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Time-delay neural networks in damage detection of railway bridges

Barai, SV and Pandey, PC (1997) Time-delay neural networks in damage detection of railway bridges. In: Advances in Engineering Software, 28 (1). pp. 1-10.

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The recent developments in multilayer perceptron using the backpropagation algorithm, has opened up new possibilities in structural identification. Limitation of traditional neural networks (TNN) in dealing with patterns that may vary in time domain has given birth to time-delay neural networks (TDNN). In the present paper the TNN and the TDNN have been implemented in detecting the damage in bridge structure using vibration signature analysis. A comparative study has been carried out for the various cases of complete as well as incomplete measurement data. It has been observed that TDNNs have performed better than Tows in this application.

Item Type: Journal Article
Publication: Advances in Engineering Software
Publisher: Elsevier
Additional Information: Copyright of this article belongs to Elsevier.
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Date Deposited: 23 Jun 2007
Last Modified: 19 Sep 2010 04:36
URI: http://eprints.iisc.ac.in/id/eprint/10163

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