Multi-anemometer optimal layout and weighted fusion method for estimation of ship surface steady-state wind parameters

Abstract

As an important observation measure of ship surface wind field, the shipborne anemometer can provide continuous wind-field observation records, which plays an important role in combating ships, safe navigation of ships, and safe takeoff and landing of shipboard aircraft. When the wind passes through the superstructure of the hull, the airflow field in the layout area of the anemometer becomes distorted, thus increases the measurement errors of the wind parameters. However, this error can be corrected using the optimal estimation strategy, which can more reliably and accurately evaluate changes in the ship surface airflow field. In this study, based on computational fluid dynamics (CFD) theory, the characteristics of the ship surface airflow field were simulated using CFD theory. The relationship between the measurement error of the anemometer and its placement was studied, and the placement of the anemometer with relatively less turbulence effect was indicated. The anemometer measurement bias at different locations was corrected, and the four-anemometer optimal weighted fusion (FAF) and bias correction combined with FAF (FAF-BC) algorithm were proposed to estimate the wind parameters on the ship surface. Performance of two algorithms were evaluated under the ideal, anemometer noise, and temporal uncertainty combined with anemometer noise conditions. Compared with the common dual-anemometer (DAT) algorithm, the results under different conditions indicate that the absolute error of wind direction (MAE) in FAF and FAF-BC algorithm are reduced by at least 2.80° and 7.99°, and the relative error of wind speed (MRE) are reduced by at least 11.09% and 13.45%, respectively, and the estimation results are more stable.