Optical Diagnostic Characterization of the Local Arc on Contaminated Insulation Surface at Low Pressure

Flashover of contaminated insulators is a major problem for power systems at high altitude. Laboratory experiments have shown that the optical diagnostic method can provide extensive information on the physical process of contamination flashover. In this paper, a study of the local arc on a wet polluted surface under low pressure by using the optical diagnostic method is presented. The thickness of the continuous spectrum, spectral line intensity and the spectral composition varies significantly in different stages of the local arc development. Thermodynamic parameters of the local arc (including electron temperature, electron density and conductivity) are obtained by analyzing the spectra. Both the electron temperature and the conductivity increase with the increase in leakage current and air pressure. Although the electron density does not change significantly with an increase in leakage current, it increases significantly with an increase in air pressure. The findings of this work could be used as supplementary information for the investigation of local arc parameters, thus providing a reliable reference for the calculation of contamination flashover at high altitude.

Research on the Non-Contact Pollution Monitoring Method of Composite Insulator Based on Space Electric Field

Through spatial electric field monitoring, it is expected to realize insulator pollution condition monitoring and contamination flashover warning in a non-contact way. Therefore, in this paper, the spatial electric field distribution characteristics of 110 kV composite insulators are simulated, where the effects of different surface states and their discharge levels on the spatial electric field of insulators are analyzed. On this basis, a non-contact monitoring method for composite insulator pollution based on the spatial electric field is proposed. The results show that there are significant differences in the spatial electric field of the composite insulator among three conditions, namely cleaning, pollution layer wetting, and dry band arcing. Increases of pollution layer wetting and dry band arcing would lead to an increase of the amplitude of the spatial electric field of the insulator. Verification experiments well indicated that it is feasible to identify the degree of pollution layer wetting as well as dry band arcing of the insulator string by fixed-point monitoring, the spatial electric field signal at the cross-strand of d = 0.5 m and directly opposite the last three positions. Research results can provide references for the online monitoring of overhead line polluted insulators and its flashover warning.

Intelligent Recognition of Insulator Contamination Grade Based on the Deep Learning of Ultraviolet Discharge Image Information

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.

Collision Mechanism and Deposition Characteristics of Particles on the Catenary Insulator Surface

To solve the problem of contamination flashover of a catenary insulator in an electrified railway, the collision mechanism and deposition characteristics of contamination particles on the insulator surface should be studied to ensure the safe operation of traction power supply systems. This research used horizontal and oblique cantilever insulators as objects, and established the collision model between particles and insulator surface under different arrangements. The deposition conditions of particles on the insulator surface were obtained, and the simulation model of insulator contamination accumulation was established by using the Euler two-phase flow. The difference of contamination deposition characteristics between horizontal and oblique cantilever insulators was analyzed with the volume fraction of contamination particles as the characterization parameter. By comparing the cantilever insulator with the positive feeder insulator, this study analyzed the influence of shed structure on the contamination deposition characteristics. Results show that the installation method of an insulator has an impact on the contamination deposition on the insulator surface. When particle size and wind velocity are fixed, the degree of contamination accumulation on the surface of the oblique cantilever insulator is constantly higher than that of the horizontal cantilever insulator. The insulator shed structure also has a certain effect on the contamination deposition on the insulator surface. For the cantilever insulator, the degree of contamination accumulation of the windward side is higher than that of the leeward side. However, for the positive feeder insulator, the degree of contamination accumulation of the windward side is consistently less than that of the leeward side. Measures to deal with contamination flashover of catenary insulator are proposed.

The Influence of Main Components in PM2.5 on Composite Insulator Contamination Flashover Characteristics

This paper studies about the influence of main components in PM2.5 on insulator pollution flashover characteristics. A paper written by Institute of Atmospheric Physics Chinese Academy of Sciences presents the main components in Beijing’s PM2.5. Basing on that, an artificial pollution test in our lab. The test result shows that components in PM2.5 have no significant effect on insulator pollution flashover characteristics. But, in haze weather, insulators are easier to be polluted. As a result, the probability of insulator flashover become higher.