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NASA NTRS2003

Tracking and Control of Gas Turbine Engine Component Damage/Life

This paper describes damage mechanisms and the methods of controlling damages to extend the on-wing life of critical gas turbine engine components. Particularly, two types of damage mechanisms are discussed: creep/rupture and thermo-mechanical fatigue. To control these damages and extend the life of engine hot-section components, we have investigated two methodologies to be implemented as additional control logic for the on-board electronic control unit. This new logic, the life-extending control (LEC), interacts with the engine control and monitoring unit and modifies the fuel flow to reduce component damages in a flight mission. The LEC methodologies were demonstrated in a real-time, hardware-in-the-loop simulation. The results show that LEC is not only a new paradigm for engine control design, but also a promising technology for extending the service life of engine components, hence reducing the life cycle cost of the engine.

Jaw, Link C.↗

NASA NTRS1998

Using Neural Networks for Sensor Validation

This paper presents the results of applying two different types of neural networks in two different approaches to the sensor validation problem. The first approach uses a functional approximation neural network as part of a nonlinear observer in a model-based approach to analytical redundancy. The second approach uses an auto-associative neural network to perform nonlinear principal component analysis on a set of redundant sensors to provide an estimate for a single failed sensor. The approaches are demonstrated using a nonlinear simulation of a turbofan engine. The fault detection and sensor estimation results are presented and the training of the auto-associative neural network to provide sensor estimates is discussed.

Mattern, Duane L.↗