Detection and Mapping of Monopiles in Offshore Wind Farms using Autonomous Surface Vehicles

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Claro, R (Author) Other; Silva, R (Author) Other; Pinto, A (Author) FEUP

Conference proceedings International

Title: GLOBAL OCEANS 2020: SINGAPORE - U.S. GULF COAST

Global OCEANS Singapore - U.S. Gulf Coast Conference

ELECTR NETWORK, OCT 05-30, 2020

Indexing

ISI Web of Knowledge - 5 Citations

Scopus - 4 Citations

Other information

Authenticus ID: P-00T-VP6

DOI: 10.1109/ieeeconf38699.2020.9389348

Abstract (EN): This paper presents an algorithm for mapping monopiles from Offshore Wind Farms (OWF). The ASV (Autonomous Surface Vehicle) surveys the environment, detects and localizes monopiles using situational awareness system based on LiDAR, GPS and IMU (Inertial Measurement Unit) data. The position of the monopile is obtained based on the relative localization between the extrapolated center of the structure that was detected and the ASV. A positive detection of a monopile is referenced to a global positioning frame based on the GPS. Results in a simulator environment demonstrate the ability of this situational awareness system to identify monopiles with a precision of 0.005 m, which is relevant for detecting structural disalignments over time that might be caused by the appearance of scour in the structure's foundation.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4