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Abstract
A Bell 206B main rotor gearbox was run at high load under test conditions in the Helicopter Transmission Test Facility operated by the Defence Science and Technology Organisation (DSTO) of Australia. The test succeeded in initiating and propagating pitting damage in one of the planet gear support bearings. Vibration acceleration signals were recorded periodically for the duration of the test. The time domain vibration signals were converted to angular domain to minimise the effects of speed variations. Auto-Regressive Moving-Average (ARMA) models were fitted to the vibration data and a change detection problem was formulated in terms of the Generalised Likelihood Ratio (GLR) algorithm. Two different forms of the GLR algorithm in window-limited online form were applied. Both methods succeeded in detecting a change in the vibration signals towards the end of the test. A companion paper submitted by the University of New South Wales outlines the corresponding diagnosis and prognosis algorithms applied to the vibration data.
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Notes on contributors
F.A. Galati
Tony Galati began his working career as an aircraft maintenance engineer, joining the Commonwealth Aircraft Corporation in 1986 as an apprentice. After successfully completing his apprenticeship he continued to work until 1991 when he left due to a decline in work in the local aircraft industry. From 1991 to 1994 he worked as a partner in a small family business before returning as a mature student to study at university. In 1998 he graduated from La Trobe University with a first class honours degree in mathematics, and in 1999 he joined the Defence Science and Technology Organisation of Australia (DSTO) as a professional officer. In 2001 he transferred to a Cadet Research Scientist position to begin his PhD studies. He graduated from The University of Melbourne in 2005 with a PhD in Engineering and commenced work at DSTO in the position of Research Scientist where he worked in the field of helicopter power train diagnostics and vibration analysis. He is currently participating in a staff exchange program, working in the field of technical airworthiness for engine structural integrity.
D. Forrester
David Forrester received a PhD in Mechanical Engineering from Swinburne University of Technology in 1996, a Graduate Diploma in Scientific Leadership from Melbourne University Private in 2002 and a diploma in Computer Science from RMIT in 1987. He has over 20 years experience in machine condition monitoring, vibration analysis, machine dynamics, data acquisition, digital signal processing, computer programming and design of vibration analysis systems. He currently manages DSTO projects in Advanced Condition Assessment Technologies, and the application of DSTO's Vibration Prognostic and Health Management Technology to helicopters and the multi-national Joint Strike Fighter
S. Dey
Subhrakanti Dey was born in India, in 1968. He received the BTech and MTech degrees from the Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur, India, in 1991 and 1993, respectively, and the PhD degree from the Department of Systems Engineering, Research School of Information Sciences and Engineering, Australian National University, Canberra, Australia, in 1996.
He has been with the Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, Australia, since February 2000, where he is now an Associate Professor. From September 1995 to September 1997 and September 1998 to February 2000, he was a postdoctoral Research Fellow with the Department of Systems Engineering, Australian National University. From September 1997 to September 1998, he was a post-doctoral Research Associate with the Institute for Systems Research, University of Maryland, College Park. His current research interests include signal processing for telecommunications, wireless communications and networks, performance analysis of communication networks, stochastic and adaptive estimation and control, and statistical and adaptive signal processing.
Dr Dey currently serves on the Editorial Board of the IEEE Transactions on Automatic Control, Elsevier Systems and Control Letters and IEEE Transactions on Signal Processing.