【作者】 赫亮；

【导师】 王言英；

【作者基本信息】 大连理工大学 ， 船舶与海洋结构物设计制造， 2005， 硕士

【摘要】 本文针对欧洲北海的一次为期六天的风暴中定点测得的波浪海面瞬时升高数据样本,应用FFT快速傅立叶变换方法分析计算得到相应的能量谱密度函数（靶谱）。根据北海ALWYN平台对于一次风暴的观测记录,进行了对经验谱公式JONSWAP谱的谱峰升高因子和峰频控制因子进行了修正。结果表明,谱矩m₀随参变量γ和峰频ω_p随T₁×ω_p变化显著,当T₁×ω_p=5,γ=3.27时,m₀与ω_p的预报值同实测分析结果符合得令人满意。应当指出,所测的波浪记录的平均过零周期和谱的零阶矩相差很大,不属于同一海况,这与观测条件是在一次风暴中测得结果的相符。通过对409个子样给出的有义波高和某一时段的统计值与实际根据FFT计算得到的有义波高和这一时段的统计值进行比较,发现两者符合得尚好。 传统的风浪谱估计方法FFT法假定在所取时间滞后数乘机之外其协方差函数为零,在周期图中假定所取数据长度为一完整周期。其谱估计实际为频谱和窗函数的乘积。本文重点进行了最大熵法风浪谱估计和传统谱估计方法的分析比较,讨论了最大熵法的原理。结果表明,最大熵法优于传统方法如快速付立叶变换方法,最大熵法避免了一些不切实际的假设,不需要使用窗函数。减少了谱泄漏,提高了谱估计精度。对于北海风浪,采用赤池定阶法和经验定阶法相结合的办法确定最小的阶数。同时,最大熵对已有的时间序列的信息量保持最大,当样本容量较小时,也能得到较好的谱估计结果。为风浪谱估计又提供了一种有效的方法。更多还原

【Abstract】 In this paper, the instantaneous surface elevation data sample, which is from a recording project in executed in North Sea and has a six day’s duration, is analyzed. The corresponding energy spectral density function (target spectrum) was estimated by using the transformation method based on FFT. Based on a set of recording data form observation platform called Alwyn, the empirical spectrum expression is modified in terms of its peak elevation parameter and peak frequency position parameter. The results shows that spectral moment m0 vary remarkablywith dependent variable y and peak frequency ωp vary remarkably with T1×ωp. When T1×ωp=5 and γ = 3.27 ,the predictive values of m0 and ωp tally with the analysis resultof actual measured data. It’s should be pointed the mean up-cross period and zero spectral moment fluctuate a lot, and they don’t belong to the same wave condition. It’s because the data are observed in a 6-day storm. By compare the given 409 significant wave heights and statistical characteristics in a duration with that obtained by FFT, it’s regard they are fitted very well.Traditional spectrum estimation method, Fast Fourier Transform, assumes that the covariance function out of the computation domain is regarded as zero, the period histogram is considered to be the whole period. The obtained spectrum function actually is the product of the real spectrum and a window function. In this paper, the maximum entropy method is compared with Fast Fourier Transform in their aspect of establishing a frequency spectrum for wave data. The algorithm of Maximum Entropy Method (MEM) is discussed and the computation results show that MEM method is better than FFT method in that it avoids some unrealistic assumption. Because it doesn’t need window function, it doesn’t have the problem of spectrum leakage. Even for some short wave record, MEM can return satisfactory result. For the storm wave data from North Sea, the combination of Akaike method and empirical method for determining the order is good. MEM method is another good option for spectrum establishment of the wave data.更多还原