WIT Press

Fault Prognosis For Large Rotating Machinery Using Neural Network

Price

Free (open access)

Paper DOI

10.2495/AI940091

Volume

6

Pages

7

Published

1994

Size

542 kb

Author(s)

X. Li, S.Y. Pei, Z. Han & L. Qu

Abstract

The way for predicting vibration value and forecasting serious malfunctions for large rotating machinery using neural networks is proposed in this paper. The topological architecture of a multi-layer neural network for this purpose and the training strategies are established. It is obtained that the back propagation neural network possess the strong ability in time series prediction by comparing it with the autoregresive modeling method. With the neural network, one-day prediction of the rotor vibration value for a 200 MW turbo-generator has been carried out quite accurately. The surging state in a CO2 compressor has also been prognosed in the same way but taking multi related values of the process parameters as the input of the neural net. 1 Introduction In

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