DocumentCode :
2520125
Title :
Soft sensors and artificial intelligence for nuclear fusion experiments
Author :
Rizzo, Alessandro
Author_Institution :
Dipt. di Elettrotec. ed Elettron., Politec. di Bari, Bari, Italy
fYear :
2010
fDate :
26-28 April 2010
Firstpage :
1068
Lastpage :
1072
Abstract :
Soft sensors are mathematical models able to estimate process variables. They can work in parallel with hardware sensors, and can be implemented at a low-cost on existing hardware. They are useful for back-up of measuring devices, reduction of measuring hardware requirements, real-time estimation for monitoring and control, sensor validation, fault detection and diagnosis, what-if analysis. In industrial applications, data-driven approaches, especially based on soft-computing techniques, are very promising. In this paper we review important issues in soft sensor design and applications, especially concerning the applications in the field of nuclear fusion.
Keywords :
artificial intelligence; fault diagnosis; mathematical analysis; nuclear fusion; power engineering computing; artificial intelligence; data-driven approaches; fault detection; fault diagnosis; hardware sensors; mathematical models; nuclear fusion experiments; parallel sensors; real-time estimation; sensor validation; soft sensors; soft-computing techniques; Artificial intelligence; Fault detection; Fusion reactors; Hardware; Intelligent sensors; Mathematical model; Monitoring; Physics; Pollution measurement; Sensor fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
MELECON 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference
Conference_Location :
Valletta
Print_ISBN :
978-1-4244-5793-9
Type :
conf
DOI :
10.1109/MELCON.2010.5476042
Filename :
5476042
Link To Document :
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