Effects of Humidity Condensation on the Trend of Gas Turbine Performance DeteriorationSource: Journal of Engineering for Gas Turbines and Power:;2015:;volume( 137 ):;issue: 012::page 122604DOI: 10.1115/1.4030815Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Performance deterioration in gas turbine engines (GTEs) depends on various factors in the ambient and the operating conditions. For example, humidity condensation at the inlet duct of a GTE creates water mist, which affects the fouling phenomena in the compressor and varies the performance. In this paper, the effective factors on the shortterm performance deterioration of a GTE are identified and studied. GTE performance level is quantified with two physicsbased performance indicators, calculated from the recorded operating data from the control system of a GTE over a full time between overhaul (TBO) period. A regularized particle filtering (RPF) framework is developed for filtering the indicator signals, and an adaptive neurofuzzy inference system (ANFIS) is then trained with the filtered signals and the effective ambient and the operating conditions, i.e., the power, the air mass flow, and the humidity condensation rate. The trained ANFIS model is then run to simulate the GTE performance deterioration in different conditions for system identification. The extracted behavior of the system clearly shows the dependency of the trend of performance deterioration on the operating conditions, especially the humidity condensation rate. The developed technique and the results can be utilized for GTE performance prediction, as well as for suggesting the optimum humidity supply at the GTE intake to control the performance deterioration rate.
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contributor author | Hanachi, Houman | |
contributor author | Liu, Jie | |
contributor author | Banerjee, Avisekh | |
contributor author | Chen, Ying | |
date accessioned | 2017-05-09T01:18:29Z | |
date available | 2017-05-09T01:18:29Z | |
date issued | 2015 | |
identifier issn | 1528-8919 | |
identifier other | gtp_137_12_122604.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/158113 | |
description abstract | Performance deterioration in gas turbine engines (GTEs) depends on various factors in the ambient and the operating conditions. For example, humidity condensation at the inlet duct of a GTE creates water mist, which affects the fouling phenomena in the compressor and varies the performance. In this paper, the effective factors on the shortterm performance deterioration of a GTE are identified and studied. GTE performance level is quantified with two physicsbased performance indicators, calculated from the recorded operating data from the control system of a GTE over a full time between overhaul (TBO) period. A regularized particle filtering (RPF) framework is developed for filtering the indicator signals, and an adaptive neurofuzzy inference system (ANFIS) is then trained with the filtered signals and the effective ambient and the operating conditions, i.e., the power, the air mass flow, and the humidity condensation rate. The trained ANFIS model is then run to simulate the GTE performance deterioration in different conditions for system identification. The extracted behavior of the system clearly shows the dependency of the trend of performance deterioration on the operating conditions, especially the humidity condensation rate. The developed technique and the results can be utilized for GTE performance prediction, as well as for suggesting the optimum humidity supply at the GTE intake to control the performance deterioration rate. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Effects of Humidity Condensation on the Trend of Gas Turbine Performance Deterioration | |
type | Journal Paper | |
journal volume | 137 | |
journal issue | 12 | |
journal title | Journal of Engineering for Gas Turbines and Power | |
identifier doi | 10.1115/1.4030815 | |
journal fristpage | 122604 | |
journal lastpage | 122604 | |
identifier eissn | 0742-4795 | |
tree | Journal of Engineering for Gas Turbines and Power:;2015:;volume( 137 ):;issue: 012 | |
contenttype | Fulltext |