Fault detection in three phase induction motor using artificial intelligence / (Record no. 2728)

MARC details
000 -LEADER
fixed length control field 01621nam a2200277 a 4500
001 - CONTROL NUMBER
control field vtls000055163
003 - CONTROL NUMBER IDENTIFIER
control field KUKTEM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251114204458.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 110801t2009 my a f m 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE0006819(Local)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201905291241
Level of effort used to assign nonsubject heading access points amirul
-- 201108011133
-- Fida
040 ## - CATALOGING SOURCE
Original cataloging agency UMP
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) TK4058 .F37 2009 rs Bc.
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Ahmad Farid Abu Bakar
245 10 - TITLE STATEMENT
Title Fault detection in three phase induction motor using artificial intelligence /
Statement of responsibility, etc. Ahmad Farid Abu Bakar
246 3# - VARYING FORM OF TITLE
Title proper/short title Fault detection in three phase induction motor using artificial intelligence
Medium [computer file]
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Kuantan, Pahang :
Name of publisher, distributor, etc. UMP,
Date of publication, distribution, etc. 2009
300 ## - PHYSICAL DESCRIPTION
Extent xii, 82 p. :
Other physical details ill. (some col.) ;
Dimensions 30 cm. +
Accompanying material 1 computer disc
502 ## - DISSERTATION NOTE
Dissertation note Project paper (Bachelor of Electrical Engineering (Power System)) -- Universiti Malaysia Pahang - 2009
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Bibliography : p. 86
520 3# - SUMMARY, ETC.
Summary, etc. Artificial intellegence (AI) techniques have proved their ability in detection of incipient faults in electrical machines. in this project, the fault diagnosis of three phase induction motors is studied detailed in unbalance voltage and stator inter turn fault using simulation models and neural networks have been used to train the data using Radial Basis Function Neural Network (RBFNN) in MATLAB with Graphical USer Interface Development Environment (GUIDE) structured.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Electric driving
General subdivision Automatic control
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Electric motors
General subdivision Automatic control
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial intelligence
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
  Not lost   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   TK4058 .F37 2009 rs Bc. 0000058373 04/09/2019 1 04/09/2019 Final Year Report
  Not lost   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   CD 5368 | TK4058 .F37 2009 rs Bc. 0000058374 04/09/2019 1 04/09/2019 Final Year Report

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