An Analysis of the Short Time Velocity and Direction of Nonstationary Wave by Using Wavelet Transform

碩士 === 國立成功大學 === 水利及海洋工程學系 === 85 === The wavelet transform was often applied to nonstationary data to decomposethe signal into a frequency and time frame. This study istrying to combinethis capability of wavelet transform with traditional phase diff...

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Bibliographic Details
Main Authors: Kuo, Woei Ming, 郭瑋明
Other Authors: Chia Chuen Kao, Shyh Shyan Chung
Format: Others
Language:zh-TW
Published: 1997
Online Access:http://ndltd.ncl.edu.tw/handle/30208223990728018685
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Summary:碩士 === 國立成功大學 === 水利及海洋工程學系 === 85 === The wavelet transform was often applied to nonstationary data to decomposethe signal into a frequency and time frame. This study istrying to combinethis capability of wavelet transform with traditional phase difference method (P.D.M.) to estimate the short time velocity and direction of random oceanwave. Also, the nonparametric density function estimation was adopted todetermine the nonstationary probability density function directly in order toeliminate the influence of bin width of classical histogram. For further understanding the meanings of wavelet transform, it was firstto simulate the waves by superposient frequencies, and then the wang two ormore regular waves of differvelet power spectrum and phase spectrum were cal-culated. It was shown that the wavelet power spectrum/phase spectrum couldonly be represented by "peak" frequencies for a specific temporal location.However, the peak frequencies could be the original input frequencies if thewidth of time-frequency window is not overlaid, otherwise they will be theinteracting ones of different frequencies. It is why we calculated the shorttime wav e velocity and direction for peak frequencies in this study. Finally, the mean values and probability density function of short timevelocity and direction of random wave were calculated and compared to theresults obtained by P.D.M.. Also, the probability density function of shorttime direction were compared to the directional spreading function estimatedby Bayesian approach parameters method (B.A.P.M.). The results show that themean values of short time direction were close to the values of P.D.M. and themean direction of B.A.P.M., but the shape of short time direction is lessspreading than the directional spreading function of B.A.P.M.. The mean valuesof short time velocity were slower than the estimation of P.D. M. and alsoslower than the linear wave velocit y of peak frequency in the ratio of 0.8.