OCEANS 2019 - Marseille最新文献_第8页

Fishing Spot Detection Using Sea Water Temperature Pattern by Nonlinear Clustering 基于非线性聚类的海水温度模式渔点检测

OCEANS 2019 - Marseille Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867301

T. Shimura, Motoharu Sonogashira, Hidekazu Kasahara, M. Iiyama

引用次数: 3

Unmanned Aerial System for use in Environmental Monitoring of Water Body Wave Motion 用于水体波动环境监测的无人机系统

OCEANS 2019 - Marseille Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867528

Steven D. Lloyd, P. Lepper, S. Pomeroy

引用次数: 0

Heat exchanger heat transfer coefficient and CFD modelling 换热器换热系数及CFD建模

OCEANS 2019 - Marseille Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867541

David Mas, Sebastien Vimeux, B. Clauzade, Pierre Lucas, Francois Hochet, Vincent Melot, Damien Thuaud

引用次数: 0

The Analysis of Structural Strength and Fatigue Strength of Vertical Axis Hydraulic Turbine 垂直轴水轮机结构强度与疲劳强度分析

OCEANS 2019 - Marseille Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867164

Fankai Kong, Hua-qiu Ding, Weiming Su

{"title":"The Analysis of Structural Strength and Fatigue Strength of Vertical Axis Hydraulic Turbine","authors":"Fankai Kong, Hua-qiu Ding, Weiming Su","doi":"10.1109/OCEANSE.2019.8867164","DOIUrl":"https://doi.org/10.1109/OCEANSE.2019.8867164","url":null,"abstract":"The floating vertical axis tidal current turbine will be subjected to complex loads when it works in the marine environment, which will cause the whole power generating device to oscillate, affect the working performance of vertical axis turbine, reduce the life expectancy of the whole power generating device, and even make its structure destroyed. Therefore, it is necessary to study the movement and stress of the turbine under complex sea conditions. Using AQWA to simulate the motion response of floating carrier in frequency domain, the frequency domain analysis of the turbine is carried out, and the hydrodynamic characteristics of floating carrier are studied. The strength of the turbine under extreme conditions is analyzed by ANSYS static analysis module. The results show that the flange connection is the position with the largest stress concentration. The wave forces are superimposed on the turbine, and the strength and fatigue life of the flange joint of the main shaft of the turbine are analyzed. The results show that the strength of the flange and the flange bolts meet the design requirements. However, the flange bolts will not meet the expected life requirements under the extreme conditions, so the turbine needs to stop operation under the extreme sea conditions. The analysis and simulation results provide a theoretical basis for the practical application of hydraulic turbines.","PeriodicalId":375793,"journal":{"name":"OCEANS 2019 - Marseille","volume":"47 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115791431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Psychological measure on fish catches and its application to optimization criterion for machine-learning-based predictors 渔获量的心理测量及其在基于机器学习的预测器优化准则中的应用

OCEANS 2019 - Marseille Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867405

Yuya Kokaki, Tetsunori Kobayashi, Tetsuji Ogawa

引用次数: 2

The dual roles of SmartBay, a multi-disciplinary subsea observatory delivering sustainable long term coastal marine observations and marine technology development SmartBay是一个多学科海底观测站，提供可持续的长期沿海海洋观测和海洋技术发展

OCEANS 2019 - Marseille Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867042

