Abstract
In order to achieve the noncontact detection of the contamination grade of insulators and to provide guidance for preventing the contamination flashover of insulators based on the pollution state, we propose a contamination grade recognition method based on the deep learning of ultraviolet discharge images using a sparse autoencoder (SAE) and a deep belief network (DBN). Under different humidity conditions, we filmed and preprocessed the ultraviolet discharge images of insulators at different contamination grades and we obtained the ultraviolet spot area sequence as original data for contamination grade recognition. A double-layer sparse autoencoder was used to extract sparse features that could characterize different contamination grades from the ultraviolet spot area sequence. Using the extracted features, a DBN composed of three layers of restricted Boltzmann machine was trained to provide contamination grade recognition. To verify the effectiveness of the method proposed in this paper, high-voltage experiments were performed on contaminated insulators at relative humidity levels of 80%, 85%, and 90%, and ultraviolet images were recorded. The proposed SAE–DBN method was used to identify the ultraviolet images of the insulators with different contamination grades. The recognition accuracy rates at the three humidity levels were 91.25%, 93.125%, and 92.5%. The experimental results showed that this method could accurately recognize the contamination grade of the insulator and provide guidance for the prevention of contamination flashover based on the pollution severity.
Highlights
The experimental results showed that this method could accurately recognize the contamination grade of the insulator and provide guidance for the prevention of contamination flashover based on the pollution severity
With the expansion of power grids and the intensification of environmental pollution, insulator flashover accidents pose a serious threat to the safe operation of a power system [1,2,3,4,5]
In order to obtain ultraviolet images of insulators with different levels of contamination while they were in service, we carried out high-voltage tests on manually smeared insulators
Summary
With the expansion of power grids and the intensification of environmental pollution, insulator flashover accidents pose a serious threat to the safe operation of a power system [1,2,3,4,5]. Due to the presence of various contaminants in natural environments, the accumulation of surface contaminants cannot be avoided. This has prevented contamination flashover accidents from being fundamentally eliminated. Damages due to insulator flashover have exceeded the damages due to lightning, and this type of damage has become the greatest threat to the safe and reliable operation of power systems. It is of important to take effective measures to prevent contamination flashover accidents and to ensure the safety of a power grid [6,7,8,9,10]
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