Methodology to the precursor of phyllite instability or failure under uniaxial compression using acoustic emission

Methodology to the precursor of phyllite instability or failure under uniaxial compression using acoustic emission | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 1 March 2025 V1 Latest version Share on Methodology to the precursor of phyllite instability or failure under uniaxial compression using acoustic emission Authors : Ruifeng Du 0000-0002-8017-1672 , Ling Zhu [email protected] , and Zhihao He Authors Info & Affiliations https://doi.org/10.22541/au.174081248.86195051/v1 182 views 98 downloads Contents Abstract 1 Rock mechanics and acoustic emission test equipment 2 Methodology of the experiment data analysis of phyllite 2.2 AE signal analysis process 3 Characteristics of the uniaxial compression of phyllite based on AE 3.2 Changes of the main frequency and its main amplitude 3.3 Changes of the main frequency ratio and the main amplitude ratio 3.4 Characterization ability of AE 4 Conclusion Author Contributions Conflicts of Interest Data Availability Statement ORCID Supplementary Material References Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract To explore the compression characteristics and failure precursor of phyllite, the acoustic emission (AE) test was carried out on the condition of uniaxial compression experiments. A self-programmed computer procedure is used to complete the filtering, time-frequency transform and data analysis of AE signals. The uniaxial compression process of phyllite can be divided into three stages: calm stage, active stage, and intense stage, which corresponds to the low-frequency band (40-198kHz), intermediate frequency band (198-232kHz), and high-frequency band (232-400kHz). The first and second dominant frequencies exhibit strong aggregation along with the sequence of AE. Low main frequency ratio corresponds to high main amplitude ratio, and vice versa. When approaching the failure stage, there is a sudden change in the main amplitude ratio, a decreasing change in main frequency ratio along with an aggregation state. There is good consistency between the compressive characteristics reflected by the stress-strain curve and the main frequency characteristics by the AE signal, highlighting the characterization of AE technology. The results of this experiment can provide a certain application reference for the precursor of instability or failure in the engineering of phyllite rock mass. Methodology to the precursor of phyllite instability or failure under uniaxial compression using acoustic emission Ruifeng Du 1 Ling Zhu 2 Zhihao He 3 (1. Geography Department, Xinzhou Normal University, Xinzhou, China) (2. School of Geosciences and Info-Physics, Central South University, Changsha, China) （3. School of Emergency Management, Xihua University, Chengdu, China） Abstract: To explore the compression characteristics and failure precursor of phyllite, the acoustic emission (AE) test was carried out on the condition of uniaxial compression experiments. A self-programmed computer procedure is used to complete the filtering, time-frequency transform and data analysis of AE signals. The uniaxial compression process of phyllite can be divided into three stages: calm stage, active stage, and intense stage, which corresponds to the low-frequency band (40-198kHz), intermediate frequency band (198-232kHz), and high-frequency band (232-400kHz). The first and second dominant frequencies exhibit strong aggregation along with the sequence of AE. Low main frequency ratio corresponds to high main amplitude ratio , and vice versa . When approaching the failure stage, there is a sudden change in the main amplitude ratio, a decreasing change in main frequency ratio along with an aggregation state. There is good consistency between the compressive characteristics reflected by the stress-strain curve and the main frequency characteristics by the AE signal, highlighting the characterization of AE technology. The results of this experiment can provide a certain application reference for the precursor of instability or failure in the engineering of phyllite rock mass. Keywords: acoustic emission; phyllite; time-frequency analysis; main frequency ratio; main amplitude ratio Correspondence: Ling Zhu ( [email protected] ) Funding: This study was financially sponsored by the Opening fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Chengdu University of Technology) (Grant No. SKLGP2023K006), National Natural Science Foundation of China (Grant Nos. 42307249 and 42377194), Sichuan Science and Technology Program (Grant No. 2023NSFSC0282), and Sichuan Province Central Government Guides Local Science and Technology Development Special Project (Grant No. 2023ZYD0151). Acoustic emission (AE) is a physical phenomenon in which solid material releases strain energy in the form of elastic wave under certain action. From the point of physics, AE is a universal physical phenomenon. Based on the principle of AE and related technical equipment, researches carried out lots of studies on rock burst monitoring, internal defects of steel vessels, fatigue characteristics of solid materials, crack coalescence or closing of rock, precise location of fracture sources in geological fault model experiments[1-7]. Nowadays, AE is the popular method to evaluate the crack of rock interior in the science and engineering. Wu et al.[3] employed the three-component acoustic emission sensor to the shale rock fracturing process, showing a new understanding of the evolution of fractures. Zhao, et al.