ULTRASONIC DETECTION METHOD AND SYSTEM FOR PARTIAL DISCHARGE OF POWER DISTRIBUTION NETWORK

• Main Authors: ZHANG Fagang, ZHANG Guangdong, LIU Kang, HUANG Zhiyong, BAI Wenyuan, XUE Ling, GUI Feifei, XIONG Peng, HE Hongtai, QIN Yuanxun, ZHANG Yugang, ZHANG Taoyun, HE Weifeng, WANG Jin
• Format: Patent
• Language: English
• Published: 03.01.2022
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS

The present disclosure relates to an ultrasonic detection method and system for partial discharge of a power distribution network based on deep learning. The method includes: training a neural network model; converting an ultrasonic signal of a partial discharge defect of to-be-detected power distribution network equipment into Mel Frequency Cepstral data; inputting the Mel Frequency Cepstral data into a periodic neural network layer for learning to obtain a first feature; inputting an image of the partial discharge defect of the to-be-detected power distribution network equipment into a convolution neural network layer for learning to obtain a second feature; linearly splicing the first feature and the second feature to obtain a third feature; and inputting the third feature into a multilayer fully-connected layer to obtain a detection result of the to-be-detected power distribution network equipment. Compared with the existing manual detection method, the detection method and system provided by the present disclosure are more efficient and accurate.