Battery module detection equipment and detection method

Abstract

The embodiment of the invention provides battery module detection equipment and a detection method. The detection equipment comprises a rack, and the rack is provided with a placement position; a camera system is installed on the driving mechanism, the driving mechanism can drive the camera system to move in the first axial direction, the second axial direction and the third axial direction, and the camera system is used for collecting battery module images at the placement positions; the control system is connected with the driving mechanism and the camera system and used for controlling movement of the driving mechanism and image acquisition of the camera system. The placing position is arranged on the rack, a reliable basis is provided for the subsequent detection process, the driving mechanism can drive the camera system to move so as to ensure that the camera system covers the whole area of the battery module located at the placing position, and the control system can carry out a series of operations such as preprocessing, feature extraction and measurement and size judgment on the collected image. And the detection accuracy of the battery module is ensured.

Description

Technical Field

[0001] This manual relates to the field of power battery technology, specifically to a battery module testing device and testing method. Background Technology

[0002] In recent years, as the new energy vehicle market has matured and power batteries have entered the era of large-scale manufacturing, the increasing battery capacity and driving range require lithium battery companies to continuously explore new technologies and processes. Reducing manufacturing costs, achieving efficient and stable production, and improving product quality consistency have become key factors for lithium battery companies to win the new round of competition.

[0003] As power batteries become increasingly integrated with the power, structure, and electrical systems of vehicles, they must also bear additional responsibilities such as stress and load-bearing, beyond just capacity and range. Consequently, the assembly requirements for power batteries are becoming more stringent, placing higher demands on the size and appearance control of battery modules before shipment. However, with the significant increase in battery module size and weight, the difficulty of inspection is rising, rendering traditional manual inspection inadequate. Coupled with new automotive-grade manufacturing requirements and new power battery safety standards, the market urgently needs an energy-efficient, highly reliable, and low-maintenance module size inspection device to meet production demands. Summary of the Invention

[0004] In view of this, embodiments of this specification provide a battery module testing device and testing method.

[0005] This specification provides the following technical solution in its embodiments: a battery module testing device, comprising:

[0006] A rack, wherein at least one placement position for placing a battery module is formed on the rack;

[0007] A driving mechanism is provided, on which a camera system is mounted. The driving mechanism can drive the camera system to move along a first axis, a second axis, and a third axis to ensure that the camera system can cover the entire area of ​​the battery module located at the placement position. The camera system is used to acquire images of the battery module at the placement position.

[0008] The control system, connected to the drive mechanism and camera system, is used to control the movement of the drive mechanism and the image acquisition of the camera system, and to process, extract and measure, determine the size of the acquired images, and output the determination results.

[0009] Preferably, the control system includes a control unit and an image processing unit. The control unit is used to control the operation of the drive mechanism and the shooting of the camera system, and the image processing unit is used to process the acquired images.

[0010] Preferably, the image processing unit includes:

[0011] Image acquisition module: When the product moves precisely below the camera's field of view, the sensor triggers the camera to take a picture;

[0012] Image preprocessing module: Performs contrast enhancement, geometric correction, binarization, and filtering on the acquired raw images;

[0013] Feature extraction and measurement module: Employing edge detection, blob analysis, template matching, and calibration techniques, it identifies and accurately measures key features representing product dimensions in images.

[0014] Size determination module: compares the measured actual physical dimensions with the preset tolerance range to determine whether the product is qualified;

[0015] Result Output and Execution Module: Sends the judgment result to the PLC or production line control system, and the PLC controls the actuator to perform the corresponding action and records the product image, measurement value, judgment result, and timestamp information.

[0016] Preferably, a lifting and positioning mechanism is provided at the placement position, the lifting mechanism being used to carry and position the tray and battery module to the testing station of the placement position.

[0017] Preferably, the lifting and positioning mechanism includes a mounting frame, on which a lifting cylinder is mounted, and the output end of the lifting cylinder is connected to a placement frame for placing the battery module.