[8] performed uniaxial compression test on sandstone samples along with AE measurement, describing the relationship between the crack levels and AE signal frequency centroid, showing the precursor characteristics of the brownish red sandstone. It is the fact that AE signal is non-stationary and its frequency characteristics can be obtained by the specific methods. Hu, et al.[9] used the 3-D short-time Fourier transform (STFT) to analyze the AE waveform, and obtained the critical point of shale rock in the uniaxial deformation process. Jiang[10] and Zhang[11], respectively applied Hilbert-Huang Transform (HHT) in the analysis of concrete beam compression and yarn tensile fracture problem, and extracted more useful frequency characteristic. Liu, et al.[12] conducted the uniaxial compression tests on the coal rock samples and collected the micro-seismic signal spectrum features mainly using HHT. AE is widely used to study the evolution of microcrack initiation, propagation, and coalescence within rocks, serving as effective means of surveying rock damage, or a precursor of rock failure. In the field of materials science, AE detection technology is a non-destructive testing method, which can evaluate the dynamic characteristics of cracks, and is very suitable for material detection or dynamic mechanical behavior measurement of structures[13-14]. In practice, AE technology has been widely used in tunnel rock mass monitoring and coal mining construction, and has obtained good application results[15-16]. In the experimental study of rock mechanics, the changes of internal cracks under different stress states can be identified by AE equipment, which can indirectly characterize the stress state or internal structure of rock. Through the time-frequency analysis of AE signals of rock materials, different main frequency value occurs in different frequency domain. Main frequency in the low frequency domain are related to rock fissure and cavity closure, and those in the medium frequency domain are related to the development of rock fissure, so the compaction stage intensively determined the appearance of high frequency domain[15,17-18]. Although AE is a useful methodology to clarify the five stages of rock failure, that is the crack closure stage, linear elastic deformation stage, stable crack growth stage, unstable crack growth, and post-peak failure stage, which is of overall significance. In reality, the precursor of rock critical instability or failure is vital to practical engineering, which can give the early warning information to save the worker’s lives and property. AE measurement can be applied for real-time monitoring of AE events during the tunnel engineering, and giving the pre-early information, and become an important means to reveal the evolution framework of the instability deformation and failure in rocks. Based on the failure phenomena of phyllite such as earthquake damage cracking and slope collapse in multi-stage earthquake disaster investigation[19-20], in order to ascertain the stress state of phyllite, uniaxial compression tests were carried out and AE signals were collected in the study. On the platform of MATLAB, a self-programmed computer procedure is to deal with the plenty of AE signals, and its main function includes the fast Fourier transform (FFT) and HHT, and extracting the main frequency and its amplitude of the AE changes of phyllite. In the paper, the characteristics of stress variation reflected by stress-strain curve are in good agreement with the variation of main frequency obtained by AE equipment, which highlights the significance of AE and proposes the precursor of instability or failure of phyllite, and can provide a certain foundation for the application of AE technology in phyllite rock mass engineering. 1 Rock mechanics and acoustic emission test equipment AE is a kind of elastic wave generated in the process of rock internal fracture and energy release, which is manifested as vibration waves of different frequency. The available parameters in AE test include ringing count, rise time, energy, duration, amplitude and so on. The ringing count and energy can not only reflect the active degree of microcrack growth in rock, but also be used to evaluate the damage degree of rock. At the same time, the AE signal of rock contains a lot of microcrack information, and the internal fracture evolution of rock can be obtained by spectrum analysis method. In this study, phyllite samples were drilled from the landslide area of Xinmo village, Sichuan Province, China. The landslide is mainly composed of medium to thick stratified metamorphic sandstone with thin-layered slate and phyllite[19], which is the critical sliding strata. The size of phyllite samples is 50mm in diameter and 100mm in height. The uniaxial compression experiment with AE test of phyllite were commonly completed on the MTS 815 rock mechanics test machine. The purpose of the experiment is to investigate the characterization ability of AE during the uniaxial compression state, so as to reveal the AE change rule, which can provide a certain identification basis for the application of AE monitoring. 