An image-based feature tracking algorithm for real-time measurement of clad height |
| |
Authors: | Mehrdad Iravani-Tabrizipour Ehsan Toyserkani |
| |
Affiliation: | (1) Department of Mechanical and Mechatronics Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON, Canada, N2L3G1 |
| |
Abstract: | 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. |
| |
Keywords: | Laser cladding Trinocular CCD-based optical detector Image processing Recurrent neural network Perspective transformation |
本文献已被 SpringerLink 等数据库收录! |