In this article, an online estimator for faulty sensor signal is proposed for industrial processes
described by nonlinear state-space models. The potential sensor fault is modeled as an …

The Digital Twin (DT) is a promising concept which aims at creating a virtual replica of an
individual system, that can provide information otherwise not available. This paper presents …

This paper addresses the robust fault diagnosis of power plant gas turbine as an uncertain
nonlinear system using a new adaptive threshold method. In order to determine the bounds …

This work discussed the design of a sliding mode observer for the estimation of actuator
faults in a Takagi–Sugeno fuzzy system with digital communication channel. Signals must …

In this study, an efficient strategy for fault detection and isolation (FDI) of an Industrial Gas
Turbine is introduced based on ensemble learning methods. Four independent Wiener …

As the flight envelope is widening continuously and operational capability is improving
sequentially, gas turbine engines are faced with new challenges of increased operation and …

Sensor fault detection and classification is a key challenge for machine monitoring and
diagnostics, since raw data cleaning represents a key process in the gas turbine industry. To …

This paper aims to design, develop and compare fault detection and isolation (FDI) schemes
including inversion-based fault reconstruction and optimal state observers for a class of …

This paper presents a framework for condition monitoring of large non-linear electro-
mechanical systems. Faults are assessed in different subsystems by means of model-based …

For the problem of multiple sensor fault detection and reconstruction in the forklift fault-
tolerant control system, a sliding mode observer (SMO) with adaptive regulation law is …