Product identification and processing parameter selection method for battery cell pole welding

Abstract

The invention provides a product identification and processing parameter selection method for battery cell pole welding, which comprises the following steps of: scanning and identifying a unique identification code carried on a product based on a code reader, and matching a target welding parameter set from a preset product model welding process parameter library; based on the target welding parameter set, an execution device in the welding section is driven to dynamically adjust the distance between the positive electrode welding head and the negative electrode welding head, and annular composite welding operation is executed on the pole position after dynamic adjustment; real-time welding parameters in the annular composite welding operation process are collected, and when the real-time welding parameters do not meet the preset standard, dynamic compensation adjustment is conducted on the real-time welding parameters, and effective welding parameters are obtained; and the unique identification code, the target welding parameter set, the real-time welding parameters and the effective welding parameters are associated and bound to obtain a welding data packet, and the welding data packet is uploaded to a manufacturing execution center. The production efficiency is obviously improved, the dependence on artificial experience is reduced, and the quality control capability is enhanced.

Description

Technical Field

[0001] This invention relates to the field of intelligent battery manufacturing technology, and in particular to a method for product identification and processing parameter selection for cell electrode welding. Background Technology

[0002] Currently, in the battery cell manufacturing process, the welding of the terminals is a key process to ensure the conductivity and structural sealing of the battery cell. As the requirements of new energy for battery production capacity, quality and model diversity continue to increase, the demand for flexibility and intelligence of welding production lines is becoming increasingly prominent. Currently, although mainstream welding stations have achieved a certain degree of automation, they still have the following shortcomings in terms of product changeover, parameter matching, and process control: First, product identification mostly relies on manual setting or simple barcode scanning, and parameter retrieval is fixed, making it difficult to adapt to the needs of rapid changeover and parameter fine-tuning. Second, the execution of welding parameters is usually open-loop control, which cannot be dynamically compensated according to the real-time working conditions during the welding process (such as the state of the molten pool and heat input), which easily leads to fluctuations in welding quality. Furthermore, the correlation between production data (such as welding parameters and quality data) and individual product information is weak, and the lack of data foundation for process traceability and optimization restricts the continuous improvement of the process and the stability of quality. Therefore, in order to overcome the above-mentioned defects, the present invention provides a method for product identification and processing parameter selection for battery cell electrode welding. Summary of the Invention

[0003] This invention provides a product identification and processing parameter selection method for battery cell electrode welding. It automatically identifies product identifiers and matches corresponding welding parameters, enabling rapid product changeover and precise process adaptation. Simultaneously, it dynamically adjusts the welding mechanism based on parameters to ensure accurate alignment of electrode positions for different product models. During welding, key parameters are monitored in real-time and automatically compensated, effectively improving the consistency and reliability of welding quality. Finally, the entire process data is integrated and uploaded, achieving full traceability and digital management of the welding process. This significantly improves production efficiency, reduces reliance on manual experience, and strengthens quality control capabilities.

[0004] This invention provides a method for product identification and processing parameter selection for battery cell electrode welding, including: Step 1: Scan and identify the unique identification code carried on the product using the code reader installed on the vehicle, and match the target welding parameter set from the preset product model welding process parameter library based on the scanning and identification results; Step 2: Based on the target welding parameter set, the actuator in the welding section dynamically adjusts the distance between the positive and negative welding heads, and after the dynamic adjustment, the electrode column is clamped and positioned. Based on the clamping and positioning result, a ring-shaped composite welding operation is performed at the electrode column position. Step 3: Collect real-time welding parameters during the ring-shaped composite welding operation, and dynamically compensate and adjust the real-time welding parameters when they do not meet the preset standards to obtain effective welding parameters; Step 4: Associate and bind the unique identifier, target welding parameter set, real-time welding parameters, and valid welding parameters to obtain a welding data package, and upload the welding data package to the manufacturing execution center.

[0005] Preferably, in a product identification and processing parameter selection method for battery cell terminal welding, step 1 involves scanning and identifying the unique identification code carried on the product using a code reader installed on the carrier, including: The business scenario requirements of the barcode reader are obtained based on the management terminal, and the value adaptation range of each item parameter in the barcode reader is determined based on the business scenario requirements. The parameters of the barcode reader are configured based on the value adaptation range, and the barcode reader set on the carrier is controlled based on the parameter configuration result to scan the unique identification code carried on the product and extract the identification code data. The identification code data is parsed to obtain the product model and basic functional parameters, and the obtained product model and basic functional parameters are matched with the preset welding data in the preset product model welding process parameter library; Based on the matching results, the target welding parameter set corresponding to the current product is obtained.

[0006] Preferably, a product identification and processing parameter selection method for battery cell electrode welding obtains a target welding parameter set corresponding to the current product based on the matching results, including: Construct a product welding parameter record table, and dynamically enter the product model and basic functional parameters of each product into the product welding parameter record table according to the welding sequence of the products on the carrier. Simultaneously, the target timestamp of each product when it is welded is obtained, and the obtained target timestamp and the corresponding target welding parameter set are synchronously mapped in the product welding parameter record table. The product welding construction record table is obtained based on the mapping results.

[0007] Preferably, in a product identification and processing parameter selection method for battery cell electrode welding, step 2 involves dynamically adjusting the distance between the positive and negative electrode welding heads using an actuator in the welding section based on a target welding parameter set, clamping and positioning the electrode after the dynamic adjustment, and performing a ring-shaped composite welding operation at the electrode position based on the clamping and positioning result. Obtain the target welding parameter set, parse the target welding parameter set, and determine the target spacing value of the positive and negative electrode welding heads corresponding to the current product model; Based on the target spacing value, control commands are generated, and based on the control commands, the spacing adjustment device in the welding section is driven to move at least one of the positive and negative welding heads relative to each other. The actual spacing data of the positive and negative electrode welding heads is obtained in real time based on the displacement sensor, and the actual spacing data is compared with the target spacing value; When the actual spacing data falls within the allowable error range of the target spacing value, the welding head position is locked, and the pole post is clamped and positioned. Based on the clamping and positioning result, a ring-shaped composite welding operation is performed at the pole post position.

