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

fYear

2007

Firstpage

2082

Lastpage

2087

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Tech, 2007 IEEE Lausanne

Conference_Location

Lausanne

Print_ISBN

978-1-4244-2189-3

Electronic_ISBN

978-1-4244-2190-9

Type

conf

DOI

10.1109/PCT.2007.4538639

Filename

4538639