A Real-Time Microseismic Monitoring System Based on Virtual Instruments

Abstract:

Many geologic hazards, such as rock burst coal and gas outburst, have an inevitable connection with microseismic phenomena in rock mass. In order to provide accurate evidence of underground safety monitoring, inspecting microseismic signal is a good way to make sure the range and the level of underground rock breaking. Previous microseismic system using DSP or singlechip can’t obtain the desired data collection, neither for the achievement of advanced algorithm. The real-time microseismic monitoring system realizes the acquisition of multiple microseismic signals and uses wavelet transform algorithm, which gives full scope to the advantages of virtual instruments. The monitoring result was very similar to actual rock burst and the error of orientation results was minor to prescriptive upper limit, which means this new system completes the monitoring of real-time microseismic emission effectively.

• Periodical: Applied Mechanics and Materials (Volumes 246-247)
• Pages: 199-203
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.246-247.199
• Online since: December 2012
• Authors: Jing Lu Cai, Wei Yu, Feng Ping An
• Keywords: Data Acquisition, Microseismic Signal, Orientation, Real-Time Monitoring, Virtual Instrument (VI)

References

[1] N.E. Huang, Z. Shen, S.R. Long, M.L. Wu, H.H. Shih, Q. Zheng, N.C. Yen, C.C. Tung, H.H. Liu, The empirical mode decomposition and Hilbert spectrum for nonlinear and non-stationary time series analysis, Proceedings of the Royal Society of London A 454(1971).

DOI: 10.1098/rspa.1998.0193

[2] G. Rilling, P. Flandrin, P. Goncalves, On empirical mode decomposition and its algorithms, in: IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing NSIP-03, Grado, Italy, (2003).

[3] Y.S. Lee, S. Tsakirtzis, A.F. Vakakis, L.A. Bergman, D.M. McFarlan, Physics-based foundation for empirical mode decomposition, AIAA Journal 47(12) (2009).

DOI: 10.2514/1.43207

[4] J.N. Yang, Y. Lei, S. Pan, N.H. Huang, System identification of linear structures based on Hilbert-Huang spectral analysis, part 1: normal modes, Earthquake Engineering and Structural Dynamics 32 (9) (2003) 1443-1467.

DOI: 10.1002/eqe.287

[5] J. N. Yang, Y. Lei, S. Pan, N.H. Huang, System identification of linear structures based on Hilbert-Huang spectral analysis, part 2: complex modes, Earthquake Engineering and Structural Dynamics 32 (10) (2003) 1533-1554.

DOI: 10.1002/eqe.288

[6] P. F. Pai, Time–frequency characterization of nonlinear normal modes and challenges in nonlinearity identification of dynamical systems, Mechanical Systems and Signal Processing 25(7) (2011) 2358-2374.

DOI: 10.1016/j.ymssp.2011.02.013