This system shows enhanced fault detection and maintenance optimization in power transformers, highlighting IoT integration.
Power Transformers (PT) are vital components in electrical power systems, playing a key role in voltage regulation and ensuring the reliable transmission of electricity. The performance and condition of transformers significantly influence the stability and efficiency of the entire power grid. Regular monitoring of transformers is essential to detect potential issues before they lead to failures, thereby minimizing downtime and maintenance costs. This paper introduces a real-time condition monitoring system for PT, utilizing Internet of Things (IoT) sensors and advanced analytics. The system collects real-time data on key operational parameters such as temperature, vibration, and load. By predictive analytics, the data is analyzed to identify anomalies and predict potential failures. This research focuses on the integration of IoT technology with advanced data analytics to enhance the detection of faults and improve maintenance practices. The results demonstrate the effectiveness of this approach in enhancing transformer reliability, optimizing maintenance schedules, and reducing the risk of unexpected breakdowns in power systems.
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