@book{0ab206d0a86a11da8341000ea68e967b,
title = "Vibration Based Damage Assessment of a Civil Engineering Structures using a Neural Networks",
abstract = "In this paper the possibility of using a Multilayer Perceptron (MLP) network trained with the Backpropagation Algorith as a non-destructive damage assessment technique to locate and quantify a damage in Civil Engineering structures is investigated. Since artificial neural networks are proving to be an effective tool for pattern recognition, the basic idea is to train a neural network with simulated values of modal parameters in order to recognize the behaviour of the damaged as well as the undamaged structure. Subjecting this trained neural network to measured modal parameters should imply information about damage states and locations. ",
keywords = "Neural Network, System Identification, Damage Assessment, Damage Detection, Neural Network, System Identification, Damage Assessment, Damage Detection",
author = "Kirkegaard, {Poul Henning} and A. Rytter",
note = "1st Workshop of the European Group for Structural Engineering Applications of Artifical Intelligence, Lausanne, March, 1994 PDF for print: 22 pp. ",
year = "1994",
language = "English",
series = "Fracture and Dynamics",
publisher = "Dept. of Building Technology and Structural Engineering, Aalborg University",
number = "53",
address = "Denmark",
}