Kirkegaard, Poul Henning

Rytter, A.

English

The paper explores the potential of using a Multilayer Perceptron (MLP) network trained with the Backpropagation algorithm for damage assessment of free-free cracked straight steel beam based on vibration measurements. The problem of damage assessment, i.e. detecting, locating and quantifying a damage, is essentially a pattern recognition problem

    Aalborg UniversitetUse of a Neural Network for Damage Detection and Location in a Steel MemberKirkegaard, Poul Henning; Rytter, A.Publication date:1992Document VersionEarly version, also known as pre-printLink to publication from Aalborg UniversityCitation for published version (APA):Kirkegaard, P. H., & Rytter, A. (1992). Use of a Neural Network for Damage Detection and Location in a SteelMember. Dept. of Building Technology and Structural Engineering, Aalborg University. Fracture and DynamicsVol. R9245 No. 41General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.            ? Users may download and print one copy of any publication from the public portal for the purpose of private study or research.            ? You may not further distribute the material or use it for any profit-making activity or commercial gain            ? You may freely distribute the URL identifying the publication in the public portal ?Take down policyIf you believe that this document breaches copyright please contact us at vbn@aub.aau.dk providing details, and we will remove access tothe work immediately and investigate your claim.Downloaded from vbn.aau.dk on: December 27, 2020

Use of a Neural Network for Damage Detection and Location in a Steel Member

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Use of a Neural Network for Damage Detection and Location in a Steel Member

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