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

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


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2018-Jun-27
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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  3/2015 - 17

Noise and Vibration Monitoring for Premium Efficiency IE 3 Three-Phase Induction Motors

NISTOR, C. G. See more information about NISTOR, C. G. on SCOPUS See more information about NISTOR, C. G. on IEEExplore See more information about NISTOR, C. G. on Web of Science, SCUTARU, G. See more information about  SCUTARU, G. on SCOPUS See more information about  SCUTARU, G. on SCOPUS See more information about SCUTARU, G. on Web of Science, CAMPEANU, R. See more information about  CAMPEANU, R. on SCOPUS See more information about  CAMPEANU, R. on SCOPUS See more information about CAMPEANU, R. on Web of Science, CERNAT, M. See more information about CERNAT, M. on SCOPUS See more information about CERNAT, M. on SCOPUS See more information about CERNAT, M. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,549 KB) | Citation | Downloads: 297 | Views: 1,096

Author keywords
acoustic noise, energy efficiency, induction motors, noise measurement, vibration measurement

References keywords
induction(21), noise(16), machines(16), motor(15), vibration(11), phase(9), optimization(9), motors(8), drives(8), power(7)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-08-31
Volume 15, Issue 3, Year 2015, On page(s): 117 - 122
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.03017
Web of Science Accession Number: 000360171500017
SCOPUS ID: 84940752492

Abstract
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The paper presents the original SV-100 platform that enables low-cost and very high accuracy determinations of noise and vibration levels. The aim of the proposed platform is to achieve an effective integration of the two topics of this analysis: vibrations and noises. To the best of our knowledge, no low price, dedicated compact platform with embedded measuring instruments exists. For proving the practical utility of the proposed platform, two induction motors of 7.5 kW and 11 kW, respectively, in single-layer winding, at 1000 rpm, with IE3 premium efficiency were analyzed. This analysis is required because, according to IEC60034-30 standard, the IE3 efficiency standard has become mandatory for induction motors of rated power greater than 7.5 kW. Therefore, in order to improve the motor operating efficiency, the power losses caused by noises and vibrations have to be reduced. Several variants of supply were studied, i.e., by the three-phase 50 Hz network and by a three-phase inverter at 40, 50 and 60 Hz, respectively. The experimental determinations of noises are presented comparatively, by using a Bruel&Kjaer sonometer and by using the new platform SV-100. The results are compared with the IEC60034 standard.


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

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References Weight

Web of Science® Citations for all references: 273 TCR
SCOPUS® Citations for all references: 343 TCR

Web of Science® Average Citations per reference: 6 ACR
SCOPUS® Average Citations per reference: 8 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 2018-07-22 02:50 in 231 seconds.




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