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A hybrid prognosis and health monitoring strategy by integrating particle filters and neural networks for gas turbine engines
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
In this paper, a novel hybrid structure is proposed for the development of health monitoring techniques of nonlinear systems by integration of model-based and computationally intelligent and data-driven techniques. In our ...
Particle filtering for state and parameter estimation in gas turbine engine fault diagnostics
(
Institute of Electrical and Electronics Engineers Inc.
, 2013 , Conference Paper)
In this paper, a novel method for a time-varying parameter estimation technique using particle filters is proposed based on the concept of Recursive Prediction Error (RPE). According to the proposed method, a parallel ...
Forecasting the health of gas turbine components through an integrated performance-based approach
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
In this study, we present an integrated method for detecting and forecasting the health of gas turbine components as degraded over time. An advanced model-based real time performance adaptation approach is developed for ...
Multiple-model based sensor fault diagnosis using hybrid kalman filter approach for nonlinear gas turbine engines
(
2013 1st American Control Conference, ACC 2013
, 2013 , Conference Paper)
In this paper, an efficient sensor fault detection and isolation (FDI) strategy is proposed based on multiple-model (MM) approach. The scheme is composed of hybrid kalman filters (HKF) by integrating a nonlinear gas turbine ...