Abstract
The growth of the electronics industry led to a need for efficient methods of testing and validation of printed circuit boards (PCB). It is necessary to identify defects that might appear in a component in early production stages. This task may be performed by automatic inspection systems, showing advantages in speed, accuracy and repeatability, over human inspection. This paper describes a visual inspection system that is able to detect solder paste deposition defects on a PCB. The PCB image is analysed to segment the areas with solder paste and then, by comparing with reference data from the PCB design files, defects are identified, either because of missing or excess solder. The system is based on low cost components, namely a Raspberry Pi Compute Module and two Raspberry Pi v2 cameras. Experimental tests performed with the prototype, regarding the PCB defect detection and execution time, allowed to conclude the system can aid human visual inspection in a production line.
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