[0018] Preferably, the driving mechanism includes a servo moving mechanism, which drives the camera system to move along the X-axis, Y-axis and Z-axis.

[0019] A detection method, applied to the detection equipment as described in any of the above claims, includes the following steps:

[0020] The drive mechanism drives the camera system to perform a three-dimensional spatial scan of the battery module at the placement location;

[0021] Image acquisition is triggered at the preset detection point;

[0022] Preprocessing and feature extraction are performed on the acquired images;

[0023] Calculate the actual physical dimensions based on the calibration data;

[0024] Compare the design tolerances to determine the output quality.

[0025] Preferably, triggering image acquisition at a preset detection point specifically includes: when the battery module moves to a designated position below the camera's field of view, the camera is triggered to take a picture by an encoder signal or a photoelectric sensor to ensure that the image is clear and the position is stable.

[0026] Preferably, the preprocessing of the acquired images specifically includes:

[0027] High contrast makes target features more prominent;

[0028] Geometric correction corrects lens distortion and ensures measurement accuracy;

[0029] Binarization converts a grayscale image into a black and white image, making it easier to distinguish the background and the target object;

[0030] Filtering can smooth images or highlight edges.

[0031] Preferably, feature extraction of the acquired image specifically includes:

[0032] Edge detection is used to find the outline edges of a product;

[0033] Blob analysis identifies the shape, location, and area features of connected regions in an image;

[0034] Template matching compares the product image with a predefined standard template and calculates the differences;

[0035] Calibration involves photographing a calibration board of known size to establish a precise conversion relationship between image pixel coordinates and actual physical dimensions.

[0036] Compared with the prior art, the beneficial effects that at least one technical solution adopted in the embodiments of this specification can achieve include at least:

[0037] By setting placement positions on the rack, the battery modules can be stably and accurately placed in the predetermined positions, providing a reliable foundation for the subsequent inspection process. The drive mechanism can drive the camera system to move, ensuring that the camera system can cover the entire area of ​​the battery modules in the placement positions. The control system controls the movement trajectory and speed of the drive mechanism, as well as the timing of image acquisition by the camera system. At the same time, it can perform a series of operations such as preprocessing, feature extraction and measurement, and size determination on the acquired images, ensuring the accuracy of battery module inspection. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of the battery module testing equipment provided in this application;

[0040] Figure 2This is a front view of the battery module testing equipment provided in this application;

[0041] Figure 3 This is a partial top view of the battery module testing equipment provided in this application;

[0042] Figure 4 This is a schematic diagram of the control system provided in this application.

[0043] In the diagram, 1 is the frame; 101 is the placement position; 2 is the drive mechanism; 3 is the camera system; 4 is the battery module; 5 is the tray; and 6 is the lifting and positioning mechanism. Detailed Implementation

[0044] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0045] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0046] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0047] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0048] Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0049] In recent years, with the rapid development and increasing maturity of the new energy vehicle market, the power battery industry has officially entered a new era of large-scale manufacturing. As the integration of power batteries with the vehicle's power system, structural layout, and electrical control deepens, the function of power batteries is no longer limited to providing energy, but has further expanded to include diversified roles such as bearing external forces and supporting weight.

[0050] This shift places more stringent demands on the assembly precision of power batteries, especially the dimensional accuracy and appearance quality of battery modules, which directly affect the safety and reliability of the entire vehicle. Therefore, the factory control standards for the size and appearance of battery modules have also been significantly raised.

[0051] However, with the significant increase in the size and weight of battery modules, the difficulty of their testing has also increased.

[0052] Traditional manual inspection methods, due to their limitations such as low efficiency and susceptibility to subjective factors, are no longer sufficient to meet the demands of today's large-scale, high-precision production. This is especially true under the dual pressures of new automotive-grade manufacturing requirements and new safety standards for power batteries, where manual inspection methods are proving increasingly inadequate.

