Implementation of intelligent relay using labVIEW for identification and classification of stator winding faults in three phase induction motor
| dc.contributor.author | Kaur, Simerjeet | |
| dc.contributor.supervisor | Sinha, Amrita | |
| dc.date.accessioned | 2015-08-14T10:27:01Z | |
| dc.date.available | 2015-08-14T10:27:01Z | |
| dc.date.issued | 2015-08-14T10:27:01Z | |
| dc.description | ME, EIED | en |
| dc.description.abstract | The induction motor fault simulation has been done by making use of direct phase quantities. The continuous signals obtained from analysis have been sampled at 800 Hz i.e. 16 samples per cycle. Pattern generation, in order to identify between healthy and faulty condition of stator winding has been done using these samples. The patterns have been generated and ANN has been trained using these using MATLAB script file. The network has been trained using back propagation algorithm. The network has been able to successfully identify the stator winding faults in MATLAB and further classified. The trained intelligent network has been implemented in LabVIEW. The model has been tested for healthy condition and different stator winding faults. The designed intelligent relay detects and classifies the faults in stator winding as A-phase, B-phase or C-phase fault within a quarter of a cycle. | en |
| dc.description.sponsorship | EIED, Thapar university | en |
| dc.format.extent | 2135747 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/10266/3591 | |
| dc.language.iso | en | en |
| dc.subject | artificial neural network | en |
| dc.subject | back propagation | en |
| dc.subject | labVIEW | en |
| dc.subject | Pattern recognition | en |
| dc.subject | stator winding faults | en |
| dc.subject | three phase induction motor | en |
| dc.subject | EIED | en |
| dc.title | Implementation of intelligent relay using labVIEW for identification and classification of stator winding faults in three phase induction motor | en |
| dc.type | Thesis | en |
