# Newly Designed Identification Scheme for Monitoring Ice Thickness on Power Transmission Lines
###### Abstract  
Overhead power transmission line icing (PTLI) disasters are one of the most severe dangers to power grid safety. Automatic iced transmission line identification is critical in various fields. However, existing methods primarily focus on the linear characteristics of transmission lines, employing a two-step process involving edge and line detection for PTLI identification. Nonetheless, these traditional methods are often complicated when confronted with challenges such as background noise or variations in illumination, leading to incomplete identification of the target area, missed target regions, or misclassification of background pixels as foreground. This paper proposes a new iced transmission line identification scheme to overcome this limitation. In the initial stage, we integrate the image restoration method with image filter enhancement to restore the image's color information. This combined approach effectively retains valuable information and preserves the original image quality, thereby mitigating the noise presented during the image acquisition. Subsequently, in the second stage, we introduce an enhanced multi-threshold algorithm to separate background and target pixels. After image segmentation, we enhance the image and obtain the region of interest (ROI) through connected component labeling modification and mathematical morphology operations, eliminating background regions. Our proposed scheme achieves an accuracy value of 97.72%, a precision value of 96.24%, a recall value of 86.22%, and a specificity value of 99.48% based on the average value of test images. Through object segmentation and location, the proposed method can avoid background interference, effectively solve the problem of transmission line icing identification, and achieve 90% measurement accuracy compared to manual measurement on the collected PTLI dataset. p 2023 13 9862 2023  
disaster happened on the electrical grid in Texas, USA, leaving millions of people without power in the cold weather [10]. Therefore, an effective monitoring and predictive alarm system for power transmission line icing (PTLI) is important for ensuring the safety of the power grid. Traditional PTLI monitoring techniques, such as artificial inspection [11], the installation of pressure sensors [12], and the development of meteorological models [13], among others, have been extensively employed to achieve this objective. In recent years, PTLI monitoring based on computer vision methods has emerged as a new research direction [14] that makes ice monitoring easier and more practical and cost-effective. Several 2D algorithms, such as adaptive threshold segmentation [15], edge extraction [16], and wavelet analysis [17], are presented to obtain accurate ice edge information. The ice thickness can be calculated by comparing the pixel dimensions between edges in normal and icy conditions. However, these algorithms perform poorly in complex contexts or situations with limited exposure. Furthermore, the 2D estimation method cannot obtain comprehensive information about ice thickness. Methods based on 3D measurement have been introduced to better monitor PTLI and obtain more accurate information to address this issue. The PTLI monitoring based on 3D monitoring mainly includes camera calibration, transmission line identification, key point matching, and ice thickness calculation. The identification of iced transmission lines is an important part of PTLI monitoring. At this stage, the goal is to identify the top and bottom of the iced transmission line because it will directly affect the ice thickness measurement. Generally, the iced transmission line identification stage consists of two parts, namely edge detection and line detection. Edge detection accuracy is related to low contrast, cluttered backgrounds, occlusion, and the image quality obtained by the camera [18]. Noise in PTLI scene images is typically introduced during image acquisition or transmission.