Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Review of Power Transformer Mechanical Condition Assessment Techniques


Affiliations
1 Crompton Greaves Limited, Kanjur Marg, Mumbai - 400 042, India
2 K. K. Wagh College of Engineering Education & Research, Nasik, Maharashtra - 422 003, India
     

   Subscribe/Renew Journal


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
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 199

PDF Views: 0




  • Review of Power Transformer Mechanical Condition Assessment Techniques

Abstract Views: 199  |  PDF Views: 0

Authors

Shubhangi Patil
Crompton Greaves Limited, Kanjur Marg, Mumbai - 400 042, India
B. E. Kushare
K. K. Wagh College of Engineering Education & Research, Nasik, Maharashtra - 422 003, India

Abstract


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



DOI: https://doi.org/10.33686/prj.v9i3.189558