Quality Detection Method for Controller Process Based on Mask R-CNN Network Model

In the production process of an automatic production line, quality detection is an important link to ensure the product quality. Visual detection is of low efficiency, and easy fatigue, unable to ensure quality and meet test standards. To solve the above problems, this paper introduces a detection method based on machine vision technology and Mask R-CNN network model. Such method is not affected by the position of the controller circuit board in the image, and facilitates the coating quality detection of hot melt adhesive for components on the controller circuit board. A visual detection system for the controller quality process is finally developed to realize the automatic detection of the controller process quality, which improves the detection efficiency and ensures the quality.