2017 IEEE Underwater Technology (UT)最新文献_第7页

Red snow crab habitat monitoring using autonomous deep sea camera 自主深海相机监测红雪蟹栖息地

2017 IEEE Underwater Technology (UT) Pub Date : 1900-01-01 DOI: 10.1109/UT.2017.7890338

Hyeonwoo Cho, Hangil Joe, Son-cheol Yu, Jae-Kil Lee, Tae eun Kwon, Myungjin Jeon, J. H. Heo

引用次数: 2

Deep learning of submerged body images from 2D sonar sensor based on convolutional neural network 基于卷积神经网络的二维声纳水下身体图像深度学习

2017 IEEE Underwater Technology (UT) Pub Date : 1900-01-01 DOI: 10.1109/UT.2017.7890309

Sejin Lee

引用次数: 10

Mechanical engineering challenges in the development of deepwater ROV (ROSUB 6000) 深水ROV (ROSUB 6000)开发中的机械工程挑战

2017 IEEE Underwater Technology (UT) Pub Date : 1900-01-01 DOI: 10.1109/UT.2017.7890286

D. Sathianarayanan, S. Pranesh, T. Chowdhury, E. Chandrasekar, M. Murugesan, M. Radhakrishnan, A. Subramanian, G. Ramadass, M. Atmanand

{"title":"Mechanical engineering challenges in the development of deepwater ROV (ROSUB 6000)","authors":"D. Sathianarayanan, S. Pranesh, T. Chowdhury, E. Chandrasekar, M. Murugesan, M. Radhakrishnan, A. Subramanian, G. Ramadass, M. Atmanand","doi":"10.1109/UT.2017.7890286","DOIUrl":"https://doi.org/10.1109/UT.2017.7890286","url":null,"abstract":"A deep water work class ROV (ROSUB 6000) rated for 6000 m subsea depth has been developed at National Institute of Ocean technology, Chennai, India. ROSUB 6000 system consists of a free swimming ROV, tether management system (TMS), power container, control console container, Launching and retrieval system (LARS) and electro optical umbilical cable. Developmental work of ROSUB 6000 system started from March 2003. During the developmental phase and several depth qualification sea trials various kinds of mechanical engineering challenges were encountered. This paper enumerates the challenges encountered. Water entry is one of the major challenges in subsea systems. Water entry through pressure housings may be catastrophic, since pressure housings carries control electronics. Control electronics switches off when water entry alarm is given stopping all the ROV operations. Water entry in the pressure cases of ROV has happened several times. Each instance the reason behind the water entry was different. Failure of components like torque arrester in TMS deep sea winch and thruster frames were analyzed and suitable methodologies to avoid these failures are brought into the practice. Challenges in deck handling of ROV and TMS are weather conditions and tether twist during initial attachment of ROV with TMS. One another big challenge is the launching and retrieval of the system. Challenges due to rough seas, launching and retrieval system hydraulic system faults, operational human errors and their effects on the system components are recorded and reviewed to improve the system reliability. The importance of buoyancy corrections and hydraulic system maintenance were learnt during the various phases of lab and field testing of the deep water ROV.","PeriodicalId":145963,"journal":{"name":"2017 IEEE Underwater Technology (UT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131051984","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

Heading control for an Autonomous Underwater Vehicle using ELM-based Q-learning 基于elm的自主水下航行器航向控制

2017 IEEE Underwater Technology (UT) Pub Date : 1900-01-01 DOI: 10.1109/UT.2017.7890340

Dianrui Wang, Yue Shen, Q. Sha, Guangliang Li, Jingtao Jiang, T. Yan, Junhe Wan, B. He

引用次数: 0

Can HF ocean radar provide vertical current profile estimates? 高频海洋雷达能提供垂直海流剖面估计吗?

