Il-Kyu Hwang , Minkyu Lee , Junsub Han , Jeeun Choi
{"title":"Wave height measurement scheme using wave detector based on convolutional neural network and PPM calculator with ocean wave images","authors":"Il-Kyu Hwang , Minkyu Lee , Junsub Han , Jeeun Choi","doi":"10.1016/j.ijnaoe.2023.100542","DOIUrl":null,"url":null,"abstract":"<div><p>The measurement of wave height is essential for weather analysis, safe navigation of ships, and ship design. This study proposes a low-cost and direct method for measuring wave height using ocean wave images. The proposed scheme comprises a Wave Detector based on Convolutional Neural Networks that takes two-dimensional ocean images as input, and a PPM Calculator that measures the size of an object in the image. The study explains the configuration and implementation of the Wave Detector and the basic principle of the PPM surface generating method for the PPM Calculator, with support from ground experiments. The proposed scheme is validated using two types of wave height measurement sensors and three types of real ocean images for the Wave Detector, as well as two rounds of ground experiments for the PPM Calculator.</p><p>The results show that the wave height values measured by the proposed scheme are highly consistent with the values from the measurement sensors.</p></div>","PeriodicalId":14160,"journal":{"name":"International Journal of Naval Architecture and Ocean Engineering","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Naval Architecture and Ocean Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2092678223000316","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MARINE","Score":null,"Total":0}
引用次数: 0
Abstract
The measurement of wave height is essential for weather analysis, safe navigation of ships, and ship design. This study proposes a low-cost and direct method for measuring wave height using ocean wave images. The proposed scheme comprises a Wave Detector based on Convolutional Neural Networks that takes two-dimensional ocean images as input, and a PPM Calculator that measures the size of an object in the image. The study explains the configuration and implementation of the Wave Detector and the basic principle of the PPM surface generating method for the PPM Calculator, with support from ground experiments. The proposed scheme is validated using two types of wave height measurement sensors and three types of real ocean images for the Wave Detector, as well as two rounds of ground experiments for the PPM Calculator.
The results show that the wave height values measured by the proposed scheme are highly consistent with the values from the measurement sensors.
期刊介绍:
International Journal of Naval Architecture and Ocean Engineering provides a forum for engineers and scientists from a wide range of disciplines to present and discuss various phenomena in the utilization and preservation of ocean environment. Without being limited by the traditional categorization, it is encouraged to present advanced technology development and scientific research, as long as they are aimed for more and better human engagement with ocean environment. Topics include, but not limited to: marine hydrodynamics; structural mechanics; marine propulsion system; design methodology & practice; production technology; system dynamics & control; marine equipment technology; materials science; underwater acoustics; ocean remote sensing; and information technology related to ship and marine systems; ocean energy systems; marine environmental engineering; maritime safety engineering; polar & arctic engineering; coastal & port engineering; subsea engineering; and specialized watercraft engineering.