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DTSTART:19700329T030000
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CREATED:20250703T143208Z
LAST-MODIFIED:20250703T143208Z
DTSTAMP:20260906T083715Z
UID:1788673035@tuc.gr
SUMMARY:Thesis presentation of Erasmus stude
 nt Adrian Martin Marron - School of 
 ECE
LOCATION:Λ - Κτίριο Επιστημών/ΗΜΜΥ, 141Π-36,1
 41Π-37
DESCRIPTION:https://www.tuc.gr/el/to-polytechnei
 o/ilektronikes-ypiresies/imerologio/
 imerologio-ekdiloseon-1?tx_tucevents
 2_tuceventsdisplay%5Baction%5D=show&
 tx_tucevents2_tuceventsdisplay%5Bcon
 troller%5D=Event&tx_tucevents2_tucev
 entsdisplay%5Bevent%5D=7890&cHash=d6
 88b010b746ce66031b3f11b9c105cb\nTECH
 NICAL UNIVERSITY OF CRETE\n School o
 f Electrical and Computer Engineerin
 g \n Undergraduate Program\n Present
 ation of the Diploma Thesis\n by Era
 smus student Adrian Martin Marron ti
 tled:\n Electromagnetic analysis and
  condition monitoring of induction m
 otors\n Thesis committee\n Associate
  Professor Konstantinos Gyftakis (su
 pervisor)\n Assistant Professor Geor
 gios Peppas\n Professor Daniel Morin
 igo-Sotelo (University of Valladolid
 )\n Abstract \n The present thesis o
 utlines the design, modelling and el
 ectromagnetic analysis of a squirrel
  cage induction motor under both hea
 lthy and faulty conditions. The deve
 lopment of a two-dimensional geometr
 y was undertaken using AutoCAD softw
 are, and consequently, a two-dimensi
 onal simulation was conducted utilis
 ing SIMCENTER MAGNET, incorporating 
 the Finite Element Analysis (FEA)met
 hod. Numerous diagnostic  techniques
 —such as Motor Current Signature Ana
 lysis (MCSA), Stray Flux Signature A
 nalysis (SFSA), and Short-Time Fouri
 er Transform (STFT)—were employed to
  determine the motor’s response in b
 oth star and delta configurations. T
 he study focuses on identifying and 
 comparing the effects of rotor bar f
 aults, with the objective of check t
 he efficiency of these preventive te
 chniques. The results demonstrate th
 at electromagnetic simulation combin
 ed with signal processing techniques
  provides a powerful tool for early 
 fault detection in industrial motors
 .\n
STATUS:CONFIRMED
ORGANIZER;RSVP=FALSE;CN=TUC;CUTYPE=TUC:mailto:webmaster@tuc.gr
DTSTART:20250709T100000
DTEND:20250709T110000
TRANSP:OPAQUE
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