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Machine learning approach for condition assessment of an oil filled power transformer

By: Dadaso, Patil Shubham

Material type: Text

TextPublisher: Hamirpur : National Institute of Technology, 2023Description: xv, 76pDDC classification: 621.31 Dissertation note: Master of Technology, Department of Electrical Engineering, National Institute of Technology Hamirpur, Himachal Pradesh, India - 177005. 2023 Guide / Supervisor: Jarial, R.K

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Item type	Current location	Call number	Status	Date due	Barcode
Thesis or Dissertation	Central Library On Display	621.31 DAD (Browse shelf)	Available		TH-1907

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Previous	621.31 CHI Comparative analysis of random pwm techniques for multi-level inverters	621.31 CHO Comparitive evaluation of nomex-910 and tuk insulating paper thermally aged in soya-based natural ester oil	621.31 CHO Modelling of partial discharge activity in solid dielectric material	621.31 DAD Machine learning approach for condition assessment of an oil filled power transformer	621.31 DAS Uncertainty modelling in control system and design of a robust controller using hx method	621.31 DEE Application of fuzzy systems to multi-objective optimal placement of res	621.31 DHI Fault diagnosis of a transformer using fuzzy model and nature- based metaheuristic algorithm	Next

Master of Technology, Department of Electrical Engineering, National Institute of Technology Hamirpur, Himachal Pradesh, India - 177005. 2023

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Machine learning approach for condition assessment of an oil filled power transformer

By: Dadaso, Patil Shubham

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