Reaserch On The Characteristics Analysis Of The Lightning Signals And Its Sorting

In the process when mankind going towards the civilization, the lightning almostalways play a role that brought the disasters and harm to mankind. With the developmentof modern scientific technology, it will bring more and more disasters and harm to themankind. Therefore, the monitoring and early warning of the lightning will becomeincreasingly important. The researchers from the worldwide investigate the lightningfrom different aspects, such as the mechanism of the occurrence of lightning, thephysical characteristics of lightning, lightning location, lightning protection and so on.Funded by the “Elevnth Five” national key technology program “lightning disastermonitoring and early warning key technology research and system development”, thetime-frequency distribution of lightning signal characteristics and multi-scalecharacteristics were studied. In the case of when multi-source signals occurring at thesame time, the sorting of TOA and DOA were studied. It is very significant for both thephysical characteristics of the lightning and lightning location accuracy.Through the theoretical analysis, experiment data analysis and experiment datasimulation test, some results from the following aspects are obtained, and they are asfollows:(1) The the signal time-frequency analysis principle and independent componentanalysis principle were given, so as the the basic principle of Fourier transform andwavelet transform. Based on that, another non-stationary nonlinear signal method,empirical mode decomposition, was introduced. Still we pointed out that the advantagesof the empirical mode decomposition method in dealing with non-stationary nonlinearsignal.(2) The multi-scale feature of the lightning signal based on wavelet transform wasinvestigated. The Fourier frequency spectrum and wavelet spectra of the lightning returnstroke signals were compared, and the results show that the wavelet spectra can show themulti-scale features of the lightning discharge process. Additionally, choosing a differentwavelet base will lead to the different spectra. It is recommended to use the wavelet basiswhich is similar to the lightning waveforms.(3) Multi-scale features of the lightning signal based on EEMD were first study.Pointed out that the components of the wavelet decomposition do not have physicalmeaning. After analyzed using EEMD, the components have the physical meaning. Thetrend item corresponds to the lightning electrostatic field. Combined with fractal analysis, the other component corresponds to the Lightning different scale characteristics of thedischarge channel. In addition, the reason that the mode mixing occurring when useEMD to analyze to lightning return stroke was investigated, and EEMD can eliminatemode mixing phenomenon. Last, it is concluded that EEMD-based Hilbert-Huangspectrum can give better display of the lightning multi-scale characteristics.(4) A method of DOA crossing sorting method was introduced to the lightning DOAcrossing sorting. The principle of spatial spectrum estimation was introduced. Thesimulation using experiment data was conducted with this method, and the results wereobtained that the method can eliminated the DOA false point. In addition, the relationshipbetween the DOA deviation and the correlation of the separated waveforms wasinvestigated, and the results were obtained that the correlation of the waveforms was notsensitive to the DOA deviation. Further, it was concluded that the DOA estimated withMUSIC algorithm is robust to noise. Still the effects of the noise levels on the separatedwaveforms were investigated and it is concluded that this crossing sorting method canalso be used to weaken signal crossing sorting.(5) A method of lightning signal sorting based on ICA was proposed. The problemthat using TOA to locate the lightning when several source signals occurring at the sametime was discussed. Taking LMA system as an example, the reason that it is unable tolocate the several branch channels was given. Based on that, the several source signalscan be separated by using FastICA algorithm, and the problem can be solved when usingthe TOA of the separated waveforms. Then the non-Gaussian characteristics of the VHFlightning signals was discussed, and the results can be obtained that the VHF lightningsignals were non-Gaussian in the case of that when the samples were small, whichsatisfies the ICA solving model. At the same time, the TOA of waveforms between themixed and the separated was compared. In addition, a FastICA sorting method of thelightning signal based on wavelet de-nosing was also proposed. The wavelet de-nosing ofthe separated waveforms was investigated, and it is concluded that the de-noisedseparated signals can have a better correlation to the source signals than the withoutde-noised.