Impact of Hydrophobicity on Wetting Characteristics of Composite Insulators

Abstract

To perfect the wetting mechanism of hydrophobic insulators, it is urgent to explore the impact of hydrophobicity on wetting characteristics of the pollution layer of composite insulators. In this paper, the wetting test of the hydrophobic pollution layer was carried out in artificial hot fog. The local surface conductivity of the pollution layer with different hydrophobicity were measured. The test results show that the local surface conductivities of different hydrophobic pollution layers are obviously different at the same wetting time. For researching the regularity of wetting process in greater detail, three characteristic quantities were proposed to represent the wetting characteristics. They are the duration of local surface conductivity close to zero (DLSCCZ), the saturated wetting time (SWT) and the maximum value of local surface conductivity (MVLSC). With the enhancement of hydrophobicity of the pollution layer, DLSCCZ and SWT increase, while MVLSC and the growth velocity of local surface conductivity both decrease.

Robust superamphiphobic coatings with gradient and hierarchical architecture and excellent anti-flashover performances

“…For more prominent comparison, the sample with WCA of 141 o displayed much lower leakage current (blue curve in Figure 4a) than that of sample with WCA of 121 o (green curve in Figure 4a). The enhancement of the hydrophobicity would reduce the effective solubility of soluble salt and the maximum value of local surface conductivity, and thus improves the flashover strength [52].…”

A Study of Multilayer Perceptron Networks Applied to Classification of Ceramic Insulators Using Ultrasound

“…Over time, surface contamination can generate discharges that can cause tracking and generate perforations that make it necessary to replace the component [40]. Various types of contamination can increase the conductivity in the vicinity of the insulator, making it more vulnerable to discharges [41][42][43].…”

Location prediction model of zero value insulator based on PNN

“…Insulators crack in the long-term operation because of manufacturing, transportation, aging and deterioration. Due to the overvoltage, the electrical performance of the deteriorated insulators seriously declines and deteriorates into zero insulators [4,5]. The zero insulator, which assumes zero voltage, leads to a more non-uniform voltage distribution of the insulator string [6][7][8].…”