AOI inspection of printed circuit board

Automatic Optical Inspection (AOI) technology mainly uses a camera to scan the surface of a printed circuit board for image processing and analysis, accurately detecting and verifying the electrical connections, component positions, and text images of the circuit board. Unlike traditional visual inspection, AOI inspection can not only detect subtle defects that are difficult to observe with the naked eye, but also greatly improve the production efficiency of boards and reduce errors that may be caused by visual fatigue in manual manufacturing processes.

Specifically, AOI technology mainly includes the following three steps:

The first step is preprocessing, which processes the scanned printed circuit board image and converts it into a digital image, that is, from a grayscale image to a binary image. The main purpose of this process is to adapt to different types of circuit boards and process white fonts.

The second step is feature extraction. Utilize image processing algorithms to extract various features of digital images, including electrical connections (solder joints), device positions, text images, etc. For the inspection of solder pads and pins, deep learning or artificial intelligence technology can be used to achieve more precise and accurate detection.

The third step is comparison verification, which uses the collected data to identify the common standards of various circuit boards. This can quickly and accurately determine whether the quality of the circuit board meets the standards, greatly improving the efficiency and overall quality of the board production.

AOI technology has become an important technology in the production and manufacturing of printed circuit boards. It can not only improve the quality and efficiency of printed circuit board production, but also reduce the dependence on the naked eye in manual processes and improve the production speed. In the future, automatic optical detection technology with higher signal-to-noise ratio and more accurate algorithms will bring us more opportunities and efficiency for intelligent manufacturing.