DocumentCode
3520263
Title
Research of intelligent condition monitoring model for AUV
Author
Yujia Wang ; Mingjun Zhang ; Ruichen Sun
Author_Institution
College of Mechanical and Electrical Engineering, Harbin Engineering University
Volume
2
fYear
2004
fDate
15-19 June 2004
Firstpage
1707
Lastpage
1711
Abstract
An intelligent condition monitoring model for propellers and rudder of autonomous underwater vehicles (AUVs) was proposed, which was based on the FALCON with a 3-step learning algorithm. The steps of the algorithm included initialization with fuzzy C clustering, rules extraction with maximum weights matrix and parameters fine-tuning with GA. It constructed the configuration of the model, analyzed the process of the monitoring, and discussed the method of evaluation for the model. The results of the computer simulation by actual experiment data of a certain AUV shows that the condition monitoring model proposed in this article is feasible and prove that the learning algorithm for the FALCON is effective.
Keywords
Algorithm design and analysis; Clustering algorithms; Computerized monitoring; Condition monitoring; Control system synthesis; Data mining; Fuzzy logic; Neural networks; Propellers; Underwater vehicles; FALCON; autonomous underwater vehicle; condition monitoring; learning algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Conference_Location
Hangzhou, China
Print_ISBN
0-7803-8273-0
Type
conf
DOI
10.1109/WCICA.2004.1340963
Filename
1340963
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