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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
(
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 ...
Fault detection and isolation of two-dimensional (2D) systems
(
Elsevier B.V.
, 2017 , Article)
In this work, we develop a novel fault detection and isolation (FDI) scheme for discrete-time two-dimensional (2D) systems that are represented by the Fornasini?Marchesini model II (FMII). This is accomplished by generalizing ...
Cost performance based control reconfiguration in multi-agent systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
In this paper, a reconfigurable control protocol for a linear multi-agent system seeking consensus in presence of actuator faults and saturations is investigated. The control protocol consists of two parts: healthy system ...
Sensor fault detection and isolation using multiple robust filters for linear systems with time-varying parameter uncertainty and error variance constraints
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
In this paper, a robust sensor fault detection and isolation (FDI) strategy is proposed by means of the multiple model (MM)-based scheme. The proposed approach is composed of robust Kalman filters (RKF) with error variance ...
Nonlinear fault diagnosis of jet engines by using a multiple model-based approach
(
ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition, GT2011
, 2011 , Conference Paper)
In this paper, a nonlinear fault detection and isolation (FDI) scheme that is based on the concept of multiple model (MM) approach is proposed for jet engines. A modular and a hierarchical architecture is proposed which ...
Multiple-model sensor and components fault diagnosis in gas turbine engines using autoassociative neural networks
(
American Society of Mechanical Engineers
, 2014 , Article)
In this paper the problem of fault diagnosis in an aircraft jet engine is investigated by using an intelligent-based methodology. The proposed fault detection and isolation (FDI) scheme is based on the multiple model ...
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 ...
Fault detection and isolation of Riesz spectral systems: A geometric approach
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
The Riesz spectral (RS) systems represent a large class of parabolic and hyperbolic partial differential equations (PDE) in infinite-dimensional systems. In this work, a fault detection and isolation (FDI) methodology for ...
A novel particle filter parameter prediction scheme for failure prognosis
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
Particle filters are well-known as powerful tools for accomplishing state and parameter estimation and their propagation prediction in nonlinear dynamical systems. Their ability to include system model parameters as part ...