Motion and condition monitoring of an industrial robot based on digital twins

Nguyen, Nguyen, My, Chu Anh, Le, Chi Hieu, Zlatov, Nikolay, Hristov, Georgi, Gao, James, Nguyen, Ho Quang, Mahmud, Jamaluddin, Bui, Trung Thanh and Packianather, Michael S. ORCID: https://orcid.org/0000-0002-9436-8206 2024. Motion and condition monitoring of an industrial robot based on digital twins. Presented at: 3rd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2022), 10-13 November 2022. Published in: Long, B.T ed. Proceedings of the 3rd Annual International Conference on Material, Machines and Methods for Sustainable Development. Lecture Notes in Mechanical Engineering Cham, Switzerland: pp. 445-446. 10.1007/978-3-031-57460-3_49

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Abstract

This paper presents a study and experimental evaluations of monitoring industrial robots based on a digital twin system, with the focus on motion monitoring and condition monitoring. Motion monitoring aims to detect, monitor, and control motion and speed, especially evaluation of the working area and determination of the motion trajectory of a robot. Condition monitoring aims to evaluate the health state during operation, to determine the condition of in-service equipment or systems, in order to predicts the health and safety for predictive maintenance, and to estimate the remaining useful life of in-service equipment or systems. The conceptual digital twin system is deployed on the Game Engine Unity3D which has an intuitive user interface, with the emerging 3D graphics technologies, and the capability of providing the bidirectional connection between the virtual robot and the real robot. The proof-of-concept prototype for the proposed conceptual digital twin system was successfully developed for the basic tests and investigations, as the foundation for further development of the cost-effective digital twin models and systems which can be used for higher educations or research, with potentials for industrial applications.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering
ISBN:	978-3-031-57459-7
ISSN:	2195-4356
Last Modified:	05 Jun 2024 09:00
URI:	https://orca.cardiff.ac.uk/id/eprint/169291

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