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 structure for both state and parameter estimation in a nonlinear non-Gaussian system is developed. The performance of the developed framework is evaluated in an application to the gas turbine engine state and health parameters estimation by using different scenarios. The developed method is identified to be applicable for fault diagnosis of an engine system while it is subjected to concurrent and simultaneous loss of effectiveness faults in the system components. 2013 AACC American Automatic Control Council.Qatar National ...
For turbine engine performance monitoring purposes, system identification techniques are often used ...
In this paper, an efficient sensor fault detection and isolation (FDI) strategy is proposed based on...
Health monitoring and prognosis of nonlinear systems is mainly concerned with system health tracking...
In this paper, a dual estimation methodology is developed for both time-varying parameters and state...
rgao @ engr.uconn.edu This paper investigates a real-time fault detection and degradation prediction...
Health condition monitoring of Gas Turbine Engine (GTE) components is key for predictive maintenance...
Health monitoring of nonlinear systems is broadly concerned with the system health tracking and its ...
Particle filters are well-known as powerful tools for accomplishing state and parameter estimation a...
This paper introduces an on-line particle-filtering-based framework for failure prognosis in nonline...
In this paper, a novel hybrid structure is proposed for the development of health monitoring techniq...
Thesis (M.S.)--University of Hawaii at Manoa, 2008.Includes bibliographical references (leaves 58-60...
Efficient diagnosis and prognosis of system faults depend on the ability to estimate the system stat...
A fully adaptive particle filtering algorithm is proposed in this paper which is capable of updating...
A fully adaptive particle filtering algorithm is proposed in this paper which is capable of updating...
Gas turbine prognostics is a promising technology that is used in aircraft maintenance because of it...
For turbine engine performance monitoring purposes, system identification techniques are often used ...
In this paper, an efficient sensor fault detection and isolation (FDI) strategy is proposed based on...
Health monitoring and prognosis of nonlinear systems is mainly concerned with system health tracking...
In this paper, a dual estimation methodology is developed for both time-varying parameters and state...
rgao @ engr.uconn.edu This paper investigates a real-time fault detection and degradation prediction...
Health condition monitoring of Gas Turbine Engine (GTE) components is key for predictive maintenance...
Health monitoring of nonlinear systems is broadly concerned with the system health tracking and its ...
Particle filters are well-known as powerful tools for accomplishing state and parameter estimation a...
This paper introduces an on-line particle-filtering-based framework for failure prognosis in nonline...
In this paper, a novel hybrid structure is proposed for the development of health monitoring techniq...
Thesis (M.S.)--University of Hawaii at Manoa, 2008.Includes bibliographical references (leaves 58-60...
Efficient diagnosis and prognosis of system faults depend on the ability to estimate the system stat...
A fully adaptive particle filtering algorithm is proposed in this paper which is capable of updating...
A fully adaptive particle filtering algorithm is proposed in this paper which is capable of updating...
Gas turbine prognostics is a promising technology that is used in aircraft maintenance because of it...
For turbine engine performance monitoring purposes, system identification techniques are often used ...
In this paper, an efficient sensor fault detection and isolation (FDI) strategy is proposed based on...
Health monitoring and prognosis of nonlinear systems is mainly concerned with system health tracking...