2 Methodology of the experiment data analysis of phyllite 2.1 Uniaxial compression test and AE signal characterization of rock Uniaxial compression experiment is often used to the evaluate the property of the phyllite, due to its comparatively simpler mechanical condition. Several phyllite samples were carried out in the uniaxial compression experiment. The stress-strain curves and AE characteristics of representative rock samples are shown in Figure 1. Figure 1a shows the stress-strain curve of the studied phyllite. In the compaction stage, the curve is relatively smoothing, but when it is close to the peak stress point, there is a phenomenon of stress drop, which is mainly related to the natural schistosity structure and multiple internal cracks. Figure 1b shows the change of AE ringing count and energy over time, indicating abrupt change. Further analysis of AE signal data needs to be completed in frequency domain. The relationship between AE count and time rate of change is expressed in logarithmic y-coordinates, as shown in Figure 1c, indicating good appearance of the abrupt change. It can be seen that the cumulative hits rate of change has a significant gathering state for many times, which indirectly states the intense development of cracks within the phyllite samples such as burst, crack and fracture. The variation of AE energy is shown in Figure 1d. FIGURE 1 Curves of stress strain of phyllite and changes of AE variables 2.2 AE signal analysis process In order to further analyze the characteristics of AE waveform signal, the phyllite experimental results and AE signal data processing are completed based on MATLAB in the study. First, the AE signals are read in batches, and the signals are filtered. Then, FFT is applied to each AE signal to realize time-frequency analysis, in which the first and second main frequency, amplitude of the AE signal can be automatically extracted. HHT is also used to more precisely show the relation between the frequency, time and the releasing energy of AE, very suitable for non-linear and non-stationary signal. Finally, the result curves from stress-strain analysis are compared with those from AE analysis. 3 Characteristics of the uniaxial compression of phyllite based on AE 3.1 Time-frequency analysis The AE analysis of the phyllite samples subjected to the uniaxial compression load is realized by the self-programmed computer procedure, realizing the fast and accurate process of data process. The whole process is composed of three stages. In the first stage, the original data files of AE signal are read into the computer procedure. The AE data are processed one by one, and the moving average method is used to filter these data. The signal noise ratio and mean-square error of the obtained results meet the requirements of signal processing standard[3]. In the second stage, the process of FFT and HHT is performed to each AE signal. A more flexible processing method can also be adopted, that is, the graphic is set to be output once every 1000 counts, which can effectively save calculation time and speed up the entire process of AE data. The change graph in time domain is plotted in Figure 2a, and the frequency change obtained by FFT and is shown in Figure2b and 2c respectively. FIGURE 2 Results of the time-frequency characteristics of AE signals of phyllite The third stage is the conclusion stage. The extracted frequency, frequency ratio, amplitude ratio and other results are written into editable files, which lays good foundation for the further analysis. 3.2 Changes of the main frequency and its main amplitude As shown in Figure 3, the change of the first and second main frequencies over time shows obvious zonation phenomenon, which was also reported in other literature[21]. The whole process is divided into three stages: calm period, active period and intense period. The corresponding frequency domain is divided into low frequency band, middle frequency band and high frequency band in terms of frequency value, namely, 40-198kHz, 198-232kHz and 232-400kHz. Figure 3a and 3b show that the first and the second main frequency have the similar indications, signifying the relevant frequency domain in line with the different time interval, and even the stress stages. FIGURE 3 Changes of the first and second main frequency with time According to the analysis of AE signal in time domain, low frequency band, middle frequency band and high frequency band coexist between 0-200s. Between 200s and 400s, middle frequency and high frequency bands are concentrated, showing high-frequency characteristics, mainly due to the gradual compression process of the phyllite samples. The failure time from 400s to 600s shows a strong coexistence of low frequency, medium frequency and high frequency band. Meanwhile, the amplitudes of the first main frequency and the second main frequency are respectively in Figure 4. It can be seen that the amplitudes of main frequency show a strong regularity, mainly distributed in the vicinity of 100kHz and 200kHz, indicating a strong accumulation. From the perspective of amplitude and frequency characteristics, low frequency is accompanied by high amplitude, and high frequency signal is done by low amplitude, which is in good agreement with other related literatures[21-22]. FIGURE 4 Changes of the main amplitude with the first and the second main frequency 3.3 Changes of the main frequency ratio and the main amplitude ratio In search of more relationship between frequency and amplitude, two variables are customized. The main frequency ratio is defined by the first main frequency dividing the second main frequency, the main amplitude ratio is done by the amplitude of the first main frequency dividing the one of the second main frequency. As shown in Figure 5, there is a strong regularity between the main frequency ratio and the amplitude ratio. It can be seen that low main frequency ratio corresponds to high amplitude ratio, and vice versa. FIGURE 5 Changes of the main amplitude ratio with main frequency ratio In Figure 6, the spatial variation relationship of the main frequency ratio and