Power fingerprint identification based on the improved V-I trajectory with color encoding and transferred CBAM-ResNet.

ABSTRACT: In power fingerprint identification, feature information is insufficient when using a single feature to identify equipment, and small load data of specific customers, difficult to meet the refined equipment classification needs. A power fingerprint identification based on the improved voltage-current(V-I) trajectory with color encoding and transferred CBAM-ResNet34 is proposed. First, the current, instantaneous power, and trajectory momentum information are added to the original V-I trajectory image using color coding to obtain a color V-I trajectory image. Then, the ResNet34 model was pre-trained using the ImageNet dataset and a new fully-connected layer meeting the device classification goal was used to replace the fully-connected layer of ResNet34. The Convolutional Block Attention Modu

SUBMITTER: Lin L 

PROVIDER: S-EPMC9910749 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature