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This paper presents electrical equipment fault diagnosis system based on the decomposition products of SF6, and makes an introduction of a method that electrical equipment fault diagnosis system of hardware and software implementation. The hardware uses ATmega128 series single-chip platform, and the software uses advanced wavelet neural network fault diagnosis method. To prove the superiority of this algorithm, we make the simulation and comparison with others. A good synergy of hardware and software is used in SF6 electrical equipment fault diagnosis, and analysis of SF6 gas content of decomposition products to judge if the electrical equipment fault happens and to make a fault prediction. In this paper we will introduce the hardware design method and the detailed design of the software just because of strong electromagnetic interference environment and it is very important to the system design, finally by giving the experimental data to prove system reliability and practicality.
Date of Conference: 9-11 Dec. 2009