01869nam a2200277 a 4500 vtls000055171 KUKTEM 20251114204338.0 110802t2009 my a f m 000 0 eng d THE0006821(Local) 201905291242 amirul 201108020925 Fida UMP TK4058 .H44 2009 rs Bc. Hee, Alvin Bryan Choon Loong On-line incipient fault detection in single-phase squirrel cage using artificial intelligence / Alvin Bryan Hee Choon Loong On-line incipient fault detection in single-phase squirrel cage using artificial intelligence [computer file] Kuantan, Pahang : UMP, 2009 xv, 83 p. : ill. (some col.) ; 30 cm. + 1 computer disc Project paper (Bachelor of Electrical Engineering (Power System)) -- Universiti Malaysia Pahang - 2009 Bibliography : p. 64-65 This project creates and develops an artificial neural network that is capable to determine the condition of a motor whether it is in a healthy state or fault state. All of the data used to train the artificial neural network is obtained by using the result from the simulation of MATLAB Simulink model that represent the real motor. The artificial neural network is trained by using radial basis function neural network method. MATLAB is used to construct and develop Graphical User Interface and interface it with the artificial neural network created. By doing so, the user will be able to test the neural network created with ease of using the Graphical User Interface Electric driving Automatic control Electric motors Automatic control Artificial intelligence 0 0 0 1 20000 20000 2019-09-04 0 TK4058 .H44 2009 rs Bc. 0000058380 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 20000 20000 2019-09-04 0 CD 5371 | TK4058 .H44 2009 rs Bc. 0000058381 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 417 423 VTLSSORT0080*0200*0400*0900*1000*2450*2460*2600*3000*5020*5040*5200*6500*6501*6502*9992