A Novel Detection Algorithm for the Icing Status of Transmission Lines

Abstract

As more and more transmission lines need to pass through areas with heavy icing, the problem of transmission line faults caused by ice and snow disasters frequently occurs. Existing ice coverage monitoring methods have defects such as the use of a single monitoring type, low accuracy of monitoring results, and an inability to obtain ice coverage data over time. Therefore, this study proposes a new algorithm for detecting the icing status of transmission lines. The algorithm uses two-dimensional multifractal detrended fluctuation analysis (2D MF-DFA) to determine the optimal sliding-window size and wave function and accurately segment and extract local feature areas. Based on the local Hurst exponent (Lh(z)) and the power-law relationship between the fluctuation function and the scale at multiple continuous scales, the ice-covered area of a transmission conductor was accurately detected. By analyzing and calculating the key target pixels, the icing thickness was accurately measured, achieving accurate detection of the icing status of the transmission lines. The experimental results show that this method can accurately detect ice-covered areas and the icing thickness of transmission lines under various working conditions, providing a strong guarantee for the safe and reliable operation of transmission lines under severe weather conditions.

Keywords

• 2D MF-DFA
• pixel decomposition
• transmission line
• ice status detection