The application provides a
machine vision-based
friction stir welding seam
quality monitoring system and method, and relates to the technical field of
friction stir welding. The
friction stir welding seam
quality monitoring system is installed in a main body of a friction stir
welding device. The
system comprises, which are connected in sequence, a vision module, a three-dimensional reconstruction module, a quality prediction module, a decision module and a
data transmission module. The vision module, the three-dimensional reconstruction module, the quality prediction module, the decision module and the
data transmission module are electrically connected. The
welding seam
quality monitoring method realizes three-dimensional reconstruction of the surface state of a
welding seam in a
welding process through the friction stir welding seam quality
monitoring system, and utilizes a
convolutional neural network to perform online nondestructive detection and evaluation on the surface defects, internal defects and welding quality of the friction stir welding seam, thereby filling the technical gap in online intelligent detection of internal defects of friction stir welding.