INVESTIGATION OF LOW-PRESSURE TURBINE AND AIRCRAFT PERFORMANCE PARAMETERS THROUGH MULTIPLE REGRESSION ANALYSIS
Faults in aircraft performance can be identified by the experts via analysis of the recorded flight information in today`s aircraft technology. The parameters used in identification of the faults include exhaust gas temperature, fuel flow, engine fan speed, vibration, oil pressure and oil temperatur...
Main Author: | |
---|---|
Format: | Article |
Language: | English |
Published: |
Hezarfen Aeronautics and Space Technologies Institue
2017-07-01
|
Series: | Havacılık ve Uzay Teknolojileri Dergisi |
Subjects: | |
Online Access: | http://www.jast.hho.edu.tr/JAST/index.php/JAST/article/view/8/8 |
id |
doaj-ca090972e8124d57b8919a0dfdc9dc55 |
---|---|
record_format |
Article |
spelling |
doaj-ca090972e8124d57b8919a0dfdc9dc552020-11-25T00:40:29ZengHezarfen Aeronautics and Space Technologies InstitueHavacılık ve Uzay Teknolojileri Dergisi1304-04481304-04482017-07-011023136INVESTIGATION OF LOW-PRESSURE TURBINE AND AIRCRAFT PERFORMANCE PARAMETERS THROUGH MULTIPLE REGRESSION ANALYSISMustagime Tülin YILDIRIM0Erciyes UniversityFaults in aircraft performance can be identified by the experts via analysis of the recorded flight information in today`s aircraft technology. The parameters used in identification of the faults include exhaust gas temperature, fuel flow, engine fan speed, vibration, oil pressure and oil temperature. In this study, a model that predicts the vibration parameters of the low pressure turbine using real time data of a Boeing 737-500 is developed. Using the developed model, it is aimed to determine a possible deterioration in performance by predicting vibration parameters of low pressure turbine and allowed vibration limits. Multiple regression analysis technique was used in the developed model. In our study, very highly significant relationships between vibration parameters of the low-pressure turbine and air speed, thrust lever angle right, N2 speed left and exhaust gas temperature were explored.http://www.jast.hho.edu.tr/JAST/index.php/JAST/article/view/8/8Low Pressure Turbine VibrationData MiningEngine Health Monitoring. |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mustagime Tülin YILDIRIM |
spellingShingle |
Mustagime Tülin YILDIRIM INVESTIGATION OF LOW-PRESSURE TURBINE AND AIRCRAFT PERFORMANCE PARAMETERS THROUGH MULTIPLE REGRESSION ANALYSIS Havacılık ve Uzay Teknolojileri Dergisi Low Pressure Turbine Vibration Data Mining Engine Health Monitoring. |
author_facet |
Mustagime Tülin YILDIRIM |
author_sort |
Mustagime Tülin YILDIRIM |
title |
INVESTIGATION OF LOW-PRESSURE TURBINE AND AIRCRAFT PERFORMANCE PARAMETERS THROUGH MULTIPLE REGRESSION ANALYSIS |
title_short |
INVESTIGATION OF LOW-PRESSURE TURBINE AND AIRCRAFT PERFORMANCE PARAMETERS THROUGH MULTIPLE REGRESSION ANALYSIS |
title_full |
INVESTIGATION OF LOW-PRESSURE TURBINE AND AIRCRAFT PERFORMANCE PARAMETERS THROUGH MULTIPLE REGRESSION ANALYSIS |
title_fullStr |
INVESTIGATION OF LOW-PRESSURE TURBINE AND AIRCRAFT PERFORMANCE PARAMETERS THROUGH MULTIPLE REGRESSION ANALYSIS |
title_full_unstemmed |
INVESTIGATION OF LOW-PRESSURE TURBINE AND AIRCRAFT PERFORMANCE PARAMETERS THROUGH MULTIPLE REGRESSION ANALYSIS |
title_sort |
investigation of low-pressure turbine and aircraft performance parameters through multiple regression analysis |
publisher |
Hezarfen Aeronautics and Space Technologies Institue |
series |
Havacılık ve Uzay Teknolojileri Dergisi |
issn |
1304-0448 1304-0448 |
publishDate |
2017-07-01 |
description |
Faults in aircraft performance can be identified by the experts via analysis of the recorded flight information in today`s aircraft technology. The parameters used in identification of the faults include exhaust gas temperature, fuel flow, engine fan speed, vibration, oil pressure and oil temperature. In this study, a model that predicts the vibration parameters of the low pressure turbine using real time data of a Boeing 737-500 is developed. Using the developed model, it is aimed to determine a possible deterioration in performance by predicting vibration parameters of low pressure turbine and allowed vibration limits. Multiple regression analysis technique was used in the developed model. In our study, very highly significant relationships between vibration parameters of the low-pressure turbine and air speed, thrust lever angle right, N2 speed left and exhaust gas temperature were explored. |
topic |
Low Pressure Turbine Vibration Data Mining Engine Health Monitoring. |
url |
http://www.jast.hho.edu.tr/JAST/index.php/JAST/article/view/8/8 |
work_keys_str_mv |
AT mustagimetulinyildirim investigationoflowpressureturbineandaircraftperformanceparametersthroughmultipleregressionanalysis |
_version_ |
1725289734498942976 |