Gas Turbine Engines
Published Online: 15 SEP 2009
Copyright © 2009 John Wiley & Sons, Ltd. All rights reserved.
Encyclopedia of Structural Health Monitoring
How to Cite
Roemer, M. J. 2009. Gas Turbine Engines. Encyclopedia of Structural Health Monitoring. .
- Published Online: 15 SEP 2009
Real-time, integrated health monitoring of gas turbine engines that can detect, classify, and predict developing engine faults is critical to reducing operating and maintenance costs while optimizing the life of critical engine components. Statistical-based anomaly detection algorithms, fault pattern recognition techniques, and advanced probabilistic models for diagnosing structural, performance and vibration-related faults and degradation continue to be developed for real-time monitoring environments. Integration and implementation of these advanced engine monitoring technologies have just begun to contribute to condition-based maintenance programs and provide operators and maintainers with the information they need to manage risk.
This article describes a few of the leading diagnostic and prognostic technologies that are currently being applied to gas turbines, which include real-time sensor validation and virtual sensing, performance anomaly detection and fault classification, vibration fault detection, and life-limited component prognostics. In selected applications, these technologies have been shown to nearly eliminate the propagation of erroneous sensor readings, improve maintenance decision effectiveness by providing early warning of incipient performance and mechanical faults, as well as gauge remaining and predicted future usage associated with critical components. Such advancements are providing operators and maintainers with a more comprehensive assessment of total engine health, both mechanically and thermodynamically, and thus are starting to be used for managing entire fleets of engines and in many cases predict future availability of those fleets.
- engine health monitoring;
- fault detection;
- performance analysis;
- vibration analysis;