Title :
Failure Detection of Fire Alarm Sensors Based on Information Fusion
Author :
Qiu, Jinshui ; Liu, Boyun
Author_Institution :
Power Eng. Coll., Naval Univ. of Eng., Wuhan, China
fDate :
Nov. 30 2009-Dec. 1 2009
Abstract :
As for the safety inspection and monitoring, it is very important to find the fault of the transducer itself. In view of the redundant transducer group are often used in the fire alarm system, this paper brings forward a fault diagnostic structure with the fire alarm sensors fault diagnosis module. This module introduces the information fusion basing on RBF neural network and the redundancy calculation, it shows that the failure of the fire alarm sensors can be detected and rehabilitated.
Keywords :
alarm systems; fault diagnosis; sensor fusion; smoke detectors; RBF neural network; failure detection; fault diagnostic structure; fire alarm sensors; fire alarm system; information fusion; safety inspection; safety monitoring; transducer faults; Alarm systems; Condition monitoring; Fault diagnosis; Fires; Inspection; Neural networks; Safety; Sensor fusion; Sensor systems; Transducers; failure detection; information fusion; sensors;
Conference_Titel :
Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3888-4
DOI :
10.1109/KAM.2009.135