Airgap flux based detection and classification of induction motor rotor and load defects during the starting transient

Yonghyun Park; Hanchun Choi; Jaehoon Shin; Jongsan Park; Sang Bin Lee; Hyunsik Jo

doi:10.1109/TIE.2019.2962470

Airgap flux based detection and classification of induction motor rotor and load defects during the starting transient

Yonghyun Park, Hanchun Choi, Jaehoon Shin, Jongsan Park, Sang Bin Lee, Hyunsik Jo

School of Electrical Engineering

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

61 Citations (Scopus)

Abstract

There has been active research on motor current signature analysis (MCSA) for over the last 30+ years, as it can provide remote monitoring of rotor and load defects using the current sensor available in the motor control center. However, many years of experience has shown that 1) rotor eccentricity and load defects cannot be distinguished and 2) false rotor cage fault indications are common in the field. There is a recent trend toward integrating 'smart' self-diagnostics in electric machines through embedded sensors, especially in applications such as submersible pumps or nuclear plants where motor inspection is difficult. The objective of this article is to evaluate airgap flux measurement as an option for providing sensitive and reliable monitoring of motor and load defects. A new method based on the analysis of the airgap flux search coil voltage during motor starting is proposed for reliable detection and classification of rotor cage, eccentricity, and mechanical defects in the load. Experimental testing is provided to verify the claims made on the proposed method, for cases where MCSA fails.

Original language	English
Article number	8948307
Pages (from-to)	10075-10084
Number of pages	10
Journal	IEEE Transactions on Industrial Electronics
Volume	67
Issue number	12
DOIs	https://doi.org/10.1109/TIE.2019.2962470
Publication status	Published - 2020 Dec

Bibliographical note

Funding Information:
Manuscript received August 10, 2019; revised October 13, 2019 and November 1, 2019; accepted November 22, 2019. Date of publication January 1, 2020; date of current version August 18, 2020.This work was supported by the National Research Foundation of Korea grant funded by the Korea government under Grant NRF-2019R1A2C1084104. (Corresponding author: Sang Bin Lee.) Y. Park, H. Choi, J. Shin, J. Park, and S. B. Lee are with the Department of Electrical Engineering, Korea University, Seoul 02841, Korea (e-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]).

Publisher Copyright:
© 1982-2012 IEEE.

Keywords

Airgap eccentricity
airgap flux
fault diagnosis
induction motor
load unbalance
misalignment
motor current signature analysis (MCSA)
rotor cage fault
search coil
spectral analysis

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/TIE.2019.2962470

Cite this

@article{cc6a148c9b654ae49788fc2bf59b5a7d,

title = "Airgap flux based detection and classification of induction motor rotor and load defects during the starting transient",

abstract = "There has been active research on motor current signature analysis (MCSA) for over the last 30+ years, as it can provide remote monitoring of rotor and load defects using the current sensor available in the motor control center. However, many years of experience has shown that 1) rotor eccentricity and load defects cannot be distinguished and 2) false rotor cage fault indications are common in the field. There is a recent trend toward integrating 'smart' self-diagnostics in electric machines through embedded sensors, especially in applications such as submersible pumps or nuclear plants where motor inspection is difficult. The objective of this article is to evaluate airgap flux measurement as an option for providing sensitive and reliable monitoring of motor and load defects. A new method based on the analysis of the airgap flux search coil voltage during motor starting is proposed for reliable detection and classification of rotor cage, eccentricity, and mechanical defects in the load. Experimental testing is provided to verify the claims made on the proposed method, for cases where MCSA fails. ",

keywords = "Airgap eccentricity, airgap flux, fault diagnosis, induction motor, load unbalance, misalignment, motor current signature analysis (MCSA), rotor cage fault, search coil, spectral analysis",

author = "Yonghyun Park and Hanchun Choi and Jaehoon Shin and Jongsan Park and Lee, {Sang Bin} and Hyunsik Jo",

