Search
Now showing items 1-10 of 25
Event-Triggered Fault Detection for Networked Control Systems Subject to Packet Dropout
(
Wiley-Blackwell
, 2018 , Article)
This paper investigates the problem of event-triggered fault detection for discrete-time networked systems subject to packet dropout. The main aim of the proposed approach is to efficiently use the communication network ...
Event-triggered fault detection and isolation for discrete-time linear systems
(
Institution of Engineering and Technology
, 2016 , Article)
In this study, the problem of event-triggered fault detection and isolation (FDI) for discrete-time linear time invariant systems is considered. Using a Leunberger observer as the residual generator, a multi-objective ...
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
Early detection of the motor faults is essential and artificial neural networks are widely used for this purpose. The typical systems usually encapsulate two distinct blocks: feature extraction and classification. Such ...
Fault and performance management in multi-cloud based NFV using shallow and deep predictive structures
(
Springer
, 2017 , Article)
Deployment of network function virtualization (NFV) over multiple clouds accentuates its advantages such as flexibility of virtualization, proximity to customers and lower total cost of operation. However, NFV over multiple ...
Sensor Fault Detection, Isolation, and Identification Using Multiple-Model-Based Hybrid Kalman Filter for Gas Turbine Engines
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
In this paper, a novel sensor fault detection, isolation, and identification (FDII) strategy is proposed using the multiple-model (MM) approach. The scheme is based on multiple hybrid Kalman filters (MHKFs), which represents ...
Robust sensor fault detection and isolation of gas turbine engines subjected to time-varying parameter uncertainties
(
Academic Press
, 2016 , Article)
In this paper, a novel robust sensor fault detection and isolation (FDI) strategy using the multiple model-based (MM) approach is proposed that remains robust with respect to both time-varying parameter uncertainties and ...
Auto-nahl: A neural network approach for condition-based maintenance of complex industrial systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Nowadays, machine learning has emerged as a promising alternative for condition monitoring of industrial processes, making it indispensable for maintenance planning. Such a learning model is able to assess health states ...
Bidirectional buck-boost inverter-based HVDC transmission system with AC-side contribution blocking capability during DC-side faults
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Article)
Offshore wind energy is now seen as a key contributor for the future renewable energy mix. HVDC technology is among the chief technologies enabling widespread use of offshore wind. Thanks to their numerous advantages, ...
Sensor data validation and fault diagnosis using Auto-Associative Neural Network for HVAC systems
(
Elsevier Ltd
, 2020 , Article)
The Heating, Ventilation, and Air conditioning (HVAC) system is a major system in buildings for conditioning the indoor environment. Sensor data validation and fault diagnosis for HVAC systems are essentially important to ...
Model-Free Geometric Fault Detection and Isolation for Nonlinear Systems Using Koopman Operator
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
This paper presents a model-free fault detection and isolation (FDI) method for nonlinear dynamical systems using Koopman operator theory and linear geometric technique. The key idea is to obtain a Koopman-based reduced-order ...