Cable Temperature Alarm Threshold Setting Method Based on Convolutional Neural Network. Issue 1 (1st January 2022)

• Record Type: Journal Article
• Authors: Wang, Lei; Niu, Lin; He, Xingwang; Guan, Meng; Li, Hongbo; Ma, Zhiguang
• Is Part Of: Journal of physics. Volume 2160:Issue 1(2022)
• Publication Date: 2022-01-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2160/1/012076
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Power cable is used more and more in the power network, and its significance to the safety and stability of the power network is increasingly prominent. Especially in the urban power grid, the high voltage cable is related to the normal production and life of the city. Because of the particularity of the laying environment, it is very difficult to find and eliminate the fault points once the cable faults occur, which seriously affects the reliability of the power grid. Currently, 25% of cable faults are caused by elevated cable temperature, so it is important to set the cable temperature alarm threshold accurately. In this paper, a method of setting temperature alarm threshold using convolutional neural network is proposed. Experiments show that this method is 60% more accurate than other methods.