WIT Press

Artificial Neural Network Approach For Multiple Fault Diagnosis: A Case Study

Price

Free (open access)

Paper DOI

10.2495/AI940081

Volume

6

Pages

10

Published

1994

Size

853 kb

Author(s)

P.V. Suresh & D. Chaudhuri

Abstract

A method is presented for multiple fault diagnosis by means of an Ar- tificial Neural Network (ANN). The major advantage of using an ANN as opposed to any other technique for fault diagnosis in condition ba:-ed maintenance is that the network produces an immediate decision with minimal computation for a given input vector, whereas conventional tech- niques like spectral analysis require complete processing of an input signal to reach a diagnosis. The basic strategy is to train a neural network to recognize the behavior of the machine condition as well as the behavior of the possible system faults. The multi-layer feed forward network is used in this paper with back propagation learning algorithm.

Keywords