[0053] Therefore, adopting machine vision inspection technology to replace traditional manual inspection has become an inevitable trend in the development of the power battery industry.

[0054] Machine vision inspection technology, with its advantages of non-contact operation, high precision, high efficiency, and good repeatability, can effectively solve the challenges in the size and appearance inspection of battery modules. However, there is still an urgent need in the market for a module size inspection device that is energy-efficient, highly reliable, and has low maintenance costs, in order to better adapt to the actual needs of large-scale production lines and ensure product quality.

[0055] The technical solutions provided by the various embodiments of this application are described below with reference to the accompanying drawings.

[0056] like Figures 1-4 As shown, a battery module testing device includes:

[0057] The frame 1 has at least one placement position 101 for placing the battery module 4. The frame 1 serves as the support structure for the entire battery module 4 testing equipment, and at least one placement position 101 for placing the battery module 4 is designed on it. This placement position 101 is typically designed to ensure that the battery module 4 can be stably and accurately placed in the predetermined position, providing a reliable foundation for the subsequent testing process.

[0058] A driving mechanism 2 is equipped with a camera system 3. The driving mechanism 2 can drive the camera system 3 to move along a first axis, a second axis, and a third axis to ensure full coverage of the battery module 4 located at the placement position 101. The camera system 3 is used to acquire images of the battery module 4 at the placement position 101. The driving mechanism 2, equipped with the camera system 3, has the ability to move precisely in three-dimensional space (i.e., the first axis X, the second axis Y, and the third axis Z). Through precision driving components such as servo motors or stepper motors, the driving mechanism 2 can drive the camera system 3 to move precisely in three axes according to the instructions of the control system, thereby achieving full-area coverage scanning of the battery module 4 on the placement position 101.

[0059] The control system, connected to the drive mechanism 2 and camera system 3, controls the movement of the drive mechanism 2 and image acquisition by the camera system 3. It also processes the acquired images, extracts and measures features, determines dimensions, and outputs the results. The control system is a crucial component of the entire inspection equipment. Closely integrated with the drive mechanism 2 and camera system 3, it controls the movement trajectory and speed of the drive mechanism 2, as well as the timing of image acquisition by the camera system 3. Furthermore, the control system integrates image processing algorithms, enabling it to perform a series of operations on the acquired images, including preprocessing, feature extraction and measurement, and dimension determination.

[0060] like Figures 1-4 As shown, in some embodiments, the control system includes a control unit and an image processing unit. The control unit controls the operation of the drive mechanism 2 and the shooting of the camera system 3, while the image processing unit processes the acquired images. As the core component of the battery module 4 size detection device, the control system mainly consists of two modules: the control unit and the image processing unit. The control unit is responsible for the overall motion control and shooting time management of the device, while the image processing unit focuses on in-depth analysis and processing of the acquired images. The two work together to ensure the efficiency and accuracy of the detection process.

[0061] The control unit receives detection commands from the host computer or a preset program. These commands include the motion path and speed parameters of the drive mechanism 2, as well as the shooting trigger conditions of the camera system 3. Based on the parsed commands, the control unit precisely controls the movement of the drive mechanism 2 in the X, Y, and Z axes via a servo driver or stepper motor driver, ensuring that the camera system 3 can perform a comprehensive scan of the battery module 4 along a predetermined path. When the drive mechanism 2 drives the camera system 3 to the designated shooting position, the control unit triggers the camera system 3 to acquire images, ensuring that each shot is taken at the optimal time to obtain clear and accurate image data.

[0062] In some embodiments, the image processing unit includes:

[0063] Image Acquisition Module: When the product moves precisely below the camera's field of view, the sensor triggers the camera to take a picture. When the product (battery module 4) moves precisely below the camera's field of view via the conveyor belt, the positioning mechanism triggers the sensor (such as a photoelectric sensor or encoder). The sensor immediately sends a trigger signal to the camera system 3, controlling the camera to take a picture at a preset time. This process ensures that the product positioning error is less than 0.1mm through the high-precision servo drive mechanism 2, thereby guaranteeing the spatiotemporal consistency of image acquisition.

