure that the tension of the sticker on the battery surface remains within the optimized range; A sensor is set in the feedback control system of the sticker machine to monitor the tension state of the sticker, compare the actual tension with the target tension, and further adjust the position of the reel to accurately control the tension; The control system continuously monitors changes in battery type, size and sticker status, automatically updates adjustment parameters and adjusts the reel position through control signals to ensure that the tension during each sticker application always meets the set standards.

7. The tension adjustment method of the automatic battery sticker machine based on machine vision according to claim 1 is characterized in that: The sticker effect is monitored in real time by the machine vision system. If the sticker does not meet the quality standards, the method for adjusting the reel position is as follows: The machine vision system acquires the battery surface image in real time, performs quality inspection on the sticker effect, and identifies defects on the sticker surface, such as wrinkles, bubbles, and deviations; Compare and analyze sticker defects detected in real time with preset quality standards to determine whether the stickers meet quality requirements; If it is detected that the sticker does not meet the quality standards, the control system immediately generates an adjustment signal to instruct the reel shaft position of the reeling mechanism to be adjusted; The control system adjusts the reel position or the tension setting of the sticker according to the type and severity of the sticker defect; The adjustment process is optimized through closed-loop feedback control, and after each adjustment, the sticker effect is verified again through the machine vision system; After the sticker quality reaches the standard, the system returns to normal operation and continues to sticker the next batch of batteries.

8. A tension adjustment system for a battery automatic sticker machine based on machine vision, characterized in that: Included are: A machine vision system is used to collect battery images in real time and analyze the type, size, appearance characteristics and surface condition of the battery through image processing; The machine vision system can identify the type and specification of the battery, determine whether there are stains or scratches on the battery surface, and detect the status of the sticker, including whether the sticker is correctly pasted and whether there are wrinkles or bubbles; A control system connected to the machine vision system, configured to receive information about battery type, size, and sticker status, and calculate and output adjustment parameters based on the information; A reeling mechanism, used to automatically adjust the position of the reeling shaft according to the adjustment parameters, thereby adjusting the tension of the sticker; The real-time monitoring module works in conjunction with the machine vision system to monitor the sticker effect in real time and adjust the position of the reel when it is detected that the sticker does not meet the quality standards.

9. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the tension adjustment method of the automatic battery sticker machine based on machine vision as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a tension adjustment method for a battery automatic sticker machine based on machine vision as described in any one of claims 1 to 7 is implemented.

Images