amplitude ratio, and the sequence of AE is expressed. It can be seen that the main frequency ratio and the main amplitude ratio show strong regularity with the evolution of AE sequence. When approaching the failure stage, the amplitude ratio appears abrupt phenomenon, the frequency ratio decreases and shows obvious accumulation state. FIGURE 6 Changes among the main frequency ratio, the main amplitude ratio and the sequency of AE signal 3.4 Characterization ability of AE In order to verify the characterization ability of AE and the accuracy of self-programmed computer procedure, the phyllite stress-strain curve is compared with the AE signal processing curve. To obtain comparative analysis, the maximum value standardization method is applied to the studied data. In Figure 7, there is good uniform change law between the accumulated AE energy and the accumulated counts curve. All of the three types of curves have similar obvious characteristic points, which shows the accuracy of AE signal acquisition, and stress curve can reflect the stress drop phenomenon of phyllite. After the peak point of the stress curve, the compression state of phyllite is that the cracks increase, the stress gradually decreases and the strain continues to increase, that is, phyllite samples rapidly tend to the failure stage, and correspondingly, the curve becomes more steeper in the AE energy curve and counts curve. FIGURE 7 Changes of the normalized stress, energy and count with time Figure 8 shows the relationship between the first main frequency, cumulative AE counts and time. Before 400s, the curve of cumulative AE hits seems a steady growth process. It is at about 400s that the AE hits began to rapidly grow, and finally a comparatively steep curve is developed. While the first main frequency also forms an obvious zonation phenomenon at this position, that is, the characteristic points of the two types of curves are consistent perfectly. FIGURE 8 Changes of the cumulative counts, the first main frequency with time 4 Conclusion Based on the extensive application research background of AE technology, in order to highlight the progressiveness of AE technology, the uniaxial compression experiment of phyllite was carried out along with AE measurement. In assist of the self-programmed computer procedure, the AE signal data is effectively completed, and AE characteristics of the phyllite on the condition of uniaxial compression are obtained. The following conclusions can be drawn from this study. (1) The AE signal in the whole phyllite uniaxial compression condition is divided into three typical stages, namely quiet period, active period and intense period, corresponding to the low band (40-198kHz), middle band (198-232kHz) and high band (232-400kHz) respectively. (2) The first main frequency and second main frequency show strong accumulation within the phyllite deformation process. Low main frequency ratio corresponds to high main amplitude ratio, vice versa. When approaching the failure stage, the main amplitude ratio shows sudden change, the main frequency ratio decreases and shows a state of accumulation, which gives a specific precursor to the coming instability or failure. (3) The analysis of the uniaxial compression experiment results of phyllite shows that there is a good consistency between the compression characteristics of phyllite reflected by the stress-strain curve and the main frequency variation characteristics reflected by AE signals, which highlights the importance of AE technology, namely, AE signals can effectively characterize different stress stages of phyllite. And it is concluded that AE signals change regularly with the change of stress. The test results can provide a certain basis for the foundation of AE technology in phyllite rock engineering. Author Contributions Ruifeng Du: conceptualization, methodology and writing. Ling Zhu: project administration and formal analysis. Zhihao He: reviewing and editing. This study was financially sponsored by the Opening fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Chengdu University of Technology) (Grant No. SKLGP2023K006), National Natural Science Foundation of China (Grant Nos. 42307249 and 42377194), Sichuan Science and Technology Program (Grant No. 2023NSFSC0282), and Sichuan Province Central Government Guides Local Science and Technology Development Special Project (Grant No. 2023ZYD0151). Conflicts of Interest The authors declare no conflicts of interest. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. ORCID Ruifeng Du, http://orcid.org/0000-0002-8017-1672 Ling Zhu, https://orcid.org/0000-0002-6838-9492 Zhihao He, https://orcid.org/0000-0002-3863-9251 Supplementary Material File (figures.rar) Download 6.30 MB References 1. 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Keywords crack initiation and propagation material mechanical properties mechanical testing Authors Affiliations Ruifeng Du 0000-0002-8017-1672 Xinzhou Normal University View all articles by this author Ling Zhu [email protected] Central South University School of Geosciences and Info Physics View all articles by this author Zhihao He Xihua University View all articles by this author Metrics & Citations Metrics Article Usage 182 views 98 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Ruifeng Du, Ling Zhu, Zhihao He. Methodology to the precursor of phyllite instability or failure under uniaxial compression using acoustic emission. Authorea . 01 March 2025. DOI: https://doi.org/10.22541/au.174081248.86195051/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. 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