istatistiksel çoziimleme ve KL U zakllglna Dayall Rulman Rata Tespit Yontemi

Arda Mollakoy; Emre Yengel; B. Ugur Toreyin

doi:10.1109/SIU.2016.7496131

istatistiksel çoziimleme ve KL U zakllglna Dayall Rulman Rata Tespit Yontemi

Translated title of the contribution: Bearing fault detection method based on statistical analysis and KL distance

Arda Mollakoy, Emre Yengel, B. Ugur Toreyin

Informatics Institute

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

Abstract

The final step of the bearing production line constitutes the inspection of the bearing which is mostly performed by visual inspection. Three groups of bearings namely, properly assembled samples, conversely assembled rubber seal and samples where rubber seals were missing are classified using visible range images of these samples. According to the proposed method, extraction of seal regions from the bearing images using circular Hough transform is followed by a higher-order statistical analysis to finalize the classification. Experimental results show that this system may be employed as an assistive tool for bearing inspectors.

Translated title of the contribution	Bearing fault detection method based on statistical analysis and KL distance
Original language	Turkish
Title of host publication	2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1881-1884
Number of pages	4
ISBN (Electronic)	9781509016792
DOIs	https://doi.org/10.1109/SIU.2016.7496131
Publication status	Published - 20 Jun 2016
Event	24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey Duration: 16 May 2016 → 19 May 2016

Publication series

Name	2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

Conference

Conference	24th Signal Processing and Communication Application Conference, SIU 2016
Country/Territory	Turkey
City	Zonguldak
Period	16/05/16 → 19/05/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Access to Document

10.1109/SIU.2016.7496131

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Mollakoy, A., Yengel, E., & Toreyin, B. U. (2016). istatistiksel çoziimleme ve KL U zakllglna Dayall Rulman Rata Tespit Yontemi. In 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings (pp. 1881-1884). Article 7496131 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2016.7496131

Mollakoy, Arda ; Yengel, Emre ; Toreyin, B. Ugur. / istatistiksel çoziimleme ve KL U zakllglna Dayall Rulman Rata Tespit Yontemi. 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1881-1884 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings).

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title = "istatistiksel {\c c}oziimleme ve KL U zakllglna Dayall Rulman Rata Tespit Yontemi",

abstract = "The final step of the bearing production line constitutes the inspection of the bearing which is mostly performed by visual inspection. Three groups of bearings namely, properly assembled samples, conversely assembled rubber seal and samples where rubber seals were missing are classified using visible range images of these samples. According to the proposed method, extraction of seal regions from the bearing images using circular Hough transform is followed by a higher-order statistical analysis to finalize the classification. Experimental results show that this system may be employed as an assistive tool for bearing inspectors.",

keywords = "Kullback-Leibler Distance, bearing, computer vision, statistical analysis",

author = "Arda Mollakoy and Emre Yengel and Toreyin, {B. Ugur}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 24th Signal Processing and Communication Application Conference, SIU 2016 ; Conference date: 16-05-2016 Through 19-05-2016",

year = "2016",

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doi = "10.1109/SIU.2016.7496131",

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series = "2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings",

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

pages = "1881--1884",

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Mollakoy, A, Yengel, E & Toreyin, BU 2016, istatistiksel çoziimleme ve KL U zakllglna Dayall Rulman Rata Tespit Yontemi. in 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings., 7496131, 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1881-1884, 24th Signal Processing and Communication Application Conference, SIU 2016, Zonguldak, Turkey, 16/05/16. https://doi.org/10.1109/SIU.2016.7496131

istatistiksel çoziimleme ve KL U zakllglna Dayall Rulman Rata Tespit Yontemi. / Mollakoy, Arda; Yengel, Emre; Toreyin, B. Ugur.
2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1881-1884 7496131 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings).

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

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T1 - istatistiksel çoziimleme ve KL U zakllglna Dayall Rulman Rata Tespit Yontemi

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AU - Yengel, Emre

AU - Toreyin, B. Ugur

PY - 2016/6/20

Y1 - 2016/6/20

N2 - The final step of the bearing production line constitutes the inspection of the bearing which is mostly performed by visual inspection. Three groups of bearings namely, properly assembled samples, conversely assembled rubber seal and samples where rubber seals were missing are classified using visible range images of these samples. According to the proposed method, extraction of seal regions from the bearing images using circular Hough transform is followed by a higher-order statistical analysis to finalize the classification. Experimental results show that this system may be employed as an assistive tool for bearing inspectors.

AB - The final step of the bearing production line constitutes the inspection of the bearing which is mostly performed by visual inspection. Three groups of bearings namely, properly assembled samples, conversely assembled rubber seal and samples where rubber seals were missing are classified using visible range images of these samples. According to the proposed method, extraction of seal regions from the bearing images using circular Hough transform is followed by a higher-order statistical analysis to finalize the classification. Experimental results show that this system may be employed as an assistive tool for bearing inspectors.

KW - Kullback-Leibler Distance

KW - bearing

KW - computer vision

KW - statistical analysis

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DO - 10.1109/SIU.2016.7496131

M3 - Konferans katkısı

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T3 - 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

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BT - 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 24th Signal Processing and Communication Application Conference, SIU 2016

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Mollakoy A, Yengel E, Toreyin BU. istatistiksel çoziimleme ve KL U zakllglna Dayall Rulman Rata Tespit Yontemi. In 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1881-1884. 7496131. (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings). doi: 10.1109/SIU.2016.7496131

istatistiksel çoziimleme ve KL U zakllglna Dayall Rulman Rata Tespit Yontemi

Abstract

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