TRANSFORMER HEALTH MONITORING

Abstract

The Transformer Health Monitoring System is designed to continuously observe key parameters that determine the condition of a distribution transformer. In this project, temperature and oil level are measured using sensors connected to an Arduino-based IoT platform. The collected data is displayed locally and also sent to a cloud server through a Wi-Fi module, allowing remote supervision from any location. Alerts are generated automatically when the temperature rises above the safe limit or when the oil level drops, helping prevent major faults.
This system reduces the need for manual inspection and makes transformer maintenance more reliable and efficient. By providing real-time updates and early warnings, the proposed model supports quick decision-making and helps avoid unexpected transformer failures. The project demonstrates a cost-effective and practical approach to improving the safety and lifespan of power distribution equipment.