Data analytics on averted and failed distribution transformers
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 s...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/141691 |
| _version_ | 1824454990218919936 |
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| author | Lim, Zhen Hao |
| author2 | Ng Beng Koon |
| author_facet | Ng Beng Koon Lim, Zhen Hao |
| author_sort | Lim, Zhen Hao |
| collection | NTU |
| description | 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. |
| first_indexed | 2025-02-19T03:31:05Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/141691 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:31:05Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1416912023-07-07T17:35:56Z Data analytics on averted and failed distribution transformers Lim, Zhen Hao Ng Beng Koon School of Electrical and Electronic Engineering SP Group EBKNg@ntu.edu.sg Engineering::Electrical and electronic engineering 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. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-06-10T03:16:00Z 2020-06-10T03:16:00Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/141691 en B2138-191 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Lim, Zhen Hao Data analytics on averted and failed distribution transformers |
| title | Data analytics on averted and failed distribution transformers |
| title_full | Data analytics on averted and failed distribution transformers |
| title_fullStr | Data analytics on averted and failed distribution transformers |
| title_full_unstemmed | Data analytics on averted and failed distribution transformers |
| title_short | Data analytics on averted and failed distribution transformers |
| title_sort | data analytics on averted and failed distribution transformers |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/141691 |
| work_keys_str_mv | AT limzhenhao dataanalyticsonavertedandfaileddistributiontransformers |