[0008] Preferably, a product identification and processing parameter selection method for battery cell terminal welding, based on the locking result, performs a ring-shaped composite welding operation at the terminal position, including: The welding preparation signal is triggered based on the welding head position locking result, and the actuator is controlled to position the pole based on the welding preparation signal; Based on the positioning results, the independent clamping mechanism in the rotary pressure welding fixture simultaneously clamps the positive and negative terminals of the product. Based on the clamping result, the laser welding head is moved to the position of the electrode according to the target welding parameter set, and the annular composite welding program is started to perform the annular composite welding operation.

[0009] Preferably, in a product identification and processing parameter selection method for cell electrode welding, step 3 involves collecting real-time welding parameters during the annular composite welding operation, and dynamically compensating and adjusting the real-time welding parameters when they do not meet preset standards to obtain effective welding parameters, including: Based on the simultaneous acquisition of molten pool image sequences and real-time heat distribution data of the welding area during the annular composite welding operation by a vision sensor and a temperature sensor integrated into a preset laser welding head; The molten pool image sequence is processed to extract the weld width and penetration feature values, and the peak temperature is extracted from the real-time heat distribution data. The extracted weld width, penetration depth, and peak temperature are compared in real time with the preset process standard range corresponding to the target welding parameters. When the weld width, penetration depth, and peak temperature exceed the corresponding preset process standard range, abnormal characteristic data is determined to exist, the current welding process is determined to be abnormal, and a dynamic compensation and adjustment mechanism is triggered. Obtain the feature data categories of abnormal feature data that exceed the preset process standard range, and select the corresponding compensation model from the pre-stored compensation rule library based on the feature data categories; Based on the selected compensation model and the deviation of the current abnormal feature data, analyze and generate at least one of the following in real time: laser power correction value, welding speed correction value, or pulse frequency correction value; During the remaining welding cycle of the current sub-ring composite welding, the correction value is superimposed on the currently executed welding parameters to obtain the effective welding parameters, and the welding action of the laser welding head is updated in real time based on the effective welding parameters.

[0010] Preferably, a method for product identification and processing parameter selection for battery cell electrode welding involves processing a sequence of molten pool images to extract weld width and penetration feature values, and simultaneously extracting peak temperature from real-time heat distribution data, including: The obtained molten pool image sequence and real-time thermal distribution data; The molten pool image sequence is time-aligned and noise is filtered to obtain preprocessed image frames. Edge detection is performed on each preprocessed image frame to determine the molten pool outline and weld edge. The pixel width along the welding direction within the molten pool contour is determined based on the molten pool contour and weld edge. The pixel width is then converted into physical dimensions based on the imaging rules of the vision sensor to obtain the real-time weld width value. Gradient analysis of grayscale distribution within the molten pool contour is performed along a cross section perpendicular to the welding direction. The location with the most significant grayscale abrupt change is taken as the fusion line. The pixel depth from the molten pool surface to the fusion line is determined and converted into a molten depth feature value based on the preset calibration parameters of the visual sensor. Simultaneously, the real-time heat distribution data is synchronously matched with the image sequence based on the acquisition timestamp to generate a time-space corresponding temperature field matrix; In the temperature field matrix, the local maximum temperature value is searched point by point along the welding trajectory to obtain the peak temperature.

[0011] Preferably, a product identification and processing parameter selection method for battery cell electrode welding, based on the selected compensation model and the deviation of current abnormal feature data, analyzes in real time and generates at least one of laser power correction value, welding speed correction value, or pulse frequency correction value, including: Compare the measured value of the current abnormal feature data with the upper or lower limit of the preset process standard range to determine the direction and absolute amount of the deviation; When the real-time weld width value exceeds the upper limit of the preset process standard range, the absolute amount of the deviation is analyzed according to the preset weld width-speed negative correlation mapping relationship in the compensation model to determine the incremental correction value for the welding speed. Otherwise, when the real-time weld width value is lower than the lower limit of the preset process standard range, the decremental correction value for the welding speed is determined. When the feature data category of the abnormal feature data is the melting depth feature, the absolute amount of the deviation of the melting depth feature is divided into multiple continuous deviation intervals based on the compensation model, and a preset power adjustment step size is associated with each deviation interval. At the same time, the absolute value of the current deviation is matched with multiple consecutive deviation intervals, and the target deviation interval to which the absolute value of the current deviation belongs and the corresponding target power adjustment step size are determined based on the matching results. The laser power correction value is obtained by adjusting the step size based on the current deviation direction and the target power; When the characteristic data category of the abnormal feature data is peak temperature, the absolute amount of the peak temperature deviation is analyzed based on the compensation function in the compensation model to obtain the adjustment coefficient of the pulse frequency. The adjustment coefficient is then multiplied by the current welding pulse frequency to obtain the pulse frequency correction value.

[0012] Preferably, in a product identification and processing parameter selection method for battery cell electrode welding, step 4 involves associating and binding a unique identifier, a target welding parameter set, real-time welding parameters, and valid welding parameters to obtain a welding data package, which is then uploaded to the manufacturing execution center. This includes: The unique identifier, target welding parameter set, real-time welding parameters, and valid welding parameters are obtained. The unique identifier is used as the primary index key to form a structured association with the target welding parameter set, real-time welding parameters, and valid welding parameters to generate a complete welding process record. Based on a preset data encapsulation protocol, a protocol header containing data length and verification rules is added to the beginning of the welding process record, and a cyclic redundancy check code based on structured associated data is added to the end of the record to obtain the welding data packet. The welding data packet is sent to the data receiving server of the manufacturing execution center via the communication interface, and a data receiving confirmation signal is received from the data receiving server after the transmission is completed.

