This paper addresses the problem of system identification and fault detection in a two DOF
nonlinear system characterized by cubic stiffness. System identification is based upon …

The target of this paper is the performance-based diagnostics of a gas turbine for the
automated early detection of components malfunctions. The paper proposes a new …

Fault detection and isolation have become one of the most important aspects of automobile
design. A new fault detection and isolation scheme is developed for automotive engines in …

A challenging problem in aircraft engine health management (EHM) system development is
to detect and isolate faults in system components (ie, compressor, turbine), actuators, and …

In this paper, a robust data-driven fault detection approach is proposed with application to a
wind turbine benchmark. The main challenges of the wind turbine fault detection lie in its …

This paper extends traditional Gaussian mixture model (GMM) techniques to provide
recognition of operational states and detection of emerging faults for industrial systems. A …

Application of artificial neural network (ANN)-based method to perform engine condition
monitoring and fault diagnosis is evaluated. Back-propagation, feedforward neural nets are …

In this study, a robust fault diagnosis scheme for V47/660 kW wind turbine is proposed. A
comprehensive mathematical model for mechanical drive train and gearbox dynamic of …

Observers are usually used in model-based FDI system for aero engines, especially for
control system sensors. However, when a bank of traditional observers is used to detect gas …

This paper presents a novel methodology for fault detection in gas turbine engines based on
the concept of dynamic neural networks. The neural network structure belongs to the class of …