Vibration Based Damage Assessment of a Civil Engineering Structures using a Neural Networks

Poul Henning Kirkegaard, A. Rytter

    Research output: Book/ReportReportResearch

    1250 Downloads (Pure)

    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.
    Original languageEnglish
    Place of PublicationAalborg
    PublisherDept. of Building Technology and Structural Engineering, Aalborg University
    Number of pages15
    Publication statusPublished - 1994
    SeriesFracture and Dynamics
    Number53
    VolumeR9408
    ISSN0902-7513

    Bibliographical note

    1st Workshop of the European Group for Structural Engineering Applications of Artifical Intelligence, Lausanne, March, 1994

    PDF for print: 22 pp.

    Keywords

    • Neural Network
    • System Identification
    • Damage Assessment
    • Damage Detection

    Fingerprint

    Dive into the research topics of 'Vibration Based Damage Assessment of a Civil Engineering Structures using a Neural Networks'. Together they form a unique fingerprint.

    Cite this