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Automatizing the detection of rotor failures in induction motors operated via soft-starters

Georgoulas, George (author)
Department of Informatics and Communications Technology, Technical Educational Institute of Epirus, 47100 Artas, Kostakioi, Department of Computer Engineering, TEI of Epirus, Arta, Greece
Karvelis, Petros (author)
Department of Computer Engineering, TEI of Epirus, Arta, Greece
Stylios, Chrysostomos D. (author)
Department of Computer Engineering, TEI of Epirus, Arta, Greece
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Tsoumas, Ioannis P. (author)
Larges Drives, Products R&D Department, Siemens Industry Sector - Drive Technologies, Nuremberg, Germany
Antonino-Daviu, Jose Alfonso (author)
Institute of Energy Engineering, University of Valencia, Spain
Hernandez, Jesus Corral (author)
Institute of Energy Engineering, University of Valencia, Spain
Alarcon, Vicente Climente (author)
Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland
Nikolakopoulos, George (author)
Luleå tekniska universitet,Signaler och system
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 (creator_code:org_t)
Piscataway, NJ : IEEE Communications Society, 2016
2016
English.
In: Annual Conference of the IEEE Industrial Electronics Society, IECON 2015. - Piscataway, NJ : IEEE Communications Society. - 9781479917624 ; , s. 3743-3748
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Implementation of unsupervised induction motor condition monitoring systems has drawn an increasing attention recently among motor drives manufacturers. In the case of soft- starters the possibility of incorporating fault detection features to their conventional functions provides an added value to those elements. Design and development of advanced algorithms that are able to automatically detect and alert about possible failures without requiring continuous human inspection is an especially challenging research goal. In this paper, an algorithm for the automatic detection of rotor damages in induction motors in the case of soft starting is proposed. The twofold approach relies, first, on the application of a time-frequency transform to the starting current signal and, second, on a pattern recognition stage based on the treatment of the time-frequency representation as a symbolic sequence. The innovation of this work is the implementation of the proposed approach for the automatic detection of rotor cage faults in soft-started motors. The experimental results prove the usefulness of the approach for the automatic detection of such faults and its potential for possible future implementation in soft-started machines.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)

Keyword

broken bar fault
boft starters
symbolic time series analysis
time-frequency analysis
Reglerteknik
Control Engineering

Publication and Content Type

ref (subject category)
kon (subject category)

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