Aiming at the problems of fault heating feature selection,extraction and fault type identification of substation equipment,a thermal fault identification method of current transformer based on hot spot position classification was proposed.Firstly,based on the detection of current transformer parts by using CNN neural network and YOLO fusion algorithm,a two dimensional coordinate reference benchmark was established.Then,the fault region was segmented by PCNN hierarchical clustering iteration method,and the hot spot equivalent center of the fault region was obtained by gray center method.Finally,parameters such as the distance and angle between the equivalent center of the hot spot and the origin of coordinates are selected and extracted,and these parameters are applied to identify the fault category attributes of the hot spot position,so as to realize the fault type identification of the CT.The results show that the accuracy of this method is as high as 92%,and it has good practicability and generalization.