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FAULT PROGNOSTICS FOR 3-PHASE INDUCTION MOTOR

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dc.contributor.author Ijaz, Hamza
dc.date.accessioned 2023-08-16T05:50:02Z
dc.date.available 2023-08-16T05:50:02Z
dc.date.issued 2014
dc.identifier.other 2010-NUST-MS PhD-Elec-33
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/36645
dc.description Supervisor: Dr. Muhammad Salman en_US
dc.description.abstract The induction motors are electro-mechanical devices used in industry applications. These motors are robust and used for general purpose as well as in severe environment. Some of the applications are conveyors, elevators, presses, packing apparatus, natural gas plant and coal plant equipment. These motors require very low maintenance and are very highly reliable. In terms of power it comes from hundreds to mega watts, which make them suitable for many industrial processes. It is necessary to identify a fault in induction motor at the initial stage to avoid severe damage of induction motor as well as unwanted shutdown of production. For the detection of broken rotor bar fault and inter-turn short fault, an online detection technique which is parameter estimation using three different non-linear estimators is implemented. All the three estimators successfully estimate the parameters with low error in different load conditions of induction motor. The estimated values are used to detect the occurrence of fault by comparing with the reference values. The non-model based technique, motor current signature analysis is also implemented. Fault of broken rotor bar, bearing related faults and fault of inter-turn short in stator windings is successfully detected using this technique. A GLRT detector is also designed for detecting low amplitude signal in power spectrum of stator current. The detector is performing very well and detector performance is shown using ROC curve. en_US
dc.language.iso en en_US
dc.publisher College of Electrical & Mechanical Engineering (CEME), NUST en_US
dc.title FAULT PROGNOSTICS FOR 3-PHASE INDUCTION MOTOR en_US
dc.type Thesis en_US


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