Real-time Defect Detection of Die Cast Rotor in Induction Motor Based on Circular Flux Sensing Coils


The die cast rotor bars in squirrel cage induction motors (SCIMs) are easily subjected to porosity or other defects in production, which considerably affects the motors' reliability and efficiency in operation. Planar flux sensing coils have been investigated for the defect detection of SCIM rotor. However, these types of sensors cannot accurately evaluate the severity of porosity or broken bar. This study develops a novel instrument to inspect and quantitatively analyze the rotor quality of SCIM. The sensor consists of the electromagnetic flux sensing coils directly from a SCIM stator. By injecting a DC voltage at phases A and B of the sensor, the induced voltage signal is generated from phase C. A quantitative fault indicator (QFI) is constructed on the basis of the instrument voltage output. The variation trend of the QFI with respect to fault severity is investigated by establishing a theoretical sensor model. Experimental results indicate that the proposed method can accurately detect the porosity and broken bar and evaluate their severities for the die cast rotor. The developed solution can be easily implemented with low cost and computational complexity, which can achieve real-time inspection of SCIM rotor in the production line.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > Aston Institute of Urban Technology and the Environment (ASTUTE)
College of Engineering & Physical Sciences > Power Electronics, Machines and Power System (PEMPS)
College of Engineering & Physical Sciences
Additional Information: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Funding: This work was supported in part by the National Natural Science Foundation of China under Grants 52075002, 51637001, and 52075001, and the Open Research Fund of Anhui Key Laboratory of Detection Technology and Energy Saving Devices, Anhui Polytechnic University, under grant DTESD2020A01
Uncontrolled Keywords: Bars,circular flux sensing coils,fault diagnosis,Induction motors,QFI,real-time edge computing,rotor defect detection,Rotors,SCIM,Sensors,Stator windings,Stators,Voltage,Control and Systems Engineering,Information Systems,Computer Science Applications,Electrical and Electronic Engineering
Publication ISSN: 1551-3203
Last Modified: 24 Apr 2024 07:20
Date Deposited: 10 Jan 2022 14:37
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://ieeexpl ... ocument/9656682 (Publisher URL)
PURE Output Type: Article
Published Date: 2021-12-20
Published Online Date: 2021-12-20
Accepted Date: 2021-12-11
Authors: Zhu, Qingyun
Wang, Xiaoxian
Wang, Hui
Xia, Min
Lu, Siliang
Liu, Bingyou
Li, Guoli
Cao, Wenping (ORCID Profile 0000-0002-8133-3020)



Version: Accepted Version

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