Application of a MLP neural network for compensation of distortions in strain gauges measurements due to temperature variations in offshore operation of a flexible pipe-lay vessel

Author

Barbosa, C. Hall ; Kühner, G.S. ; Lima, E. Andrade ; Vellasco, M. ; Pacheco, M.

Author_Institution

Pontificia Univ. Catolica do Rio de Janeiro, Brazil

Volume

1

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

92

Lastpage

96

Abstract

Strain gauges are often affected by temperature variations, yielding unacceptable distortions on load measurements. Such effects have been observed on a flexible pipe-lay vessel, in which the load indication presents a large distortion around noon everyday. In this paper, a neural network scheme is employed to overcome such difficulties

Keywords

compensation; multilayer perceptrons; oil technology; signal processing; strain gauges; MLP neural network; distortion compensation; flexible pipe-laying vessel; multilayer perceptron; offshore operation; strain gauge measurements; temperature variations; Capacitive sensors; Distortion measurement; Intelligent networks; Neural networks; Ocean temperature; Pulleys; Sea measurements; Strain measurement; Temperature measurement; Winches;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on

Conference_Location

Honolulu, HI

ISSN

1098-7576

Print_ISBN

0-7803-7278-6

Type

conf

DOI

10.1109/IJCNN.2002.1005449

Filename

1005449