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Proceedings Paper

Helicopter gearbox diagnostics and prognostics using vibration signature analysis
Author(s): B. Eugene Parker; Todd M. Nigro; Monica P. Carley; Roger L. Barron; David G. Ward; H. Vincent Poor; Dennis Rock; Thomas A. DuBois
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Paper Abstract

Rotocraft safety, survivability, and mission effectiveness depend on the structural integrity of dynamic components. The need exists to develop an on-board, continuous vibration diagnostic system to detect and to prognosticate faults in these components prior to failure. This paper overviews a generic fault detection, isolation, and estimation (FDIE) architecture for condition-based machinery maintenance applications. Neural network-based fault pattern recognition is used to analyze normal and defect vibration signatures in helicopter transmissions. Data from nine seeded-fault test-rig experiments, each corresponding to one of six different fault/no fault conditions, were used to train and evaluate polynomial neural networks at pattern classification tasks. Features were generated using the amplitude spectra of the time-series vibration signatures. The Algorithm for Synthesis of Polynomial Networks for Classification (CLASS), a neural network software package that utilizes a constrained, minimum-logistic-loss criterion for multiclass problem, was used to perform the pattern recognition tasks. By employing a multiple-look post-processing strategy, perfect vibration signature classification was achieved.

Paper Details

Date Published: 2 September 1993
PDF: 12 pages
Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); doi: 10.1117/12.152553
Show Author Affiliations
B. Eugene Parker, Barron Associates, Inc. (United States)
Todd M. Nigro, Barron Associates, Inc. (United States)
Monica P. Carley, Barron Associates, Inc. (United States)
Roger L. Barron, Barron Associates, Inc. (United States)
David G. Ward, Barron Associates, Inc. (United States)
H. Vincent Poor, Princeton Univ. (United States)
Dennis Rock, Boeing Defense & Space Group (United States)
Thomas A. DuBois, Boeing Defense & Space Group (United States)

Published in SPIE Proceedings Vol. 1965:
Applications of Artificial Neural Networks IV
Steven K. Rogers, Editor(s)

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