[0064] Image preprocessing module: Performs contrast enhancement, geometric correction, binarization, and filtering on the acquired raw images. This process optimizes image quality for subsequent analysis. Common techniques include: contrast enhancement to make target features (such as edges) more prominent; geometric correction to correct lens distortion and ensure measurement accuracy; binarization to convert grayscale images to black and white images to distinguish between background and target objects (especially useful in backlit contour measurements); and filtering to smooth the image or highlight edges.

[0065] Feature extraction and measurement module: Employing edge detection, blob analysis, template matching, and calibration techniques, this module identifies and accurately measures key features representing product dimensions in images. Edge detection uses algorithms combined with sub-pixel localization technology to precisely extract product contour edges; blob analysis identifies surface defects using a connected component labeling algorithm, calculating parameters such as defect area and location; template matching compares real-time images with standard templates using SSIM (structural similarity) matching; and calibration conversion uses a checkerboard calibration board to establish a mapping relationship between pixel coordinates and physical coordinates.

[0066] Dimension Judgment Module: Compares the measured actual physical dimensions with the preset tolerance range to determine whether the product is qualified; compares the measured values ​​with the preset tolerance range (upper and lower limits) using a three-level judgment logic: single-item judgment, independently judging whether each dimension is within the tolerance zone; overall judgment, the product is judged as qualified only when all dimensions are qualified (AND logic); combined judgment, verifying the geometric relationship of related dimensions (such as hole distance and edge distance) to ensure assembly compatibility.

[0067] Result Output and Execution Module: Sends the judgment result to the PLC or production line control system, and the PLC controls the actuator to perform the corresponding action and records the product image, measurement value, judgment result, and timestamp information.

[0068] like Figures 1-3As shown, in some embodiments, a lifting and positioning mechanism 6 is provided at the placement position 101. The lifting mechanism is used to carry and position the tray 5 and the battery module 4 to the inspection station of the placement position 101. The function of the lifting and positioning mechanism 6 is to lift the tray 5 and the battery module 4 from the conveyor line to the inspection station through precise vertical movement, and to achieve precise spatial positioning.

[0069] like Figures 1-3 As shown, in some embodiments, the lifting and positioning mechanism 6 includes a mounting frame, on which a lifting cylinder is mounted. The output end of the lifting cylinder is connected to a placement frame, which is used to place the battery module 4. The lifting cylinder drives the placement frame to move up and down, thereby moving the tray 5 and the battery module 4 to a designated position. The lifting cylinder can be a pneumatic lifting mechanism or an electric lifting mechanism.

[0070] like Figures 1-3 As shown, in some embodiments, the drive mechanism 2 includes a servo moving mechanism, which drives the camera system 3 to move along the X, Y, and Z axes. Using a servo moving mechanism to drive the linear module transmission mechanism achieves precise movement in the X, Y, and Z directions, improving detection speed. The X, Y, and Z servo moving mechanisms drive the camera system 3 to achieve full-area coverage of the module detection, increasing the effective detection range of the module; it is compatible with modules of different sizes (length, width, height) to meet process requirements.

[0071] Please see Figures 1-4 Based on the same inventive concept, embodiments of this specification provide a detection method applied to the detection equipment described in any of the above claims, comprising the following steps:

[0072] The drive mechanism drives the camera system to perform a three-dimensional spatial scan of the battery module at the placement location;

[0073] Image acquisition is triggered at the preset detection point;

[0074] Preprocessing and feature extraction are performed on the acquired images;

[0075] Calculate the actual physical dimensions based on the calibration data;

[0076] Compare the design tolerances to determine the output quality.

