Distribution Transformer Secondary Bushing Temperature Detection Device using Feed Forward Neural Network

The distribution transformer turns high voltage into low voltage. On the secondary transformator, the voltage and current are sufficiently large that excessive heat dissipation occurs due to the appearance of electric retention at the point of secondary connection of the transformator to the output cable. This causes current imbalance and overheating, resulting in lost contact that disrupts power supply and voltage drop. Unfortunately, field inspections are carried out every six months and lost contact can occur at any time. So we suggested developing a real-time overheat detection tool on secondary bushing using a temperature classification method based on the Feed Forward Neural Network (FFNN) equipped with the Internet of Things. With FFNN, the system successfully classifies the temperature with a value of 0 for a temperature of 30 ̊ C-50 ̊ C, a value 0 for the temperature of 51°C-90 ̊ C that requires repair, and a value 1 for a temperatur above 90 ̊ C with a relay disconnect, then the system sends a real-time lost contact notification. Thus this tool increases the effectiveness of inspection and can be applied to reduce inspection actions directly.