GAS turbine sensor fault diagnostic system in a real-time executable digital-twin

Cruz-Manzo, Samuel, Panov, Vili and Bingham, Chris (2023) GAS turbine sensor fault diagnostic system in a real-time executable digital-twin. Journal of the Global Power and Propulsion Society, 7 . pp. 85-94. ISSN 2515-3080

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GAS turbine sensor fault diagnostic system in a real-time executable digital-twin
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In this study, a sensor fault diagnostic system to detect/isolate and accommodate faults in sensors from an industrial gas turbine has been developed. The sensor fault diagnostic module is integrated with a gas turbine real-time executable digital-twin (RT xDT) reported in a previous study. The sensor fault diagnostic module of the digital-twin considers analytical sensor redundancy using a reference engine model to provide redundant estimates of measured engine variables. A Software-in-the-Loop (S-i-L) architecture and Hardware-in-the-Loop (H-i-L) facility are constructed to assess the sensor diagnostic module (fault detection/ fault isolation) during failure in sensors from the engine. The results demonstrated that if the discrepancy between virtual measurement (provided by digital-twin) and sensor measurement exceeds the prescribed tolerance levels, the sensor fault diagnostic logic determines the state of switching between the virtual and engine sensor measurements in a dual lane control configuration of the gas turbine control system. The sensor fault detection system implemented in the gas turbine RT xDT can be deployed onto a distributed control system of industrial gas turbines to diagnose sensor deficiencies and ensure continuous and safe operation of the gas turbine. Consequently, the developed system will increase engine availability and reliability by diagnosing engine operational deficiencies before severe failure.

Keywords:Industrial gas turbines, Digital twin
Subjects:J Technologies > J910 Energy Technologies
H Engineering > H300 Mechanical Engineering
Divisions:College of Science > School of Engineering
ID Code:54122
Deposited On:18 Apr 2023 10:57

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