Rossi Giovanni Battista, Crenna Francesco, Piscopo Vincenzo, Scamardella Antonio
Department of Mechanical, Energy, Management and Transportation Engineering, University of Genova, Via Opera Pia 15A, 16145 Genova, Italy.
Department of Science and Technology, University of Naples "Parthenope", Centro Direzionale Isola C4, 80143 Naples, Italy.
Sensors (Basel). 2020 Mar 5;20(5):1416. doi: 10.3390/s20051416.
The monitoring of sea state conditions, either for weather forecasting or ship seakeeping analysis, requires the reliable assessment of the sea spectra encountered by the ship, either as a final result or intermediate step for the measurement of the relevant wave-motion parameters. In current analyses, different spectrum estimation methods, namely the Welch, Thomson and ARMA models, have been applied and compared based on a set of random wave signals, with different durations, representative of several sea state conditions. Subsequently, two sea spectrum reconstruction techniques were described and applied in order to detect the main sea state parameters, namely the significant wave height, the mean wave period and the spectrum peak enhancement factor. The performances of both spectral analysis and sea state reconstruction methods are discussed in order to provide some preliminary guidelines for practical application purposes. In this respect, based on current results, the Welch and Thomson methods seem to be the most promising techniques, combined with the nonlinear least-square reconstruction technique.
无论是用于天气预报还是船舶耐波性分析，对海况条件的监测都需要可靠地评估船舶遇到的海谱，这要么是测量相关波浪运动参数的最终结果，要么是中间步骤。在当前的分析中，基于一组具有不同持续时间、代表几种海况条件的随机波浪信号，应用并比较了不同的谱估计方法，即韦尔奇（Welch）、汤姆森（Thomson）和自回归滑动平均（ARMA）模型。随后，描述并应用了两种海谱重建技术，以检测主要的海况参数，即有效波高、平均波周期和谱峰增强因子。讨论了谱分析和海况重建方法的性能，以便为实际应用提供一些初步指导。在这方面，根据目前的结果，韦尔奇和汤姆森方法似乎是最有前途的技术，并与非线性最小二乘重建技术相结合。
