Abstract
The electromagnetic radiation (EMR) signal collected by monitoring system during coal or rock dynamic disaster may be interferred easily by electromagnetic noises in mines. The noises have a direct influence on the recognition and analysis of the EMR signal features during the disaster. With the aim of removing these noises, an ensemble empirical mode decomposition (EEMD) adaptive morphological filter was proposed. From the result of the simulation and the experiment, it is shown that the method can restrain the random noise and white Gaussian noise mixed with EMR signal effectively. The filter is highly useful for improving the robustness of the coal or rock dynamic disaster monitoring system.
Similar content being viewed by others
References
Dou L M, He X Q, Wang E Y, 2004. Electromagnetic emission technique of monitoring rock burst and its application. Journal of China Coal Society, 29(4): 396–399.
Esposito A, D’Andria P, 2003. An adaptive learning algorithm for ECG noise and baseline drift removal. //Neural nets, 14th Italian workshop on neural nets (Apolloni, Bruno, Marinaro, Maria, Tagliaferri, Roberto). Berlin: Springer. 139–147.
Frid V I, 1997. Electromagnetic radiation method for rock and gas outburst forecast. Journal of Applied Geophysics, 38(1–2): 97–104.
Gao Z H, He F L, Meng J Q, Wang B, 2011. Determine the warning value of drilling cuttings weight coal and rock dynamic disaster through electromagnetic radiation. Journal of China Coal Society, 36(4): 615–618.
Hao R J, Lu W X, Chu F L, 2008. Multiscale morphological analysis on fault signals of rolling element bearing. Chinese Journal of Mechanical Engineering, 44(11): 160–165.
He Y G, Zhang Y, Zhou H, 2009. Detection of dynamic disturbance voltage using hybrid filter algorithm of morphological filtering and “specific harmonic elimination”. High Voltage Engineering, 35(12): 3093–3098.
Hu A J, 2008. Research on the application of Hilbert-Huang transform in vibration signal analysis of rotating machinery. Doctor’s Thesis, North China Electric Power University.
Huang N E, Shen Z, Long S R, Wu M C, Shih H H, Zheng Q N, Yen N C, Tung C C, Liu H H, 1998. The empirical mode decomposition and the Hilbert spectrum for nonlinear non-stationary time series analysis. Proceeding of Royal Society London A, 454: 903–995.
Jiang Z, Deng A D, Cai B H, 2011. Application of an adaptive generalized morphological filter based on the gradient method in rubbing acoustic emission signal denoise. Chinese Journal of Construction Machinery, 26(8): 87–92.
Lei T F, Yang Y, 2011. Double operator morphological filters. Acta Automatica Sinica, 37(4): 449–463.
Li G F, 2009. Mode domain signal processing technique and its applicationin under water acoustic system. Doctor’s Thesis, Harbin Engineering University.
Li H, Lin Q Z, Wang Q J, Liu Q J, Wu Y Z, 2010. Research on spectrum denoising methods based on the combination of wavelet package transformation and mathematical morphology. Spectroscopy and Spectral Analysis, 30(3): 644–648.
Maragos P, Schafer R, 1987a. Morphological filters-Part I: Their set-theoretic analysis and relations to linear shift-invariant filters. Acoustics, Speech and Signal Processing, 35(8): 1153–1169.
Maragos P, Schafer R, 1987b. Morphological filters-Part II: Their relations to median, order-statistic, and stack filters. Acoustics, Speech and Signal Processing, 35(8): 1170–1184.
Nie B S, He X Q, He J, Zhai S R, 2006, Research on removing noise of electromagnetic emission signals with wavelet transform. Journal of Taiyuan University of Technology, 37(5): 557–560.
Qu L S, Zhang X N, Shen Y D, 2009. Theories and methods for machinery fault diagnosis. Xi’an: Xi’an Jiaotong University Press.
Sa Z Y, Wang E Y, 2007. Short-time fractal fuzzy filtering of electromagnetic emission signal during the fracture of coal or rock. Chinese Journal of Radio Science, 22(2): 191–196.
Shen L, 2010. Study on application of mornhologv in machinery fault diagnosis. Doctor’s Thesis, Zhejiang University.
Sun J P, 2011. Research on characteristics and key technology in coal mine internet of things. Journal of China Coal Society, 36(1): 167–171.
Sun J P, Ren J B, Feng D W Zheng Z W, 2010. The measurement on the electromagnetic radiation property of electrical equipment at transformer station in the underground coalmine. Journal of China Coal Society, 35(5): 861–864.
Sun J P, Wang F Z, 2009. Analysis of affection of electromagnetic interference on communication and monitoring and control system in coal mine underground. Industry and Mine Automation, (2): 23–27.
Wang E Y, He X Q, Nie B S, Liu Z T, 2000. Principle of predicting coal and gas outburstusing electromagnetic emission. Journal of China University of Mining & Technology, 29(3): 225–229.
Wang W, Zhao G J, Li Q, 2007. Study of novel adaptive denoising approach and its application. Computer Engineering and Applications, 43(26): 184–186.
Zhang J C, Wu X J, 2007. Research on applications of morphological filtering in real-time signal processing. Chinese Journal of Sensors and Actuators, 20(4): 828–831.
Zhang Q M, Liu H J, 2006. New power system sampled data processing method based on morphology theory. Electric Power Automation Equipment, 26(10): 45–49.
Zhang W B, Zhou X J, Li J S, Shen L, Lin Y, Yang X Y, 2010. Purification of rotor center’s orbit based on generalized morphological filter. Journal of Zhejiang University (Engineering Science Edition), 44(5): 893–896.
Zhao C H, 1998. Research on digital morphological filter theory and its algorithms. Doctor’s Thesis, Harbin Institute of Technology.
Zhao J, He Z Y, Qian Q Q, 2009. Detection of power quality disturbances utilizing generalized morphological filter and difference-entropy. Proceedings of the CSEE, 29(7): 121–127.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chen, Sh., Wang, Ey. Removal of noises from electromagnetic radiation of coal or rock with EEMD-adaptive morphological filter. J Coal Sci Eng China 18, 330–336 (2012). https://doi.org/10.1007/s12404-012-0319-1
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12404-012-0319-1