A Novel Pix2Pix Enabled Traveling Wave-Based Fault Location Method

Sensors

Yubo Wang¹  Haojie Zhang¹  Jinxian Zhang¹  Yilin Wang¹  Qingwu Gong¹ 

[1] School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, Hubei, China;

关键词: deep learning;    Phasor Measurement Unit (PMU);    Pix2Pix;    YOLO v3;    wavelet transform;    fault location;   

DOI  :  10.3390/s21051633

来源: DOAJ

【 摘 要 】

This paper proposes a new Image-to-Image Translation (Pix2Pix) enabled deep learning method for traveling wave-based fault location. Unlike the previous methods that require a high sampling frequency of the PMU, the proposed method can translate the scale 1 detail component image provided by the low frequency PMU data to higher frequency ones via the Pix2Pix. This allows us to significantly improve the fault location accuracy. Test results via the YOLO v3 object recognition algorithm show that the images generated by pix2pix can be accurately identified. This enables to improve the estimation accuracy of the arrival time of the traveling wave head, leading to better fault location outcomes.

【 授权许可】

Unknown