US 11,867,397 B2
Gas turbine
Leonard Charles Angello, Mountain View, CA (US); Benjamin Emerson, East Point, GA (US); Timothy Charles Lieuwen, Atlanta, GA (US); David Robert Noble, Vale, NC (US); and Jared Kee, Atlanta, GA (US)
Assigned to ELECTRIC POWER RESEARCH INSTITUTE, INC., Palo Alto, CA (US)
Filed by Electric Power Research Institute, Inc., Palo Alto, CA (US)
Filed on May 10, 2019, as Appl. No. 16/409,248.
Prior Publication US 2020/0355368 A1, Nov. 12, 2020
Int. Cl. F23N 5/24 (2006.01); F01D 21/00 (2006.01)
CPC F23N 5/242 (2013.01) [F01D 21/003 (2013.01); F05D 2260/80 (2013.01); F05D 2270/303 (2013.01); F05D 2270/802 (2013.01); F23N 2223/04 (2020.01); F23N 2225/08 (2020.01); F23N 2227/20 (2020.01); F23N 2241/20 (2020.01)] 18 Claims
OG exemplary drawing
 
1. A non-transitory computer readable medium with instructions stored thereon, the instructions executable by one or more processors for:
selecting infrequent or frequent autotuning of a combustor having a combustion dynamics monitoring (CDM) algorithm having the capability to detect combustion system fault precursors, wherein the non-transitory computer readable medium is configured to be switchable between infrequent or frequent autotuning of the combustor; and
determining the health of the combustor, wherein said determining the health of the combustor comprises receiving real-time fuel gas temperature data from at least one thermocouple, wherein said determining the health of the combustor comprises comparing the real-time combustor fuel split data and fuel gas temperature data with data in a reference database.