Multi-Sensor Fault Diagnosis of Underwater Thruster Propeller Based on Deep Learning
With the rapid development of unmanned surfaces and underwater vehicles, fault diagnoses for underwater thrusters are important to prevent sudden damage, which can cause huge losses. The propeller causes the most common type of thruster damage. Thus, it is important to monitor the propeller’s health...
Saved in:
Main Authors: | Chia-Ming Tsai, Chiao-Sheng Wang, Yu-Jen Chung, Yung-Da Sun, Jau-Woei Perng |
---|---|
Format: | article |
Language: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/ea40d441dbfd439aa7df334d990a27b3 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Performance Simulation of a 5 kW hall Thruster
by: L. Yang, et al.
Published: (2021) -
Fault Diagnosis of Electric Motors Using Deep Learning Algorithms and Its Application: A Review
by: Yuanyuan Yang, et al.
Published: (2021) -
Influences of Magnetic Flux Density on Discharge Characteristics of Low-Power Hall Thruster
by: Weilong Guo, et al.
Published: (2021) -
Single Fault Diagnosis Method of Sensors in Cascade System Based on Data-Driven
by: Wenbo Na, et al.
Published: (2021) -
Inductive Coupling Discharge Characteristics of a 10-cm Dual-Stage 4-Grid Radiofrequency Ion Thruster
by: Yanxu Pu, et al.
Published: (2021)