Abstract
Abstract: Transformers are critical components of electric powersystems, yet precise fault identification remains difficult. The study presents a novel transformer defect diagnostic approach based on an Internet of Things (IoT) monitoring system and ensemble machine learning (EML). The IoT based monitoring system is divided into two parts: a data measuring subsystemand a data reception subsystem.To begin, the data measuring subsystem measures transformer vibration signals, which are then relayed to the remote server via the data receipt subsystem.
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