Pole piece burr detection device based on machine vision

Abstract

The utility model discloses a pole piece burr detection device based on machine vision, which relates to the technical field of burr detection and comprises a longitudinal detection camera mounted on the right side of a prism, and a longitudinal avoidance motor module fixedly connected to the rear side of the longitudinal detection camera. A transverse focus tracking motor module is installed at the bottom of the right side of the longitudinal detection camera, a transverse detection camera is installed on the left side of the bottom of the transverse focus tracking motor module, a Y-axis traveling groove is fixedly connected to the right end of the rear side of the transverse detection camera, and a correlation type edge measurement sensor is fixedly connected to the left side of the bottom of the transverse detection camera. According to the utility model, the transverse detection camera is responsible for carrying out image acquisition on the transverse surface of the workpiece, the transverse focus tracking motor module works cooperatively, and through comprehensive processing of image data in two directions, whether burrs exist on the surface of the workpiece and the specific position, size and shape of the burrs can be judged more comprehensively and accurately, so that burr detection can be completed.

Description

Technical Field

[0001] This utility model relates to the field of burr detection technology, and in particular to a device for detecting electrode burrs based on machine vision. Background Technology

[0002] A burr inspection device is a specialized instrument used to detect minute defects such as burrs, flash, and sharp corners on the surface and inside of workpieces. It is a core component of the inspection equipment, responsible for capturing clear images of the inspected workpiece. Cameras typically feature high resolution, high frame rate, and low noise to ensure the capture of minute burr details. Different types and specifications of cameras, such as industrial cameras, CCD cameras, and CMOS cameras, can be selected depending on the specific inspection requirements. The choice of light source is crucial to providing clear and uniform lighting conditions so that the camera can accurately capture images of the workpiece. Common light sources include LED lights, halogen lamps, and fluorescent lamps. LED lights, with their advantages of high brightness, low energy consumption, long lifespan, and adjustable color and angle, are widely used in burr inspection devices. Through reasonable light source layout and optical path design, shadows and reflections can be reduced, improving image quality.

[0003] As the control core of a machine vision-based electrode burr detection device, the computer control system is responsible for the operation management, data acquisition, image processing, result judgment, and output of the entire equipment. The computer control system typically uses a high-performance computer or embedded system, equipped with professional image processing software and control programs, to conveniently and quickly automate and intelligently implement the detection process. The lens's role is to focus the image of the workpiece onto the camera's sensor. Depending on the different detection objects and working distances, appropriate lens focal lengths and apertures need to be selected. The quality and optical performance of the lens directly affect the clarity and accuracy of the image; therefore, high-quality industrial lenses are usually selected to ensure the reliability of the detection results. However, traditional machine vision-based electrode burr detection devices can only detect from a single angle or direction, failing to comprehensively detect burrs hidden in different positions and angles, easily leading to missed detections. This reduces the accuracy of burr inspection and diminishes the equipment's effectiveness. Utility Model Content

[0004] To overcome the above shortcomings, this utility model provides a machine vision-based electrode burr detection device, which aims to improve the problem that the existing traditional machine vision-based electrode burr detection device can only detect from a single angle or direction, and cannot comprehensively detect burrs hidden in different positions and angles, which easily leads to missed detections and reduces the accuracy of burr inspection.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a machine vision-based electrode burr detection device, comprising a prism, a longitudinal detection camera mounted on the right side of the prism, a longitudinal avoidance motor module fixedly connected to the rear side of the longitudinal detection camera, a lateral tracking motor module mounted on the bottom right side of the longitudinal detection camera, a lateral detection camera mounted on the bottom left side of the lateral tracking motor module, a Y-axis travel groove fixedly connected to the rear right end of the lateral detection camera, and a through-beam edge measurement sensor fixedly connected to the bottom left side of the lateral detection camera.

[0006] As a further description of the above technical solution:

[0007] The left side of the through-beam edge measurement sensor is rotatably connected to a rotating rod.

[0008] As a further description of the above technical solution:

[0009] The bottom right side of the through-beam edge measurement sensor is rotatably connected to a rotating rod.

[0010] As a further description of the above technical solution:

[0011] The rear right end of the through-beam edge measurement sensor is rotatably connected to a rotating rod.

[0012] As a further description of the above technical solution:

[0013] Both the prism and the longitudinal detection camera are square in design.

[0014] This utility model has the following beneficial effects:

[0015] 1. In this utility model, a transverse detection camera is responsible for acquiring images of the transverse surface of the workpiece. A transverse tracking motor module works in conjunction with the transverse detection camera. Based on the actual position and surface condition of the workpiece, the motor drives the adjustment of the focal length and position of the transverse detection camera to ensure that the camera can always capture clear and accurate images of the transverse surface of the workpiece. The image data acquired by the longitudinal detection camera is also transmitted to the image processing system and integrated with the data acquired by the transverse detection camera. Through the comprehensive processing of the image data from both directions, it is possible to more comprehensively and accurately determine whether there are burrs on the surface of the workpiece and the specific location, size, and shape of the burrs, thus completing the burr detection. Attached Figure Description

[0016] Figure 1 This is a front perspective view of a machine vision-based electrode burr detection device proposed in this utility model.

[0017] Figure 2 This is a partial structural exploded view of a machine vision-based electrode burr detection device proposed in this utility model.

[0018] Figure 3 This is a partial structural diagram of a machine vision-based electrode burr detection device proposed in this utility model;

[0019] Figure 4 This is a partial structural diagram of a machine vision-based electrode burr detection device proposed in this utility model.

[0020] Figure 5 This is a partial structural schematic diagram of a machine vision-based electrode burr detection device proposed in this utility model.