2017 IEEE Underwater Technology (UT) Pub Date : 1900-01-01 DOI: 10.1109/UT.2017.7890343

M. Heron

引用次数: 0

Planning and correction of the AUV coverage path in real time 实时规划和修正水下机器人覆盖路径

2017 IEEE Underwater Technology (UT) Pub Date : 1900-01-01 DOI: 10.1109/UT.2017.7890299

A. Bagnitckii, A. Inzartsev, A. Pavin

引用次数: 13

Depth control methods of variable buoyancy AUV 变浮力水下航行器的深度控制方法

2017 IEEE Underwater Technology (UT) Pub Date : 1900-01-01 DOI: 10.1109/UT.2017.7890333

Andrei V. Medvedev, V. Kostenko, A. Tolstonogov

引用次数: 22

Wideband time-varying underwater acoustic channel emulator 宽带时变水声信道仿真器

2017 IEEE Underwater Technology (UT) Pub Date : 1900-01-01 DOI: 10.1109/UT.2017.7890341

Acta Withamana, H. Kondo

{"title":"Wideband time-varying underwater acoustic channel emulator","authors":"Acta Withamana, H. Kondo","doi":"10.1109/UT.2017.7890341","DOIUrl":"https://doi.org/10.1109/UT.2017.7890341","url":null,"abstract":"Robust underwater acoustic (UWA) communication is still a big challenge due to physical properties of the sea-water. Underwater acoustic propagation characterized by high attenuation, time-varying multipath propagation, and low speed of sound. Recent advancement in the cooperative operation of Autonomous Underwater Vehicles (AUVs) and Underwater Sensor Network (UWSN) are limited by these factors. Necessities to develop more robust UWA communication is not negligible. Sea trial is an expensive operation. A prior simulation and optionally emulation are usually used to enhance mission success rate. UWA emulator is a replica of an underwater channel and may contain hardware-in-the-loop (HIL). This tool is a bridge between the gaps of the simulation and real hardware-software behavior. However, UWA channel emulator is still underdeveloped. This paper explains the framework and the development of UWA channel emulator for a wideband and time-varying channel. Implementation of the convolution process has successfully done by using reloadable coefficient Finite Impulse Response (FIR) filter. First path propagation delay has also successfully implemented using a circular buffer. Designed emulator is applicable for less than 10 nodes before processing time is getting too high.","PeriodicalId":145963,"journal":{"name":"2017 IEEE Underwater Technology (UT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121019582","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

A new wave energy converter using flap-type blade and its power generation test 一种新型襟翼型波浪能变换器及其发电试验

2017 IEEE Underwater Technology (UT) Pub Date : 1900-01-01 DOI: 10.1109/UT.2017.7890332

Hangil Joe, H. Roh, Son-cheol Yu

引用次数: 3

Obstacle avoidance and target search of an Autonomous Surface Vehicle for 2016 Maritime RobotX challenge 2016年海上机器人x挑战赛中自主水面车辆的避障和目标搜索

2017 IEEE Underwater Technology (UT) Pub Date : 1900-01-01 DOI: 10.1109/UT.2017.7890308

Joohyun Woo, Jooho Lee, Nakwan Kim

{"title":"Obstacle avoidance and target search of an Autonomous Surface Vehicle for 2016 Maritime RobotX challenge","authors":"Joohyun Woo, Jooho Lee, Nakwan Kim","doi":"10.1109/UT.2017.7890308","DOIUrl":"https://doi.org/10.1109/UT.2017.7890308","url":null,"abstract":"This paper describes algorithms for Autonomous Surface Vehicle(ASV) obstacle avoidance and target search task. This work is primarily designed for task mission of 2016 Maritime RobotX competition. In this task, ASV must avoid obstacle buoys, while it is searching for totem-shaped buoy. To deal with such problem, algorithms for both perception and motion planning stage was designed. In perception stage, 2D scanning LIDAR and monocular vision sensor are used to detect any floating objects on the water. To recognize target (totem buoy), HSV color space information was used. Detected object (both obstacle and totem buoy) information is tracked by using Kalman filter. In action planning stage, both deliberative and reflexive action [2] planning are designed. In deliberative action planning stage, based on the Kalman filter tracked obstacle information, a grid map can be generated. Using the grid map and A∗ search algorithm, desired path for searching totem can be calculated. In reflexive action planning stage, once ASV accidently enters hazardous region, where it has high probability of getting collide, it is designed to reflexively escape the region by making pure sway motion. An ASV experiment was performed to validate proposed method.","PeriodicalId":145963,"journal":{"name":"2017 IEEE Underwater Technology (UT)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125442186","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: 11