Using Deep Learning to Detect Anomalies in On-Load Tap Changer Based on Vibro-Acoustic Signal Features

Using Deep Learning to Detect Anomalies in On-Load Tap Changer Based on Vibro-Acoustic Signal Features

An On-Load Tap Changer (OLTC) that regulates transformer voltage is one of the most important and strategic components of a transformer. Detecting faults in this component at early stages is, therefore, crucial to prevent transformer outages. In recent years, Hydro Quebec initiated a project to moni...

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Bibliographic Details
Main Authors: Fataneh Dabaghi-Zarandi, Vahid Behjat, Michel Gauvin, Patrick Picher, Hassan Ezzaidi, Issouf Fofana
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Energies
Subjects:
power transformer
OLTC
vibro-acoustic signals
anomaly detection
autoencoder
kernel density estimation (KDE)
Online Access:https://www.mdpi.com/1996-1073/17/7/1665

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https://www.mdpi.com/1996-1073/17/7/1665

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