Traditional transformer operation and maintenance rely on regular inspections, which easily miss hidden faults (such as local overheating of windings, insulation aging). Pufeike Electric's intelligent transformers integrate a "multi-parameter condition monitoring system". Through built-in temperature sensors (monitoring winding/core temperature), partial discharge sensors (detecting insulation defects), and dissolved gas in oil sensors (analyzing fault types), real-time data is collected and uploaded to the cloud platform. The system can predict fault trends through AI algorithms. For example, when the acetylene content in oil exceeds 5μL/L, it automatically sends maintenance reminders, reducing the incidence of sudden faults by 70% and extending the service life of the transformer to more than 25 years.
