Detection and diagnosis of induction motor's broken rotor bars in Kalman filter based drives

Samieh Abusaad; Baderadin Elforjani; Naima Hamad; Khaled Almezhghwi; Fengshou Gu; Andrew D. Ball

doi:10.1109/MI-STA54861.2022.9837501

Detection and diagnosis of induction motor's broken rotor bars in Kalman filter based drives

Samieh Abusaad, Baderadin Elforjani, Naima Hamad, Khaled Almezhghwi, Fengshou Gu, Andrew D. Ball

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

Abstract

Sensorless variable speed drives enable motors to operate at highest possible torques with an enhanced dynamic performance. Drives utilize estimators that estimate the motor speed and other state variables. Yet, for accurate calculations, speed estimators must have motor parameters and model that match the actual values. Variations in motor parameters, either due to environment or abnormality, would influence the estimation accuracy. Many techniques are employed to estimate the motor speed and state variables. In this work a sensorless drive with an extended Kalman filter (EKF) is examined under different rotor fault cases. Three broken rotor bars (BRBs) of different degrees of severities were tested. Moreover, variables from the EKF are processed and further analyzed as to examine the potential of detecting and diagnosing BRBs. It was observed that rotor time constant is effective in detecting the BRB faults. While on the other hand, both estimated current and slip spectra found rich of information about this kind of faults and can be effectively used for BRB faults diagnostics even under low loads.

Original language	English
Title of host publication	2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2022 - Proceeding
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	99-104
Number of pages	6
ISBN (Electronic)	9781665479189
ISBN (Print)	9781665479196
DOIs	https://doi.org/10.1109/MI-STA54861.2022.9837501
Publication status	Published - 27 Jul 2022
Event	2nd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering - Sabratha, Libya Duration: 23 May 2022 → 25 May 2022 Conference number: 2

Conference

Conference	2nd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering
Abbreviated title	MI-STA 2022
Country/Territory	Libya
City	Sabratha
Period	23/05/22 → 25/05/22

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Abusaad, S., Elforjani, B., Hamad, N., Almezhghwi, K., Gu, F., & Ball, A. D. (2022). Detection and diagnosis of induction motor's broken rotor bars in Kalman filter based drives. In 2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2022 - Proceeding (pp. 99-104). [9837501] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MI-STA54861.2022.9837501

Abusaad, Samieh ; Elforjani, Baderadin ; Hamad, Naima et al. / Detection and diagnosis of induction motor's broken rotor bars in Kalman filter based drives. 2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2022 - Proceeding. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 99-104

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title = "Detection and diagnosis of induction motor's broken rotor bars in Kalman filter based drives",

abstract = "Sensorless variable speed drives enable motors to operate at highest possible torques with an enhanced dynamic performance. Drives utilize estimators that estimate the motor speed and other state variables. Yet, for accurate calculations, speed estimators must have motor parameters and model that match the actual values. Variations in motor parameters, either due to environment or abnormality, would influence the estimation accuracy. Many techniques are employed to estimate the motor speed and state variables. In this work a sensorless drive with an extended Kalman filter (EKF) is examined under different rotor fault cases. Three broken rotor bars (BRBs) of different degrees of severities were tested. Moreover, variables from the EKF are processed and further analyzed as to examine the potential of detecting and diagnosing BRBs. It was observed that rotor time constant is effective in detecting the BRB faults. While on the other hand, both estimated current and slip spectra found rich of information about this kind of faults and can be effectively used for BRB faults diagnostics even under low loads.",

keywords = "Condition Monitoring, Extended Kalman Filters, Fault Detection, Induction MotorBRBs, Sensorless VSDs",

author = "Samieh Abusaad and Baderadin Elforjani and Naima Hamad and Khaled Almezhghwi and Fengshou Gu and Ball, {Andrew D.}",

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Abusaad, S, Elforjani, B, Hamad, N, Almezhghwi, K, Gu, F & Ball, AD 2022, Detection and diagnosis of induction motor's broken rotor bars in Kalman filter based drives. in 2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2022 - Proceeding., 9837501, Institute of Electrical and Electronics Engineers Inc., pp. 99-104, 2nd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, Sabratha, Libya, 23/05/22. https://doi.org/10.1109/MI-STA54861.2022.9837501

Detection and diagnosis of induction motor's broken rotor bars in Kalman filter based drives. / Abusaad, Samieh; Elforjani, Baderadin; Hamad, Naima et al.

2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2022 - Proceeding. Institute of Electrical and Electronics Engineers Inc., 2022. p. 99-104 9837501.

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

TY - GEN

T1 - Detection and diagnosis of induction motor's broken rotor bars in Kalman filter based drives

AU - Abusaad, Samieh

AU - Elforjani, Baderadin

AU - Hamad, Naima

AU - Almezhghwi, Khaled

AU - Gu, Fengshou

AU - Ball, Andrew D.

N1 - Conference code: 2

PY - 2022/7/27

Y1 - 2022/7/27

N2 - Sensorless variable speed drives enable motors to operate at highest possible torques with an enhanced dynamic performance. Drives utilize estimators that estimate the motor speed and other state variables. Yet, for accurate calculations, speed estimators must have motor parameters and model that match the actual values. Variations in motor parameters, either due to environment or abnormality, would influence the estimation accuracy. Many techniques are employed to estimate the motor speed and state variables. In this work a sensorless drive with an extended Kalman filter (EKF) is examined under different rotor fault cases. Three broken rotor bars (BRBs) of different degrees of severities were tested. Moreover, variables from the EKF are processed and further analyzed as to examine the potential of detecting and diagnosing BRBs. It was observed that rotor time constant is effective in detecting the BRB faults. While on the other hand, both estimated current and slip spectra found rich of information about this kind of faults and can be effectively used for BRB faults diagnostics even under low loads.

AB - Sensorless variable speed drives enable motors to operate at highest possible torques with an enhanced dynamic performance. Drives utilize estimators that estimate the motor speed and other state variables. Yet, for accurate calculations, speed estimators must have motor parameters and model that match the actual values. Variations in motor parameters, either due to environment or abnormality, would influence the estimation accuracy. Many techniques are employed to estimate the motor speed and state variables. In this work a sensorless drive with an extended Kalman filter (EKF) is examined under different rotor fault cases. Three broken rotor bars (BRBs) of different degrees of severities were tested. Moreover, variables from the EKF are processed and further analyzed as to examine the potential of detecting and diagnosing BRBs. It was observed that rotor time constant is effective in detecting the BRB faults. While on the other hand, both estimated current and slip spectra found rich of information about this kind of faults and can be effectively used for BRB faults diagnostics even under low loads.

KW - Condition Monitoring

KW - Extended Kalman Filters

KW - Fault Detection

KW - Induction MotorBRBs

KW - Sensorless VSDs

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U2 - 10.1109/MI-STA54861.2022.9837501

DO - 10.1109/MI-STA54861.2022.9837501

M3 - Conference contribution

AN - SCOPUS:85135753289

SN - 9781665479196

SP - 99

EP - 104

BT - 2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2022 - Proceeding

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering

Y2 - 23 May 2022 through 25 May 2022

ER -

Abusaad S, Elforjani B, Hamad N, Almezhghwi K, Gu F , Ball AD. Detection and diagnosis of induction motor's broken rotor bars in Kalman filter based drives. In 2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2022 - Proceeding. Institute of Electrical and Electronics Engineers Inc. 2022. p. 99-104. 9837501 doi: 10.1109/MI-STA54861.2022.9837501

Detection and diagnosis of induction motor's broken rotor bars in Kalman filter based drives

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