DocumentCode :
2797436
Title :
Self-similarity analysis of Coal or Rock Electromagnetic Emission signal
Author :
Nannan, Lu ; Jiansheng, Qian ; Zhikai, Zhao ; Liqin, Zhang ; Jin, Lu
Author_Institution :
Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
fYear :
2009
fDate :
17-19 June 2009
Firstpage :
2895
Lastpage :
2899
Abstract :
Coal or rock electromagnetic emission is a new perspective of predicting rock burst, but most present researches have been investigated into physical properties. This paper analyzes coal or rock electromagnetic emission (coal or rock EME) with self-similarity by rescaled range method from fractal characteristic and validates the feasibility and applicability of prediction model based on chaos theory. According to EME signal from two sides of railway lane and transportation lane from Dongtan coal mine respectively, we compute hurst exponent and fractal dimension D, and verify hurst exponent by the standard of S. Our experiments in this domain show that the signal has significant statistical self-similarity. Consequently, we conclude that Coal or rock EME has a favorable fractal feature. Moreover, we can utilize non-linear method to make prediction further.
Keywords :
coal; computational electromagnetics; rocks; Dongtan coal mine; coal; nonlinear method; railway lane; rock electromagnetic emission signal; self-similarity analysis; transportation lane; Chaos; Computer science; Electromagnetic analysis; Electronic mail; Fractals; Mathematical model; Predictive models; Rail transportation; Signal analysis; Stress; Coal or Rock Electromagnetic Emission; Fractal; Hurst Exponent; R/S Method; Self-similarity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
Type :
conf
DOI :
10.1109/CCDC.2009.5192693
Filename :
5192693
Link To Document :
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