TitleNeural network approach to condition monitoring of industrial robotic-manipulators
OrganizationМogilev State University of Food Technologies
AbstractThe paper presents a novel technique for condition monitoring of industrial robotic manipulators, which is based on neural network analyses of the dynamic model parameters obtained by means of on-line identification. There were derived analytical expressions that allow minimising impact of the measurement errors on the identification accuracy. Efficiency of the proposed technique has been verified by real-life case studies from industrial monitoring systems.
Keywordscondition monitoring, robotic-manipulators, neural network
For citing this articleKazheunikau M.M. Neural network approach to condition monitoring of industrial robotic-manipulators // The Research of the Science City, 2013, no. 1, pp. 42-48.
This Article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).