[0077] In some implementations, triggering image acquisition at a preset detection point specifically includes: when the battery module moves to a designated position below the camera's field of view, the camera is triggered to take a picture by an encoder signal or a photoelectric sensor to ensure that the image is clear and the position is stable.

[0078] In some implementations, preprocessing the acquired images specifically includes:

[0079] High contrast makes target features more prominent;

[0080] Geometric correction corrects lens distortion and ensures measurement accuracy;

[0081] Binarization converts a grayscale image into a black and white image, making it easier to distinguish the background and the target object;

[0082] Filtering can smooth images or highlight edges.

[0083] In some implementations, feature extraction of the acquired image specifically includes:

[0084] Edge detection is used to find the outline edges of a product;

[0085] Blob analysis identifies the shape, location, and area features of connected regions in an image;

[0086] Template matching compares the product image with a predefined standard template and calculates the differences;

[0087] Calibration involves photographing a calibration board of known size to establish a precise conversion relationship between image pixel coordinates and actual physical dimensions.

[0088] The detection method will be described in detail below:

[0089] Image acquisition hardware: Utilizes a high-resolution industrial camera (CCD / CMOS), suitable lenses, and light sources optimized for product characteristics and inspection needs (such as contours and surface defects) (e.g., ring light, backlight, coaxial light, dome light). Triggering: When the product is precisely moved below the camera's field of view, a sensor (such as a photoelectric sensor or encoder) triggers the camera to take a picture, ensuring a clear image and stable position.

[0090] Image preprocessing involves processing the acquired raw images to optimize their quality and facilitate subsequent analysis.

[0091] Common techniques include: Contrast enhancement to make target features (such as edges) more prominent; Geometric correction to correct lens distortion and ensure measurement accuracy; Binarization to convert grayscale images to black and white images to facilitate the distinction between background and target objects (especially common in backlit contour measurements); and Filtering to smooth images or highlight edges.

[0092] Feature extraction and measurement are the core steps: the system identifies and accurately measures key features representing product dimensions in the image. Common techniques and methods include: edge detection, using algorithms to find the product's contour edges, which is the foundation of dimensional measurement; blob analysis, where the communication vision system sends the judgment result (OK / NG) to the PLC or production line control system via I / O signals, industrial bus, or host computer software interface; and action execution: the PLC controls the actuators based on the received results: OK products are allowed to enter the next process or the qualified product area; NG products trigger rejection or alarm shutdown. Data recording: the system typically records information such as the image, measurement value, judgment result, and timestamp for each product for process monitoring, traceability, and statistical analysis (such as SPC statistical process control). Features such as the shape, position, and area of ​​connected regions in the image are identified. Template matching compares the product image with a predefined standard template and calculates the differences. Calibration: by photographing a calibration board of known dimensions (such as a checkerboard), a precise conversion relationship is established between image pixel coordinates and actual physical dimensions (millimeters). Without precise calibration, pixel measurements cannot be converted into meaningful physical dimensions.

[0093] Dimensional judgment compares the measured actual physical dimensions with preset tolerance ranges (i.e., upper and lower specification limits). Judgment logic: `IF` (measured value >= lower specification limit `AND` measured value <= upper specification limit) `THEN` OK `ELSE` NG. A product typically requires checking multiple critical dimensions. Judgment can be: Individual judgment: Each dimension is judged OK / NG separately. Overall judgment: The product is OK only if all critical dimensions are OK; if any dimension is NG, the product is NG (most common). Combined judgment: Certain dimensional combinations need to satisfy specific relationships.

[0094] Output and Execution Communication: The vision system sends the judgment result (OK / NG) to the PLC or production line control system via I / O signals, industrial bus, or host computer software interface. Execution Action: The PLC controls the actuators based on the received result: OK products: allowed to enter the next process or qualified product area (e.g., conveyor belt continues running, diversion baffle does not move). NG products: trigger rejection action (e.g., pneumatic push rod, swing arm, diversion baffle pushes the product into the rework line), or alarm shutdown. Data Recording: The system typically records images, measurements, judgment results, timestamps, etc., for each product for process monitoring, traceability, and statistical analysis.

