US20240135280
2024-04-25
Physics
G06Q10/06312
A transformer monitoring system is designed to enhance the operational efficiency of transformers in power distribution systems. It achieves this by collecting sensor data from various sensors during the transformer's operation. The system then generates energy loss data that predicts the energy loss associated with the transformer based on the collected sensor data.
In addition to tracking energy loss, the monitoring system trains a failure rate prediction model using historical failure data. This model calculates failure probability distribution data, indicating when a transformer is most likely to fail. By predicting potential failures, the system helps in timely maintenance and reduces the risk of unexpected outages.
The transformer monitoring system also generates replacement data that identifies the optimal time for replacing a transformer. This timing is determined by analyzing energy loss data, failure probability distribution data, and specific transformer specifications. This proactive approach helps ensure that transformers are replaced at the right time, avoiding both premature replacements and unexpected failures.
Transformers face several challenges, including wear from environmental factors and operational stresses. Detecting imminent failures is complicated due to their design, which often requires de-energizing the transformer for inspection. Additionally, replacing transformers involves logistical challenges and requires specialized training due to their size and weight.
The monitoring module utilizes time-series sensor data from multiple distribution transformers to analyze their conditions and develop optimal replacement schedules. By integrating various types of sensor data—such as temperature, voltage, and humidity—the system can provide precise recommendations for when each transformer should be replaced, ultimately improving reliability in power distribution.