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A Study on Standard Ocean Lighted Buoy Type System for Real-time Ocean Meteorological Observation

실시간 해양관측을 위한 표준형 등부표용 시스템 연구

  • Received : 2018.08.31
  • Accepted : 2018.09.20
  • Published : 2018.09.30

Abstract

We propose a marine observation system using existing light buoys to observe various marine information of marine locations. Our proposed ocean observation system is composed of the existing standard light buoy type and can be easily connected to the light buoy. The proposed marine observation system measures the mean wave height, maximum wave height, mean wave height and water temperature measured in the ocean. Besides, it can measure the air pressure, temperature, wind speed and wind speed in real time. In order to measure important peaks in marine observations, 2200 peak data are collected for 10 minutes, and the collected data are subjected to spectral analysis to extract significant wave and wave period data. The developed system removes the noise by using the filter because the marine observation system attaches to the light buoy. We compare and analyze the measurement data of the existing proven floating marine observation system and the standard equivalent system developed. Also, it is proved that the data of the standard type backbone ocean observation system developed through the comparative experiment is similar to that of the existing ocean observation system.

본 논문에서는 해양 위치에 따른 다양한 해양 정보를 관측하기 위하여 기존에 설치된 등부표를 활용한 해양관측 시스템을 제안하고자 한다. 본 논문에서 제안하는 해양관측 시스템은 기존 표준형 등부표용 형태로써 등부표에 손쉽게 연결이 가능한 구조로 구성되어 있다. 제안한 해양관측 시스템은 기존 해양에서 관측하고 있는 유의파고, 최대파고, 평균파고, 수온을 측정하며 추가적으로 기압, 기온, 풍향/풍속까지 실시간 측정이 가능하다. 해양관측에서 중요한 파고를 측정하기 위해서는 10분 동안 2200개의 파고 데이터를 수집하며 수집한 자료는 스펙트럼 분석을 통하여 유의파고와 파주기 데이터를 추출한다. 개발된 시스템은 등부표 위에 해양관측 시스템이 부착이 되기 때문에 필터를 사용하여 노이즈를 제거한다. 본 논문에서는 검증된 기존 부이형태의 해양관측 시스템과 개발한 표준형 등부표용 해양관측 시스템의 측정 데이터를 비교 분석한다. 또한 비교 실험을 통하여 개발한 표준형 등부표용 해양관측 시스템이 기존 해양관측 시스템과 데이터가 유사하다는 것을 증명하였다.

