Data Analytics for Performance Monitoring of Gas Turbine Engine

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Published Sep 24, 2018
Yuan Liu Avisekh Banerjee Thambirajah Ravichandran Amar Kumar Glenn Heppler

Abstract

Performance analysis of a low power rating and partially loaded industrial gas turbine engine (GTE) was carried out by using a model-free data analytic approach. By adopting an efficient input selection method, several performance indices (PI) are proposed to quantify the performance of the GTE. These indices are extracted using engine operating data related to power output and parameters related to fuel consumption, and validated with engine performance monitoring measurements for a three year period corresponding to one time between overhaul intervals. The dependency of the PIs on ambient temperature has been studied by using linear and polynomial fitting curves. Then novel methods are introduced for analysis of short-term and long-term performance deterioration arising from compressor fouling and structural degradation respectively. The results have clearly shown the ability of the proposed PIs to detect short-term compressor fouling as well as long-term performance deterioration, which is directly relevant to the Prognostics and Health Management of gas turbine engine.

How to Cite

Liu, Y., Banerjee, A., Ravichandran, T., Kumar, A., & Heppler, G. (2018). Data Analytics for Performance Monitoring of Gas Turbine Engine. Annual Conference of the PHM Society, 10(1). https://doi.org/10.36001/phmconf.2018.v10i1.470
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Keywords

Performance Monitoring, model-free data analytic approach, gas turbine engine

Section
Technical Papers

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