Processing of acoustic emission test signals in determining the Kaiser impact point of rocks using discrete wavelet transform

Document Type : Research Article

Authors

1 Dept. of Mining Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Dept. of Mining, Petroleum and Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran

3 Dept. of Mining Engineering , Tarbiat Modares University, Tehran, Iran

Abstract

Summary
One of the geomechanical parameters that is very important in the design and analysis of various rock engineering projects is the in situ stress state of the rock mass. In this research, acoustic emission signal processing has been used to determine the Kaiser effect point of the experimental data on Phyllite rock by discrete wavelet transform method.
 
Introduction
There are different methods to determine in situ stress. In this regard, direct measurement methods are the best and most accurate in situ stress measurement methods. However, these methods are very time-consuming and costly. Therefore, nowadays laboratory and indirect rock core-based methods for estimating in situ stress have been taken into consideration. One of the laboratory methods is the acoustic emission method based on Kaiser effect. In this method, determining the Kaiser effect point is usually done by the parameters of acoustic emission signals, which in some cases, determining the Kaiser effect point by parametric method are ambiguous and do not have sufficient clarity. Signal processing based on wavelet transform is a powerful tool to process acoustic emission signals, which has been used in several papers.
 
Methodology and Approaches
In this study some Phyllite samples were used to be loaded under indirect tensile loading (Brazilian test). The acoustic emission test consisted of two cycles. In the first cycle, the samples were preloaded to a predetermined level, and in the second cycle, they were reloaded until reaching the failure. Before using the discrete wavelet transform, the appropriate mother wavelet was selected. Then, the signals obtained from the acoustic emission test were processed using wavelet transform. The maximum approximation coefficient parameter was used as a suitable feature for the analysis. Using K-means method, the obtained data are clustered in five clusters. Then, the highest density of data in the fifth cluster was considered as the occurrence point of the Kaiser effect.
 
Results and Conclusions
The results show that according to the parameters of correlation coefficient and noise to signal ratio and the type of acoustic signals the mother wave db6 was suitable for analysis. Among the parameters that can be used for analysis, the maximum approximation coefficient parameter is also selected as a suitable feature for analysis. Also, the results of the discrete wavelet transform method were in good agreement with the results of the parametric method, so that the occurrence times of the Kaiser effect obtained from the two methods are mutually acceptable.

Keywords

Main Subjects

Full Text

به‌طورکلی سنگ‌ها و اغلب مواد زمانی که تحت تنش قرار می‌گیرند از خود صدا و سیگنال‌های لرزه‌ای با فرکانس زیاد ساطع می‌کنند. این پدیده انتشار آکوستیک نام دارد. در سال‌های اخیر به‌کارگیری روش انتشار اکوستیک که جزء آزمایش‌های غیر مخرب به‌حساب می‌آید رو به فزونی گذاشته است و این روش به‌طورکلی کاربرد زیادی درزمینه‌ی مهندسی معدن، عمران، علم مواد، زلزله‌شناسی و معدن یافته است. آزمایش انتشار اکوستیک یک روش با حساسیت زیاد برای دریافت این امواج در یک ماده بوده که از آن در زمینه‌های رفتار نگاری در مصالح جامد نظیر سنگ، فلز، شیشه و سرامیک که تحت تنش قرار دارند و نیز بررسی فرآیند شکست در این مواد استفاده می‌شود.

