Detection of broken outer-cage bars for double-cage induction motors under the startup transient

Jose Antonino-Daviu; Martin Riera-Guasp; Joan Pons-Llinares; Jongbin Park; Sang Bin Lee; Jiyoon Yoo; Christian Kral

doi:10.1109/TIA.2012.2210173

Detection of broken outer-cage bars for double-cage induction motors under the startup transient

Jose Antonino-Daviu, Martin Riera-Guasp, Joan Pons-Llinares, Jongbin Park, Sang Bin Lee, Jiyoon Yoo, Christian Kral

School of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

85 Citations (Scopus)

Abstract

Unlike single-cage rotor fault detection, fast Fourier transform (FFT)-based steady-state spectrum analysis techniques can fail to detect outer-cage faults in double-cage induction motors due to the small outer-cage current under running conditions. Double-cage motors are typically employed in applications that require loaded starts. This makes the outer cage vulnerable to fatigue failure since it must withstand the high starting current and long startup time frequently. However, there are only a few publications that investigate detection techniques specifically for double-cage motors. In this paper, considering that the influence of the faulty outer cage is strong at startup due to the large outer-cage current, detection of outer-cage faults under the startup transient is investigated. A discrete-wavelet-transform-based method is proposed as a viable solution to the detection of outer-cage faults for double-cage motors. An experimental study on fabricated copper double-cage induction motors shows that the proposed method provides sensitive and reliable detection of double-cage rotor faults compared to FFT.

Original language	English
Article number	13
Pages (from-to)	1539-1548
Number of pages	10
Journal	IEEE Transactions on Industry Applications
Volume	48
Issue number	5
DOIs	https://doi.org/10.1109/TIA.2012.2210173
Publication status	Published - 2012

Keywords

AC machine
condition monitoring
double-cage rotor
fast Fourier transform (FFT)
fault diagnostics
induction motor
motor current signature analysis (MCSA)
outer-cage fault
transient analysis
wavelet transform

ASJC Scopus subject areas

Control and Systems Engineering
Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/TIA.2012.2210173

Fingerprint Dive into the research topics of 'Detection of broken outer-cage bars for double-cage induction motors under the startup transient'. Together they form a unique fingerprint.

Cite this

Detection of broken outer-cage bars for double-cage induction motors under the startup transient. / Antonino-Daviu, Jose; Riera-Guasp, Martin; Pons-Llinares, Joan; Park, Jongbin; Lee, Sang Bin; Yoo, Jiyoon; Kral, Christian.

In: IEEE Transactions on Industry Applications, Vol. 48, No. 5, 13, 2012, p. 1539-1548.

Research output: Contribution to journal › Article › peer-review

@article{d5ae6f62534c41c1a546f7b7f54c1544,

title = "Detection of broken outer-cage bars for double-cage induction motors under the startup transient",

abstract = "Unlike single-cage rotor fault detection, fast Fourier transform (FFT)-based steady-state spectrum analysis techniques can fail to detect outer-cage faults in double-cage induction motors due to the small outer-cage current under running conditions. Double-cage motors are typically employed in applications that require loaded starts. This makes the outer cage vulnerable to fatigue failure since it must withstand the high starting current and long startup time frequently. However, there are only a few publications that investigate detection techniques specifically for double-cage motors. In this paper, considering that the influence of the faulty outer cage is strong at startup due to the large outer-cage current, detection of outer-cage faults under the startup transient is investigated. A discrete-wavelet-transform-based method is proposed as a viable solution to the detection of outer-cage faults for double-cage motors. An experimental study on fabricated copper double-cage induction motors shows that the proposed method provides sensitive and reliable detection of double-cage rotor faults compared to FFT.",

keywords = "AC machine, condition monitoring, double-cage rotor, fast Fourier transform (FFT), fault diagnostics, induction motor, motor current signature analysis (MCSA), outer-cage fault, transient analysis, wavelet transform",

author = "Jose Antonino-Daviu and Martin Riera-Guasp and Joan Pons-Llinares and Jongbin Park and Lee, {Sang Bin} and Jiyoon Yoo and Christian Kral",