[0095] The same or similar parts between the various embodiments in this specification can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the method embodiments described later are relatively simple in description since they correspond to the system, and relevant parts can be referred to the descriptions in the system embodiments.

[0096] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A battery module testing device, characterized in that, include: A rack, wherein at least one placement position for placing a battery module is formed on the rack; A driving mechanism is provided, on which a camera system is mounted. The driving mechanism can drive the camera system to move along a first axis, a second axis, and a third axis to ensure that the camera system can cover the entire area of ​​the battery module located at the placement position. The camera system is used to acquire images of the battery module at the placement position. The control system, connected to the drive mechanism and camera system, is used to control the movement of the drive mechanism and the image acquisition of the camera system, and to process, extract and measure, determine the size of the acquired images, and output the determination results.

2. The battery module testing equipment according to claim 1, characterized in that, The control system includes a control unit and an image processing unit. The control unit is used to control the operation of the drive mechanism and the shooting of the camera system, and the image processing unit is used to process the acquired images.

3. The battery module testing equipment according to claim 2, characterized in that, The image processing unit includes: Image acquisition module: When the product moves precisely below the camera's field of view, the sensor triggers the camera to take a picture; Image preprocessing module: Performs contrast enhancement, geometric correction, binarization, and filtering on the acquired raw images; Feature extraction and measurement module: Employing edge detection, blob analysis, template matching, and calibration techniques, it identifies and accurately measures key features representing product dimensions in images. Size determination module: compares the measured actual physical dimensions with the preset tolerance range to determine whether the product is qualified; Result Output and Execution Module: Sends the judgment result to the PLC or production line control system, and the PLC controls the actuator to perform the corresponding action and records the product image, measurement value, judgment result, and timestamp information.

4. The battery module testing equipment according to any one of claims 1-3, characterized in that, A lifting and positioning mechanism is provided at the placement position. The lifting mechanism is used to carry and position the tray and battery module to the testing station of the placement position.

5. The battery module testing equipment according to claim 4, characterized in that, The lifting and positioning mechanism includes a mounting frame, on which a lifting cylinder is mounted. The output end of the lifting cylinder is connected to a placement frame, which is used to place the battery module.

6. The battery module testing equipment according to claim 5, characterized in that, The driving mechanism includes a servo moving mechanism, which drives the camera system to move along the X-axis, Y-axis and Z-axis.

7. A detection method, characterized in that, Applied to the testing equipment as described in any one of claims 1-6, comprising the following steps: The drive mechanism drives the camera system to perform a three-dimensional spatial scan of the battery module at the placement location; Image acquisition is triggered at the preset detection point; Preprocessing and feature extraction are performed on the acquired images; Calculate the actual physical dimensions based on the calibration data; Compare the design tolerances to determine the output quality.

8. The detection method according to claim 7, characterized in that, Triggering image acquisition at a preset detection point specifically includes: when the battery module moves to a designated position below the camera's field of view, the camera is triggered to take a picture by an encoder signal or photoelectric sensor to ensure that the image is clear and the position is stable.

9. The detection method according to claim 8, characterized in that, Preprocessing of the acquired images specifically includes: High contrast makes target features more prominent; Geometric correction corrects lens distortion and ensures measurement accuracy; Binarization converts a grayscale image into a black and white image, making it easier to distinguish the background and the target object; Filtering can smooth images or highlight edges.

10. The detection method according to claim 9, characterized in that, Feature extraction from acquired images specifically includes: Edge detection is used to find the outline edges of a product; Blob analysis identifies the shape, location, and area features of connected regions in an image; Template matching compares the product image with a predefined standard template and calculates the differences; Calibration involves photographing a calibration board of known size to establish a precise conversion relationship between image pixel coordinates and actual physical dimensions.

Images