[0013] Preferably, a method for product identification and processing parameter selection for battery cell electrode welding, which involves sending welding data packets to a data receiving server in the manufacturing execution center via a communication interface, includes: The manufacturing execution center receives and parses the received welding data packets, and extracts the product model and corresponding valid welding parameters of the current product based on the parsing results. Extract the preset process standard range corresponding to the target welding parameter set, and compare the values ​​of the effective welding parameters with the preset process standard range; When the effective welding parameters are within the preset process standard range, the reference welding parameters corresponding to the current product model are extracted from the preset product model welding process parameter library, and the deviation between the effective welding parameters and the reference welding parameters is determined. When the deviation value meets the preset convergence condition, the stored benchmark welding parameters are replaced with the effective welding parameters based on the product model, thus completing the dynamic optimization and update of the process library.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: By automatically identifying product identifiers and matching corresponding welding parameters, rapid model changeover and precise process adaptation are achieved. At the same time, the welding mechanism is dynamically adjusted according to the parameters to ensure accurate alignment of the pole positions for different product models. Key parameters are monitored in real time during the welding process and automatically compensated, effectively improving the consistency and reliability of welding quality. Finally, the entire process data is linked, integrated, and uploaded to achieve full traceability and digital management of the welding process, thereby significantly improving production efficiency, reducing reliance on manual experience, and strengthening quality control capabilities.

[0015] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in this application.

[0016] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of a product identification and processing parameter selection method for battery cell electrode welding according to an embodiment of the present invention; Figure 2 This is a device structure diagram of a rotary pressure welding fixture used in a product identification and processing parameter selection method for welding battery cell terminals in an embodiment of the present invention, when performing an annular composite welding operation; Figure 3 This is a flowchart of step 4 in a product identification and processing parameter selection method for battery cell electrode welding according to an embodiment of the present invention. Detailed Implementation

[0018] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0019] Example 1: This example provides a method for product identification and processing parameter selection for battery cell electrode welding, such as... Figure 1 As shown, it includes: Step 1: Scan and identify the unique identification code carried on the product using the code reader installed on the vehicle, and match the target welding parameter set from the preset product model welding process parameter library based on the scanning and identification results; Step 2: Based on the target welding parameter set, the actuator in the welding section dynamically adjusts the distance between the positive and negative welding heads, and after the dynamic adjustment, the electrode column is clamped and positioned. Based on the clamping and positioning result, a ring-shaped composite welding operation is performed at the electrode column position. Step 3: Collect real-time welding parameters during the ring-shaped composite welding operation, and dynamically compensate and adjust the real-time welding parameters when they do not meet the preset standards to obtain effective welding parameters; Step 4: Associate and bind the unique identifier, target welding parameter set, real-time welding parameters, and valid welding parameters to obtain a welding data package, and upload the welding data package to the manufacturing execution center.

[0020] In this embodiment, the unique identifier refers to the QR code or other machine-readable code carried on the product to uniquely identify the product.

[0021] In this embodiment, the preset product model welding process parameter library refers to a database that pre-stores welding process parameters (such as welding trajectory, laser power, welding speed, etc.) corresponding to different product models.

[0022] In this embodiment, the target welding parameter set refers to the set of welding parameters related to the current product model that is matched from the preset product model welding process parameter library.

[0023] In this embodiment, the spacing between the positive and negative electrode welding heads refers to the physical distance between the welding heads used for welding the positive and negative electrodes in the welding equipment, which needs to be adjusted according to the product model.

[0024] In this embodiment, the annular composite welding operation refers to the process of welding the electrode post using an annular laser welding head.

[0025] In this embodiment, real-time welding parameters refer to welding-related data collected in real time during the annular composite welding operation, such as molten pool images and temperature distribution.

[0026] In this embodiment, the preset standard refers to a pre-defined range of welding quality parameters, which is used to determine whether the real-time welding parameters are qualified.

[0027] In this embodiment, dynamic compensation adjustment refers to the process of adjusting the welding parameters in real time based on the deviation between the real-time welding parameters and the preset standard during the welding process.

[0028] In this embodiment, the effective welding parameters refer to the welding parameters that are finally used after dynamic compensation and adjustment.

[0029] In this embodiment, the welding data packet refers to the data packet formed by associating and binding the unique identifier, the target welding parameter set, the real-time welding parameters, and the valid welding parameters.

[0030] In this embodiment, the manufacturing execution center refers to the data management center in the manufacturing execution system (MES) used to receive, store, and manage welding data packets.

[0031] The beneficial effects of the above technical solution are as follows: by automatically identifying product identifiers and matching corresponding welding parameters, rapid model changeover and precise process adaptation can be achieved. At the same time, the welding mechanism is dynamically adjusted according to the parameters to ensure accurate alignment of the pole positions for different product models. Key parameters are monitored in real time and automatically compensated during the welding process, effectively improving the consistency and reliability of welding quality. Finally, the data of the entire process is linked, integrated and uploaded to achieve full traceability and digital management of the welding process, thereby significantly improving production efficiency, reducing reliance on manual experience, and strengthening quality control capabilities.

[0032] Example 2: Based on Example 1, this example provides a product identification and processing parameter selection method for cell electrode welding. In step 1, the unique identification code carried on the product is scanned and identified using a code reader installed on the carrier, including: The business scenario requirements of the barcode reader are obtained based on the management terminal, and the value adaptation range of each item parameter in the barcode reader is determined based on the business scenario requirements. The parameters of the barcode reader are configured based on the value adaptation range, and the barcode reader set on the carrier is controlled based on the parameter configuration result to scan the unique identification code carried on the product and extract the identification code data. The identification code data is parsed to obtain the product model and basic functional parameters, and the obtained product model and basic functional parameters are matched with the preset welding data in the preset product model welding process parameter library; Based on the matching results, the target welding parameter set corresponding to the current product is obtained.

[0033] In this embodiment, the management terminal refers to a host computer or human-machine interface used for setting parameters, monitoring and managing industrial equipment such as barcode readers.

[0034] In this embodiment, business scenario requirements refer to the reader's operating conditions requirements determined based on factors such as lighting conditions in the production environment, product identification code type, and conveyor belt speed.

[0035] In this embodiment, the project parameters refer to the specific adjustable parameters in the reader settings, such as exposure time, gain, decoding algorithm, etc.

[0036] In this embodiment, the value adaptation range refers to the reasonable numerical range set for each item parameter to ensure reliable code reading.

[0037] In this embodiment, parameter configuration refers to the process of assigning and setting specific values ​​to various parameters of the barcode reader according to the determined value adaptation range.

