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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 34
DEVELOPMENTS IN NEURAL NETWORKS AND EVOLUTIONARY COMPUTING FOR CIVIL AND STRUCTURAL ENGINEERING
Edited by: B.H.V. Topping
Paper I.1

Integrity Testing of Concrete Surfaces using Artificial Neural Networks

R. Begum, D. Chamberlain and A. Hirson

Construction Robotics Unit, City University, London, UK

Full Bibliographic Reference for this paper
R. Begum, D. Chamberlain, A. Hirson, "Integrity Testing of Concrete Surfaces using Artificial Neural Networks", in B.H.V. Topping, (Editor), "Developments in Neural Networks and Evolutionary Computing for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 1-6, 1995. doi:10.4203/ccp.34.1.1
Abstract
Reinforced concrete decay has become an important issue, demanding improvements in inspection methods and procedures. Deploying non-destructive testing (NDT) methods by a robot system is seen as a practical contribution. The impact-echo method is one of the NDT methods that is being investigated for inclusion in this. Finite element modelling has been used to simulate defective components subjected to impact-echo systems. The outputs of this are interpreted by a neural network, which is trained using a range of case studies. Preliminary results are encouraging.

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