Power plant fault monitoring using Recursive Principal Component Analysis RPCA

Abstract

Recursive Principal Components Analysis is explored as a method to identify and classify fault sources in a 12MW steam dual fuel power plant. The algorithm assessment is performed off-line by using data of relevant plant wide-information. A simple contributions matrix based in normalized data is proposed to diagnose plant faults. Results indicate it is possible to detect, classify and possibly even predict sources of plant failure.