[0021] Legend:

[0022] 1. Prism; 2. Through-beam edge measurement sensor; 3. Lateral detection camera; 4. Lateral tracking motor module; 5. Longitudinal avoidance motor module; 6. Longitudinal detection camera; 7. Y-axis travel slot; 8. Rotating rod one; 9. Rotating rod two; 10. Rotating rod three. Detailed Implementation

[0023] The technical solutions of the present utility model will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present utility model, and not all embodiments. Based on the embodiments of the present utility model, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of the present utility model.

[0024] Please see the appendix Figure 1 - Appendix Figure 3 The present invention provides an embodiment of an electrode burr detection device based on machine vision, comprising a prism 1, a longitudinal detection camera 6 mounted on the right side of the prism 1, a longitudinal avoidance motor module 5 fixedly connected to the rear side of the longitudinal detection camera 6, a transverse tracking motor module 4 mounted on the bottom right side of the longitudinal detection camera 6, a transverse detection camera 3 mounted on the bottom left side of the transverse tracking motor module 4, a Y-axis travel groove 7 fixedly connected to the rear right end of the transverse detection camera 3, and a through-beam edge measurement sensor 2 fixedly connected to the bottom left side of the transverse detection camera 3.

[0025] Specifically, this longitudinal inspection camera 6 not only possesses high-resolution imaging capabilities but also rapid image processing capabilities. It can capture and process image information from the right side of the prism 1 in real time to ensure accurate capture of the image of the required detection area. At the bottom right side of the longitudinal inspection camera 6, a lateral tracking motor module 4 is also installed. This lateral tracking motor module 4 is also a high-precision drive device. After receiving a control signal, it can drive the camera lens to move laterally. At the rear right end of the lateral inspection camera 3, a Y-axis travel groove 7 is also fixedly connected. This Y-axis travel groove 7 is a guide rail structure that can provide stable support and guidance for the lateral inspection camera 3, enabling it to move in the direction of the Y-axis travel groove 7. This improves the stability and accuracy of the entire device and can also meet the needs of tracking target objects.

[0026] Please see the appendix Figure 3 - Appendix Figure 5 Rotating rod 2 9 is rotatably connected to the bottom right side of the through-beam edge measurement sensor 2, rotating rod 1 8 is rotatably connected to the left side of the through-beam edge measurement sensor 2, and rotating rod 3 10 is rotatably connected to the rear right end of the through-beam edge measurement sensor 2. Both prism 1 and longitudinal detection camera 6 adopt a square design.

[0027] Specifically, by cooperating with rotating rod 8 and rotating rod 9, the tilt angle and position of the through-beam edge measurement sensor 2 can be further adjusted to meet the measurement needs in different scenarios and improve measurement stability. A rotating rod 10 is also rotatably connected. The addition of rotating rod 10 allows the through-beam edge measurement sensor 2 to be adjusted in all directions to meet more complex measurement needs. Whether adjusting the vertical angle or the horizontal angle of the sensor, it can be achieved by rotating rod 10.

[0028] Working Principle: The lateral detection camera 3 is responsible for acquiring images of the workpiece's lateral surface. The lateral tracking motor module 4 works in conjunction, adjusting the focal length and position of the lateral detection camera 3 according to the actual position and surface condition of the workpiece, ensuring that the camera can always clearly and accurately capture images of the workpiece's lateral surface. The through-beam edge measurement sensor 2 plays an important role in lateral detection, accurately measuring the position and shape information of the workpiece's lateral edges. When the workpiece is placed in the detection area, the through-beam edge measurement sensor 2 quickly senses the workpiece edge, providing accurate edge positioning reference for the lateral detection camera 3. This allows the camera to focus more specifically on the workpiece edge area when acquiring images, improving the detection accuracy of burrs at the edges. The longitudinal detection camera 6 is mainly responsible for acquiring image information of the workpiece's longitudinal surface. During this process, the longitudinal obstacle avoidance motor module 5, based on the height of the workpiece and the possible obstacles, also transmits the image data acquired by the longitudinal detection camera 6 to the image processing unit. This data is integrated and analyzed with the data acquired by the lateral detection camera 3. Through comprehensive processing of image data from both directions, the system can more comprehensively and accurately determine whether there are burrs on the workpiece surface and the specific location, size, and shape of the burrs, thus completing burr detection.

[0029] Finally, it should be noted that the above description is only a preferred embodiment of the present utility model and is not intended to limit the present utility model. Although the present utility model has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present utility model should be included within the protection scope of the present utility model.

Claims

1. A machine vision-based electrode burr detection device, comprising a prism (1), characterized in that: A longitudinal detection camera (6) is installed on the right side of the prism (1). A longitudinal avoidance motor module (5) is fixedly connected to the rear side of the longitudinal detection camera (6). A lateral tracking motor module (4) is installed at the bottom right side of the longitudinal detection camera (6). A lateral detection camera (3) is installed on the bottom left side of the lateral tracking motor module (4). A Y-axis travel groove (7) is fixedly connected to the rear right side of the lateral detection camera (3). A through-beam edge measurement sensor (2) is fixedly connected to the bottom left side of the lateral detection camera (3).

2. The electrode burr detection device based on machine vision according to claim 1, characterized in that: The left side of the through-beam edge measurement sensor (2) is rotatably connected to a rotating rod (8).

3. The electrode burr detection device based on machine vision according to claim 1, characterized in that: The bottom right side of the through-beam edge measurement sensor (2) is rotatably connected to a rotating rod (9).

4. The electrode burr detection device based on machine vision according to claim 1, characterized in that: The right rear end of the through-beam edge measurement sensor (2) is rotatably connected to a rotating rod three (10).

5. The electrode burr detection device based on machine vision according to claim 1, characterized in that: Both the prism (1) and the longitudinal detection camera (6) adopt a square design.

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