References

[1]     Kaiser, J., An investigation into the occurrence of noises in tensile tests, or a study of acoustic phenomena in tensile tests. Doctor of Philosophy, Technical University of Munich, Munich, Germany, 1950.
[2]     Li, C. and E. Nordlund, Experimental verification of the Kaiser effect in rocks. Rock Mechanics and Rock Engineering, 1993. 26(4): p. 333-351.
[3]     Lavrov, A., The Kaiser effect in rocks: principles and stress estimation techniques. International Journal of Rock Mechanics and Mining Sciences, 2003. 40(2): p. 151-171.
[4]     Pestman, B. and J. Van Munster. An acoustic emission study of damage development and stress-memory effects in sandstone. in International journal of rock mechanics and mining sciences & geomechanics abstracts. 1996. Elsevier.
[5]     Stuart, C., et al. Anisotropic crack damage and stress-memory effects in rocks under triaxial loading. in The 34th US Symposium on Rock Mechanics (USRMS). 1993. OnePetro.
[6]     Seto, M., et al., In situ stress determination by acoustic emission technique. International Journal of Rock Mechanics and Mining Sciences, 1997. 34(3-4): p. 281. e1-281. e16.
[7]     Chen, Z., et al., Confinement effects for damage and failure of brittle rocks. International journal of rock mechanics and mining sciences (1997), 2006. 43(8): p. 1262-1269.
[8]     Kyriazis, P., et al., Wavelet analysis on pressure stimulated currents emitted by marble samples. Natural Hazards and Earth System Sciences, 2006. 6(6): p. 889-894.
[9]     Zhao, K., et al., Advances in Kaiser effect of rock acoustic emission based on wavelet analysis, in Boundaries of Rock Mechanics. 2008, CRC Press. p. 993-996.
[10]     Nikkhah, M., M. Ahmadi, and A. Ghazvinian. Application of pattern recognition analysis of rock acoustic emission for determination of Kaiser Effect. in 12th ISRM Congress. 2011. OnePetro.
[11]     Sagar, R.V., B.R. Prasad, and R. Singh, Kaiser effect observation in reinforced concrete structures and its use for damage assessment. Archives of Civil and Mechanical Engineering, 2015. 15(2): p. 548-557.
[12]     Cao, A., et al., Mining-induced static and dynamic loading rate effect on rock damage and acoustic emission characteristic under uniaxial compression. Safety Science, 2019. 116: p. 86-96.
[13]     Liu, W.-r., J.-k. Liu, and C. Zhu, Multi-scale effect of acoustic emission characteristics of 3D rock damage. Arabian Journal of Geosciences, 2019. 12(22): p. 1-13.
[14]     Gajst, H., et al., Relating strain localization and Kaiser effect to yield surface evolution in brittle rocks. Geophysical Journal International, 2020. 221(3): p. 209. 1-2103
[15]     Jiang, Z., et al., Acoustic emission characteristics in hydraulic fracturing of stratified rocks: a laboratory study. Powder Technology, 2020. 371: p. 267-276.
[16]     Seto, M., D. Nag, and V. Vutukuri, Evaluation of rock mass damage using acoustic emission technique in the laboratory, in Rock Fragmentation by Blasting. 2020, CRC Press. p. 139-145.
[17]     Chen, Z., L. Xu, and Y. Shang, Influence of joint angle on the acoustic emission evolution characteristics and energy dissipation rule of rock mass. Geotechnical and Geological Engineering, 2021. 39(2): p. 1621-1635.
[18]     King, T., et al., Acoustic emission waveform picking with time delay neural networks during rock deformation laboratory experiments. Seismological Society of America, 2021. 92(2A): p. 923-932.
[19]     Li, Z. and R. Xu, An early-warning method for rock failure based on Hurst exponent in acoustic emission/microseismic activity monitoring. Bulletin of Engineering Geology and the Environment, 2021: p. 1-15.
[20]     Wang, Y., et al., Study on crack dynamic evolution and damage-fracture mechanism of rock with pre-existing cracks based on acoustic emission location. Journal of Petroleum Science and Engineering, 2021. 201: p. 108420.
[21]     Wang, Z., et al., Crack propagation process and acoustic emission characteristics of rock-like specimens with double parallel flaws under uniaxial compression. Theoretical and Applied Fracture Mechanics, 2021. 114: p. 102983.
[22]     Zhou, Z., et al., Microscopic Failure Mechanism Analysis of Rock Under Dynamic Brazilian Test Based on Acoustic Emission and Moment Tensor Simulation. Frontiers in Physics, 2021. 8: p. 619.
[23]     Kharghani, M., et al., Investigation of the Kaiser effect in anisotropic rocks with different angles by acoustic emission method. Applied Acoustics, 2021,175.
[24]     Dinmohammadpour, M. et al., Application of Wavelet Transform in Evaluating the Kaiser Effect of Rocks in Acoustic Emission Test. Measurement, 2022, 192.
[25]     Ramos, R., et al., The discrete wavelet transform and its application for noise removal in localized corrosion measurements. International Journal of Corrosion, 2017. 2017.
[26]     Percival, D.B. and A.T. Walden, Wavelet methods for time series analysis. Vol. 4. 2000: Cambridge university press.
[27]     Soundararajan, V., H. Atharifar, and R. Kovacevic, Monitoring and processing the acoustic emission signals from the friction-stir-welding process. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2006. 220(10): p. 1673-1685.
[28]     Polikar, R., The wavelet tutorial. 1996.
[29]     Dinmohammadpour, M., et al. The Mechanism of Kaiser Effect in Phyllite under Indirect Tensile Loading. The Mining-Geology-Petroleum Engineering Bulletin, 2022, 59.  DOI: 10.17794/rgn.2022.3.2

Files

History

  • Receive Date: 28 November 2021
  • Revise Date: 26 February 2022
  • Accept Date: 15 March 2022

Share

How to cite

Statistics