General Electric Company

Matthew Everett Moore

Alexander James Pistner

Sanjeev Shyam Heda

Sachin Srivastava

Sameer Vittal

Xiaomo Jiang

Devang Jagdish Gandhi

Ilan Leibu

Lijie Yu

Karen Warren Miller

Ketan Kalele

Raghavan Varadhan

Systems and methods for determining risk to operating a turbomachine are provided. According to one embodiment of the disclosure, a method may include receiving historical risk profile data associated with a fleet of turbomachines by at least one processor from a repository. The method can also include receiving ambient conditions of an environment in which a turbomachine is to be operated. Based at least in part on the historical risk profile data and in view of the ambient conditions, at least one risk threshold for at least one known operating profile can be developed. The method may continue with determining that the at least one risk threshold for the at least one known operating profile is reached. Based at least in part on a determination that the at least one risk threshold is reached, a mitigating action associated with the turbomachine can be taken.

Systems and methods for determining risk of operating a turbomachine

Systems and methods for predicting a surge event in a compressor of a turbomachine are provided. According to one embodiment of the disclosure, a system may include one or more computer processors associated with the turbomachine. The one or more computer processors may be operable to receive a plurality of performance parameters of the compressor and analyze the plurality of performance parameters to determine corrected performance values of the performance parameters. Based at least partially on the corrected performance values, a compressor efficiency may be determined. The processor may be further operable to standardize the compressor efficiency for a standard mode of operation, ascertain historical performance data associated with the standard mode of operation, and analyze the compressor efficiency based at least partially on the historical performance data. Based on the analysis of the compressor efficiency, a surge event may be selectively predicted.

Predicting a surge event in a compressor of a turbomachine

A monitoring system for a gas turbine includes a processor configured to receive an operating signal indicating an operating parameter of the gas turbine. The processor is configured to predict an occurrence of a lean blowout (LBO) event based on the operating parameter and an entropy ratio of combustion dynamics associated with a combustor of the gas turbine, wherein the LBO event corresponds to when the combustor stops firing. The processor is configured to send an alarm signal indicating the predicted LBO event to an electronic device prior to the occurrence of the LBO event.

System and method to enhance lean blowout monitoring

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Atlanta, GA, United States of America

Matthew Everett Moore