A Multi‐Dimensional Sensing Method for Icing Thickness, Icing Shape, and Sag of Transmission Lines Based on Triboelectric Nanogenerator

Abstract The icing of transmission lines, primarily caused by frost weather‐induced freezing disasters, poses a severe threat to the grids. Real‐time early warning for icing monitoring is of great significance in preventing power outages and ensuring a stable energy supply. This study proposes a multi‐dimensional sensing method for icing thickness, shape, and sag based on triboelectric nanogenerator (TENG). The pressure and sag sensing model of TSS‐TENG (Thickness‐shape‐sag TENG) is established, and a prototype of the multi‐dimensional sensing device for icing thickness, icing shape, and sag is developed. Experimental verification based on this method shows that within the range of 0–20 mm icing thickness, TSS‐TENG achieves high‐precision measurement with durability and stability, with the coefficient of determination R 2 of its linear regression model consistently maintained between 0.98 and 0.99. To achieve a high degree of consistency between experimental signals and theoretical predictions, a multi‐channel signal acquisition unit is designed, enabling TSS‐TENGs to effectively recognize icing shapes. To reduce the complexity of sag signal processing, a signal waveform transformation unit is designed to achieve efficient statistics of sag signals. This device integrates self‐powered energy, high‐precision icing recognition, and sag measurement, thereby providing robust technical support for the safe and stable operation of power grids.