Algorithms for Object Detection in Substations
Bingying Jin Yadong Liu Qinlin Qian
Inspection of high-voltage power equipment is an effective way to ensure
power supply reliability. Object recognition, one of the key technologies in
automatic power equipment inspection, attracts attention of many researchers
and engineers. Although quite a few existing models have some their own
advantages, object relationship between equipment which is very important in
this task is scarcely considered. This paper combining object relationship
modeling and Transformer Model proposes a Relation Transformer Model. It has
four parts -- backbone, encoder, decoder and prediction heads. With this
structure, the proposed method shows in experiments a much better performance
than other three commonly used models in object recognition in substation,
largely promoting the development of automatic power equipment inspection.