Scheme Design of Convolutional Neural Network for Fault Identification of Medium Voltage Power Equipment
Convolutional Neural Network(CNN)is a type of deep learning algorithm commonly used for image recognition and pro-cessing tasks.It can extract features of images through multiple convolutional and pooling layers to identify issues.By applying this functional-ity to the fault identification of power equipment,using convolutional layers to extract features of power equipment images,such as equip-ment structure and damaged parts,can improve the accuracy and efficiency of fault identification.In view of this,this paper explores the scheme design of convolutional neural network for fault identification of medium voltage power equipment.It first analyzes the image recog-nition principles of CNN,then investigates the common fault types and manifestations of medium voltage power equipment,and finally proposes design measures to provide good academic references for related identification mechanisms.
Convolutional neural networkMedium voltage power equipmentFault identification