On-Line Monitoring of Engine Performance Parameters and Algorithms to Identify Compressor Instabilities

Propulsion subsystems of future flight vehicles will run to higher thermal and aerodynamic loads for increased efficiencies. Increased loading and operating requirements cause serious mismatch between stages and components during off-design conditions with attendant compromise on stability margin. Another factor that affects component efficiencies is deviation in predicted performance due to in-flight damages and component aging. This deviation can propagate into more serious problems if not detected in time. More importantly, the deviation may be misinterpreted by control and decision unit as problems in other components. Misinterpretation of failures is crippling to future engines and aircrafts that incorporate performance seeking control methodology to optimize system performance on the fly. To ensure reliable and sustained improvement in subsystem performance, accurate monitoring and diagnosis are essential; therefore, the firm proposes to conduct a program of research and development on on-line monitoring of engine performance and advanced algorithms to identify compression system instabilities. This program will utilize artificial intelligence techniques and analytical redundancy features. The diagnostic algorithms will be model-based with inherent abilities to learn, reason, and adapt to failures.