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 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.