Transmission Line Lightning Fault Detection Based on Fiber Optic Temperature Measurement Recursive Accumulative Average Denoising

Fiber optic temperature sensors are widely used for temperature monitoring of transmission lines due to their insulation, corrosion resistance, and resistance to electromagnetic interference. Therefore, this paper proposes a transmission line lightning fault detection method based on fiber optic temperature measurement recursive cumulative average denoising. Firstly, use fiber optic temperature sensors to obtain preliminary data for lightning fault detection in transmission lines. Then, in order to optimize the results of fiber optic temperature measurement and detection, a recursive cumulative average denoising method is used to process the collected data, reduce noise interference, and improve the signal-to-noise ratio of the signal. Standardize the collected sample frequency values within the range of $500-950 \mathrm{kHz}$, and based on the calculation results of the fault characteristic vector of the transient current traveling wave frequency window, divide the lightning fault frequency band information into three levels: A, B, and C. Among them, A level indicates that lightning activity is far away, B level indicates that lightning is more likely and close, and C level indicates that lightning is about to occur and very close, requiring immediate emergency measures. The experimental results show that the proposed method not only improves the accuracy of lightning fault detection in transmission lines, but also provides strong guarantees for the safe operation of transmission lines.