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Sensor Fault Detection, Isolation, and Identification Using Multiple-Model-Based Hybrid Kalman Filter for Gas Turbine Engines
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Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
In this paper, a novel sensor fault detection, isolation, and identification (FDII) strategy is proposed using the multiple-model (MM) approach. The scheme is based on multiple hybrid Kalman filters (MHKFs), which represents ...
Robust sensor fault detection and isolation of gas turbine engines subjected to time-varying parameter uncertainties
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Academic Press
, 2016 , Article)
In this paper, a novel robust sensor fault detection and isolation (FDI) strategy using the multiple model-based (MM) approach is proposed that remains robust with respect to both time-varying parameter uncertainties and ...
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 ...
A hybrid prognosis and health monitoring strategy by integrating particle filters and neural networks for gas turbine engines
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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 ...
Adaptive sliding mode observer for sensor fault diagnosis of an industrial gas turbine
(
Elsevier Ltd
, 2015 , Article)
Sensors are one of the crucial components in gas turbines and the failure in sensor measurements can lead to serious problems in maintaining their safety and performance requirements. Our aim in this paper is to develop ...
Derivative-driven window-based regression method for gas turbine performance prognostics
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Elsevier Ltd
, 2017 , Article)
The domination of gas turbines in the energy arena is facing many challenges from environmental regulations and the plethora of renewable energy sources. The gas turbine has to operate under demand-driven modes and its ...
Particle filtering for state and parameter estimation in gas turbine engine fault diagnostics
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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
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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 ...
A novel affine qLPV model derivation method for fault diagnosis H∞ performance improvement
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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 ...
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 ...