A knowledge model for gray scale image interpretation with emphasis on welding defect classification—An ontology based approach

Image interpretation is the process of mapping the content of the image to a real world object that is easily understandable by any user. To perform any image interpretation, the image information is extracted through feature extraction and is then mapped to the known objects of any domain. In order to retain the extracted feature information of the domain for reusability, a proper modeling of the image content is required. This helps in maximizing the leverage of knowledge in image interpretation of specific domain through a computer interpretable model which results as a knowledgebase. This paper focuses on such a modeling for gray scale image interpretation emphasizing on welding defect classification which resulted in domain ontology of welding defects. Domain ontology is created by formalizing the information related to the gray scale image and its significance in welding defects. The developed system is evaluated using industrial radiographs to detect and classify welding defects.     

A barrier composite energy function approach for robot manipulators under alignment condition with position constraints

In this work, we propose an iterative learning control scheme with a novel barrier composite energy function approach to deal with position constrained robotic manipulators with uncertainties under alignment condition. The classical assumption of initial resetting condition is removed. Through rigorous analysis, we show that uniform convergence is guaranteed for joint position and velocity tracking error. By introducing a novel tan‐type barrier Lyapunov function into barrier composite energy function and keeping it bounded in closed‐loop analysis, the constraint on joint position vector will not be violated. A simulation study has further demonstrated the efficacy of the proposed scheme. Copyright © 2013 John Wiley & Sons, Ltd.