Keywords

Acknowledgement

Supported by : 연구개발특구진흥재단

References

  1. Akyuz, Emre, "A marine accident analysing model to evaluate potential operational causes in cargo ships," Safety science, Vol. 92, pp. 17-25, 2017. https://doi.org/10.1016/j.ssci.2016.09.010
  2. Ram, Kondamudi Siva Sai, and A. N. P. S. Gupta, "IoT based Data Logger System for weather monitoring using Wireless sensor networks," International Journal of Engineering Trends and Technology(IJETT), Vol. 32, No. 2, pp. 71-75, 2016. https://doi.org/10.14445/22315381/IJETT-V32P213
  3. Hyunjin Lee, “The Development of the Predict Model for Solar Power Generation based on Current Temperature Data in Restricted Circumstances,” Journal of Digital Contents Society, Vol. 17, No. 3, pp. 157-164, 2016. https://doi.org/10.9728/dcs.2016.17.3.157
  4. Sujeong Ko, "Predicting Plant Biological Environment Using Intelligent IoT," Journal of Digital Contents Society, Vol. 19, No. 7, pp. 1423-1431, 2018. https://doi.org/10.9728/dcs.2018.19.7.1423
  5. Korea Meteorological Adminstration: http://www.kma.go.kr
  6. Statistics Korea: http://kostat.go.kr
  7. Gutierrez Antunano, Miguel A., Jordi Tiana Alsina and Francesc Rocadenbosch, "Performance evaluation of a floating lidar buoy in nearshore conditions," Wind energy, Vol. 20, No. 10, pp. 1711-1726, 2017. https://doi.org/10.1002/we.2118
  8. Fangqing Gu, Hai-lin Liu, Yiu-Ming Cheung and Shengli Xie, "Optimal WCDMA etwork plaig by multiobjective evolutioary algorithm with problem-specific geetic operatio," Knowledge and Information Systems, Vol. 45, No. 3, pp. 679-703, 2015. https://doi.org/10.1007/s10115-014-0799-y
  9. Melgar, Diego, and Yehuda Bock, “Kinematic earthquake source inversion and tsunami runup prediction with regional geophysical data,” Journal of Geophysical Research: Solid Earth, Vol. 120, No. 5, pp. 3324-3349, 2015. https://doi.org/10.1002/2014JB011832
  10. Kenek: http://www.kenek-co.com
  11. Riley, Rodney E. and Richard H. Bouchard, "An Accuracy Statement for the Buoy Heading Component of NDBC Directional Wave Measurements," The Twenty-fifth International Ocean and Polar Engineering Conference, International Society of Offshore and Polar Engineers, pp. 1-4, 2015.
  12. Graeme Anderson, Fiona Carse, Jon Turton and Andrew Saulter, “Quantification of bias of wave measurements from lightvessels,” Journal of Operational Oceanography, Vol. 9, No. 2, pp. 93-102, 2016. https://doi.org/10.1080/1755876X.2016.1239242
  13. Chunjing Lin, Sichuan Xu, Guofeng Chang and Jinling Liu, "Experiment and simulation of a LiFePO4 battery pack with a passive thermal management system using composite phase change material and graphite sheets," Journal of Power Sources, Vol. 275, pp. 742-749, 2015. https://doi.org/10.1016/j.jpowsour.2014.11.068
  14. Jinyu Wang, Jun Liang, Feng Gao, Li Zhang and Zhuodi Wang, “A method to improve the dynamic performance of moving average filter-based PLL,” IEEE Trans. Power Electron, Vol. 30, No. 10, pp. 5978-5990, 2015. https://doi.org/10.1109/TPEL.2014.2381673
  15. Gowribanu, G., and S. Anbumalar, "Dynamic performance improvement of a moving average filter based-PLL using PI and fuzzy controller," Electrical, Electronics, and Optimization Techniques (ICEEOT), International Conference on. IEEE, pp. 2384-2389, 2016.
  16. Tamura, Takahiro, Ryo Matsuda, and Masaki Suido, "Development of a Measurement System Aiming at Detection of Ground Contact in Running and Providing Immediate Feedback Using 3-Axial Acceleration Sensor and Wireless Communication Installed on a Smart Device," The Journal of Information and Systems in Education, Vol. 17, No. 1, pp. 1-6, 2018. https://doi.org/10.12937/ejsise.17.1
  17. Bocheng Bao, Tao Jiang, Quan Xu, Mo Chen, Huagan Wu and Yihua Hu, “Coexisting infinitely many attractors in active band-pass filter-based memristive circuit,” Nonlinear Dynamics, Vol. 86, No. 3, pp. 1711-1723, 2016. https://doi.org/10.1007/s11071-016-2988-6
  18. Adiono, Trio, and Syifaul Fuada, "Optical interference noise filtering over visible light communication system utilizing analog high-pass filter circuit," Proc. of the 2017 Int. Symp. on Nonlinear Theory and Its Applications, pp. 616-619, 2017.
  19. Carrasco, Ruben, Michael StreBer, and Jochen Horstmann, "A simple method for retrieving significant wave height from Dopplerized X-band radar," Ocean Science, Vol. 13, No. 1, pp. 95-103, 2017. https://doi.org/10.5194/os-13-95-2017
  20. Xu, Guochang and Yan Xu, GPS: theory, algorithms and applications, Springer, 2016.
  21. Ewan Nurse, Benjamin S. Mashford, Antonio Jimeno Yepes, Isabell Kiral-Kornek, Stefan Harrer and Dean R. Freestone, "Decoding EEG and LFP signals using deep learning: heading TrueNorth," Proceedings of the ACM International Conference on Computing Frontiers. ACM, pp. 259-266, 2016.
  22. Zhenyu Zhang, Wei Liu, Wen Leng, Anguo Wang and Heping Shi, "Interference-plus-noise covariance matrix reconstruction via spatial power spectrum sampling for robust adaptive beamforming," IEEE Signal Processing Letters, Vol. 23, No. 1, pp. 121-125, 2016. https://doi.org/10.1109/LSP.2015.2504954