Fault detection in induction machines by using power spectral density on the wavelet decompositions

J. Cusido; J. A. Rosero; L. Romeral; J. A. Ortega; A. Garcia

doi:10.1109/PESC.2006.1712271

Fault detection in induction machines by using power spectral density on the wavelet decompositions

J. Cusido^*
, J. A. Rosero
, L. Romeral
, J. A. Ortega
, A. Garcia

^*Corresponding author for this work

Polytechnic University of Catalonia

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

11 Citations (Scopus)

Abstract

Motor Current Signature Analysis has been successfully used in induction machines for fault diagnosis. The method however does not always achieve good results when the load torque is not constant. This paper proposes a new approach to motor fault detection, by analyzing the spectrogram and further combination of Wavelet and Power Spectral Density techniques. Theoretical development and experimental results are presented to support the research.

Original language	English
Title of host publication	37th IEEE Power Electronics Specialists Conference 2006, PESC'06
DOIs	https://doi.org/10.1109/PESC.2006.1712271
Publication status	Published - 2006
Externally published	Yes
Event	37th IEEE Power Electronics Specialists Conference 2006, PESC'06 - Jeju, Korea, Republic of Duration: 18 Jun 2006 → 22 Jun 2006

Publication series

Name	PESC Record - IEEE Annual Power Electronics Specialists Conference
ISSN (Print)	0275-9306

Conference

Conference	37th IEEE Power Electronics Specialists Conference 2006, PESC'06
Country/Territory	Korea, Republic of
City	Jeju
Period	18/06/06 → 22/06/06

Keywords

Electrical drives
Fault detection
Induction motor
Wavelet analysis

Access to Document

10.1109/PESC.2006.1712271

Cite this

Cusido, J., Rosero, J. A., Romeral, L., Ortega, J. A., & Garcia, A. (2006). Fault detection in induction machines by using power spectral density on the wavelet decompositions. In 37th IEEE Power Electronics Specialists Conference 2006, PESC'06 Article 1712271 (PESC Record - IEEE Annual Power Electronics Specialists Conference). https://doi.org/10.1109/PESC.2006.1712271

@inproceedings{35cff50ffe09476191aeecd5783092df,

title = "Fault detection in induction machines by using power spectral density on the wavelet decompositions",

abstract = "Motor Current Signature Analysis has been successfully used in induction machines for fault diagnosis. The method however does not always achieve good results when the load torque is not constant. This paper proposes a new approach to motor fault detection, by analyzing the spectrogram and further combination of Wavelet and Power Spectral Density techniques. Theoretical development and experimental results are presented to support the research.",

keywords = "Electrical drives, Fault detection, Induction motor, Wavelet analysis",

author = "J. Cusido and Rosero, \{J. A.\} and L. Romeral and Ortega, \{J. A.\} and A. Garcia",

year = "2006",

doi = "10.1109/PESC.2006.1712271",

language = "English",

isbn = "0780397169",

series = "PESC Record - IEEE Annual Power Electronics Specialists Conference",

booktitle = "37th IEEE Power Electronics Specialists Conference 2006, PESC'06",

note = "37th IEEE Power Electronics Specialists Conference 2006, PESC'06 ; Conference date: 18-06-2006 Through 22-06-2006",

}

Cusido, J, Rosero, JA, Romeral, L, Ortega, JA & Garcia, A 2006, Fault detection in induction machines by using power spectral density on the wavelet decompositions. in 37th IEEE Power Electronics Specialists Conference 2006, PESC'06., 1712271, PESC Record - IEEE Annual Power Electronics Specialists Conference, 37th IEEE Power Electronics Specialists Conference 2006, PESC'06, Jeju, Korea, Republic of, 18/06/06. https://doi.org/10.1109/PESC.2006.1712271

Fault detection in induction machines by using power spectral density on the wavelet decompositions. / Cusido, J.; Rosero, J. A.; Romeral, L. et al.
37th IEEE Power Electronics Specialists Conference 2006, PESC'06. 2006. 1712271 (PESC Record - IEEE Annual Power Electronics Specialists Conference).

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

TY - GEN

T1 - Fault detection in induction machines by using power spectral density on the wavelet decompositions

AU - Cusido, J.

AU - Rosero, J. A.

AU - Romeral, L.

AU - Ortega, J. A.

AU - Garcia, A.

PY - 2006

Y1 - 2006

N2 - Motor Current Signature Analysis has been successfully used in induction machines for fault diagnosis. The method however does not always achieve good results when the load torque is not constant. This paper proposes a new approach to motor fault detection, by analyzing the spectrogram and further combination of Wavelet and Power Spectral Density techniques. Theoretical development and experimental results are presented to support the research.

AB - Motor Current Signature Analysis has been successfully used in induction machines for fault diagnosis. The method however does not always achieve good results when the load torque is not constant. This paper proposes a new approach to motor fault detection, by analyzing the spectrogram and further combination of Wavelet and Power Spectral Density techniques. Theoretical development and experimental results are presented to support the research.

KW - Electrical drives

KW - Fault detection

KW - Induction motor

KW - Wavelet analysis

UR - https://www.scopus.com/pages/publications/42449095452

U2 - 10.1109/PESC.2006.1712271

DO - 10.1109/PESC.2006.1712271

M3 - Conference contribution

AN - SCOPUS:42449095452

SN - 0780397169

SN - 9780780397163

T3 - PESC Record - IEEE Annual Power Electronics Specialists Conference

BT - 37th IEEE Power Electronics Specialists Conference 2006, PESC'06

T2 - 37th IEEE Power Electronics Specialists Conference 2006, PESC'06

Y2 - 18 June 2006 through 22 June 2006

ER -

Fault detection in induction machines by using power spectral density on the wavelet decompositions

Abstract

Publication series

Conference

Keywords

Access to Document

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