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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/3558
Title: Time-delay neural networks in damage detection of railway bridges
Authors: Barai, Sudhir Kumar
Keywords: Civil Engineering
Artificial neural networks
Railway bridges
Damage detection
Issue Date: Jan-1997
Publisher: Elsiever
Abstract: 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 TNNs in this application.
URI: https://www.sciencedirect.com/science/article/pii/S0965997896000385
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/3558
Appears in Collections:Department of Chemistry

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