Sutaryono, Gaffar Lutfi (2015) Analisa Indeks Kesehatan Transformator Daya Berbasis Neural Network Untuk Mereduksi Jumlah Test Pada Trafo. UNSPECIFIED thesis, Institut Technology Sepuluh Nopember.
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Abstract
Transformator daya merupakan salah satu peralatan listrik yang
mempunyai peran sentral dan kritis pada sistem tenaga listrik. Untuk
menghindari kegagalan pada transformator daya, dibutuhkan antisipasi
dengan pemantauan dan pemeliharaan kondisi transformator. Penelitian
ini menyajikan informasi mengenai diagnosis kondisi transformator
berdasarkan metode Indeks Kesehatan Transformator dengan
menggunakan Neural Network. Metode Indeks Kesehatan Transformator
memberikan penilaian kondisi transformator secara komprehensif.
Analisis gas-gas terlarut, minyak isolasi trafo, dan furan (kertas isolasi)
dilakukan untuk membagi penilaian kondisi transformator daya menjadi
beberapa kategori, sesuai dengan prediksi umur operasi transformator
dan level penurunan kondisi komponen transformator. Target dari tugas
akhir ini adalah mendesain sistem diagnosis berbasis Neural Network
dengan input salah satu dari ketiga test yang dilakukan pada trafo.
Diharapkan dengan hanya menggunakan satu dari tiga jenis test, maka
proses diagnosis kondisi trafo menjadi lebih mudah dan murah.
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Power transformer is one of the electrical appliances that have a
central and critical role in power system. To avoid failure in the power
transformer, it takes anticipation with transformer condition monitoring
and maintenance. This study presents information on the diagnosis of
the condition of the transformer using Transformer Health Index method
by based on Neural Network. Transformer Health Index Method
provides a comprehensive transformer’s condition assessment. This
method divides the power transformer condition assessment into several
categories, according to the prediction of the operating life of the
transformer and the level of deterioration of transformer components.
Analysis of dissolved gases, transformer insulating oil, and furans (paper
insulation) was conducted to determine the type of failure that occurred
in the transformer. The results of this analysis are operating life
prediction, the type of the possibility of failure, and action
recommendations for next transformer maintenance. The target of this
final project is to design a neural network-based diagnosis system with
the input one of the three tests conducted on the transformer. Using only
one of three types of test, the diagnosis of the condition of the
transformer is expected to become easier and cheaper.
| Item Type: | Thesis (UNSPECIFIED) |
|---|---|
| Additional Information: | RSE 621.314 Sut a |
| Uncontrolled Keywords: | Analisis, diagnosis, indeks kesehatan transfomator, neural network, transformator daya |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK201 Electric Power Transmission |
| Divisions: | Faculty of Industrial Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Tondo Indra Nyata |
| Date Deposited: | 28 Jun 2018 02:00 |
| Last Modified: | 13 May 2024 07:44 |
| URI: | http://repository.its.ac.id/id/eprint/52051 |
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