Fractal characteristics research of lightning and its application to automatic recognition

Huo Yuan-Lian; Zhang Guang-Shu; Lü Shi-Hua; Yuan Ping

doi:10.7498/aps.62.059201

Abstract

By analyzing the fractal feature of 120 cloud-to-ground lightning signals and 77 intracloud lightning signals obtained by the fast antenna system in Qinghai area during the summer of 2009, the results show fractal dimension of cloud-to-ground lightning signal is obviously different from that of intracloud lightning signal. Then 5 characteristic values of fractal dimension are used to recognize the discharge types of lightning signal via support vector machine, and the recognition rate is higher than 95%. The construction of cloud-to-ground lightning time series signal fractal dimension trajectory map shows that the fractal dimension minimum value corresponds to the return stroke of the original time series signal, which can be used to quickly and accurately detect the return stroke of lightning signal, and the detection rate can reach 100%.The fractal dimension is a discriminatively physical property which can be used for intelligently analyzing and automatically processing the lightning signal.

Keywords:

Authors and contacts

1.
Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China;
2.
College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 41075002, 40775004), the Key Program of the National Natural Science Foundation of China (Grant No. 41030960), and the Special Scientific Research Fund of Meteorological Public Welfare Profession of China (Grant No. GYHY201006005-03).

References

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[17]	Murphy M J, Cummins K L, Alburt E P 2003 United States Patent, pub. No: US 2003/0151397 A1
[18]	Liu H Y, Dong W S, Wang T, Qiu S 2009 Meteorological Monthly 35 49 (in Chinese) [刘恒毅, 董万胜, 王涛, 邱实 2009 气象 35 49]
[19]	Li P, Zheng Y, Zhang Y J 2007 High Power Laser and Particle Beams 19 1512 (in Chinese) [李鹏, 郑毅, 张义军 2007 强激光与粒子束 19 1512]
[20]	Xiang Z, Liu M, Li P, Zheng Y, Fan J B 2011 Opto-Electronic Engineering 38 28 (in Chinese) [项震, 刘明, 李鹏, 郑毅, 范江兵 2011 光电工程 38 28]
[21]	Falconer K J 1990 Fractal Geometry: Mathematical Foundation and Application (New York: John Wiley and Sons) p86
[22]	Vapnik V N 1995 The nature of statistical learning (New York: Springer-Verlag) p235
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Cited By

[1]	Cao D J, Qie X S, Duan S, Xuan Y J, Wang D F 2012 Acta Phy. Sin. 61 069202 (in Chinese) [曹冬杰, 郄秀书, 段树 ,宣越建, 王东方 2012 61 069202]
[2]	Zhao X Y, Yuan P, Wang J, Shen X Z, Guo Y X, Qiao H Z 2009 Acta Phy. Sin. 58 3243 (in Chinese) [赵学燕, 袁萍, 王杰, 申晓志, 郭逸潇, 乔红贞 2009 58 3243]
[3]	Zhao Y, Qie X S, Kong X Z, Zhang G S, Zhang T, Yang J, Feng G L, Zhang Q L, Wang D F 2009 Acta Phy. Sin. 58 6616 (in Chinese) [赵阳, 郄秀书, 孔祥贞, 张广庶, 张彤, 杨静, 冯桂力, 张其林, 王东方 2009 58 6616]
[4]	Mandelbrot B B 1982 The Fractal Geometry of Nature (New York:Freeman) p28
[5]	Deng Y, Shi W K, Liu Q 2002 Acta Phys. Sin. 51 759 (in Chinese) [邓勇, 施文康, 刘棋 2002 51 759]
[6]	Tsonis A A, Elsner J B 1987 Beitr Phys. Atmos. 60 187
[7]	Vecchi G, Labate D, Canavero F 1994 Radio Sci. 29 694
[8]	Ren S P, Chi J P, Zhang H C, Liu L C 1999 Power System Technology 23 11 (in Chinese) [任顺平, 迟建平, 庄洪春, 刘来存 1999 电网技术 23 11]
[9]	Gou X Q, Zhang Y J, Dong W S 2006 Acta Phys.Sin. 55 957 (in Chinese) [苟学强, 张义军, 董万胜 2006 55 957]
[10]	Gou X Q, Zhang Y J, Dong W S, Qie X S 2007 Chinese J. Geophys. 50 101 (in Chinese) [苟学强, 张义军, 董万胜, 郄秀书 2007 地球 50 101]
[11]	Gou X Q, Chen M L, Zhang Y J, Dong W S, Qie X S 2008 Journal of Lanzhou University (Natural Sciences) 44 24 (in Chinese) [苟学强, 陈明理, 张义军, 董万胜, 郄秀书 2008 兰州大学学报(自然科学版) 44 24]
[12]	Krider E P, Noggle R C, Uman M A 1976 Appl. Metoer 15 301
[13]	Weidman C D, Krider E P 1979 J. Geophys. Res. 84 3159
[14]	Massey R S, Eack K B, Eberle M H, Shao X M,Smith D A 1999 the 11th international conference on atmospheric electricity Guntersville, AL (United States), Jun 7-11 1999 p684
[15]	Smith D A, Eack K B, Harlin J 2002 J. Geophys. Res. 13 4183
[16]	Shao X M, Mark Stanley, Amy Regan 2006 J. Atmos. Ocean. Tech. 23 1273
[17]	Murphy M J, Cummins K L, Alburt E P 2003 United States Patent, pub. No: US 2003/0151397 A1
[18]	Liu H Y, Dong W S, Wang T, Qiu S 2009 Meteorological Monthly 35 49 (in Chinese) [刘恒毅, 董万胜, 王涛, 邱实 2009 气象 35 49]
[19]	Li P, Zheng Y, Zhang Y J 2007 High Power Laser and Particle Beams 19 1512 (in Chinese) [李鹏, 郑毅, 张义军 2007 强激光与粒子束 19 1512]
[20]	Xiang Z, Liu M, Li P, Zheng Y, Fan J B 2011 Opto-Electronic Engineering 38 28 (in Chinese) [项震, 刘明, 李鹏, 郑毅, 范江兵 2011 光电工程 38 28]
[21]	Falconer K J 1990 Fractal Geometry: Mathematical Foundation and Application (New York: John Wiley and Sons) p86
[22]	Vapnik V N 1995 The nature of statistical learning (New York: Springer-Verlag) p235
[23]	Cristianini N, Taylor J An Introduction to Support Vector Machines and Other Kernel-based Learning Methods (New York:Cambridge University Press) p78

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Vol. 62, Issue 5 - 2013-03-05

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