Title :
Sensor fusion and sensor fault detection with fuzzy clustering
Author :
ElMadbouly, E.E. ; Abdalla, A.E. ; ElBanby, Gh.M.
Author_Institution :
Fac. Of Electron. Eng., Menoufia Univ., Menoufia, Egypt
fDate :
Nov. 30 2010-Dec. 2 2010
Abstract :
In this paper, an efficient approach for multisensor fusion and fault detection is presented. This approach uses Fuzzy Cluster-Means (FCM) algorithm for signal separation. Subsequently, a fused signal is generated by the fusion engine based on the concept of the center of gravity (COG) deffuzification method. Sensor fault detector is designed based on the residual between the total fused signal and the output of each sensor separately. The simulation results showed that the proposed approach using FCM and fusion engine based COG techniques improved the diagnosis accuracy.
Keywords :
fuzzy set theory; pattern clustering; sensor fusion; source separation; center of gravity; deffuzification method; fusion engine; fuzzy cluster means; multisensor fusion; sensor fault detection; signal separation; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Engines; Fault detection; Sensor fusion; Simulation; Fuzzy C-Means and Fault detection; Sensor fusion;
Conference_Titel :
Computer Engineering and Systems (ICCES), 2010 International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-7040-2
DOI :
10.1109/ICCES.2010.5674866