Stationary wavelet transform for fault detection in rotating machinery

Serhat Seker; Erinc Karatoprak; A. H. Kayran; Tayfun Senguler

doi:10.1117/12.735537

Stationary wavelet transform for fault detection in rotating machinery

Serhat Seker
, Erinc Karatoprak^*
, A. H. Kayran
, Tayfun Senguler

^*Bu çalışma için yazışmadan sorumlu yazar

Elektrik Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

2 Atıf (Scopus)

Özet

This research presents a different fault diagnostic approach using the Stationary Wavelet Transform (SWT) as an alternative method to Discrete Wavelet Transform (DWT). In this sense, it is aimed to find potential defects, which exist in healthy motor bearings as manufacturing defects as compared to the faulty case. This approach extracts the origin of the bearing damage that develops during the aging process. In this manner, the advantage of the SWT over the DWT is emphasized. Hence, it can be introduced as a new approach for condition monitoring studies in rotating machineries like the induction motors.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Wavelet Applications in Industrial Processing V
DOI'lar	https://doi.org/10.1117/12.735537
Yayın durumu	Yayınlandı - 2007
Etkinlik	Wavelet Applications in Industrial Processing V - Boston, MA, United States Süre: 11 Eyl 2007 → 12 Eyl 2007

Yayın serisi

Adı	Proceedings of SPIE - The International Society for Optical Engineering
Hacim	6763
ISSN (Basılı)	0277-786X

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???event.eventtypes.event.conference???	Wavelet Applications in Industrial Processing V
Ülke/Bölge	United States
Şehir	Boston, MA
Periyot	11/09/07 → 12/09/07

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

SKH 9 Sanayi, Yenilikçilik ve Altyapı

Belgeye Erişim

10.1117/12.735537

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

@inproceedings{be3827d4fa174034a902fbb4e5d8e1b7,

title = "Stationary wavelet transform for fault detection in rotating machinery",

abstract = "This research presents a different fault diagnostic approach using the Stationary Wavelet Transform (SWT) as an alternative method to Discrete Wavelet Transform (DWT). In this sense, it is aimed to find potential defects, which exist in healthy motor bearings as manufacturing defects as compared to the faulty case. This approach extracts the origin of the bearing damage that develops during the aging process. In this manner, the advantage of the SWT over the DWT is emphasized. Hence, it can be introduced as a new approach for condition monitoring studies in rotating machineries like the induction motors.",

keywords = "Bearing damage, Bearing fluting, Fault detection, Stationary wavelet transform",

author = "Serhat Seker and Erinc Karatoprak and Kayran, \{A. H.\} and Tayfun Senguler",

year = "2007",

doi = "10.1117/12.735537",

language = "English",

isbn = "9780819469236",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

booktitle = "Wavelet Applications in Industrial Processing V",

note = "Wavelet Applications in Industrial Processing V ; Conference date: 11-09-2007 Through 12-09-2007",

}

Seker, S, Karatoprak, E, Kayran, AH & Senguler, T 2007, Stationary wavelet transform for fault detection in rotating machinery. in Wavelet Applications in Industrial Processing V., 67630A, Proceedings of SPIE - The International Society for Optical Engineering, hac. 6763, Wavelet Applications in Industrial Processing V, Boston, MA, United States, 11/09/07. https://doi.org/10.1117/12.735537

Stationary wavelet transform for fault detection in rotating machinery. / Seker, Serhat; Karatoprak, Erinc; Kayran, A. H. et al.
Wavelet Applications in Industrial Processing V. 2007. 67630A (Proceedings of SPIE - The International Society for Optical Engineering; Hac. 6763).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Stationary wavelet transform for fault detection in rotating machinery

AU - Seker, Serhat

AU - Karatoprak, Erinc

AU - Kayran, A. H.

AU - Senguler, Tayfun

PY - 2007

Y1 - 2007

N2 - This research presents a different fault diagnostic approach using the Stationary Wavelet Transform (SWT) as an alternative method to Discrete Wavelet Transform (DWT). In this sense, it is aimed to find potential defects, which exist in healthy motor bearings as manufacturing defects as compared to the faulty case. This approach extracts the origin of the bearing damage that develops during the aging process. In this manner, the advantage of the SWT over the DWT is emphasized. Hence, it can be introduced as a new approach for condition monitoring studies in rotating machineries like the induction motors.

AB - This research presents a different fault diagnostic approach using the Stationary Wavelet Transform (SWT) as an alternative method to Discrete Wavelet Transform (DWT). In this sense, it is aimed to find potential defects, which exist in healthy motor bearings as manufacturing defects as compared to the faulty case. This approach extracts the origin of the bearing damage that develops during the aging process. In this manner, the advantage of the SWT over the DWT is emphasized. Hence, it can be introduced as a new approach for condition monitoring studies in rotating machineries like the induction motors.

KW - Bearing damage

KW - Bearing fluting

KW - Fault detection

KW - Stationary wavelet transform

UR - https://www.scopus.com/pages/publications/42449157161

U2 - 10.1117/12.735537

DO - 10.1117/12.735537

M3 - Conference contribution

AN - SCOPUS:42449157161

SN - 9780819469236

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Wavelet Applications in Industrial Processing V

T2 - Wavelet Applications in Industrial Processing V

Y2 - 11 September 2007 through 12 September 2007

ER -

Stationary wavelet transform for fault detection in rotating machinery

Özet

Yayın serisi

???event.eventtypes.event.conference???

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap