Parameter estimation for online condition monitoring of robotic machines

T. Hui, Honghai Liu, David J. Brown

Research output: Contribution to journalArticlepeer-review

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Abstract

This paper proposes a novel learning approach to online condition monitoring of robotic machines. The real-time learning process comprises three stages, domain knowledge defining, random learning and ordinal learning. Domain knowledge defining abstracts the model of a robotic machine; random learning and ordinal learning stages train the parameters of the abstract model with random data selection and ordinal data selection, respectively. Simulation results have proved that the pro-posed method is efficient and feasible for online fault diagnosis of robotic machines.
Original languageEnglish
Pages (from-to)185-196
Number of pages12
JournalFacta Universitatis Series Mechanics, Automatic Control and Robotics
Volume7
Issue number1
Publication statusPublished - 2008

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