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

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.