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Accurate detection of SF 6 decomposition characteristics components in SF 6 gas insulated equipment is one of the important technical method to realize fault diagnosis and condition monitoring of SF 6 gas insulated equipment. In this paper, based on the density functional theory, the infrared spectrum of SOF2 and SO 2 F 2 , that is two key SF 6 sulfur-containing decomposition characteristics components, were simulated and analyzed. The research found that the infrared spectrum of SOF2 molecule included four main absorption peaks at 485.106 cm−1, 678.479 cm−1, 748.357 cm−1, and 1295.070 cm−1, respectively. And the infrared spectrum of SO 2 F 2 molecule included five main absorption peaks at 501.852 cm−1, 779.442 cm−1, 814.284 cm−1, 1221.181 cm−1, and 1460.246 cm−1, respectively. This study lay a theoretical foundation for fault diagnosis and condition monitoring of SF 6 insulated equipment by mid infrared, and ensure the safety of power equipment.

SF 6 partial discharge decomposition characteristic component analysis method is one of the most efficient and convenient technology to diagnose latent defects in SF 6 gas insulated equipment. Compared with the traditional SF 6 characteristic decomposition gas detection method, the spectral method has many outstanding advantages, such as non-destructive detection of gas, high detection speed, high precision, and no need for mixed gas separation. However, the Raman characteristics of SF 6 partial discharge decomposition characteristic gas have not been fully clarified. Therefore, based on the density functional theory, the Raman spectra of SOF2 and SO 2 F 2 are calculated, which lays a solid theoretical foundation for SF 6 gas insulated equipment insulation fault diagnosis and condition monitoring method based on spectral technology.

In sensor networks concerning about data, data management and representation have become a crucial issue. In this paper, sensor networks deployed to monitor wetland are built with the visualization of their data and topology. The environmental data, such as temperature, humidity, both in atmosphere and soil, illumination intensity and PH around the wetland are sent by the wireless sensor networks to a base station which is connected to the visualization platform on a PC. The approach presented in this paper utilizes serial communication, database management, data and topology visualization to visualize the data gathered by the wireless sensor networks. The data visualization platform can get and display real time information of networks and makes the system convenient to users.