Flux-Based Detection and Classification of Induction Motor Eccentricity, Rotor Cage, and Load Defects

Jaehoon Shin; Yonghyun Park; Sang Bin Lee

doi:10.1109/TIA.2021.3066960

Flux-Based Detection and Classification of Induction Motor Eccentricity, Rotor Cage, and Load Defects

Jaehoon Shin, Yonghyun Park, Sang Bin Lee

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

52 Citations (Scopus)

Abstract

Motor current signature analysis (MCSA) has been accepted in the field as a reliable means of detecting faults in the rotor cage of induction motors. However, there are many limitations to MCSA-based detection for other types of faults including rotor eccentricity and load defects. Recently, there has been increasing interest in airgap or leakage flux monitoring as an alternative to replace or complement MCSA. Flux monitoring can provide a reliable means of detecting rotor faults since anomalies in the rotor magnetomotive force or airgap can be directly observed. In this article, a new method based on monitoring the attenuation of rotor rotational frequency sidebands in the flux spectra is proposed for reliable detection and classification of rotor cage and eccentricity faults. It is also shown that flux monitoring can provide detection of rotor faults that is insensitive to the load defects. An experimental study under controlled broken bar, eccentricity, misalignment, and load unbalance conditions are given to support the claims. The results show that rotor cage, eccentricity, and load defects can be detected and distinguished for cases where MCSA alone is ineffective. A comparative evaluation between the proposed flux monitoring method and existing methods (MCSA, vibration analysis) is also given.

Original language	English
Article number	9380953
Pages (from-to)	2471-2480
Number of pages	10
Journal	IEEE Transactions on Industry Applications
Volume	57
Issue number	3
DOIs	https://doi.org/10.1109/TIA.2021.3066960
Publication status	Published - 2021 May 1

Bibliographical note

Funding Information:
Manuscript received October 30, 2020; revised December 28, 2020 and January 28, 2021; accepted March 14, 2021. Date of publication March 17, 2021; date of current version May 19, 2021. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) under Grant NRF-2019R1A2C1084104. Paper 2020-EMC-1597.R2, presented at the 2020 IEEE Energy Conversion Congress and Exposition, Detroit, MI, USA, Oct. 11–15, and approved for publication in the IEEE Transactions on Industry Applications by the Electric Machines Committee of the IEEE Industry Applications Society. (Corresponding author: Sang Bin Lee.) The authors are with the Department of Electrical Engineering, Korea University, Seoul 163-713, South Korea (e-mail: [email protected]; [email protected]; [email protected]).

Publisher Copyright:
© 1972-2012 IEEE.

Keywords

Airgap flux
eccentricity
fault diagnostics
leakage flux
load unbalance
misalignment
search coil
spectral analysis
squirrel cage induction motor
vibration

ASJC Scopus subject areas

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

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10.1109/TIA.2021.3066960

Cite this

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title = "Flux-Based Detection and Classification of Induction Motor Eccentricity, Rotor Cage, and Load Defects",

abstract = "Motor current signature analysis (MCSA) has been accepted in the field as a reliable means of detecting faults in the rotor cage of induction motors. However, there are many limitations to MCSA-based detection for other types of faults including rotor eccentricity and load defects. Recently, there has been increasing interest in airgap or leakage flux monitoring as an alternative to replace or complement MCSA. Flux monitoring can provide a reliable means of detecting rotor faults since anomalies in the rotor magnetomotive force or airgap can be directly observed. In this article, a new method based on monitoring the attenuation of rotor rotational frequency sidebands in the flux spectra is proposed for reliable detection and classification of rotor cage and eccentricity faults. It is also shown that flux monitoring can provide detection of rotor faults that is insensitive to the load defects. An experimental study under controlled broken bar, eccentricity, misalignment, and load unbalance conditions are given to support the claims. The results show that rotor cage, eccentricity, and load defects can be detected and distinguished for cases where MCSA alone is ineffective. A comparative evaluation between the proposed flux monitoring method and existing methods (MCSA, vibration analysis) is also given. ",

keywords = "Airgap flux, eccentricity, fault diagnostics, leakage flux, load unbalance, misalignment, search coil, spectral analysis, squirrel cage induction motor, vibration",

