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Enhanced navigation and tether manag...

Zand, Jonathan.

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Enhanced navigation and tether management of inspection class Remotely Operated Vehicles.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Enhanced navigation and tether management of inspection class Remotely Operated Vehicles./
作者:	Zand, Jonathan.
面頁冊數:	182 p.
附註:	Source: Masters Abstracts International, Volume: 49-02, page: 1369.
Contained By:	Masters Abstracts International49-02.
標題:	Engineering, Marine and Ocean. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR66821
ISBN:	9780494668214

Enhanced navigation and tether management of inspection class Remotely Operated Vehicles.
Zand, Jonathan.

Enhanced navigation and tether management of inspection class Remotely Operated Vehicles. - 182 p.

Source: Masters Abstracts International, Volume: 49-02, page: 1369.

Thesis (M.Sc.A.)--University of Victoria (Canada), 2010.

Remotely Operated Vehicles (ROVs) provide access to underwater environments too deep and dangerous for commercial divers. A tether connects the ROV to a vessel on the surface, providing power and communication channels. During extended manoeuvres, hydrodynamic forces on the tether produce large tensions which hinder ROV manoeuvrability. The research presented in this thesis focuses on the design of new tether management strategies that alleviate the tether disturbance problem, and the implementation of a navigation suite for tracking the ROV position and velocity which are needed to close the loop on the tether management method. To improve the estimation of the ROV state, an Extended Kalman Filter (EKF) is developed.

ISBN: 9780494668214Subjects--Topical Terms:

1019064
Engineering, Marine and Ocean.

Enhanced navigation and tether management of inspection class Remotely Operated Vehicles.
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245 1 0 $a Enhanced navigation and tether management of inspection class Remotely Operated Vehicles.
300 $a 182 p.
500 $a Source: Masters Abstracts International, Volume: 49-02, page: 1369.
502 $a Thesis (M.Sc.A.)--University of Victoria (Canada), 2010.
520 $a Remotely Operated Vehicles (ROVs) provide access to underwater environments too deep and dangerous for commercial divers. A tether connects the ROV to a vessel on the surface, providing power and communication channels. During extended manoeuvres, hydrodynamic forces on the tether produce large tensions which hinder ROV manoeuvrability. The research presented in this thesis focuses on the design of new tether management strategies that alleviate the tether disturbance problem, and the implementation of a navigation suite for tracking the ROV position and velocity which are needed to close the loop on the tether management method. To improve the estimation of the ROV state, an Extended Kalman Filter (EKF) is developed.
520 $a An inspection class Falcon(TM) ROV was used for this research. Typical of the ROVs in its class, the Falcon(TM) ROV has a neutrally buoyant tether which reacts to hydrodynamic forces that accumulate over its length when exposed to currents or when the ROV attempts to move at high speed. Dynamics models of the ROV and the tether were utilized in numerical simulations of deepwater Falcon(TM) operations and were also embedded in the process model of the EKF. The parameters of these Falcon(TM) dynamic models, including the propulsive thrusts, hydrodynamic drag forces and added masses, were identified through a series of shallow water tests. The physical parameters of the ROV tether were measured in a dry laboratory.
520 $a Transect and transit manoeuvres at 200m depth were investigated through numerical simulation of the tether and ROV. The position of the ship relative to the ROV was optimized to minimize steady-state tether disturbance for transect manoeuvres and to maximize sustained transit speed for transit manoeuvres. Driving the ship to lead the ROV by 26m was found to be optimal for the transect manoeuvres at 200m depth. At the 0.2m/s transect speed, this optimal configuration produces 25N of tether disturbance, whereas the conventional method was shown to produce tether disturbances up to 43N. The fastest sustainable ROV transit speed for operations at 200m depth with the neutrally buoyant tether was found to be 0.67m/s and was obtained by driving the ship 90m ahead of the ROV. Beyond this speed, the demanded ROV thrust exceeds capacity during long transits. However, attaching a depressor mass to the otherwise neutrally buoyant tether provides more control of the tether profile through ship motion. With use of a depressor, controlled ship and winch motion further reduce tether disturbance and allowed ROV transit speeds exceeding 1m/s.
520 $a A navigation suite was developed to track ROV position and velocity with the accuracy and frequency necessary for the proposed tether management strategies. The Falcon(TM) ROV was instrumented with an acoustic positioning system, a Doppler Velocity Log (DVL), a depth sensor, a compass, and an Inertial Measurement Unit (IMU). Asynchronous measurements from the individual devices were processed with an EKF that used a kinetic model of translational motion to blend the data into a single estimate of the vehicle state. The EKF performance was tested experimentally with measurements collected during a shallow water test. The accuracy of the EKF estimate of ROV position was quantified through comparison with optical motion measurements. The optical motion measurement system accurately tracked ROV position at 100Hz, but needed optical markers mounted to a mast on the ROV to be above the water surface, restricting the test domain to shallow water.
520 $a ROV operations are typically beyond commercial diver depth, so the shallow water test results were extended to deepwater operation by applying the EKF to numerically simulated instrument measurements generated for a 200m deep ROV manoeuvre. The EKF estimated ROV position at 10Hz with root mean square (RMS) errors less than 3.5m. The ROV velocity was also estimated at 10Hz with RMS errors less than 0.04m/s.
590 $a School code: 0244.
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650 4 $a Engineering, Mechanical. $3 783786
650 4 $a Engineering, Robotics. $3 1018454
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710 2 $a University of Victoria (Canada). $3 1019404
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