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A recognition method of the thunder signal based on the end-point detection method with a noise-estimation algorithm for highly non-stationary environments is proposed. To determine the parameter of the algorithm and verify the effectiveness and accuracy of the method we analyze the acoustic signals obtained from two microphone arrays installed at the top platform on a seven-floor building in Wuhan. In this paper, we have chosen two acoustic signals to test the endpoint detection method. It is revealed from the recognition result that the method can find out the accurate beginning and ending time of the thunder signal from the acoustic signals.

A single-station-based three-dimensional (3D) acoustic lighting mapping system comprising a microphone array has been developed and used for lightning observations, in which a new broadband direction-of-arrival (DOA) estimation techniques namely incoherent signal-subspace method are proposed for thunder signals in the far-field. Two cloud-to-ground (CG) flashes with highly branch channels recorded by the system are analyzed and presented in this paper. The acoustic mapping results can not only locate on the main channel produced by the return stroke process but also depict the branch channels. Moreover, the located thunder sources by the mapping system and the photography of the high speed camera agree well with each other demonstrating the effectiveness and correctness of the estimation techniques and the mapping system.

In order to obtain optical path photographs of lightning strike with a higher resolution, providing the necessary technical means for the accurate identification of 500kV transmission line lightning fault in mountain area, we developed an embedded, low-power remote online Lightning Optical Path Monitoring System based on 3G communication technology. Then, a case containing a lightning which struck the transmission line was analyzed in this paper combined with the results of the Lightning Optical Path Monitoring System, State Grid Lightning Location System and the Transmission Line Distributed Fault Diagnosis System.