[0038] In this embodiment, the identification code data refers to the original encoded information obtained after the reader successfully scans the code.

[0039] In this embodiment, the product model refers to the classification code used to distinguish battery cell terminals of different specifications and sizes.

[0040] In this embodiment, the basic functional parameters refer to the key dimensions, materials, and other basic attribute information corresponding to the product model.

[0041] In this embodiment, the preset welding data refers to a set of standard welding process parameters that are pre-stored in the process parameter library and bound to a specific product model.

[0042] The beneficial effects of the above technical solution are: by flexibly configuring the code reading parameters in combination with specific business scenarios, the success rate and accuracy of identification code recognition in complex industrial environments are significantly improved; the precise matching of process data based on the parsed product information ensures that the welding parameters are fully compatible with the product model, fundamentally avoiding quality risks caused by parameter mismatch, and providing a reliable data foundation for subsequent automated welding.

[0043] Example 3: Based on Example 2, this example provides a product identification and processing parameter selection method for cell electrode welding. Based on the matching results, a target welding parameter set corresponding to the current product is obtained, including: Construct a product welding parameter record table, and dynamically enter the product model and basic functional parameters of each product into the product welding parameter record table according to the welding sequence of the products on the carrier. Simultaneously, the target timestamp of each product when it is welded is obtained, and the obtained target timestamp and the corresponding target welding parameter set are synchronously mapped in the product welding parameter record table. The product welding construction record table is obtained based on the mapping results.

[0044] In this embodiment, the product welding parameter record table refers to a temporary data structure used to sequentially record the model, basic functional parameters and corresponding target welding parameter set of each product to be welded.

[0045] In this embodiment, the welding sequence refers to the time or logical order in which the products conveyed on the carrier enter the welding station for processing.

[0046] In this embodiment, dynamic entry refers to the process of adding relevant information to the record table in real time when the product enters the processing flow.

[0047] In this embodiment, the target timestamp refers to the precise time point recorded by the system when the product actually begins welding.

[0048] In this embodiment, the corresponding mapping refers to the operation of establishing and saving the association between the target timestamp and its corresponding target welding parameter set in the record table.

[0049] In this embodiment, the product welding construction record table refers to the final generated structured data table that contains a complete mapping relationship between product information, welding parameters, and welding timestamps.

[0050] The beneficial effects of the above technical solution are: by constructing a dynamically linked parameter record table, it ensures that the welding parameters of each product are accurately bound to its real-time processing time, thereby realizing the single-piece traceability capability of the entire process and providing a complete, reliable and structured data foundation for welding quality analysis, process optimization and production management.

[0051] Example 4: Based on Example 1, this example provides a product identification and processing parameter selection method for cell electrode welding. In step 2, the actuator in the welding section dynamically adjusts the distance between the positive and negative electrode welding heads based on the target welding parameter set, and clamps and positions the electrode after dynamic adjustment. Based on the clamping and positioning result, a ring-shaped composite welding operation is performed at the electrode position, including: Obtain the target welding parameter set, parse the target welding parameter set, and determine the target spacing value of the positive and negative electrode welding heads corresponding to the current product model; Based on the target spacing value, control commands are generated, and based on the control commands, the spacing adjustment device in the welding section is driven to move at least one of the positive and negative welding heads relative to each other. The actual spacing data of the positive and negative electrode welding heads is obtained in real time based on the displacement sensor, and the actual spacing data is compared with the target spacing value; When the actual spacing data falls within the allowable error range of the target spacing value, the welding head position is locked, and the pole post is clamped and positioned. Based on the clamping and positioning result, a ring-shaped composite welding operation is performed at the pole post position.

[0052] In this embodiment, the target spacing value refers to the theoretical distance value that needs to be set between the positive and negative electrode welding heads corresponding to the current product model, as specified in the target welding parameter set.

[0053] In this embodiment, the control command refers to the digital or analog signal command generated based on the target spacing value and used to drive the servo motor.

[0054] In this embodiment, the displacement sensor refers to a measuring device that detects changes in the position of the substrate or the spacing between the solder joints in real time and converts them into electrical signals.

[0055] In this embodiment, the actual spacing data refers to the actual distance between the positive and negative electrode welding heads, which is measured in real time by a displacement sensor.

[0056] In this embodiment, the allowable error range refers to the maximum permissible deviation range set around the target spacing value for determining whether the actual spacing is qualified.

[0057] The beneficial effects of the above technical solution are as follows: by automatically parsing parameters and generating control commands, high-precision and automated adjustment of the welding head spacing is achieved. Real-time displacement monitoring and closed-loop comparison ensure the accuracy of the spacing adjustment, effectively avoiding welding defects caused by spacing deviation. After reaching the allowable error, the mechanism is locked and welding is executed, ensuring the consistency of welding positions for different product models and significantly improving the adaptability and reliability of the welding process.

[0058] Example 5: Based on Example 4, this example provides a method for product identification and processing parameter selection for cell electrode welding, such as... Figure 2 As shown, an annular composite welding operation is performed at the pole position based on the locking result, including: The welding preparation signal is triggered based on the welding head position locking result, and the actuator is controlled to position the pole based on the welding preparation signal; Based on the positioning results, the independent clamping mechanism in the rotary pressure welding fixture simultaneously clamps the positive and negative terminals of the product. Based on the clamping result, the laser welding head is moved to the position of the electrode according to the target welding parameter set, and the annular composite welding program is started to perform the annular composite welding operation.

[0059] In this embodiment, the positioning of the pole by the control actuator refers to controlling the lifting mechanism to lift the pressure welding fixture on the carrier into the rotating pressure welding fixture, and completing the positioning through the cooperation of the positioning pin that can move up and down elastically with the fixture bushing.

[0060] In this embodiment, the welding preparation signal refers to the control signal issued after the substrate position is locked, which allows entry into the welding preparation stage.

[0061] In this embodiment, the clamping mechanism refers to the mechanical device in the rotary pressure welding fixture used to apply pressure from both sides simultaneously to fix the positive and negative terminals.

[0062] In this embodiment, the clamping result refers to the stable clamping state formed after the clamping mechanism has completed clamping the positive and negative terminals.

