Design and evaluation a portable intelligent rescue system for unmanned underwater vehicles

Sheng-Chih Shen, Y. T. Yang

Research output: Contribution to journalArticle

Abstract

This research is based on the attitude sensing algorithm to design a portable intelligent rescue system for AUVs. To lower the possibility of losing the underwater vehicle and reduce the difficulty of rescuing, when an AUV intelligent rescue system (AIRS) detects that the fault of AUVs and could not be reclaimed, AIRS can pump carbon dioxide into the airbag immediately to make the vehicle resurface. AIRS consists of attitude sensing module, double-trigger inflator mechanism, and activity recognition algorithm. The sensing module is an 11-DOF sensor that makes up of a six-axis inertial sensor, a three-axis magnetometer, a barometer, and a thermometer. Furthermore, the signal calibration and extended Kalman filter (SC-EKF) is proposed to be used subsequently to calibrate and fuse the data from the sensing module. Then, classify the attitude data with the principle of feature extraction (FE), and backpropagation network (BPN) classifier. Finally, the designed double-trigger inflator not only can trigger by electricity but also trigger by water damage when the waterproof cabin is severely broken. With the AIRS technology, the safety of detecting and investigating of using AUVs can be increased since there is no need to send divers to engage in the rescuing mission under the water.

Original languageEnglish
Pages (from-to)117-126
Number of pages10
JournalJournal of Taiwan Society of Naval Architects and Marine Engineers
Volume37
Issue number3
Publication statusPublished - 2018 Jan 1

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Barometers
Thermometers
Sensors
Extended Kalman filters
Electric fuses
Magnetometers
Backpropagation
Feature extraction
Water
Carbon dioxide
Classifiers
Electricity
Pumps
Calibration
Unmanned underwater vehicles

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Mechanical Engineering

Cite this

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