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Transient gas turbine performance diagnostics through nonlinear adaptation of compressor and turbine maps
(
American Society of Mechanical Engineers (ASME)
, 2015 , Article)
Gas turbines are faced with new challenges of increasing flexibility in their operation while reducing their life cycle costs, leading to new research priorities and challenges. One of these challenges involves the ...
A novel affine qLPV model derivation method for fault diagnosis H∞ performance improvement
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
In this paper, a methodology for an affine quasilinear parameter varying (qLPV) model derivation is proposed. The nonlinear model of the system is converted into a qLPV model by hiding the nonlinearities in the scheduling ...
Performance-based prognosis scheme for industrial gas turbines
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
In this paper, we present a novel method for performance-based prognostics of industrial gas turbines. The concept of performance adaptation is implemented through a dynamic engine model that is developed in Matlab/Simulink ...
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 ...
Sensor fault detection and isolation of an industrial gas turbine using partial kernel PCA
(
9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2015
, 2015 , Conference Paper)
In this paper, partial kernel principal component analysis (PKPCA) is studied for sensor fault detection and isolation of an aeroderivative industrial gas turbine. Principal component analysis (PCA) is an effective tool ...
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 ...
Dynamic performance simulation of an aeroderivative gas turbine using the matlab simulink environment
(
American Society of Mechanical Engineers (ASME)
, 2013 , Conference Paper)
In fossil fuel applications, such as air transportation and power generation systems, gas turbine is the prime mover which governs the aircraft's propulsive and the plant's thermal efficiency, respectively. Therefore, an ...
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 ...
Health monitoring and degradation prognostics in gas turbine engines using dynamic neural networks
(
American Society of Mechanical Engineers (ASME)
, 2015 , Conference Paper)
In this paper two artificially intelligent methodologies are proposed and developed for degradation prognosis and health monitoring of gas turbine engines. Our objective is to predict the degradation trends by studying ...
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 ...