Data-driven fault diagnosis based on coal-fired power plant operating data

This paper discusses data-driven fault diagnosis of the power plant reheater tube leakage based on their operating data. From the temperature sensors, fault data and normal data are measured. Mahalanobis distance (MD) analysis was performed to quantitatively analyze whether the distribution of fault data differed from that of the normal data. Then, sequential probability ratio test (SPRT) was performed to determine the time to anomalies (TTAs). To verify detected TTAs, power-generation data was used. This paper demonstrated the feasibility of the proposed approach to detect reheater tube leakage prior to the failure.