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Intelligent Based Aircraft Engine Health Monitoring: Improving Aircraft Engine Maintenance Effectiveness and Reliability - Tapa blanda

Demirci, Şeref; Hajiyev, Chingiz

 
9783845419657: Intelligent Based Aircraft Engine Health Monitoring: Improving Aircraft Engine Maintenance Effectiveness and Reliability
Tapa blanda
ISBN 10: 3845419652 ISBN 13: 9783845419657
Editorial: LAP LAMBERT Academic Publishing, 2011

Sinopsis

Engine Health monitoring (EHM) has been very popular subject to increase aircraft availability with the minimum maintenance cost. The study is aimed at providing a method to monitor the aircraft engine health during the flight with the aim of providing an opportunity for early fault detection to improve airline maintenance effectiveness and reliability. Since the impending engine failures may cause to change the engine parameters such as Fuel Flow (FF), Exhaust Gas Temperature (EGT), engine fan speed (N1), engine compressor speed (N2), etc., engine deteriorations or faults may be identified before they occur by monitoring them. So as to monitor engine health in flight, the automation of current work for EHM done manually by airlines is developed by using fuzzy logic (FL) and neural network (NN) models. FL is selected to develop automated EHM system (AEHMS), since it is very useful method for automation health monitoring. The fuzzy rule inference system for different engine faults is based on the expert knowledge and real life data in Turkish Airlines fleet. The complete loop of EHM is automatically performed by the visual basic programs and Fuzzy Logic Toolbox in MATLAB.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

Engine Health monitoring (EHM) has been very popular subject to increase aircraft availability with the minimum maintenance cost. The study is aimed at providing a method to monitor the aircraft engine health during the flight with the aim of providing an opportunity for early fault detection to improve airline maintenance effectiveness and reliability. Since the impending engine failures may cause to change the engine parameters such as Fuel Flow (FF), Exhaust Gas Temperature (EGT), engine fan speed (N1), engine compressor speed (N2), etc., engine deteriorations or faults may be identified before they occur by monitoring them. So as to monitor engine health in flight, the automation of current work for EHM done manually by airlines is developed by using fuzzy logic (FL) and neural network (NN) models. FL is selected to develop automated EHM system (AEHMS), since it is very useful method for automation health monitoring. The fuzzy rule inference system for different engine faults is based on the expert knowledge and real life data in Turkish Airlines fleet. The complete loop of EHM is automatically performed by the visual basic programs and Fuzzy Logic Toolbox in MATLAB.

Biografía del autor

Seref Demirci has a BSc, MSc and PhD degree inAeronautical Engineering at the Istanbul TechnicalUniversity. He had held positions in ReliabilityManager, Maintenance EngineeringManager in Turkish Airlines. In his lastposition, he is responsible for the management of providing engineering support to the THY fleet of about 200 aircraft.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2011
Idioma
Inglés
ISBN 10 
3845419652
ISBN 13 
9783845419657
Encuadernación
Tapa blanda
Número de páginas
132
Contacto del fabricante
no disponible
Persona responsable
no disponible