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7. CONCLUSIONS
Simulation techniques for estimating ship response in waves are proposed. In this system, directional wave spectrum is estimated from time-history data of ship motion. Using the estimated spectra, ship response to all possible course and speed changes can be simulated. Information about ship response can then be predicted before a decision to change course or speed is made.
Fig.5 Instantaneous autospectra of pitch angle.
Fig.6 Estimated directional wave spectrum.
Fig.7 Comparison of predicted and measured pitching motion.
Fig.8 |
Comparison of the longitudinal bending stress power spectrum. |
Results of the on-board experiments that were carried out to verify the system are summarized below:
(1) It is possible to estimate the directional wave spectra based on the instantaneous cross spectrum analysis and the recursive Bayesian modeling procedure even under nonstationary conditions.
(2) Assuming that the directional wave spectrum is stationary in time, future ship motions can be evaluated based on the previously estimated directional wave spectrum.
The authors thank the captain and crew of the training ship Shioji Maru, Tokyo University of Mercantile Marine. This work is partly supported by Grant-in-Aid for Scientific Research (No.14550858) from the Ministry of Education, Culture, Sports, Science and Technology of Japan. The authors would like to acknowledge their support.
REFERENCES
[1] Iseki, T and Terada, D. "Bayesian Estimation of Directional Wave Spectra for Ship Guidance System," Int. J Offshore and Polar Eng, ISOPE, Vol 12 No 1, pp 25-30, 2002.
[2] Terada, D and Iseki, T. "Onboard Ship Motion Analyzer Based on Nonstationary Time Series Analysis, "Proc 12th International Offshore and Polar Engineering Conference, ISOPE, Vol 3, pp 438-443, 2002.
[3] Kitagawa, G and Gersch, W. "A smoothness priors time varying AR coefficient modeling of nonstationary covariance time series," IEEE Transaction on Automatic Control, Vol AC-30, No 1, pp 48-56, 1985.
[4] Jiang, XQ and Kitagawa, G. "A time varying coefficient vector AR modeling of nonstationary covariance time series," Signal Processing, Vol 33, No 3, pp 315-331, 1993.
[5] Iseki, T. and Terada, D. "Recursive Bayesian Modeling for Online Estimation of Directional Wave Spectra," Proc 13th International Offshore and Polar Engineering Conference, ISOPE, 2003.
[6] Akaike, H et al. "TIMSAC-78," Computer Science Monographs, No 11, The Institute of Statistical Mathematics, Tokyo, Japan, 1979.
[7] Kitagawa, G and Akaike, H. "OnTIMSAC-78," Applied Time Series Analysis II, Academic Press, pp 499-547, 1981.
[8] Akaike, H. "Likelihood and Bayes procedure" Bayesian Statistics, University Press, Valencia, pp 143-166, 1980.
AUTHOR' S BIOGRAPHY
Toshio Iseki:
Graduated from Dept. of Naval Architecture, Kyushu University (1984), and completed graduate course for doctor's degree (1989)
Lecturer (1989). Associate Professor (1990) of Tokyo University of Mercantile Marine.
Daisuke Terada:
Graduated from Dept. of Marine System Engineering, Tokyo University of Mercantile Marine (1998), and completed graduate course for doctor's degree (2003).
M.O. Marine Consulting, Ltd (2003)
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