A neuro-fuzzy based system for fault detection and diagnosis of 3-phase PFC rectifier

Daniel Foito; V. Fernao Pires; F. G. Amaral; J. F. Martins

doi:10.1109/EPEPEMC.2014.6980563

A neuro-fuzzy based system for fault detection and diagnosis of 3-phase PFC rectifier

Daniel Foito, V. Fernao Pires, F. G. Amaral, J. F. Martins

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

3 Citations (Scopus)

Abstract

Fault diagnosis in PFC rectifiers is becoming more and more important in many industrial applications. PFC rectifiers allow high power factor operation in AC/DC conversion. This power converter is normally the first interface between the ac power system network and the electronic equipment. In this way a good diagnosis system can avoid unplanned standstill. Under this context, this work presents a method to detect and identify the open transistor circuit fault. The developed method has two major steps. First, the input line currents are converted into a new pattern representation. Second, a neuro-fuzzy algorithm will be used to identify the fault. Several simulation and experimental results are presented to show the effectiveness of the proposed approach.

Original language	English
Title of host publication	16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	71-76
Number of pages	6
ISBN (Electronic)	9781479920600
DOIs	https://doi.org/10.1109/EPEPEMC.2014.6980563
Publication status	Published - 9 Dec 2014
Event	16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014 - Antalya, Turkey Duration: 21 Sept 2014 → 24 Sept 2014

Conference

Conference	16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014
Country/Territory	Turkey
City	Antalya
Period	21/09/14 → 24/09/14

Keywords

AC/DC conversion
Fault detection
Neuro-fuzzy
Power factor correction
Rectifier

Access to Document

10.1109/EPEPEMC.2014.6980563

Cite this

Foito, D., Pires, V. F., Amaral, F. G., & Martins, J. F. (2014). A neuro-fuzzy based system for fault detection and diagnosis of 3-phase PFC rectifier. In 16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014 (pp. 71-76). Article 6980563 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/EPEPEMC.2014.6980563

@inproceedings{7c87b5a47c0646baa5371a495ac5f3be,

title = "A neuro-fuzzy based system for fault detection and diagnosis of 3-phase PFC rectifier",

abstract = "Fault diagnosis in PFC rectifiers is becoming more and more important in many industrial applications. PFC rectifiers allow high power factor operation in AC/DC conversion. This power converter is normally the first interface between the ac power system network and the electronic equipment. In this way a good diagnosis system can avoid unplanned standstill. Under this context, this work presents a method to detect and identify the open transistor circuit fault. The developed method has two major steps. First, the input line currents are converted into a new pattern representation. Second, a neuro-fuzzy algorithm will be used to identify the fault. Several simulation and experimental results are presented to show the effectiveness of the proposed approach.",

keywords = "AC/DC conversion, Fault detection, Neuro-fuzzy, Power factor correction, Rectifier",

author = "Daniel Foito and Pires, {V. Fernao} and Amaral, {F. G.} and Martins, {J. F.}",

year = "2014",

month = dec,

day = "9",

doi = "10.1109/EPEPEMC.2014.6980563",

language = "English",

pages = "71--76",

booktitle = "16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014 ; Conference date: 21-09-2014 Through 24-09-2014",

}

Foito, D, Pires, VF, Amaral, FG & Martins, JF 2014, A neuro-fuzzy based system for fault detection and diagnosis of 3-phase PFC rectifier. in 16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014., 6980563, Institute of Electrical and Electronics Engineers (IEEE), pp. 71-76, 16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014, Antalya, Turkey, 21/09/14. https://doi.org/10.1109/EPEPEMC.2014.6980563

A neuro-fuzzy based system for fault detection and diagnosis of 3-phase PFC rectifier. / Foito, Daniel; Pires, V. Fernao; Amaral, F. G. et al.
16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014. Institute of Electrical and Electronics Engineers (IEEE), 2014. p. 71-76 6980563.

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

TY - GEN

T1 - A neuro-fuzzy based system for fault detection and diagnosis of 3-phase PFC rectifier

AU - Foito, Daniel

AU - Pires, V. Fernao

AU - Amaral, F. G.

AU - Martins, J. F.

PY - 2014/12/9

Y1 - 2014/12/9

N2 - Fault diagnosis in PFC rectifiers is becoming more and more important in many industrial applications. PFC rectifiers allow high power factor operation in AC/DC conversion. This power converter is normally the first interface between the ac power system network and the electronic equipment. In this way a good diagnosis system can avoid unplanned standstill. Under this context, this work presents a method to detect and identify the open transistor circuit fault. The developed method has two major steps. First, the input line currents are converted into a new pattern representation. Second, a neuro-fuzzy algorithm will be used to identify the fault. Several simulation and experimental results are presented to show the effectiveness of the proposed approach.

AB - Fault diagnosis in PFC rectifiers is becoming more and more important in many industrial applications. PFC rectifiers allow high power factor operation in AC/DC conversion. This power converter is normally the first interface between the ac power system network and the electronic equipment. In this way a good diagnosis system can avoid unplanned standstill. Under this context, this work presents a method to detect and identify the open transistor circuit fault. The developed method has two major steps. First, the input line currents are converted into a new pattern representation. Second, a neuro-fuzzy algorithm will be used to identify the fault. Several simulation and experimental results are presented to show the effectiveness of the proposed approach.

KW - AC/DC conversion

KW - Fault detection

KW - Neuro-fuzzy

KW - Power factor correction

KW - Rectifier

UR - http://www.scopus.com/inward/record.url?scp=84920520111&partnerID=8YFLogxK

U2 - 10.1109/EPEPEMC.2014.6980563

DO - 10.1109/EPEPEMC.2014.6980563

M3 - Conference contribution

AN - SCOPUS:84920520111

SP - 71

EP - 76

BT - 16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 16th International Power Electronics and Motion Control Conference and Exposition, PEMC 2014

Y2 - 21 September 2014 through 24 September 2014

ER -

A neuro-fuzzy based system for fault detection and diagnosis of 3-phase PFC rectifier

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this