Trend Analysis and Continuous Wavelet Transform for Bearing Fault Detection in Induction Motors

Ilker Aydin; Serhat Seker

doi:10.1109/ELECO60389.2023.10416018

Trend Analysis and Continuous Wavelet Transform for Bearing Fault Detection in Induction Motors

Ilker Aydin^*
, Serhat Seker

^*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

In this research, we studied on fault detection at the inner race of bearing in induction motors using trend analysis and continuous wavelet transform. Vibration signals collected from a test setup for normal and faulty cases are analyzed by the trend analysis method. This method aims to determine intersection points of trend lines that represent fault information carrying frequency. Then, the faulty vibration signal is examined with continuous wavelet transform. By using continuous wavelet transform (CWT), it is aimed to calculate the frequency resulting the highest wavelet coefficients which describe the fault signal frequency.

Original language	English
Title of host publication	14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350360493
DOIs	https://doi.org/10.1109/ELECO60389.2023.10416018
Publication status	Published - 2023
Externally published	Yes
Event	14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Virtual, Bursa, Turkey Duration: 30 Nov 2023 → 2 Dec 2023

Publication series

Name	14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings

Conference

Conference	14th International Conference on Electrical and Electronics Engineering, ELECO 2023
Country/Territory	Turkey
City	Virtual, Bursa
Period	30/11/23 → 2/12/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Access to Document

10.1109/ELECO60389.2023.10416018

Cite this

Aydin, I., & Seker, S. (2023). Trend Analysis and Continuous Wavelet Transform for Bearing Fault Detection in Induction Motors. In 14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings (14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ELECO60389.2023.10416018

Aydin, Ilker ; Seker, Serhat. / Trend Analysis and Continuous Wavelet Transform for Bearing Fault Detection in Induction Motors. 14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings).

@inproceedings{c9117640583544e98bb5e724428290e5,

title = "Trend Analysis and Continuous Wavelet Transform for Bearing Fault Detection in Induction Motors",

abstract = "In this research, we studied on fault detection at the inner race of bearing in induction motors using trend analysis and continuous wavelet transform. Vibration signals collected from a test setup for normal and faulty cases are analyzed by the trend analysis method. This method aims to determine intersection points of trend lines that represent fault information carrying frequency. Then, the faulty vibration signal is examined with continuous wavelet transform. By using continuous wavelet transform (CWT), it is aimed to calculate the frequency resulting the highest wavelet coefficients which describe the fault signal frequency.",

author = "Ilker Aydin and Serhat Seker",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 14th International Conference on Electrical and Electronics Engineering, ELECO 2023 ; Conference date: 30-11-2023 Through 02-12-2023",

year = "2023",

doi = "10.1109/ELECO60389.2023.10416018",

language = "English",

series = "14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings",

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

booktitle = "14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings",

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}

Aydin, I & Seker, S 2023, Trend Analysis and Continuous Wavelet Transform for Bearing Fault Detection in Induction Motors. in 14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings. 14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 14th International Conference on Electrical and Electronics Engineering, ELECO 2023, Virtual, Bursa, Turkey, 30/11/23. https://doi.org/10.1109/ELECO60389.2023.10416018

Trend Analysis and Continuous Wavelet Transform for Bearing Fault Detection in Induction Motors. / Aydin, Ilker; Seker, Serhat.
14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings).

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

TY - GEN

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AU - Aydin, Ilker

AU - Seker, Serhat

PY - 2023

Y1 - 2023

N2 - In this research, we studied on fault detection at the inner race of bearing in induction motors using trend analysis and continuous wavelet transform. Vibration signals collected from a test setup for normal and faulty cases are analyzed by the trend analysis method. This method aims to determine intersection points of trend lines that represent fault information carrying frequency. Then, the faulty vibration signal is examined with continuous wavelet transform. By using continuous wavelet transform (CWT), it is aimed to calculate the frequency resulting the highest wavelet coefficients which describe the fault signal frequency.

AB - In this research, we studied on fault detection at the inner race of bearing in induction motors using trend analysis and continuous wavelet transform. Vibration signals collected from a test setup for normal and faulty cases are analyzed by the trend analysis method. This method aims to determine intersection points of trend lines that represent fault information carrying frequency. Then, the faulty vibration signal is examined with continuous wavelet transform. By using continuous wavelet transform (CWT), it is aimed to calculate the frequency resulting the highest wavelet coefficients which describe the fault signal frequency.

UR - https://www.scopus.com/pages/publications/85185834123

U2 - 10.1109/ELECO60389.2023.10416018

DO - 10.1109/ELECO60389.2023.10416018

M3 - Conference contribution

AN - SCOPUS:85185834123

T3 - 14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings

BT - 14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th International Conference on Electrical and Electronics Engineering, ELECO 2023

Y2 - 30 November 2023 through 2 December 2023

ER -

Aydin I, Seker S. Trend Analysis and Continuous Wavelet Transform for Bearing Fault Detection in Induction Motors. In 14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings). doi: 10.1109/ELECO60389.2023.10416018

Trend Analysis and Continuous Wavelet Transform for Bearing Fault Detection in Induction Motors

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