STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Semiconductor Devices and Circuits

“Automated Real-Time Transformer Health Monitoring System Using IoT”

  1. Shishupal Yelgatte
  2. Anup Wasu
  3. Chetan Korde
  4. Piyush Kumar
  5. Limay Kolhe

Abstract

Transformers play a crucial role in the architecture of electricity production and distribution. To guarantee that a transformer performs successfully and efficiently, performance must be closely monitored. Manual and time-consuming procedures are used to monitor transformer characteristics such oil level, temperature, and pressure. To solve this issue, an IoT-based transformer parameter monitoring system may be a good choice. Designing and implementing an IoT-based transformer parameter monitoring system that enables real-time monitoring and reporting of critical performance parameters is the goal of this project. The suggested solution employs sensors to gather data from the transformer and wirelessly communicate it to a platform in the cloud for analysis. The sensors for the system are positioned at strategic locations inside the transformer to measure variables including oil level, temperature, and pressure. Microcontrollers process the information gathered by the sensors and wirelessly transmit it to a platform that is situated in the cloud. When the parameters differ from the expected values, the platform analyses the data, produces reports, and sends alarms. Real-time monitoring, increased effectiveness, predictive maintenance, and cost savings are among the outputs that the proposed system is projected to produce. The infrastructure for electricity generation and distribution will be more reliable and efficient overall as a result of the effective deployment of this system.

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