Title :
An approach to fault diagnosis based on a hierarchical information fusion scheme [and turbine application]
Author :
Fu, Qiang ; Shen, Yi ; Zhang, Jian Qiu ; Liu, Shengli
Author_Institution :
Dept. of Control Sci. & Eng., Harbin Inst. of Technol., China
Abstract :
A novel approach, based on a hierarchical information fusion scheme and using the different symptoms of the faults in the various locations of a system, to fault diagnosis of the system is presented. Firstly, the data fusion of various location sensors in a system is used to guarantee the reliability and accuracy of measurements. Then, the different symptoms of the faults in various locations of a system are classified via multiple neural networks to obtain local decisions. These local decisions are fused by fuzzy integral in which the relative importance of each network is also considered. Finally, we apply this approach to a model of a turbine system. The simulation results verify the effectiveness of the proposed method
Keywords :
diagnostic expert systems; fault diagnosis; feedforward neural nets; fuzzy logic; fuzzy set theory; sensor fusion; steam turbines; data fusion; different fault symptoms; fault diagnosis; feedforward neural net; fuzzy integral; hierarchical information fusion scheme; local decisions; measurement accuracy; measurement reliability; multiple neural networks; steam turbine system model; Availability; Fault diagnosis; Neural networks; Pollution measurement; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Signal processing; Signal resolution; Turbines;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2001. IMTC 2001. Proceedings of the 18th IEEE
Conference_Location :
Budapest
Print_ISBN :
0-7803-6646-8
DOI :
10.1109/IMTC.2001.928202
