Standard Article

Monitoring of Aircraft Engines

Aerospace Applications

Aircraft Systems

  1. Visakan Kadirkamanathan,
  2. Peter Fleming

Published Online: 15 SEP 2009

DOI: 10.1002/9780470061626.shm139

Encyclopedia of Structural Health Monitoring

Encyclopedia of Structural Health Monitoring

How to Cite

Kadirkamanathan, V. and Fleming, P. 2009. Monitoring of Aircraft Engines. Encyclopedia of Structural Health Monitoring. .

Author Information

  1. University of Sheffield, Rolls-Royce University Technology Centre, Department of Automatic Control and Systems Engineering, Sheffield, UK

Publication History

  1. Published Online: 15 SEP 2009


Aircraft engines are highly reliable complex systems with enhanced safety requirements. Monitoring engine component degradations to avoid the high flight shut down and repair costs is vital for the aircraft manufacturers and operators in the current business model. Monitoring systems are required to perform diagnosis of developing faults and prognosis to plan maintenance actions. The common engine faults are due to the mechanical components requiring vibration analysis and oil and debris monitoring, as well as the gas path component faults requiring efficiency and other performance parameter monitoring. For vibration monitoring, spectral signatures are used for detecting changes to the normal engine operation. On the other hand, prognosis is often based on trending the gas path performance parameters. The use of intelligent systems methods such as case-based reasoning, neural networks, and fuzzy systems has proved popular because of the lack of precise knowledge about the behavior of a complex system like the aircraft engine. Where accurate models are available, model-based methods such as the Kalman filter, observers and, where dynamic data are available, system identification approaches have found application. Often, information from more than one analysis is integrated in decision making. The grid computing architecture-based distributed Aircraft Maintenance Environment (DAME) project shows the future direction in which aircraft engine monitoring is heading.


  • aircraft engine;
  • fault diagnosis;
  • prognosis;
  • anomaly detection;
  • intelligent systems;
  • Kalman filter;
  • trending analysis