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Review of Power Transformer Mechanical Condition Assessment Techniques
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Today’s trend of global electricity market has created a competitive environment in power industry. To reduce operational cost, optimize usage of critical equipments, to improve reliability and customer service, fast and enhanced diagnostic techniques are being developed and utilized in power industry. In recent years, transformer fault diagnosis has become an interesting research area.This paper presents the literature review done in the area of power transformer designs, failure causes and effects and on existing and new diagnostic techniques to generate the baseline for the development of mechanical condition assessment system. The survey has included the 90 technical reports and papers from CIGRE, IEEE transactions and conferences along with standards and books based on power transformer conditioning and monitoring. In this paper an attempt has been made to analyze, generate real data based approach for development of enhanced and automated diagnostic system for mechanical faults detection.
Keywords
Artificial Intelligence, Neural Networks, Neuro-fuzzy, Equivalent Circuit Modeling, Estimation Approach, Power Transformer Modeling, SFRA, Automated Interpretation Algorithm
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