Artificial Neural Network Approach For Multiple Fault Diagnosis: A Case Study
Price
Free (open access)
Volume
6
Pages
10
Published
1994
Size
853 kb
Paper DOI
10.2495/AI940081
Copyright
WIT Press
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.
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