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- W2048996836 abstract "This paper is proposing Naive Bayes classifier detection system to identify the symptom of stator winding deterioration. The proposed system is based on probabilistic classifier with strong independence assumption of each fault case. The temporary short circuit case is defined as non permanent short circuit fault with high impedance. This fault case is representing the early stage of stator insulation break down. The laboratory experiment is performed to simulate the fault cases consist of induction motor with stator modification and current measurement system. The detection system is trained to identify the temporary short circuit occurrence consist of transient starting, steady state and ending of temporary short circuit. The system is also tested using non trained data to clarify the detection performance." @default.
- W2048996836 created "2016-06-24" @default.
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- W2048996836 date "2013-08-01" @default.
- W2048996836 modified "2023-09-25" @default.
- W2048996836 title "Naïve Bayes classifier for temporary short circuit fault detection in stator winding" @default.
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- W2048996836 doi "https://doi.org/10.1109/demped.2013.6645730" @default.
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