P. Gaughan, A. Berry, Conall O Malley

{"title":"The dual roles of SmartBay, a multi-disciplinary subsea observatory delivering sustainable long term coastal marine observations and marine technology development","authors":"P. Gaughan, A. Berry, Conall O Malley","doi":"10.1109/OCEANSE.2019.8867042","DOIUrl":"https://doi.org/10.1109/OCEANSE.2019.8867042","url":null,"abstract":"The SmartBay cabled subsea observatory is a shallow water marine infrastructure with two distinct operational roles, namely the provision of high quality, multidisciplinary, marine coastal data for scientific analysis combined with a role in facilitating marine technology testing and innovation projects. This paper highlights the unique aspects in the bespoke design of the infrastructure that facilitates both these roles by allowing multiple suites of instrumentation and equipment to operate simultaneously and how the supporting cyber Infrastructure system ensures real-time access to environmental data for scientists as well as secure real time access for commercial marine technology developers and researchers. The longevity of the infrastructure was a key component of the system design and these unique features are highlighted and discussed in terms of how they allow the infrastructure to carry out multiple projects while maintaining long term data collection capabilities from a suite of core instrumentation. SmartBay’s dual purpose of scientific environmental monitoring and technology development has seen the deployment and completion of a range of projects involving a variety of international researchers both scientific and commercial. We illustrate how the SmartBay observatory engineering and software systems have been adapted and enhanced to facilitate the most efficient usage of the observatory and how operational efficiencies maximise the long-term commercial viability and sustainability of the infrastructure.","PeriodicalId":375793,"journal":{"name":"OCEANS 2019 - Marseille","volume":"445 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122150919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Acoustic Scattering from a one-dimension Gaussian surface on a pressure-release boundary 压力释放边界上一维高斯表面的声散射

OCEANS 2019 - Marseille Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867184

Xue Runze, Ma Yuanliang, Yang Kunde, Yang Qiulong, Huang Chunlong, Z. Yukun

引用次数: 0

Convolutional Neural Network Architectures for Sonar-Based Diver Detection and Tracking 基于声纳的潜水员探测与跟踪的卷积神经网络结构

OCEANS 2019 - Marseille Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867461

Igor Kvasić, N. Mišković, Z. Vukic

{"title":"Convolutional Neural Network Architectures for Sonar-Based Diver Detection and Tracking","authors":"Igor Kvasić, N. Mišković, Z. Vukic","doi":"10.1109/OCEANSE.2019.8867461","DOIUrl":"https://doi.org/10.1109/OCEANSE.2019.8867461","url":null,"abstract":"Autonomous underwater navigation presents a whole set of challenges to be resolved in order to become adequately accurate and reliable. That is particularly critical when human divers work in close collaboration with autonomous underwater vehicles (AUVs). In absence of global positioning signals underwater, acoustic based sensors such as LBL (long-baseline), SBL (short-baseline) and USBL (ultrashort-baseline) are commonly used for navigation and localization. In addition to these low-bandwidth and high latency technologies, cameras and sonars can provide position measurements relative to the vehicle which can be used as an aid for navigation as well as for keeping a safe working distance between the diver and the AUV. While optical cameras are highly affected by water turbidity and lighting conditions, sonar images often become hard to interpret using conventional image processing methods due to image granulation and high noise levels.This paper focuses on finding a robust and reliable sonar image processing method for detection and tracking of human divers using convolutional neural networks. Machine learning algorithms are making a huge impact in computer vision applications but are not always considered when it comes to sonar image processing. After presenting commonly used image processing techniques the paper will focus on giving an overview of state-of-the-art machine learning algorithms and explore their performance in custom sonar image dataset processing. Finally, the performance of these algorithms will be compared on a set of sonar recordings to determine their reliability and applicability in a real-time operation.","PeriodicalId":375793,"journal":{"name":"OCEANS 2019 - Marseille","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124538650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 27

Design of a Self-moving Autonomous Buoy for the Localization of Underwater Targets 一种用于水下目标定位的自移动自主浮标设计

OCEANS 2019 - Marseille Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867202

A. Meschini, J. Gelli, M. Pagliai, Andrea Della Valle, Matteo Franchi, M. Bianchi, A. Ridolfi, B. Allotta

引用次数: 2

Deep-sea submarine terrain monitoring——a brand new way 深海海底地形监测——一种全新的方式

OCEANS 2019 - Marseille Pub Date : 2019-06-01 DOI: 10.1109/OCEANSE.2019.8866880

C. Cao, Jia-wang Chen, M. Feng, Chunying Xu, Peihao Zhang, P. Zhou

引用次数: 0