Adaptive sensor fault detection and identification using particle filter algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Disturbance attenuation in fault detection of gas turbine engines: a discrete robust observer design
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Aircraft engine controllers are designed and operated to provide desired performance and stability margins. This paper addresses the relationship between acceleration action and engine component life usage. Based upon this relationship, an intelligent approach for designing acceleration schedules that provide proper tradeoffs between performance and engine life usage is proposed. The benefit of this approach is that it is expected to maintain safety while minimizing the overall operating costs. With the advances of computer technology, engine operation models, and damage physics, it is necessary to reevaluate the control strategy for overall operating cost consideration. This paper uses the thermal--mechanical fatigue (TMF) of a critical component to demonstrate how an intelligent acceleration algorithm can drastically reduce the engine life usage with minimum sacrifice in performance. We have modeled and calculated the probability of failure due to TMF damage. A Monte Carlo simulation is also performed to evaluate the likelihood of engine damage accumulation under various operating conditions. By means of genetic search algorithms, optimal acceleration schedules can be obtained with multiple constraints. The simulation results show that a selected best acceleration schedule can provide a significant life saving in selected engine components.