Failure Mode Effect Classification for Power Electronics Converters Operating in a Grid-Connected System

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU146863" target="_blank" >RIV/00216305:26220/22:PU146863 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/abstract/document/9924178" target="_blank" >https://ieeexplore.ieee.org/abstract/document/9924178</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/JSYST.2022.3213071" target="_blank" >10.1109/JSYST.2022.3213071</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Failure Mode Effect Classification for Power Electronics Converters Operating in a Grid-Connected System

Popis výsledku v původním jazyce

Power electronic interfaces are the key aspects for achieving efficient grid integration for various distributed generation applications. As these interfaces continue to increase, their failure will result in major power losses and unstable operation of the electrical network. This article proposes a failure mode effect classification (FMEC) approach for localizing the faults in power electronic converters. The approach is developed with model-driven fault detection for identifying the fault signatures and data-driven fault identification for classifying the fault. This aims at identifying the fault effect on inputs, components, and sensors without compromising with the power stage of the converter. Furthermore, numerical simulations are carried out with a three-phase converter to acquire the fault signature library, and k-nearest neighbor approach is used to train the datasets. The fault signature library handles the information related to filter residuals obtained from the fault magnitude of each fault scenario. The proposed approach is validated through the experimental analysis of a real-time operation of a three-phase converter. The classifier training showed 96.5% accuracy, testing accuracy is 95.75%, and the fault detection time is 0.04 s. The testing results of the FMEC accurately identified various faults under varying load conditions without compromising the dynamic performance of the algorithm.

Název v anglickém jazyce

Failure Mode Effect Classification for Power Electronics Converters Operating in a Grid-Connected System

Popis výsledku anglicky

Power electronic interfaces are the key aspects for achieving efficient grid integration for various distributed generation applications. As these interfaces continue to increase, their failure will result in major power losses and unstable operation of the electrical network. This article proposes a failure mode effect classification (FMEC) approach for localizing the faults in power electronic converters. The approach is developed with model-driven fault detection for identifying the fault signatures and data-driven fault identification for classifying the fault. This aims at identifying the fault effect on inputs, components, and sensors without compromising with the power stage of the converter. Furthermore, numerical simulations are carried out with a three-phase converter to acquire the fault signature library, and k-nearest neighbor approach is used to train the datasets. The fault signature library handles the information related to filter residuals obtained from the fault magnitude of each fault scenario. The proposed approach is validated through the experimental analysis of a real-time operation of a three-phase converter. The classifier training showed 96.5% accuracy, testing accuracy is 95.75%, and the fault detection time is 0.04 s. The testing results of the FMEC accurately identified various faults under varying load conditions without compromising the dynamic performance of the algorithm.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Systems Journal

ISSN

1932-8184

e-ISSN

1937-9234

Svazek periodika

17

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

12

Strana od-do

3138-3149

Kód UT WoS článku

001006039000130

EID výsledku v databázi Scopus

2-s2.0-85140712195