Utilizing data mining algorithms for identification and reconstruction of sensor faults: a Thermal Power Plant case study

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.