Research And Application Of PCB Detection Device

The smart grid is the new trend in the development of electric power system in the world in twenty-first Century. Smart electric meter and its supporting equipment comprising senior measuring system, which is very important in the construction of the smart grid. Quality of smart electric meter will affect the effectiveness of smart grid construction In this context, quality consistency problems of smart electric meter has attracted increasing attention. Quality consistency means the bid smart electric meter have the same quality status with the on-site operation smart electric meter., including PCB (printed circuit board) quality, the quality of smart electric meter software and material. PCB quality consistency Is a key part of quality consistency. With the continuous improvement of production technology, PCB technology develops into high precision, super fine and multi direction.With the smart electric meter demand increases day by day, It is very important to establish a detection system which can automatic and fast batch alignment the PCB quality consistency.This paper first lists the commonly used PCB automatic detection technology, Through comparison and analysis, select AOI technology, using PCB detection algorithm based on hierarchical template matching. And then put forward the PCB conformance testing system based on five axis linkage control subsystem.and design the architecture of the system, give a detailed description of the core part of the system, The five axis linkage control subsystem is key part of smart electric meter PCB consistency detection system hardware, so that the camera can not only perform plane scan on the PCB, but also through the PCB to achieve the positioning table of X, Y and Z axis direction and the horizontal rotation, swing, namely the five axis motion, thus can scan side and multi angle, improve the ability of detection system and precision.PCB plate classification template matching detection algorithm is used to fast realize image recognition and matching. After the completion of system development, we apply it to practice, after lot’s of tests, we analysis problems, propose solutions.