Konferensartikel

A Data-Driven Sensitivity Analysis Approach for Dynamically Positioned Vessels

Xu Cheng
School of Computer Science and Technology, Tianjin University of Technology, China / Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway

Robert Skulstad
Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway

Guoyuan Li
Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway

Shengyong Chen
School of Computer Science and Technology, Tianjin University of Technology, China

Hans Petter Hildre
Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway

Houxiang Zhang
Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp18153156

Ingår i: Proceedings of The 59th Conference on Simulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway

Linköping Electronic Conference Proceedings 153:22, s. 156-161

Visa mer +

Publicerad: 2018-11-19

ISBN: 978-91-7685-494-5

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

For safety-critical marine operations, the dynamically positioned (DP) vessel should maintain a predetermined heading and position for varying environmental conditions using the thrusters. Studying the effect of each thruster to the capability of DP vessels is significance but challenging. This paper presents a data-driven and variance-based sensitivity analysis (SA) approach that can dig into the ship sensor data to estimate the influence of each thruster for DP operations. Considering high-computational cost of variance-based SA, an Extreme Learning Machine (ELM) -based SA is proposed. To apply the SA to sensor data, an ANN is built and trained on the basis of ship sensor data and then employed as a surrogate model to generate Monte Carlo (MC) samples. A benchmark test shows the correctness of the proposed approach. A case study of SA in DP operation is conducted and the experimental results show that the proposed approach can rank and identify the most sensitive factors. The proposed approach highlights the application of variance-based SA in data-driven modeling for ship intelligence.

Nyckelord

dynamical positioning, sensitivity analysis, thrust analysis, data-driven modeling

Referenser

Inga referenser tillgängliga

Citeringar i Crossref