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

^*Corresponding author for this work

Department of Electrical Engineering

Istanbul Technical University

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

2 Citations (Scopus)

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.

Original language	English
Title of host publication	Wavelet Applications in Industrial Processing V
DOIs	https://doi.org/10.1117/12.735537
Publication status	Published - 2007
Event	Wavelet Applications in Industrial Processing V - Boston, MA, United States Duration: 11 Sept 2007 → 12 Sept 2007

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	6763
ISSN (Print)	0277-786X

Conference

Conference	Wavelet Applications in Industrial Processing V
Country/Territory	United States
City	Boston, MA
Period	11/09/07 → 12/09/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Bearing damage
Bearing fluting
Fault detection
Stationary wavelet transform

Access to Document

10.1117/12.735537

Cite this

@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, vol. 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; Vol. 6763).

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

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

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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