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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

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With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  3/2010 - 6

A New MLP Approach for the Detection of the Incipient Bearing Damage

SENGULER, T. See more information about SENGULER, T. on SCOPUS See more information about SENGULER, T. on IEEExplore See more information about SENGULER, T. on Web of Science, KARATOPRAK, E. See more information about  KARATOPRAK, E. on SCOPUS See more information about  KARATOPRAK, E. on SCOPUS See more information about KARATOPRAK, E. on Web of Science, SEKER, S. See more information about SEKER, S. on SCOPUS See more information about SEKER, S. on SCOPUS See more information about SEKER, S. on Web of Science
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Download PDF pdficon (818 KB) | Citation | Downloads: 993 | Views: 3,475

Author keywords
bearing damage, vibration analysis, MLP neural networks, feature extraction, condition monitoring

References keywords
neural(16), networks(10), bearing(8), applications(7), signal(6), processing(6), artificial(6), monitoring(5), electric(5), condition(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2010-08-31
Volume 10, Issue 3, Year 2010, On page(s): 34 - 39
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.03006
Web of Science Accession Number: 000281805600006
SCOPUS ID: 77956621055

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In this study, it is aimed to track the aging trend of the incipient bearing damage in an induction motor which is subjected to an accelerated aging process. For this purpose, a new Multilayer perceptron (MLP) neural network approach is introduced. The input signals are extracted from power spectral densities (PSD) of the vibration signals taken from a 5-HP induction motor. Principal component analysis (PCA) has been applied to select the best possible feature vectors as a dimensionality reduction purpose. Variance and entropy values are used as the targets of the MLP network. The healthy motor condition was modelled by the MLP network considering all load conditions. The results showed that the incipient bearing damage was clearly extracted by the oscillations of the MLP output error.

References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 9,068 TCR
SCOPUS® Citations for all references: 11,514 TCR

Web of Science® Average Citations per reference: 245 ACR
SCOPUS® Average Citations per reference: 311 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-07-18 21:20 in 98 seconds.

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