As an important part of modern electronic equipment, PCB board is an information carrier that integrates various electronic components. It is widely used in the electronic field, and its quality can directly affect the performance of the product. With the development of electronic technology and electronic manufacturing, due to the small size and high installation density of chip components, this requires the integration of PCB boards to be further improved. In order to ensure the performance of electronic products, PCB board defect detection technology has become a very critical technology in the electronics industry.
The traditional manual method of detecting PCB defects is prone to missed detections, slow detection speed, low efficiency, and cannot meet the needs of rapid production. Therefore, it is very important to use machines to replace human eyes for measurement and judgment—machine vision inspection technology is very important as a substitute for traditional manual visual inspection. practical significance.
Machine vision is widely used in PCB (Printed Circuit Board), mainly including the following aspects:
1. PCB inspection and quality control: Machine vision can be used to inspect and control the quality of PCBs. By analyzing and comparing PCB images, problems such as soldering defects, component position deviation, short circuits and open circuits on the PCB can be detected, thereby improving the quality and reliability of the PCB.
(1) Imaging comparison-collect the same image and compare it with the original image
(2) Comparison of results – comparison between OK and NG
2. Automated control of PCB assembly process: Machine vision can be used for automated control of PCB assembly process. For example, through visual positioning and image processing algorithms, automatic and precise positioning and assembly of components can be achieved, improving assembly efficiency and accuracy. It mainly finds fixed mark points through visual positioning.
3. Monitoring and management of PCB production process: Machine vision can monitor various aspects of the PCB production process in real time, such as printing, patching, welding, etc. Through the analysis and processing of image data, abnormalities and problems in the production process can be discovered in time, and early warnings and adjustments can be made to improve production efficiency and quality.
4. PCB traceability and data analysis: Machine vision can collect and analyze PCB production data to achieve traceability and data analysis of the PCB production process. Through the processing and comparison of image data, the production process and quality information of each PCB can be tracked, providing a basis for quality control and optimization.
In general, the application of machine vision in PCB can improve the quality and reliability of PCB, improve production efficiency and precision, realize automated control and optimization of the PCB production process, and promote the transformation and upgrading of the PCB industry to intelligent manufacturing.
Defects involved in machine vision in PCB inspection mainly include the following aspects:
1. Welding defects: Machine vision can detect welding defects on PCB, such as missing solder joints, poor welding, short circuits and open circuits of solder joints, etc. By analyzing and comparing images of solder joints, it can be judged whether the quality of the welding meets the requirements.
2. Component position deviation: Machine vision can detect the position deviation of components on the PCB. By analyzing and comparing the images of components, it can be determined whether the components are offset and whether the degree of offset exceeds the allowable range.
3. Missing or misplaced components: Machine vision can detect whether there are missing or misplaced components on the PCB. By analyzing and comparing the images of components, it can be determined whether there are missing or misplaced components.
4. Short circuits and open circuits: Machine vision can detect short circuits and open circuits on PCBs. By analyzing and comparing images of PCB circuits, you can determine whether there are short circuits and open circuits. There may also be defects such as too much tin, too little tin, or lack of tin.
5. Color difference and color mismatch: Machine vision can detect color difference and color mismatch on PCB. By analyzing and comparing the color information of PCB images, it can be determined whether there are color differences and color mismatch problems.
In general, machine vision in PCB inspection can detect problems such as welding defects, component position deviation, missing or misplaced components, short circuits and open circuits, chromatic aberration and color mismatch through the analysis and comparison of PCB images. Improve PCB quality and reliability.