Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/155109
Título: Incipient Fault Diagnosis of a Grid-Connected T-Type Multilevel Inverter Using Multilayer Perceptron and Walsh Transform
Autor: Amaral, Tito G.
Pires, Vítor Fernão
Cordeiro, Armando
Foito, Daniel
Martins, João F.
Yamnenko, Julia
Tereschenko, Tetyana
Laikova, Liudmyla
Fedin, Ihor
Palavras-chave: artificial neural networks (ANNs)
fault diagnosis
incipient and intermittent fault
multilevel T-type inverter
open transistor
Walsh transform
Renewable Energy, Sustainability and the Environment
Fuel Technology
Engineering (miscellaneous)
Energy Engineering and Power Technology
Energy (miscellaneous)
Control and Optimization
Electrical and Electronic Engineering
SDG 7 - Affordable and Clean Energy
Data: 13-Mar-2023
Resumo: This article deals with fault detection and the classification of incipient and intermittent open-transistor faults in grid-connected three-level T-type inverters. Normally, open-transistor detection algorithms are developed for permanent faults. Nevertheless, the difficulty to detect incipient and intermittent faults is much greater, and appropriate methods are required. This requirement is due to the fact that over time, its repetition may lead to permanent failures that may lead to irreversible degradation. Therefore, the early detection of these failures is very important to ensure the reliability of the system and avoid unscheduled stops. For diagnosing these incipient and intermittent faults, a novel method based on a Walsh transform combined with a multilayer perceptron (MLP)-based classifier is proposed in this paper. This non-classical approach of using the Walsh transform not only allows accurate detections but is also very fast. This last characteristic is very important in these applications due to their practical implementation. The proposed method includes two main steps. First, the acquired AC currents are used by the control system and processed using the Walsh transform. This results in detailed information used to potentially identify open-transistor faults. Then, such information is processed using the MLP to finally determine whether a fault is present or not. Several experiments are conducted with different types of incipient transistor faults to create a relevant dataset.
Descrição: Publisher Copyright: © 2023 by the authors.
Peer review: yes
URI: http://hdl.handle.net/10362/155109
DOI: https://doi.org/10.3390/en16062668
ISSN: 1996-1073
Aparece nas colecções:Home collection (FCT)

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