Article

Cover

Title

Neural network approach to condition monitoring of industrial robotic-manipulators

Author

M.M. Kazheunikau

Organization

Мogilev State University of Food Technologies
Mogilev, Belarus

Abstract

The 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.

Keywords

condition monitoring, robotic-manipulators, neural network

For citing this article

Kazheunikau 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).