author = "Jaehoon Shin and Yonghyun Park and Lee, {Sang Bin}",

note = "Funding Information: Manuscript received October 30, 2020; revised December 28, 2020 and January 28, 2021; accepted March 14, 2021. Date of publication March 17, 2021; date of current version May 19, 2021. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) under Grant NRF-2019R1A2C1084104. Paper 2020-EMC-1597.R2, presented at the 2020 IEEE Energy Conversion Congress and Exposition, Detroit, MI, USA, Oct. 11–15, and approved for publication in the IEEE Transactions on Industry Applications by the Electric Machines Committee of the IEEE Industry Applications Society. (Corresponding author: Sang Bin Lee.) The authors are with the Department of Electrical Engineering, Korea University, Seoul 163-713, South Korea (e-mail: [email protected]; [email protected]; [email protected]). Publisher Copyright: {\textcopyright} 1972-2012 IEEE.",

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AU - Lee, Sang Bin

N1 - Funding Information: Manuscript received October 30, 2020; revised December 28, 2020 and January 28, 2021; accepted March 14, 2021. Date of publication March 17, 2021; date of current version May 19, 2021. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) under Grant NRF-2019R1A2C1084104. Paper 2020-EMC-1597.R2, presented at the 2020 IEEE Energy Conversion Congress and Exposition, Detroit, MI, USA, Oct. 11–15, and approved for publication in the IEEE Transactions on Industry Applications by the Electric Machines Committee of the IEEE Industry Applications Society. (Corresponding author: Sang Bin Lee.) The authors are with the Department of Electrical Engineering, Korea University, Seoul 163-713, South Korea (e-mail: [email protected]; [email protected]; [email protected]). Publisher Copyright: © 1972-2012 IEEE.

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N2 - Motor current signature analysis (MCSA) has been accepted in the field as a reliable means of detecting faults in the rotor cage of induction motors. However, there are many limitations to MCSA-based detection for other types of faults including rotor eccentricity and load defects. Recently, there has been increasing interest in airgap or leakage flux monitoring as an alternative to replace or complement MCSA. Flux monitoring can provide a reliable means of detecting rotor faults since anomalies in the rotor magnetomotive force or airgap can be directly observed. In this article, a new method based on monitoring the attenuation of rotor rotational frequency sidebands in the flux spectra is proposed for reliable detection and classification of rotor cage and eccentricity faults. It is also shown that flux monitoring can provide detection of rotor faults that is insensitive to the load defects. An experimental study under controlled broken bar, eccentricity, misalignment, and load unbalance conditions are given to support the claims. The results show that rotor cage, eccentricity, and load defects can be detected and distinguished for cases where MCSA alone is ineffective. A comparative evaluation between the proposed flux monitoring method and existing methods (MCSA, vibration analysis) is also given.

AB - Motor current signature analysis (MCSA) has been accepted in the field as a reliable means of detecting faults in the rotor cage of induction motors. However, there are many limitations to MCSA-based detection for other types of faults including rotor eccentricity and load defects. Recently, there has been increasing interest in airgap or leakage flux monitoring as an alternative to replace or complement MCSA. Flux monitoring can provide a reliable means of detecting rotor faults since anomalies in the rotor magnetomotive force or airgap can be directly observed. In this article, a new method based on monitoring the attenuation of rotor rotational frequency sidebands in the flux spectra is proposed for reliable detection and classification of rotor cage and eccentricity faults. It is also shown that flux monitoring can provide detection of rotor faults that is insensitive to the load defects. An experimental study under controlled broken bar, eccentricity, misalignment, and load unbalance conditions are given to support the claims. The results show that rotor cage, eccentricity, and load defects can be detected and distinguished for cases where MCSA alone is ineffective. A comparative evaluation between the proposed flux monitoring method and existing methods (MCSA, vibration analysis) is also given.

KW - Airgap flux

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KW - load unbalance

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KW - search coil

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KW - vibration

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JF - IEEE Transactions on Industry Applications

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M1 - 9380953

ER -

Flux-Based Detection and Classification of Induction Motor Eccentricity, Rotor Cage, and Load Defects

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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