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The automatic interpretation of vibration data from gas turbines

Published online by Cambridge University Press:  04 July 2016

R.J. Allwood ,
S.P. King  and
N.J. Pitts
R.J. Allwood
Affiliation:
Department of Civil and Building Engineering, Loughborough University of Technology, Loughborough
S.P. King
Affiliation:
Rolls-Royce, Derby
N.J. Pitts
Affiliation:
Rolls-Royce, Bristol
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Abstract

A knowledge-based computer system has been developed to automatically scan and interpret graphical displays of vibration data taken from strain gauges mounted on the blades of gas turbines performing acceleration tests. The various characteristic lines which appear on these displays are recognised and classified and the lines representing modes of vibration are examined to determine which mode is being excited and the severity of the excitation. All lines are compared, by a “blackboard” technique, against those predicted by the system working from the engine specification, laboratory tests and finite element analyses. Any unexpected features are reported for manual inspection.

Several series of tests have now been made on the system. In the first test on 130 diagrams, every one of over 3000 features visible to the human eye was detected and then classified.

Type
Research Article
Information
The Aeronautical Journal , Volume 100 , Issue 993 , March 1996 , pp. 99 - 107
Copyright
Copyright © Royal Aeronautical Society 1996 

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References

1. Allwood, R.J. and Christie, P.I. Vibration analysis of gas turbines by an intelligent knowledge-based system, Proc Institution Mech Eng, 1991,205, pp 115–121.Google Scholar
2. Billington, R. .The application of expert systems for vibration based diagnosis, condition monitoring and diagnostic technology, 1991, 1, (3), pp 99–101.Google Scholar
3. Anvar, A.M. and Massod, S.H. A knowledge-based system for vibration monitoring in turbo-generator machinery, The Institution of Engineers of Australia, Vibration and Noise Conference Melbourne, 1990, pp 222–226.Google Scholar
4. Scheibel, J.R., Desilva, H.M., Fritsch, T.J. and Smiley, R.G. VIAD expert system for vibration monitoring, Proceedings of the American Power Conference, 1991, 53, pp 44–47.Google Scholar
5. Nishie, Y., Ikeda, H. and Kirkuchi, M. Development of an expert system for diagnosis of rotating machines, Q Railway Tech Res (Japan), 1990, 31, (1), pp 7–14.Google Scholar
6. Englemore, R.S. and Morgan, A.J. Blackboard Systems (The In sight series of Artificial Intelligence), Addison Wesley, 1988, pp 2–7.Google Scholar
7. King, S.P. and Allwood, R.J. A blackboard approach to the inter pretation of vibration characteristics in gas turbines, Proc 6th Inter national Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Edinburgh, 1993, pp 123–131.Google Scholar
8. Allwood, R.J., King, S.P. and Pitts, N.J. A knowledge-based black board system to interpret graphical data from vibration tests of gas turbines, Proc Conf Applications of Artificial Intelligence in Engineering VII, Waterloo, Canada, 1992, pp 271–288.Google Scholar