Damage Evaluation Through Radial Basis Function Network Based Artificial Neural Network Scheme
IR@SERC: CSIR-Structural Engineering Research Centre, Chennai
View Archive Info| Field | Value | |
| Title |
Damage Evaluation Through Radial Basis Function Network Based Artificial Neural Network Scheme
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| Creator |
Lakshmanan, N.
Raghuprasad, B.K. Muthumani, K. Gopalakrishnan, N. Dhiman Basu |
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| Subject |
Damage evaluation
Radial basis function Network Artificial neural network |
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| Description |
The paper presents a health monitoring scheme of bridges, modeled as simply supported beams, through tracking the changes in the measured natural frequencies and damage detection through a trained Artificial Neural Network (ANN) scheme. Radial basis function network (RBFN) is trained with a database of known frequency-damage pair of vectors such that for any available frequency vector, damage vector can be evaluated. Typical error analysis due to measurement noise is also reported.
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| Date |
2009
2009 2008 |
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| Type |
Article
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| Identifier |
Smart Structures and Systems, Vol.4, No.1 2008, pp 99-102,
http://hdl.handle.net/123456789/21 |
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| Language |
en
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| Rights |
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the knowledge. If it is brought to our notice that the rights are violated then
the item would be withdrawn.
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| Publisher |
Structural Engineering Research Centre, Chennai
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