Fault Diagnosis of Underwater Vehicle Propulsion System Based on Deep Learning

2020 ◽  
Vol 107 (sp1) ◽  
pp. 65
Author(s):  
Ying Wang ◽  
Yourong Li
Author(s):  
Libero Paolucci ◽  
Emanuele Grasso ◽  
Francesco Grasso ◽  
Niklas König ◽  
Marco Pagliai ◽  
...  

Underwater vehicle propulsion performed by exploiting electrical motor is in general the most flexible solution and it is growing in popularity because of its high efficiency both at high and at low advance speed, quick and simple deployment, low costs, and encumbrance. In the present work, permanent magnet synchronous motors for underwater propulsion are proposed. In particular, advanced sensorless control techniques of permanent magnet synchronous motors permit reduced costs, high reliability, and performances. When dealing with small autonomous underwater vehicle propulsion, such devices are hard to find in the market. Hence, the authors focused the research in the development of a system able to perform a reliable rotational speed and torque sensorless estimation. The design and implementation of a complete solution for underwater propulsion are presented as well as a novel rotor polarity identification technique exploiting a high-frequency injection control. Pool tests for the identification of the performances and of the dynamic parameters of the propulsion system are presented. Finally, the possibility of operating a sensorless estimation of the thrust and torque exerted by the propeller and pool test measurements are presented. These features could be exploited to improve navigation accuracy and involves obvious benefits in terms of cost reduction and reliability of the system.


2021 ◽  
Vol 234 ◽  
pp. 109223
Author(s):  
Artur K. Lidtke ◽  
Nicholas P. Linton ◽  
Hannah L. Wright ◽  
Stephen R. Turnock ◽  
Jon Downes

2020 ◽  
Vol 53 (2) ◽  
pp. 10749-10754
Author(s):  
Francesco Cordoni ◽  
Gianluca Bacchiega ◽  
Giulio Bondani ◽  
Robert Radu ◽  
Riccardo Muradore

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