An image-based feature tracking algorithm for real-time measurement of clad height

This paper presents a novel algorithm for real-time detection of clad height in laser cladding which is known as a layered manufacturing technique. A real-time measurement of clad geometry is based on the use of a developed trinocular optical detector composed of three CCD cameras and the associated interference filters and lenses. The images grabbed by the trinocular optical detector are fed into an algorithm which combines an image-based tracking protocol and a recurrent neural network to extract the clad height in real-time. The image feature tracking strategy is a synergy between a simple image selecting protocol, a fuzzy thresholding technique, a boundary tracing method, a perspective transformation and an extraction of elliptical features of the projected melt pool's images. The proposed algorithm and the trained network were utilized in the process resulting in excellent detection of the clad height at various working conditions in which SS303L was deposited on mild steel. It was concluded that the developed system can detect the clad height independent from clad paths with about 12% maximum error.