Robust fault diagnosis of aircraft engines: A nonlinear adaptive estimation-based approach
X Zhang, L Tang, J Decastro - IEEE Transactions on Control …, 2012 - ieeexplore.ieee.org
In this brief, a fault detection and isolation (FDI) method is developed for aircraft engines by
utilizing nonlinear adaptive estimation techniques. The fault diagnosis method follows a …
utilizing nonlinear adaptive estimation techniques. The fault diagnosis method follows a …
Fault diagnosis in gas turbine based on neural networks: Vibrations speed application
The diagnosis of faults and failures in industrial systems is becoming increasingly essential.
This work proposes the development of a fault diagnostics system based on artificial …
This work proposes the development of a fault diagnostics system based on artificial …
An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines
M Amozegar, K Khorasani - Neural Networks, 2016 - Elsevier
In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines
is proposed by developing an ensemble of dynamic neural network identifiers. For health …
is proposed by developing an ensemble of dynamic neural network identifiers. For health …
Gray-box approach for fault detection of dynamical systems
HG Park, M Zak - J. Dyn. Sys., Meas., Control, 2003 - asmedigitalcollection.asme.org
We present a fault detection method called the gray-box. The term “gray-box” refers to the
approach wherein a deterministic model of system, ie,“white box,” is used to filter the data …
approach wherein a deterministic model of system, ie,“white box,” is used to filter the data …
Nonlinear Gaussian Belief Network based fault diagnosis for industrial processes
Abstract A Nonlinear Gaussian Belief Network (NLGBN) based fault diagnosis technique is
proposed for industrial processes. In this study, a three-layer NLGBN is constructed and …
proposed for industrial processes. In this study, a three-layer NLGBN is constructed and …
Sensor fault detection, isolation and reconstruction in nuclear power plants
The widespread sensors in a nuclear power plant (NPP) provide vital support to its
operation. Any fault in these sensors can be a severe issue, threatening the safety of the …
operation. Any fault in these sensors can be a severe issue, threatening the safety of the …
Fault detection in distillation column using NARX neural network
Fault detection in the process industries is one of the most challenging tasks. It requires
timely detection of anomalies which are present with noisy measurements of a large number …
timely detection of anomalies which are present with noisy measurements of a large number …
Dynamic threshold generators for robust fault detection in linear systems with parameter uncertainty
A Johansson, M Bask, T Norlander - Automatica, 2006 - Elsevier
The problem of developing robust thresholds for fault detection is addressed. An inequality
for the solution of a linear system with uncertain parameters is provided and is shown to be a …
for the solution of a linear system with uncertain parameters is provided and is shown to be a …
Non-linear system identification and fault detection method using RBF neural networks with set membership estimation
W Chai, J Qiao - International Journal of Modelling …, 2013 - inderscienceonline.com
A modelling method is proposed and applied in fault detection for non-linear dynamic
systems with bounded noises. Since the radial basis function (RBF) neural network is a …
systems with bounded noises. Since the radial basis function (RBF) neural network is a …
Novel gas turbine fault diagnosis method based on performance deviation model
Z Li, SS Zhong, L Lin - Journal of Propulsion and Power, 2017 - arc.aiaa.org
Effective fault detection and identification methods are crucial in gas turbine maintenance.
To express the gas turbine performance of the fault symptom state precisely and to reduce …
To express the gas turbine performance of the fault symptom state precisely and to reduce …