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Fault detection in three phase induction motor using artificial intelligence / Ahmad Farid Abu Bakar

By:

Ahmad Farid Abu Bakar

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2009Description: xii, 82 p. : ill. (some col.) ; 30 cm. + 1 computer discISBN:

THE0006819(Local)

Other title:

Fault detection in three phase induction motor using artificial intelligence [computer file]

Subject(s):

Dissertation note: Project paper (Bachelor of Electrical Engineering (Power System)) -- Universiti Malaysia Pahang - 2009 Abstract: 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.

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Holdings ( 2 )
Title notes ( 3 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB PEKAN	TK4058 .F37 2009 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000058373
Final Year Report	UMPLIB PEKAN	CD 5368 \| TK4058 .F37 2009 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000058374

Project paper (Bachelor of Electrical Engineering (Power System)) -- Universiti Malaysia Pahang - 2009

Bibliography : p. 86

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.