Title :
Utilizing data mining algorithms for identification and reconstruction of sensor faults: a Thermal Power Plant case study
Author :
Athanasopoulou, Christina ; Chatziathanasiou, Vasilis ; Petridis, Ioannis
Author_Institution :
Electr. & Comput. Eng. Dept., Aristotle Univ. of Thessaloniki, Thessaloniki
Abstract :
This paper describes a procedure of identifying sensor faults and reconstructing the erroneous measurements. Data mining algorithms are successfully applied for deriving models that estimate the value of one variable based on correlated others. The estimated values can then be used instead of the recorded ones of a measuring instrument with false reading. The aim is to reassure the correctness of data entered to an optimization software application under development for the Thermal Power Plants of Western Macedonia, Greece.
Keywords :
data mining; power engineering computing; power generation faults; power system identification; sensors; thermal power stations; Western Macedonia thermal power plant; data mining algorithm; sensor fault identification; sensor fault reconstruction; Application software; Data mining; Fault diagnosis; Instruments; Intelligent sensors; Personnel; Power generation; Redundancy; Sensor phenomena and characterization; Thermal sensors; Data mining; power generation; sensor;
Conference_Titel :
Power Tech, 2007 IEEE Lausanne
Conference_Location :
Lausanne
Print_ISBN :
978-1-4244-2189-3
Electronic_ISBN :
978-1-4244-2190-9
DOI :
10.1109/PCT.2007.4538639
