The Fault Diagnosis Research for the Underwater Vehicle System Based on SOFCMAC
Component Analysis(PCA)and Self-Organizing Fuzzy Cerebellar Model Articulation Controller(SOFCMAC).The signal prediction model approach based on PCA and SOFCMAC is proposed in this paper.According to the history data,it can predict the signal data in the future time using the SOFCMAC method.And the statistic,Squared Prediction Error(SPE),is introduced into the approach.According to the change of the SPE value,this model can judge whether the underwater system fault occurs.Then the linear variable reconstruction method is used to isolate the fault.The water tank experimental results show that the proposed approach is capable of detecting and isolating the fault in the vehicle sensor systems efficiently and accurately.
fault diagnosis principal component analysis neural network fault detection fault isolation
Ting Zhu Daqi Zhu
Laboratory of Underwater Vehicles and Intelligent Systems,Shanghai Maritime University,Haigang Avenue 1550,Shanghai 200135,China
国际会议
长沙
英文
1390-1394
2014-05-31（万方平台首次上网日期，不代表论文的发表时间）