✦ LIBER ✦

Modeling and classification of non-linear systems using neural networks--II. A preliminary experiment

✍ Scribed by K. Worden; G.R. Tomlinson; W. Lim; G. Sauer

Publisher: Elsevier Science
Year: 1994
Tongue: English
Weight: 679 KB
Volume: 8
Category: Article
ISSN: 0888-3270
DOI: 10.1006/mssp.1994.1030

No coin nor oath required. For personal study only.

✦ Synopsis

In the first part of this study, a method for classifying non-linear systems using neural networks was proposed and validated using data from numerical simulation. In order to extend this validation to experimental data, a system was required with a repeatable non-linearity of controllable severity, which could be simply relocated within the system. A preliminary study is presented here of a free-free beam containing a non-linear gap element which induces a bilinear stiffness characteristic. It is shown that the dynamic behaviour is characteristic of a beam with an actual fatigue crack. A neural network is trained to distinguish between cracked and uncracked states of the beam when presented with measured time data.

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