A Current Vector based Open Circuit Fault Detection Technique for Industrial dc-ac Power Converters

Marif Daula Siddique; Mrutyunjaya Sahani; Prasanth Sundararajan; Diptak Pal; Sanjib Kumar Panda

doi:10.1109/ETFG55873.2023.10408254

A Current Vector based Open Circuit Fault Detection Technique for Industrial dc-ac Power Converters

Marif Daula Siddique^*
, Mrutyunjaya Sahani
, Prasanth Sundararajan
, Diptak Pal
, Sanjib Kumar Panda

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Research on power converters has been an important focus in the field of power electronics over the past many decades. In recent years, two-level, as well as three-level converters, have garnered a lot of attention due to their simple structure and control for a wide variety of applications. From the initial stage of idea development all the way to manufacturing, the reliability of the converter is an essential performance measure that needs to be taken into account. The 2L and 3L converters are vulnerable to a variety of failure modes and processes due to the large number of interdependent components and subassemblies that make it up. Fault detection of the topologies is very crucial for the reliable operation of the overall system. This paper provides a simplified method for the detection of open-circuit fault (OCF) in the converter. The adopted method is based on the park's transformation and it can detect the gate driver as well as wire breakdown faults. Simulation results have been provided for 2L converter.

Original language	English
Title of host publication	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665471640
DOIs	https://doi.org/10.1109/ETFG55873.2023.10408254
State	Published - 2023
Event	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 - Wollongong, Australia Duration: 3 Dec 2023 → 6 Dec 2023

Publication series

Name	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

Conference

Conference	2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023
Country/Territory	Australia
City	Wollongong
Period	3/12/23 → 6/12/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

2L converter
dc-ac power converters
fault detection
park's transformation

ASJC Scopus subject areas

Artificial Intelligence
Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Control and Optimization
Safety, Risk, Reliability and Quality

Access to Document

10.1109/ETFG55873.2023.10408254

Cite this

Siddique, M. D., Sahani, M., Sundararajan, P., Pal, D., & Panda, S. K. (2023). A Current Vector based Open Circuit Fault Detection Technique for Industrial dc-ac Power Converters. In 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETFG55873.2023.10408254

Siddique, Marif Daula ; Sahani, Mrutyunjaya ; Sundararajan, Prasanth et al. / A Current Vector based Open Circuit Fault Detection Technique for Industrial dc-ac Power Converters. 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023).

@inproceedings{de721a813bf24d83837ac76e1b145aa1,

title = "A Current Vector based Open Circuit Fault Detection Technique for Industrial dc-ac Power Converters",

abstract = "Research on power converters has been an important focus in the field of power electronics over the past many decades. In recent years, two-level, as well as three-level converters, have garnered a lot of attention due to their simple structure and control for a wide variety of applications. From the initial stage of idea development all the way to manufacturing, the reliability of the converter is an essential performance measure that needs to be taken into account. The 2L and 3L converters are vulnerable to a variety of failure modes and processes due to the large number of interdependent components and subassemblies that make it up. Fault detection of the topologies is very crucial for the reliable operation of the overall system. This paper provides a simplified method for the detection of open-circuit fault (OCF) in the converter. The adopted method is based on the park's transformation and it can detect the gate driver as well as wire breakdown faults. Simulation results have been provided for 2L converter.",

keywords = "2L converter, dc-ac power converters, fault detection, park's transformation",

author = "Siddique, \{Marif Daula\} and Mrutyunjaya Sahani and Prasanth Sundararajan and Diptak Pal and Panda, \{Sanjib Kumar\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 ; Conference date: 03-12-2023 Through 06-12-2023",

year = "2023",

doi = "10.1109/ETFG55873.2023.10408254",

language = "English",

series = "2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023",

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}

Siddique, MD, Sahani, M, Sundararajan, P, Pal, D & Panda, SK 2023, A Current Vector based Open Circuit Fault Detection Technique for Industrial dc-ac Power Converters. in 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023, Wollongong, Australia, 3/12/23. https://doi.org/10.1109/ETFG55873.2023.10408254

A Current Vector based Open Circuit Fault Detection Technique for Industrial dc-ac Power Converters. / Siddique, Marif Daula; Sahani, Mrutyunjaya; Sundararajan, Prasanth et al.
2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Siddique, Marif Daula

AU - Sahani, Mrutyunjaya

AU - Sundararajan, Prasanth

AU - Pal, Diptak

AU - Panda, Sanjib Kumar

PY - 2023

Y1 - 2023

N2 - Research on power converters has been an important focus in the field of power electronics over the past many decades. In recent years, two-level, as well as three-level converters, have garnered a lot of attention due to their simple structure and control for a wide variety of applications. From the initial stage of idea development all the way to manufacturing, the reliability of the converter is an essential performance measure that needs to be taken into account. The 2L and 3L converters are vulnerable to a variety of failure modes and processes due to the large number of interdependent components and subassemblies that make it up. Fault detection of the topologies is very crucial for the reliable operation of the overall system. This paper provides a simplified method for the detection of open-circuit fault (OCF) in the converter. The adopted method is based on the park's transformation and it can detect the gate driver as well as wire breakdown faults. Simulation results have been provided for 2L converter.

AB - Research on power converters has been an important focus in the field of power electronics over the past many decades. In recent years, two-level, as well as three-level converters, have garnered a lot of attention due to their simple structure and control for a wide variety of applications. From the initial stage of idea development all the way to manufacturing, the reliability of the converter is an essential performance measure that needs to be taken into account. The 2L and 3L converters are vulnerable to a variety of failure modes and processes due to the large number of interdependent components and subassemblies that make it up. Fault detection of the topologies is very crucial for the reliable operation of the overall system. This paper provides a simplified method for the detection of open-circuit fault (OCF) in the converter. The adopted method is based on the park's transformation and it can detect the gate driver as well as wire breakdown faults. Simulation results have been provided for 2L converter.

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KW - dc-ac power converters

KW - fault detection

KW - park's transformation

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DO - 10.1109/ETFG55873.2023.10408254

M3 - Conference contribution

AN - SCOPUS:85185796824

T3 - 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

BT - 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

Y2 - 3 December 2023 through 6 December 2023

ER -

Siddique MD, Sahani M, Sundararajan P, Pal D, Panda SK. A Current Vector based Open Circuit Fault Detection Technique for Industrial dc-ac Power Converters. In 2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023). doi: 10.1109/ETFG55873.2023.10408254

A Current Vector based Open Circuit Fault Detection Technique for Industrial dc-ac Power Converters

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this