Intelligent condition monitoring system (ICMS) for unmanned air vehicle (UAV), unmanned surface vehicle (USV) and autonomous underwater vehicle (AUV), robots: a feasibility study

Date

2013

Authors

Xu, X.
Anvar, A.

Editors

Piantadosi, J.
Anderssen, R.S.
Boland, J.

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Conference paper

Citation

MODSIM2013: 20th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2013 / J. Piantadosi, R. S. Anderssen and J. Boland (eds.): pp.977-983

Statement of Responsibility

Xiang Xua and Amir Anvara

Conference Name

International Congress on Modelling and Simulation (20th : 2013 : Adelaide, South Australia)

Abstract

An Intelligent Condition Monitoring System (ICMS) is important for different types of vehicles used to perform unmanned tasks. The main function of the ICMS is to ensure that the unmanned vehicle is in robust condition. In this paper, three main sections are built in ICMS. That is, structure health monitoring, power management and speed detection. For the structure monitoring, the pressure distribution of the vehicle is obtained by using CFD modelling. CFD is fluent software that contains the broad physical modelling capabilities needed to model flow, turbulence and heat transfer ranging from air flow over an aircraft wing to combustion in a furnace. In the test, the vehicle is required to work in regular condition, and the pressure distribution is obtained. The pressure distribution graph indicates the pressure at each part of the structure. Then, the part of the structure that needs to be monitored is determined. In relation to power management, the DS2788 as a battery chip constantly monitors the status of multiple cell batteries. These include the current, voltage, temperature and available capacity. It is applied for the detection remaining power in the battery. For the speed detection part, the RPM sensors are used to detect speed in real time and to make sure that the vehicle is running in the speed expected.

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22nd National Conference of the Australian Society for Operations Research — ASOR 2013 DSTO led Defence Operations Research Symposium — DORS 2013

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