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Fault Detection and Diagnosis of Compressor Faults in a Gas Turbine Electric Generator

Fault Detection and Diagnosis of Compressor Faults in a Gas Turbine Electric Generator

ABSTRACT

In modern mechanical and aviation industries, gas turbine engines are essential components. However, due to the intricacy of their nature and functioning, they need to be completely monitored to prevent unanticipated damages and operational faults. The goal of this study is to provide a viable diagnostic approach, estimation of compressor faults in a gas turbine electric generator. An improved frame work for the diagnosis and estimation of fault in a gas turbine was proposed using an extended kalman filter algorithm. The extended kalman filter utilizes data collected over time that contains noise (random variations) and other errors to provide values that are often closer to the actual condition of the system as it pertains to achieving a specific objective. The proposed fault diagnosis framework developed show a 99.85% accurate fault estimation and early detection of compressor faults in a gas turbine electric generator.

Keywords: Fault Diagnosis; Diagnosis of Compressor Faults; Gas Turbine Electric Generator

Authorship
1Ufuoma Onochojah and 2Innocent I. Eneh

DOI: https://doi.org/10.5281/zenodo.7426561 | FULL PDF

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