Please use this identifier to cite or link to this item:
Title: Model-based diagnosis and prognosis of induction motors under stator winding fault
Authors: Nguyen, Viet Hung
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2018
Source: Nguyen, V. H. (2018). Model-based diagnosis and prognosis of induction motors under stator winding fault. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: Induction machines are widely used in industries and essential parts of industrial systems. Despite their rugged construction, they are subject to fault due to aging, severe operating conditions, and harsh environments. Industrial surveys have shown that stator winding accounts for a significant portion of faults in electrical machines. Stator winding inter-turn short is one of the most common root causes of stator winding fault which can spread over and lead to catastrophic damages. In this thesis, a framework for diagnosis and prognosis of electrical machines under stator winding inter-turn short fault, and the associated techniques for sub-problems including early fault detection, fault severity estimation, and degradation modeling and RUL estimation, are proposed. Model-based is the applied technique including parity equation approach using sequence component model, multiple-model approach, and particle-filter based approach.
DOI: 10.32657/10220/46022
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

Files in This Item:
File Description SizeFormat 
PhDThesis_NguyenVietHung.pdf17.91 MBAdobe PDFThumbnail

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.