Title :
Fault diagnosis based on data-driven of ship course control
Author :
Xiuyan Peng ; Chunzhi Sun
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
Abstract :
A method of data driven fault diagnosis for ship course control of sensor fault and steering gear fault in this paper. The offline data are used to identify the parity space and vector, and designed observer class residual generator, which can construct the residual signal, and evaluate the threshold value, so as to realize fault diagnosis of abnormal condition. The results showed that the residual signal can detect the fault signal accurately and quickly.
Keywords :
fault diagnosis; gears; marine control; observers; ships; signal detection; steering systems; velocity control; class residual generator; data driven fault diagnosis method; fault signal detection; offline data; parity space; parity vector; residual signal; sensor fault; ship course control; steering gear fault; threshold value evaluation; Abstracts; Automation; Educational institutions; Fault diagnosis; Generators; Intelligent control; Marine vehicles; fault diagnosis; offline data; parity space; residual generator; threshold;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7053523