[0063] In this embodiment, the laser welding head refers to the actuator used to emit a laser beam to achieve ring-shaped composite welding.

[0064] In this embodiment, the annular composite welding program refers to an automated program that controls the laser welding head to perform welding according to a preset annular trajectory and process parameters.

[0065] The beneficial effects of the above technical solution are: through the continuous control of trigger signal, positioning, pressing and welding, the precise positioning and stable pressing of the electrode welding position are achieved, effectively preventing positional deviation and incomplete welding during the welding process. At the same time, through parameterized control, the consistency of welding quality of different product models is ensured, and the welding accuracy and reliability are improved.

[0066] Example 6: Based on Example 1, this example provides a product identification and processing parameter selection method for cell electrode welding. In step 3, real-time welding parameters are collected during the annular composite welding operation. When the real-time welding parameters do not meet the preset standard, the real-time welding parameters are dynamically compensated and adjusted to obtain effective welding parameters, including: Based on the simultaneous acquisition of molten pool image sequences and real-time heat distribution data of the welding area during the annular composite welding operation by a vision sensor and a temperature sensor integrated into a preset laser welding head; The molten pool image sequence is processed to extract the weld width and penetration feature values, and the peak temperature is extracted from the real-time heat distribution data. The extracted weld width, penetration depth, and peak temperature are compared in real time with the preset process standard range corresponding to the target welding parameters. When the weld width, penetration depth, and peak temperature exceed the corresponding preset process standard range, abnormal characteristic data is determined to exist, the current welding process is determined to be abnormal, and a dynamic compensation and adjustment mechanism is triggered. Obtain the feature data categories of abnormal feature data that exceed the preset process standard range, and select the corresponding compensation model from the pre-stored compensation rule library based on the feature data categories; Based on the selected compensation model and the deviation of the current abnormal feature data, analyze and generate at least one of the following in real time: laser power correction value, welding speed correction value, or pulse frequency correction value; During the remaining welding cycle of the current sub-ring composite welding, the correction value is superimposed on the currently executed welding parameters to obtain the effective welding parameters, and the welding action of the laser welding head is updated in real time based on the effective welding parameters.

[0067] In this embodiment, the compensation rule refers to a database that stores the mapping relationship between different abnormal feature data categories and corresponding compensation models, including at least a welding speed adjustment model for weld width, a laser power step compensation model for weld penetration characteristics, and a pulse frequency adjustment model for peak temperature.

[0068] In this embodiment, the preset laser welding head refers to a laser output device that integrates vision and temperature sensors for performing ring-shaped composite welding.

[0069] In this embodiment, the molten pool image sequence refers to a set of images continuously captured by a vision sensor during the welding process, reflecting the changes in the morphology of the molten metal region.

[0070] In this embodiment, real-time heat distribution data refers to the set of data collected by temperature sensors during the welding process, which reflects the temperature changes of the welding area over time and space.

[0071] In this embodiment, the preset convolutional network refers to a pre-trained deep learning model used to automatically extract weld width and weld depth feature values ​​from the molten pool image sequence.

[0072] In this embodiment, the weld width refers to the size of the molten pool perpendicular to the welding direction.

[0073] In this embodiment, the melt depth characteristic value refers to the quantitative index of the size or shape of the melt pool in the depth direction.

[0074] In this embodiment, peak temperature refers to the highest temperature value that appears in the real-time heat distribution data.

[0075] In this embodiment, abnormal feature data refers to weld width, penetration depth, or peak temperature data that exceed the preset process standard range during real-time comparison.

[0076] In this embodiment, the dynamic compensation adjustment mechanism refers to a program or logic that is automatically triggered when an abnormality in the welding process is detected, and is used to correct the welding parameters in real time.

[0077] In this embodiment, the compensation model refers to a mathematical model or set of rules used to calculate the correction value of welding parameters (such as laser power, welding speed, and pulse frequency) based on the deviation of specific types of characteristic data.

[0078] The beneficial effects of the above technical solution are as follows: by synchronously collecting visual and thermal data of the welding process through multiple sensors, real-time and multi-dimensional monitoring of welding quality can be achieved; key process features can be automatically extracted using convolutional networks and intelligently compared with preset standards, which significantly improves the accuracy and timeliness of anomaly identification; furthermore, based on the anomaly category, pre-stored compensation models can be dynamically called to correct parameters, which can complete online adjustment within a single welding cycle, effectively suppressing the expansion of welding defects, ensuring the stability and consistency of welding quality, and enhancing the autonomous adaptability and intelligence level of the process.

[0079] Example 7: Based on Example 6, this example provides a method for product identification and processing parameter selection for battery cell electrode welding. It processes the molten pool image sequence to extract weld width and penetration feature values, and simultaneously extracts peak temperature from real-time heat distribution data, including: The obtained molten pool image sequence and real-time thermal distribution data; The molten pool image sequence is time-aligned and noise is filtered to obtain preprocessed image frames. Edge detection is performed on each preprocessed image frame to determine the molten pool outline and weld edge. The pixel width along the welding direction within the molten pool contour is determined based on the molten pool contour and weld edge. The pixel width is then converted into physical dimensions based on the imaging rules of the vision sensor to obtain the real-time weld width value. Gradient analysis of grayscale distribution within the molten pool contour is performed along a cross section perpendicular to the welding direction. The location with the most significant grayscale abrupt change is taken as the fusion line. The pixel depth from the molten pool surface to the fusion line is determined and converted into a molten depth feature value based on the preset calibration parameters of the visual sensor. Simultaneously, the real-time heat distribution data is synchronously matched with the image sequence based on the acquisition timestamp to generate a time-space corresponding temperature field matrix; In the temperature field matrix, the local maximum temperature value is searched point by point along the welding trajectory to obtain the peak temperature.

[0080] In this embodiment, time alignment refers to the operation of synchronizing data from different sensors (such as vision and temperature sensors) according to a unified time base.

[0081] In this embodiment, noise filtering refers to the process of removing non-target interference information from an image or signal using a digital filtering algorithm.

[0082] In this embodiment, the molten pool contour refers to the boundary shape of the molten metal region identified by edge detection in the preprocessed image frame.

