Clustering Fenomena Corona Discharge berdasarkan Suara menggunakan Metode LPC dan Euclidean Distance

MIFTAHUL FIKRI, CHRISTIONO CHRISTIONO, IWA GARNIWA MULYANA K.

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ABSTRAK

Kegagalan isolasi akibat fenomena tegangan tinggi seperti corona discharge (CD) masih banyak terjadi pada sistem kelistrikan di Indonesia. Hal ini disebabkan belum dapat dilakukannya deteksi dini kegagalan isolasi. Salah satu bentuk CD berupa suara. Sebagai langkah awal deteksi dini kegagalan isolasi diperlukan suatu penelitian yang dapat mengklaster suara CD (pada kubikal 20 kV) yang merupakan tujuan penelitian. Berdasarkan pengamatan pada elektroda jarum-batang berjarak 3 cm diperoleh breakdown terkecil pada 34,3 kV. Klasifikasi suara CD ditetapkan menjadi 3 cluster yang dimulai dari tegangan cubicle 20 kV hingga sebelum breakdown terjadi yaitu 33 kV. Clustering dilakukan menggunakan metode linear predictive coding (LPC) sebagai ekstraksi ciri dan Euclidean distance sebagai pencocokan pola hasil ekstraksi. Adapun suhu di dalam kubikal antara 27,5℃ - 35,3℃ dan kelembaban berkisar 70% - 95%. Hasil akurasi clustering rata-rata yang diperoleh adalah 100% untuk data training dan 85,15% untuk data testing.

Kata kunci: corona discharge, Euclidean distance, kegagalan isolasi, linear predictive coding, tegangan tinggi

 

ABSTRACT

Insulation failures due to high voltage phenomena such as corona discharge (CD) are still common in the electricity system in Indonesia. This is because early detection of insulation failure cannot be carried out. One form of CD is sound. As the first step in early detection, a study is needed to cluster CD sound (at 20 kV cubical). By observations on the needle-rod electrode at 3 cm, the smallest breakdown was at 34.3 kV. CD sound classification is set into 3 clusters starting from a cubicle voltage of 20 kV until before breakdown occurs, which is 33 kV. Clustering was carried out using linear predictive coding (LPC) as feature extraction and Euclidean distance as pattern matching extracted results. The temperature and humidity inside the cubical are 27.5℃-35.3℃ and 70%-95% respectively. For training and testing data average clustering accuracy results obtained are 100% and 85.15% respectively.

Keywords: corona discharge, Euclidean distance,, insulation failure, linier predictive coding, high voltage


Kata Kunci


corona discharge; Euclidean distance; kegagalan isolasi; linear predictive coding; tegangan tinggi

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Referensi


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DOI: https://doi.org/10.26760/elkomika.v10i3.689

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