Data analytics on averted and failed distribution transformers

• Main Author: Lim, Zhen Hao
• Other Authors: Ng Beng Koon
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2020
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/141691
• Institution: Nanyang Technological University

Oil analysis is an effective method to diagnose the incipient faults in power and distribution transformer. The Dissolved Gases Analysis (DGA) is one of the oil analysis method to identify potential faults happening in the distribution transformer. As such distribution transformer are hermetically sealed and are mineral oil-filled with an aid of a nitrogen cushion, it is impossible to open it up to visually identify the faults. This project aims to implement a software to better observe and analyse the data collected from the DGA tests. Currently, transformer data are scattered among different data sheet as the samples are being taken at a different date and time. In addition, statistical methods will be used to analyse the data, feedback warning trends for fail and averted cases. The program will be used to aid in identifying batch problems. This project serves as a starting point and additional function can be built upon this project to make the program more reliable and useful.