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A Novel Data-Driven Framework for Real-Time Ocean Wave Monitoring Using High Frequency Radar Systems

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A Novel Data-Driven Framework for Real-Time Ocean Wave Monitoring Using High Frequency Radar Systems A Novel Data-Driven Framework for Real-Time Ocean Wave Monitoring Using High Frequency Radar Systems By Nuoyi Zhu A Dissertation Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE in partial fulfillment of the requirements for the Degree of Doctor of Philosophy In Civil Engineering March 2018 APPROVED: Prof. Tahar El-Korfchi, Major Advisor Department of Civil and Environmental Engineering Worcester Polytechnic Institute Prof. Yeesock Kim, Co-Advisor Department of Civil Engineering and Construction Management California Baptist University Prof. Leonard Albano, Committee Member Department of Civil and Environmental Engineering Worcester Polytechnic Institute Abstract Every year, frequent high waves induced by the tsunami, earthquakes, strong wind, and/or other climate change conditions have become one of the major factors of the various coastal disasters in the shoreline. In order to mitigate the coastal disaster, monitoring of ocean surface conditions such as wave heights and periods in real time is of high importance. However, the real-time ocean wave monitoring is a challenging problem, which has not yet been definitively resolved. With this in mind, a novel data-driven framework is proposed for the forecasting, identifying and classifying ocean waves in real-time using high frequency (HF) radar systems. The first part of the research investigates the effects of the ocean wave forecasting model using the nonlinear auto-regressive and moving average algorithms (ARMA). The second part of the research compares the three different identification features in ocean wave: frequency-based feature, AR-based feature, and ICA-based feature. The third part of the research introduces a classification model to identify the difference of ocean waves using the support vector machine (SVM) with radial basis function (RBF) kernel function. To validate the proposed algorithms, the Samcheok City, Gangwond-do, located on the East Coast of Korea is selected as the study area. A 2-year ocean wave height data from this area is collected using two Wellen radar systems. It is shown that the proposed algorithms have good performance in forecasting, identifying and classifying ocean waves. It is expected that the proposed system will accurately predict natural hazards and provide adequate warning time for people to evacuate. Hence this framework will directly increase the reliability and functionality of coastal hazard warning systems and contribute to the reduction in the potential for injuries and deaths in natural disasters of the coastal areas. 2 Acknowledgement I would like to sincerely thank my advisor Professor Tahar El-Korchi and Professor Yeesock Kim for their guidance, insights, support and friendship throughout my PhD years in WPI. I would like to thank my committee member Professor Leonard Albano for his acceptance in being part of my PhD committee, and for his time and priceless insights. I would like to thank Professor Kwonmoo Lee for his time and priceless insights. I would like to give special thanks to Agata Lajoie, Marylou Horazny, Cynthia Bergeron and Maryann Watts. They were always there when I needed. I would like to thank my fellow graduate students for their feedback, cooperation and of course friendship. It was great sharing with all of you during last four years. I would like to thank the Department of Civil and Environmental Engineering at WPI for giving me the chance to pursue my doctorate and for providing the financial support with a teaching assistantship. I would like to thank the Regional Technology Innovation Program from Ministry of Land, Transport and Maritime Affairs of Korean Government for providing the financial support with a research assistantship. More than all, I would like to thank my family, this could not be done without their support. I am grateful to my mom and my dad, who have provided me through moral and emotional support in my life. I am also grateful to my other family members and friends who have supported me along the way. 3 Table of Contents Abstract ........................................................................................................................................... 2 Acknowledgement .......................................................................................................................... 3 Table of Contents ............................................................................................................................ 4 List of Figures ................................................................................................................................. 7 List of Tables ................................................................................................................................ 10 1. Introduction ............................................................................................................................... 11 2. Real-time Forecasting of Ocean Wave Signals Using High Frequency Radar Systems .......... 17 2.1 Introduction ......................................................................................................................... 17 2.2 Proposed forecasting model ................................................................................................ 23 2.2.1 Linear ARMA model .................................................................................................... 24 2.2.2 Proposed nonlinear ARMA model ............................................................................... 24 2.2.3 Optimization of model structure and its parameters ..................................................... 25 2.3. Case study .......................................................................................................................... 29 2.4. Modeling results and analysis ............................................................................................ 33 2.4.1 Model parameter setup ................................................................................................. 33 2.4.2 Performance evaluation ................................................................................................ 33 2.5. Conclusion .......................................................................................................................... 44 3. Change Detection of Ocean Wave Characteristics ................................................................... 45 3.1 Introduction ......................................................................................................................... 45 3.1.1 Ocean wave measurement ............................................................................................ 45 3.1.2 High frequency (HF) radar systems .............................................................................. 46 3.1.3 Estimation of wave spectra ........................................................................................... 47 3.1.4 Short-time Fourier transform (STFT) ........................................................................... 49 3.1.5 Feature extraction ......................................................................................................... 50 3.2 Proposed algorithm ............................................................................................................. 53 3.2.1 Short-time Fourier transform (STFT) ........................................................................... 53 3.2.2 Fuzzy C-means clustering-based feature extraction approach ..................................... 58 3.3 Case study ........................................................................................................................... 63 3.3.1 Study area ..................................................................................................................... 63 3.3.2 Test setup ...................................................................................................................... 64 4 3.3.3 Data set ......................................................................................................................... 65 3.3.4 Result analysis .............................................................................................................. 66 3.4 Conclusion ........................................................................................................................... 75 4. Regression Models for Ocean Wave Identification Using High Frequency Radar Systems .... 77 4.1 Introduction ......................................................................................................................... 77 4.2 Proposed detection model ................................................................................................... 80 4.2.1 Autoregressive (AR) model .......................................................................................... 81 4.2.2 Short-time Fourier transform (STFT) ........................................................................... 83 4.2.3 Ocean wave characteristic detection ............................................................................. 84 4.3 Case study ........................................................................................................................... 85 4.4 Modeling result and analysis ............................................................................................... 89 4.4.1 Model parameter setup ................................................................................................. 89 4.4.2 AR model performance
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