[0083] In this embodiment, the weld edge refers to the two boundary lines in the molten pool outline that are in contact with the base material and characterize the weld width.

[0084] In this embodiment, the fusion line refers to the location in the grayscale distribution of the molten pool cross-section where the grayscale value changes drastically, marking the boundary between the molten zone and the heat-affected zone.

[0085] In this embodiment, the temperature field matrix refers to a two-dimensional or three-dimensional data structure that organizes the synchronized real-time heat distribution data according to spatial coordinates and time series.

[0086] In this embodiment, the preset calibration parameters refer to the proportional coefficients or mapping relationships that are determined in advance through experiments and used to convert the image pixel size into the real physical size.

[0087] The beneficial effects of the above technical solution are as follows: By performing precise temporal alignment and preprocessing of images and thermal data, environmental interference is effectively eliminated, providing high-quality input for subsequent feature extraction. Combined with edge detection and grayscale gradient analysis, key welding morphology features can be automatically and accurately quantified, realizing objective measurement of weld size and penetration depth. By establishing a spatiotemporally synchronized temperature field and intelligently searching for peak temperatures, the welding thermal process can be accurately characterized, significantly improving the accuracy, consistency, and efficiency of feature extraction, and providing a reliable data foundation for real-time process judgment and closed-loop control.

[0088] Example 8: Based on Example 6, this example provides a method for product identification and processing parameter selection for cell electrode welding. Based on the selected compensation model and the deviation of current abnormal feature data, it analyzes in real time and generates at least one of the following: laser power correction value, welding speed correction value, or pulse frequency correction value, including: Compare the measured value of the current abnormal feature data with the upper or lower limit of the preset process standard range to determine the direction and absolute amount of the deviation; When the real-time weld width value exceeds the upper limit of the preset process standard range, the absolute amount of the deviation is analyzed according to the preset weld width-speed negative correlation mapping relationship in the compensation model to determine the incremental correction value for the welding speed. Otherwise, when the real-time weld width value is lower than the lower limit of the preset process standard range, the decremental correction value for the welding speed is determined. When the feature data category of the abnormal feature data is the melting depth feature, the absolute amount of the deviation of the melting depth feature is divided into multiple continuous deviation intervals based on the compensation model, and a preset power adjustment step size is associated with each deviation interval. At the same time, the absolute value of the current deviation is matched with multiple consecutive deviation intervals, and the target deviation interval to which the absolute value of the current deviation belongs and the corresponding target power adjustment step size are determined based on the matching results. The laser power correction value is obtained by adjusting the step size based on the current deviation direction and the target power; When the characteristic data category of the abnormal feature data is peak temperature, the absolute amount of the peak temperature deviation is analyzed based on the compensation function in the compensation model to obtain the adjustment coefficient of the pulse frequency. The adjustment coefficient is then multiplied by the current welding pulse frequency to obtain the pulse frequency correction value.

[0089] In this embodiment, the direction of deviation refers to the qualitative judgment of whether the measured value is too high (positive deviation) or too low (negative deviation) relative to the preset process standard range.

[0090] In this embodiment, the absolute value of the deviation refers to the absolute value of the difference between the measured value and the preset standard upper or lower limit value.

[0091] In this embodiment, the weld width-speed negative correlation mapping relationship refers to a pre-established mathematical model or data correspondence table that describes the inverse relationship between weld width and welding speed.

[0092] In this embodiment, the power adjustment step size refers to the fixed adjustment amount set for each preset melt depth characteristic deviation range, which is used to calculate the laser power correction value.

[0093] In this embodiment, the compensation function refers to a specific mathematical function used to calculate the pulse frequency adjustment coefficient based on the peak temperature deviation, such as a first-order hysteresis function or other fitting relationship.

[0094] In this embodiment, the adjustment coefficient refers to the multiplication factor used to scale the current welding pulse frequency, which is calculated through the compensation function.

[0095] The beneficial effects of the above technical solution are as follows: by accurately identifying and directionally compensating for different types of process deviations, precise closed-loop control of the welding process is achieved. Key parameters are adaptively adjusted according to the direction and degree of deviation, which not only effectively corrects real-time welding defects, but also enhances the system's adaptability and adjustment fineness to different abnormal working conditions through step-by-step and functional compensation strategies, thereby significantly improving the stability, consistency and quality reliability of the welding process and the final product.

[0096] Example 9: Based on Example 1, this example provides a method for product identification and processing parameter selection for battery cell electrode welding, such as... Figure 3 As shown, in step 4, the unique identifier, target welding parameter set, real-time welding parameters, and valid welding parameters are associated and bound to obtain a welding data package, which is then uploaded to the manufacturing execution center, including: Step 401: Obtain the unique identifier, target welding parameter set, real-time welding parameters, and valid welding parameters, and use the unique identifier as the primary index key to perform a structured association with the target welding parameter set, real-time welding parameters, and valid welding parameters to generate a complete welding process record; Step 402: Based on the preset data encapsulation protocol, add a protocol header containing data length and verification rules to the beginning of the welding process record, and add a cyclic redundancy check code based on structured associated data to the end of the record to obtain the welding data packet; Step 403: Send the welding data packet to the data receiving server of the manufacturing execution center via the communication interface, and receive the data receiving confirmation signal returned by the data receiving server after the sending is completed.

[0097] In this embodiment, the primary index key refers to the key field used in data association to uniquely identify and index a complete welding process record; in this case, it is the unique identifier code.

[0098] In this embodiment, structured association refers to the process of organizing data from different sources into records with a fixed format according to predefined logical relationships.

[0099] In this embodiment, the welding process record refers to a complete data entry that includes a unique identifier, a target welding parameter set, real-time welding parameters, and effective welding parameters.

[0100] In this embodiment, the preset data encapsulation protocol refers to a predefined standard or rule used to format and encapsulate data before data transmission.

[0101] In this embodiment, the Cyclic Redundancy Check (CRC) code refers to a check value calculated based on structured associated data and used to verify the integrity of data at the receiving end.

[0102] In this embodiment, the welding data packet refers to a transmittable data unit that is encapsulated according to a preset data encapsulation protocol and contains complete welding process records and verification information.

