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Sensor Fault Detection, Isolation, and Identification Using Multiple-Model-Based Hybrid Kalman Filter for Gas Turbine Engines
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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
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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 ...
Event-triggered fault detection for discrete-time linear multi-agent systems
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Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
This paper studies the design and development of event-triggered fault detection (FD) filters for discrete-time linear multi-agent systems. For each agent, an FD filter is designed that receives the output measurements ...
An Agreement Based Dynamic Routing Method for Fault Diagnosis in Power Network with Enhanced Noise Immunity
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
The stable operation of a power system often depends on inscribing the faults that may arise when transmitting and distributing electrical power. Characterizing these faults is necessary to analyze the post-fault oscillography ...
A Greedy Layer-Wise Learning Algorithm for Open-Circuit Fault Diagnosis of Grid-Connected Inverters
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
This paper introduces a greedy layer-wise learning algorithm to diagnose open-circuit faults of grid-connected inverters. Inverters play important roles in energy conversion, especially when converting direct current to ...
Auto-nahl: A neural network approach for condition-based maintenance of complex industrial systems
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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 ...
A directional protection technique for MTDC networks
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Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
This paper suggests a new protection algorithm for a multi-terminal direct current (MTDC) networks. The current values and directions at each bus connecting more than one line are determined. The measured values of line ...
Bidirectional buck-boost inverter-based HVDC transmission system with AC-side contribution blocking capability during DC-side faults
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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
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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 ...