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

Ilker Aydin*, Serhat Seker

*Bu çalışma için yazışmadan sorumlu yazar

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Özet

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.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9798350360493
DOI'lar
Yayın durumuYayınlandı - 2023
Harici olarak yayınlandıEvet
Etkinlik14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Virtual, Bursa, Turkey
Süre: 30 Kas 20232 Ara 2023

Yayın serisi

Adı14th International Conference on Electrical and Electronics Engineering, ELECO 2023 - Proceedings

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???event.eventtypes.event.conference???14th International Conference on Electrical and Electronics Engineering, ELECO 2023
Ülke/BölgeTurkey
ŞehirVirtual, Bursa
Periyot30/11/232/12/23

Bibliyografik not

Publisher Copyright:
© 2023 IEEE.

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