[0103] In this embodiment, the data receiving server refers to the software service or interface used by the manufacturing execution center to receive, parse, and process uploaded welding data packets.

[0104] The beneficial effects of the above technical solution are as follows: through structured association and protocol-based encapsulation, complete, traceable recording and reliable transmission of welding process data are realized. The verification mechanism ensures the integrity and consistency of data during transmission, ensuring that the data obtained by the manufacturing execution center is accurate and usable, improving the credibility, traceability efficiency and stability of data interaction between systems of welding process data, and providing a reliable data foundation for production decision-making and quality analysis.

[0105] Example 10: Based on Example 9, this example provides a method for product identification and processing parameter selection for cell electrode welding, which sends welding data packets to the data receiving server of the manufacturing execution center based on a communication interface, including: The manufacturing execution center receives and parses the received welding data packets, and extracts the product model and corresponding valid welding parameters of the current product based on the parsing results. Extract the preset process standard range corresponding to the target welding parameter set, and compare the values ​​of the effective welding parameters with the preset process standard range; When the effective welding parameters are within the preset process standard range, the reference welding parameters corresponding to the current product model are extracted from the preset product model welding process parameter library, and the deviation between the effective welding parameters and the reference welding parameters is determined. When the deviation value meets the preset convergence condition, the stored benchmark welding parameters are replaced with the effective welding parameters based on the product model, thus completing the dynamic optimization and update of the process library.

[0106] In this embodiment, the preset process standard range refers to the pre-set numerical range for determining whether the welding parameters are qualified.

[0107] In this embodiment, the reference welding parameters refer to the verified standard welding parameters for the corresponding product model stored in the preset product model welding process parameter library.

[0108] In this embodiment, the deviation value refers to the quantified value of the difference between the effective welding parameters and the reference welding parameters.

[0109] In this embodiment, the preset convergence condition refers to a pre-set threshold condition used to determine whether the deviation value is stable and can be adopted as a process optimization.

[0110] In this embodiment, dynamic optimization and updating refers to the process of safely and in a controlled manner updating the corresponding parameters in the preset product model welding process parameter library based on effective welding parameters that meet the conditions.

[0111] The beneficial effects of the above technical solution are: through the dual verification mechanism, it ensures that only qualified and stable optimized parameters are updated to the process library, effectively preventing erroneous updates caused by temporary anomalies, improving the reliability of the process library and the safety of the welding process, and supporting the autonomous and continuous optimization of process parameters.

[0112] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for product identification and processing parameter selection for battery cell electrode welding, characterized in that, include: Step 1: Scan and identify the unique identification code carried on the product using the code reader installed on the vehicle, and match the target welding parameter set from the preset product model welding process parameter library based on the scanning and identification results; Step 2: Based on the target welding parameter set, the actuator in the welding section dynamically adjusts the distance between the positive and negative welding heads, and after the dynamic adjustment, the electrode column is clamped and positioned. Based on the clamping and positioning result, a ring-shaped composite welding operation is performed at the electrode column position. Step 3: Collect real-time welding parameters during the ring-shaped composite welding operation, and dynamically compensate and adjust the real-time welding parameters when they do not meet the preset standards to obtain effective welding parameters; Step 4: Associate and bind the unique identifier, target welding parameter set, real-time welding parameters, and valid welding parameters to obtain a welding data package, and upload the welding data package to the manufacturing execution center.

2. The method for product identification and processing parameter selection for battery cell electrode welding according to claim 1, characterized in that, In step 1, the unique identification code carried on the product is scanned and identified using a code reader installed on the vehicle, including: The business scenario requirements of the barcode reader are obtained based on the management terminal, and the value adaptation range of each item parameter in the barcode reader is determined based on the business scenario requirements. The parameters of the barcode reader are configured based on the value adaptation range, and the barcode reader set on the carrier is controlled based on the parameter configuration result to scan the unique identification code carried on the product and extract the identification code data. The identification code data is parsed to obtain the product model and basic functional parameters, and the obtained product model and basic functional parameters are matched with the preset welding data in the preset product model welding process parameter library; Based on the matching results, the target welding parameter set corresponding to the current product is obtained.

3. The method for product identification and processing parameter selection for battery cell electrode welding according to claim 2, characterized in that, Based on the matching results, the target welding parameter set corresponding to the current product is obtained, including: Construct a product welding parameter record table, and dynamically enter the product model and basic functional parameters of each product into the product welding parameter record table according to the welding sequence of the products on the carrier. Simultaneously, the target timestamp of each product when it is welded is obtained, and the obtained target timestamp and the corresponding target welding parameter set are synchronously mapped in the product welding parameter record table. The product welding construction record table is obtained based on the mapping results.

4. The method for product identification and processing parameter selection for battery cell electrode welding according to claim 1, characterized in that, In step 2, the actuator in the welding section dynamically adjusts the distance between the positive and negative welding heads based on the target welding parameter set, and clamps and positions the electrode post after the dynamic adjustment. Based on the clamping and positioning result, a ring-shaped composite welding operation is performed at the electrode post position, including: Obtain the target welding parameter set, parse the target welding parameter set, and determine the target spacing value of the positive and negative electrode welding heads corresponding to the current product model; Based on the target spacing value, control commands are generated, and based on the control commands, the spacing adjustment device in the welding section is driven to move at least one of the positive and negative welding heads relative to each other. The actual spacing data of the positive and negative electrode welding heads is obtained in real time based on the displacement sensor, and the actual spacing data is compared with the target spacing value; When the actual spacing data falls within the allowable error range of the target spacing value, the welding head position is locked, and the pole post is clamped and positioned. Based on the clamping and positioning result, a ring-shaped composite welding operation is performed at the pole post position.

5. The method for product identification and processing parameter selection for cell electrode welding according to claim 4, characterized in that, Based on the clamping and positioning results, a ring-shaped composite welding operation is performed at the pole position, including: The welding preparation signal is triggered based on the welding head position locking result, and the actuator is controlled to position the pole based on the welding preparation signal; Based on the positioning results, the independent clamping mechanism in the rotary pressure welding fixture simultaneously clamps the positive and negative terminals of the product. Based on the clamping result, the laser welding head is moved to the position of the electrode according to the target welding parameter set, and the annular composite welding program is started to perform the annular composite welding operation.

