Abstract
The hydrophobicity of composite insulators is a great significance to the safe and stable operation of transmission lines. In this paper, a recognition method of the hydrophobicity class (HC) of composite insulators based on features optimization was proposed. Through the spray method, many hydrophobic images of water droplets on the insulator surface at various hydrophobicity classes (HCs) were taken. After processing of the hydrophobic images, seven features were extracted: the number n, mean eccentricity Eav and coverage rate k1 of the water droplets, and the coverage rate k2, perimeter Lmax, shape factor fc, and eccentricity Emax of the maximum water droplet. Then, the maximum value Δxmax, the minimum value Δxmin, and the average value Δxav of the change rate of each feature value between adjacent HCs, and the volatility Δs of each feature value, were used as the evaluation indexes for features optimization. After this features optimization, the five features that are most closely related to the HC were obtained. Lastly, a recognition model of the HC with the five features as input and the seven HCs as output was established. When compared with the spray method and the contact angle method, the correct rate of the proposed recognition method was 98.1% and 95.2%, respectively. The influence of subjective factors on the spray method was effectively overcome.
Highlights
Composite insulators have been widely used because of their good hydrophobicity and unique hydrophobic migration characteristics [1]
The change rate of the feature between adjacent hydrophobicity class (HC) is demonstrated by formula (5). ∆xmax, ∆xmin, ∆xav, and ∆s are as shown in formulas (6)–(9)
We selected 30 images of each HC that were closest to the standard images given by STRI, from the hydrophobic images obtained by the spray method
Summary
Composite insulators have been widely used because of their good hydrophobicity and unique hydrophobic migration characteristics [1]. After the processing of the hydrophobic images, the most widely used seven geometric parameters are extracted including: the number n, mean eccentricity Eav and coverage rate k1 of the water droplets, and the coverage rate k2 , perimeter Lmax , shape factor f c , and eccentricity Emax of the maximum water droplet. These features are used to evaluate the HC. The results of the recognition model are compared with those that were obtained by the spray method and contact angle method
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