note = "Funding Information: Manuscript received August 10, 2019; revised October 13, 2019 and November 1, 2019; accepted November 22, 2019. Date of publication January 1, 2020; date of current version August 18, 2020.This work was supported by the National Research Foundation of Korea grant funded by the Korea government under Grant NRF-2019R1A2C1084104. (Corresponding author: Sang Bin Lee.) Y. Park, H. Choi, J. Shin, J. Park, and S. B. Lee are with the Department of Electrical Engineering, Korea University, Seoul 02841, Korea (e-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]). Publisher Copyright: {\textcopyright} 1982-2012 IEEE.",

year = "2020",

month = dec,

doi = "10.1109/TIE.2019.2962470",

language = "English",

volume = "67",

pages = "10075--10084",

journal = "IEEE Transactions on Industrial Electronics",

issn = "0278-0046",

publisher = "IEEE Industrial Electronics Society",

number = "12",

}

TY - JOUR

T1 - Airgap flux based detection and classification of induction motor rotor and load defects during the starting transient

AU - Park, Yonghyun

AU - Choi, Hanchun

AU - Shin, Jaehoon

AU - Park, Jongsan

AU - Lee, Sang Bin

AU - Jo, Hyunsik

N1 - Funding Information: Manuscript received August 10, 2019; revised October 13, 2019 and November 1, 2019; accepted November 22, 2019. Date of publication January 1, 2020; date of current version August 18, 2020.This work was supported by the National Research Foundation of Korea grant funded by the Korea government under Grant NRF-2019R1A2C1084104. (Corresponding author: Sang Bin Lee.) Y. Park, H. Choi, J. Shin, J. Park, and S. B. Lee are with the Department of Electrical Engineering, Korea University, Seoul 02841, Korea (e-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]). Publisher Copyright: © 1982-2012 IEEE.

PY - 2020/12

Y1 - 2020/12

N2 - There has been active research on motor current signature analysis (MCSA) for over the last 30+ years, as it can provide remote monitoring of rotor and load defects using the current sensor available in the motor control center. However, many years of experience has shown that 1) rotor eccentricity and load defects cannot be distinguished and 2) false rotor cage fault indications are common in the field. There is a recent trend toward integrating 'smart' self-diagnostics in electric machines through embedded sensors, especially in applications such as submersible pumps or nuclear plants where motor inspection is difficult. The objective of this article is to evaluate airgap flux measurement as an option for providing sensitive and reliable monitoring of motor and load defects. A new method based on the analysis of the airgap flux search coil voltage during motor starting is proposed for reliable detection and classification of rotor cage, eccentricity, and mechanical defects in the load. Experimental testing is provided to verify the claims made on the proposed method, for cases where MCSA fails.

AB - There has been active research on motor current signature analysis (MCSA) for over the last 30+ years, as it can provide remote monitoring of rotor and load defects using the current sensor available in the motor control center. However, many years of experience has shown that 1) rotor eccentricity and load defects cannot be distinguished and 2) false rotor cage fault indications are common in the field. There is a recent trend toward integrating 'smart' self-diagnostics in electric machines through embedded sensors, especially in applications such as submersible pumps or nuclear plants where motor inspection is difficult. The objective of this article is to evaluate airgap flux measurement as an option for providing sensitive and reliable monitoring of motor and load defects. A new method based on the analysis of the airgap flux search coil voltage during motor starting is proposed for reliable detection and classification of rotor cage, eccentricity, and mechanical defects in the load. Experimental testing is provided to verify the claims made on the proposed method, for cases where MCSA fails.

KW - Airgap eccentricity

KW - airgap flux

KW - fault diagnosis

KW - induction motor

KW - load unbalance

KW - misalignment

KW - motor current signature analysis (MCSA)

KW - rotor cage fault

KW - search coil

KW - spectral analysis

UR - http://www.scopus.com/inward/record.url?scp=85090577596&partnerID=8YFLogxK

U2 - 10.1109/TIE.2019.2962470

DO - 10.1109/TIE.2019.2962470

M3 - Article

AN - SCOPUS:85090577596

SN - 0278-0046

VL - 67

SP - 10075

EP - 10084

JO - IEEE Transactions on Industrial Electronics

JF - IEEE Transactions on Industrial Electronics

IS - 12

M1 - 8948307

ER -

Airgap flux based detection and classification of induction motor rotor and load defects during the starting transient

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this