6. The method for product identification and processing parameter selection for cell electrode welding according to claim 1, characterized in that, In step 3, real-time welding parameters are collected during the annular composite welding operation. When the real-time welding parameters do not meet the preset standards, dynamic compensation and adjustment are performed on the real-time welding parameters to obtain effective welding parameters, including: Based on the simultaneous acquisition of molten pool image sequences and real-time heat distribution data of the welding area during the annular composite welding operation by a vision sensor and a temperature sensor integrated into a preset laser welding head; The molten pool image sequence is processed to extract the weld width and penetration feature values, and the peak temperature is extracted from the real-time heat distribution data. The extracted weld width, penetration depth, and peak temperature are compared in real time with the preset process standard range corresponding to the target welding parameters. When the weld width, penetration depth, and peak temperature exceed the corresponding preset process standard range, abnormal characteristic data is determined to exist, the current welding process is determined to be abnormal, and a dynamic compensation and adjustment mechanism is triggered. Obtain the feature data categories of abnormal feature data that exceed the preset process standard range, and select the corresponding compensation model from the pre-stored compensation rule library based on the feature data categories; Based on the selected compensation model and the deviation of the current abnormal feature data, analyze and generate at least one of the following in real time: laser power correction value, welding speed correction value, or pulse frequency correction value; During the remaining welding cycle of the current sub-ring composite welding, the correction value is superimposed on the currently executed welding parameters to obtain the effective welding parameters, and the welding action of the laser welding head is updated in real time based on the effective welding parameters.

7. The method for product identification and processing parameter selection for battery cell electrode welding according to claim 6, characterized in that, The molten pool image sequence is processed to extract weld width and penetration feature values, and peak temperature is extracted from real-time heat distribution data, including: The obtained molten pool image sequence and real-time thermal distribution data; The molten pool image sequence is time-aligned and noise is filtered to obtain preprocessed image frames. Edge detection is performed on each preprocessed image frame to determine the molten pool outline and weld edge. The pixel width along the welding direction within the molten pool contour is determined based on the molten pool contour and weld edge. The pixel width is then converted into physical dimensions based on the imaging rules of the vision sensor to obtain the real-time weld width value. Gradient analysis of grayscale distribution within the molten pool contour is performed along a cross section perpendicular to the welding direction. The location with the most significant grayscale abrupt change is taken as the fusion line. The pixel depth from the molten pool surface to the fusion line is determined and converted into a molten depth feature value based on the preset calibration parameters of the visual sensor. Simultaneously, the real-time heat distribution data is synchronously matched with the image sequence based on the acquisition timestamp to generate a time-space corresponding temperature field matrix; In the temperature field matrix, the local maximum temperature value is searched point by point along the welding trajectory to obtain the peak temperature.

8. The method for product identification and processing parameter selection for cell electrode welding according to claim 6, characterized in that, Based on the selected compensation model and the deviation of the current abnormal feature data, at least one of the following is analyzed in real time: laser power correction value, welding speed correction value, or pulse frequency correction value, including: Compare the measured value of the current abnormal feature data with the upper or lower limit of the preset process standard range to determine the direction and absolute amount of the deviation; When the real-time weld width value exceeds the upper limit of the preset process standard range, the absolute amount of the deviation is analyzed according to the preset weld width-speed negative correlation mapping relationship in the compensation model to determine the incremental correction value for the welding speed. Otherwise, when the real-time weld width value is lower than the lower limit of the preset process standard range, the decremental correction value for the welding speed is determined. When the feature data category of the abnormal feature data is the melting depth feature, the absolute amount of the deviation of the melting depth feature is divided into multiple continuous deviation intervals based on the compensation model, and a preset power adjustment step size is associated with each deviation interval. At the same time, the absolute value of the current deviation is matched with multiple consecutive deviation intervals, and the target deviation interval to which the absolute value of the current deviation belongs and the corresponding target power adjustment step size are determined based on the matching results. The laser power correction value is obtained by adjusting the step size based on the current deviation direction and the target power; When the characteristic data category of the abnormal feature data is peak temperature, the absolute amount of the peak temperature deviation is analyzed based on the compensation function in the compensation model to obtain the adjustment coefficient of the pulse frequency. The adjustment coefficient is then multiplied by the current welding pulse frequency to obtain the pulse frequency correction value.

9. The method for product identification and processing parameter selection for battery cell electrode welding according to claim 1, characterized in that, In step 4, the unique identifier, target welding parameter set, real-time welding parameters, and valid welding parameters are associated and bound to obtain a welding data package, which is then uploaded to the manufacturing execution center, including: The unique identifier, target welding parameter set, real-time welding parameters, and valid welding parameters are obtained. The unique identifier is used as the primary index key to form a structured association with the target welding parameter set, real-time welding parameters, and valid welding parameters to generate a complete welding process record. Based on a preset data encapsulation protocol, a protocol header containing data length and verification rules is added to the beginning of the welding process record, and a cyclic redundancy check code based on structured associated data is added to the end of the record to obtain the welding data packet. The welding data packet is sent to the data receiving server of the manufacturing execution center via the communication interface, and a data receiving confirmation signal is received from the data receiving server after the transmission is completed.

10. A method for product identification and processing parameter selection for cell electrode welding according to claim 9, characterized in that, The data receiving server at the manufacturing execution center sends welding data packets via a communication interface, including: The manufacturing execution center receives and parses the received welding data packets, and extracts the product model and corresponding valid welding parameters of the current product based on the parsing results. Extract the preset process standard range corresponding to the target welding parameter set, and compare the values ​​of the effective welding parameters with the preset process standard range; When the effective welding parameters are within the preset process standard range, the reference welding parameters corresponding to the current product model are extracted from the preset product model welding process parameter library, and the deviation between the effective welding parameters and the reference welding parameters is determined. When the deviation value meets the preset convergence condition, the stored benchmark welding parameters are replaced with the effective welding parameters based on the product model, thus completing the dynamic optimization and update of the process library.

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