note = "Funding Information: Manuscript received September 20, 2011; revised February 3, 2012; accepted April 9, 2012. Date of publication July 24, 2012; date of current version September 14, 2012. Paper 2011-EMC-500.R1, presented at the 2011 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, Bologna, Italy, September 5–8, and approved for publication in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Electric Machines Committee of the IEEE Industry Applications Society. This work was supported in part by the Spanish “Ministerio de Educaci{\'o}n y Ciencia,” in the framework of the “Programa Nacional de Proyectos de Investigaci{\'o}n Fundamental,” under Project Reference DPI2008-06583/DPI, and in part by the Human Resources Development of Korea Institute of Energy Technology Evaluation and Planning under Grant 20114010203010 funded by the Korean Government Ministry of Knowledge Economy.",

year = "2012",

doi = "10.1109/TIA.2012.2210173",

language = "English",

volume = "48",

pages = "1539--1548",

journal = "IEEE Transactions on Industry Applications",

issn = "0093-9994",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "5",

}

TY - JOUR

T1 - Detection of broken outer-cage bars for double-cage induction motors under the startup transient

AU - Antonino-Daviu, Jose

AU - Riera-Guasp, Martin

AU - Pons-Llinares, Joan

AU - Park, Jongbin

AU - Lee, Sang Bin

AU - Yoo, Jiyoon

AU - Kral, Christian

N1 - Funding Information: Manuscript received September 20, 2011; revised February 3, 2012; accepted April 9, 2012. Date of publication July 24, 2012; date of current version September 14, 2012. Paper 2011-EMC-500.R1, presented at the 2011 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, Bologna, Italy, September 5–8, and approved for publication in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Electric Machines Committee of the IEEE Industry Applications Society. This work was supported in part by the Spanish “Ministerio de Educación y Ciencia,” in the framework of the “Programa Nacional de Proyectos de Investigación Fundamental,” under Project Reference DPI2008-06583/DPI, and in part by the Human Resources Development of Korea Institute of Energy Technology Evaluation and Planning under Grant 20114010203010 funded by the Korean Government Ministry of Knowledge Economy.

PY - 2012

Y1 - 2012

N2 - Unlike single-cage rotor fault detection, fast Fourier transform (FFT)-based steady-state spectrum analysis techniques can fail to detect outer-cage faults in double-cage induction motors due to the small outer-cage current under running conditions. Double-cage motors are typically employed in applications that require loaded starts. This makes the outer cage vulnerable to fatigue failure since it must withstand the high starting current and long startup time frequently. However, there are only a few publications that investigate detection techniques specifically for double-cage motors. In this paper, considering that the influence of the faulty outer cage is strong at startup due to the large outer-cage current, detection of outer-cage faults under the startup transient is investigated. A discrete-wavelet-transform-based method is proposed as a viable solution to the detection of outer-cage faults for double-cage motors. An experimental study on fabricated copper double-cage induction motors shows that the proposed method provides sensitive and reliable detection of double-cage rotor faults compared to FFT.

AB - Unlike single-cage rotor fault detection, fast Fourier transform (FFT)-based steady-state spectrum analysis techniques can fail to detect outer-cage faults in double-cage induction motors due to the small outer-cage current under running conditions. Double-cage motors are typically employed in applications that require loaded starts. This makes the outer cage vulnerable to fatigue failure since it must withstand the high starting current and long startup time frequently. However, there are only a few publications that investigate detection techniques specifically for double-cage motors. In this paper, considering that the influence of the faulty outer cage is strong at startup due to the large outer-cage current, detection of outer-cage faults under the startup transient is investigated. A discrete-wavelet-transform-based method is proposed as a viable solution to the detection of outer-cage faults for double-cage motors. An experimental study on fabricated copper double-cage induction motors shows that the proposed method provides sensitive and reliable detection of double-cage rotor faults compared to FFT.

KW - AC machine

KW - condition monitoring

KW - double-cage rotor

KW - fast Fourier transform (FFT)

KW - fault diagnostics

KW - induction motor

KW - motor current signature analysis (MCSA)

KW - outer-cage fault

KW - transient analysis

KW - wavelet transform

UR - http://www.scopus.com/inward/record.url?scp=84866538866&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84866538866&partnerID=8YFLogxK

U2 - 10.1109/TIA.2012.2210173

DO - 10.1109/TIA.2012.2210173

M3 - Article

AN - SCOPUS:84866538866

VL - 48

SP - 1539

EP - 1548

JO - IEEE Transactions on Industry Applications

JF - IEEE Transactions on Industry Applications

SN - 0093-9994

IS - 5

M1 - 13

ER -

Detection of broken outer-cage bars for double-cage induction motors under the startup transient

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Cite this