Deteksi dan Klasifikasi Sinyal Listrik Non-Stasioner yang Mengandung Masalah Kualitas Daya Menggunakan Transformasi Hilbert Huang
DOI:
https://doi.org/10.30736/je.v2i2.81Keywords:
Dekomposisi Mode Empiris, Jaringan Saraf Tiruan, Klasifikasi Sinyal, Kualitas Daya, Transformasi Hilbert Huang.Abstract
Makalah ini menyajikan klasifikasi sinyal listrik non-stasioner yang mengandung masalah Kualitas Daya (KD) berbasis Transformasi Hilbert Huang (THH) dan Jaringan Saraf Tiruan (JST). Transformasi Hilbert Huang (THH) adalah metode analisis sinyal yang relatif baru, yang terdiri dari dua tahap - Dekomposisi Mode Empiris (DME) dan Transformasi Hilbert (TH). Proses DME menguraikan sinyal menjadi komponen – komponennya dalam bentuk Fungsi Mode Intrinsik (FMI) sementara TH digunakan untuk memperoleh amplitudo dan frekuensi sesaat dari masing-masing FMI. Fitur yang diekstraksi melalui THH digunakan untuk melatih JST guna mengenali kelas sinyal yang diproses. Kelas sinyal yang diidentifikasi mulai dari sinyal normal, interupsi, sag, swell, harmonisa, transien, dan gabungannya. Hasil simulasi menunjukkan bahwa kombinasi THH dan JST dapat secara efektif mendeteksi dan mengklasifikasikan sinyal yang mengandung berbagai masalah KD.Downloads
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