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A prototype USAF engine health management (EHM) system was developed and ground tested during this Phase II SBIR program. The EHM system is capable of real-time mechanical monitoring and diagnostics, aero-thermal performance monitoring and diagnostics, and "engine signature" based life accumulation. For the first time, state-of-the-art anomaly detection, monitoring, diagnosis and advanced life prediction analysis were integrated together in a single real-time engine health monitoring system. Additionally, the EHM system was developed to assist the 2-level maintenance concept and IHPTET initiatives.
Presented at the International Gas Turbine & Aeroengine Congress & Exhibition, Orlando, FL, Jun 2-Jun 5, 1997.
Widely used for power generation, gas turbine engines are susceptible to faults due to the harsh working environment. Most engine problems are preceded by a sharp change in measurement deviations compared to a baseline engine, but the trend data of these deviations over time are contaminated with noise and non-Gaussian outliers. Gas Turbine Diagnostics: Signal Processing and Fault Isolation presents signal processing algorithms to improve fault diagnosis in gas turbine engines, particularly jet engines. The algorithms focus on removing noise and outliers while keeping the key signal features that may indicate a fault. The book brings together recent methods in data filtering, trend shift detection, and fault isolation, including several novel approaches proposed by the author. Each method is demonstrated through numerical simulations that can be easily performed by the reader. Coverage includes: Filters for gas turbines with slow data availability Hybrid filters for engines equipped with faster data monitoring systems Nonlinear myriad filters for cases where monitoring of transient data can lead to better fault detection Innovative nonlinear filters for data cleaning developed using optimization methods An edge detector based on gradient and Laplacian calculations A process of automating fault isolation using a bank of Kalman filters, fuzzy logic systems, neural networks, and genetic fuzzy systems when an engine model is available An example of vibration-based diagnostics for turbine blades to complement the performance-based methods Using simple examples, the book describes new research tools to more effectively isolate faults in gas turbine engines. These algorithms may also be useful for condition and health monitoring in other systems where sharp changes in measurement data indicate the onset of a fault.
Contents: Engine test; Definition of engine transient; Data reduction and analysis; Bounaries and limitations; Engine commonality and parameter selection; and Real time analysis.
A study was conducted to determine if the 'health' of an operating jet engine could be determined during the transient operating mode. This study was conducted as part of the preliminary work necessary for the design and development of an on-board NAVY fighter jet engine monitoring system. The ultimate objective of the on-board system will be to analyze the health of the engine in real-time and inform the pilot of the condition of the engine(s). This study concentrated on evaluating the gas path parameters since these parameters are responsive indicators of the majority of the causes of NAVY engine removals. The transient analysis investigated in this study indicated that parameter repeatability during the engine transient is adequate to verify specification performance. Also, gas path related anomalies can be detected through transient analysis; and corrected high pressure rotor speed used as the independent variable provides the accuracy and sensitivity necessary for baseline establishment and performance comparison. The inclusion of transient analysis with steady state analysis in a real-time on-board monitoring and analysis system will expand the mission coverage and provide an immediate performance check prior to takeoff as a result of a snap acceleration to takeoff power. (Author).