Health monitoring of floating structure by utilizing support vector machines

  • Abstract
  • Keywords
  • References
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  • Abstract

    We explored the damage detection method for a floating structure by utilizing the natural ocean waves for the floating body. And we utilized the discrete Fourier transform as well as the learning and judgment functions of the support vector machines. It showed a possibility that it can perform the health diagnosis for the floating structure even using the strain response vibrations by inputting the natural waves with different cycles and wave heights.

  • Keywords

    Remote Monitoring; Support Vector Machines; Piezoelectric Films.

  • References

      [1] Tomoki Ikoma, Koichi Masuda, Yuka Watanabe and Hisaaki Maeda, “Hydroelastic Responses and Performance of OWC Type WECs of a Large Scale Floating Structure”, Proceedings of the sixth International Conference on Hydroelasticity in Marine Technology, Tokyo, 2012, pp:445-455.

      [2] H. Osawa, Y. Washio, T. Miyazaki, T. Hotta and T. Miyazaki, “R&D of Technologies of Wave Energy Application- Development of Offshore Floating Wave Power Device named Mighty-Whale-”, JAMSTEC, 2004.

      [3] J.A. Pinkster and E.J.A. Meevers Scholte, “The behaviour of a large air-supported MOB at sea”, Proceedings of the 3rd International Workshop on Very Large Floating Structures, VLFS '99, Vol. II, pp:567-576, 1999.

      [4] Tomoki Ikoma, Koichi Masuda, Hikaru Omori, Hiroyuki Osawa and Hisaaki Maeda, “Improvement of Wave Power Take-Off Performance due to the Projecting Walls for OWC Type WEC”, Proceedings of the ASME 32nd International Conference on Ocean, Offshore and Arctic Engineering (OMAE’13), ASME, 10384, 2013.

      [5] H. Maeda, C.H. Rheem, Y. Washio, H. Osawa, Y. Nagata, T. Ikoma, N. Fujita and M. Arita, “Reduction Effects of Hydroelastic Responses on a Very Large Floating Structure With Wave Energy Absorption Devices Using OWC System”, Proceedings of the 20th International Conference on OMAE 2001, ASME, CD-ROM file is OSU-5013, 2001.6.

      [6] Hiroaki Eto, Chiaki Sato, Koichi Masuda, Tomoki Ikoma, Ken Shimizu, Akio Kuroyanagi, Akio Kobayashi, Sachio Togawa, Sotaro Tsuboi, Kosaku Kinoshita, Junko Yamaguchi, Toshikatsu Saito, Masako Takada, and Atsuko Tanigome, “Feasibility Study of MEDI-FLOAT installed in the River”, Proceedings of Pacific Congress on Marine Science & Technology (PACON) 24th International Conference, 2014.

      [7] Kentaro Tsuji, Kazuhisa Naoi, Mitsuhiro Shiono, Katsuyuki Suzuki, “Study on the Gear Ratio for a Tidal Current Power Generation System Using the MPPT Control Method”, Proceedings of the Twenty-fourth (2014) International Ocean and Polar Engineering Conference, 2014, pp:568-574.

      [8] Vladimir N. Vapnik, Statistical Learning Theory, Wiley-Interscience, (1998).

      [9] B. Schölkopf, P. Simard, A. Smola, and V. Vapnik, “Prior knowledge in support vector kernels”, Advances in Neural Information Processing Systems 10, pp.640-646, 1997.

      [10] D. Decoste, “Training invariant support vector machines”, Machine Learning, vol. 46, pp. 161-190, on Internet. Patient Education and Counseling 53, 309–313.




Article ID: 5503
DOI: 10.14419/ijet.v5i2.5503

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