FRACTALS AND CHAOS CHARACTERISTICS OF ACOUSTIC EMISSION ENERGY ABOUT GAS-BEARING COAL DURING LOADED FAILURE

Fractals ◽  
2019 ◽  
Vol 27 (05) ◽  
pp. 1950072 ◽  
Author(s):  
XIANGGUO KONG ◽  
ENYUAN WANG ◽  
SHUGANG LI ◽  
HAIFEI LIN ◽  
PENG XIAO ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Chaotic Behavior ◽  
High Stress ◽  
Multifractal Spectrum ◽  
High Energy ◽  
Time Varying ◽  
Multifractal Theory ◽  
Coal Damage ◽  
Gas Bearing ◽  
Ae Signals

To study the damage evolution mechanism of gas-bearing coal and formation causes of acoustic emission signals during this process, the loaded experiments of gas-bearing coal were performed, and acoustic emission (AE) data radiated in this process were collected. Based on the multifractal theory, the causes of AE were explored in various loaded phases. The results showed that at the low stress stage, the fractures close and the friction/slip could cause low-energy acoustic emission events, and the multifractal spectrum had a smaller width. By contrast, at the high stress stage, the cracks expand, penetrate, and rupture, which would lead to AE events with the release of high energy, reflecting an increase in the width of the multifractal spectrum. At the initial loading stage, the time-varying multifractal spectrum was characterized by a chaotic behavior, but as the loading progressed, it gradually became orderly. In the elastic stage, coal experienced elastic deformation without damage, the ratio of strong and weak AE signals was almost the same, and both [Formula: see text] and [Formula: see text] were close to 0. In the plastic fracture stage, coal body consumed huge amounts of energy and suffered fracture. This also caused the coal body to radiate a large amount of AE signals. An analysis of these signals indicated that strong signals dominated and showed an increasing trend, and [Formula: see text] was less than 0 and continued to decrease. The time-varying multifractal characteristics reveal the formation mechanism of AE signals from gas-bearing coal, which contributes to improve our understanding of the mechanism of gas-bearing coal damage.

MULTIFRACTAL CHARACTERISTICS AND ACOUSTIC EMISSION OF COAL WITH JOINTS UNDER UNIAXIAL LOADING

Fractals ◽  
2017 ◽  
Vol 25 (05) ◽  
pp. 1750045 ◽  
Author(s):  
XIANGGUO KONG ◽  
ENYUAN WANG ◽  
XUEQIU HE ◽  
ZHONGHUI LI ◽  
DEXING LI ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Multifractal Spectrum ◽  
Crack Evolution ◽  
Spectrum Width ◽  
Multifractal Theory ◽  
Macroscopic Fracture ◽  
The Right ◽  
Ae Counts ◽  
Ae Signals ◽  
Over Time

In order to explore the causes of acoustic emission (AE) signals during coal failure, the coal samples with original joints were subjected to uniaxial compression experiments, and the AE signals were monitored by AEwin Test for Express-8.0. Based on the multifractal theory, the multifractal characteristics of AE were analyzed. The results showed that the AE counts and accumulative counts change over time corresponded well with the load-time, which reflected the degree of crack evolution and loading. During the initial loading stage, the cracks expanded gradually along the trace of the original cracks, which could induce a few AE events, while with the increase of load, the cracks enlarged gradually and then joined together to form a macroscopic fracture, which would cause much more AE events within a larger value. Multifractal spectrum [[Formula: see text]] of AE was more concentrated in the right side, illustrating that the frequency of small signals was greater than that of the large signals in AE sequences, which revealed cracks expanding and microfracture events dominated during the loading process. The greater the multifractal spectrum width ([Formula: see text] was, the larger the AE signals differences were, which reflected that AE varied more intensely. The more developed the original cracks, the more obvious the multifractal characteristics. This research revealed the causes and percentage of the AE events within small or large signals, which would help us to recognize crack evolution of coal and generation mechanism of AE.

Dynamic Singularity Spectrum Distribution of Sea Clutter

2014 ◽  
Vol 14 (01) ◽  
pp. 1550004 ◽  
Author(s):  
Gang Xiong ◽  
Wenxian Yu ◽  
Shuning Zhang
Keyword(s):  
Signal Processing ◽  
Multifractal Spectrum ◽  
Singularity Analysis ◽  
Radar Signal ◽  
Time Varying ◽  
Singularity Spectrum ◽  
Sea Clutter ◽  
Multifractal Theory ◽  
Spectrum Distribution ◽  
Target Detecting

The fractal and multifractal theory have provided new approaches for radar signal processing and target-detecting under the background of ocean. However, the related research mainly focuses on fractal dimension or multifractal spectrum (MFS) of sea clutter. In this paper, a new dynamic singularity analysis method of sea clutter using MFS distribution is developed, based on moving detrending analysis (DMA-MFSD). Theoretically, we introduce the time information by using cyclic auto-correlation of sea clutter. For transient correlation series, the instantaneous singularity spectrum based on multifractal detrending moving analysis (MF-DMA) algorithm is calculated, and the dynamic singularity spectrum distribution of sea clutter is acquired. In addition, we analyze the time-varying singularity exponent ranges and maximum position function in DMA-MFSD of sea clutter. For the real sea clutter data, we analyze the dynamic singularity spectrum distribution of real sea clutter in level III sea state, and conclude that the radar sea clutter has the non-stationary and time-varying scale characteristic and represents the time-varying singularity spectrum distribution based on the proposed DMA-MFSD method. The DMA-MFSD will also provide reference for nonlinear dynamics and multifractal signal processing.

scholarly journals Comparative analysis of the strength of restoration polymers of light polymerization for dental restoration using the acoustic emission method: part one

2021 ◽  
Vol 107 (3) ◽  
pp. 26-32
Author(s):  
V. Kukhta ◽  
◽  
V. Makeev ◽  
O. Kyrmanov ◽  
V. Skalsky ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Comparative Analysis ◽  
High Energy ◽  
Dental Restoration ◽  
Acoustic Emission Method ◽  
Local Loading ◽  
Emission Method ◽  
Composite Failure ◽  
Initial Stage ◽  
Ae Signals

Purpose. Comparative analysis of the strength of hybrid restoration composites of light polymerization during their local loading using the phenomenon of acoustic emission. The following restoration composites were studied: Latelux, Tetric N-Ceram, Charisma Classic. Results. It was determined that the nature of the destruction of all composites is the same: elastic-plastic at the initial stage of the load with a transition to brittle as its further growth. Three types of composite failure are observed: correct, incorrect and mixed. The first predominated during fracture under the action of local loading of the Latelux composite, for Tetric N-Ceram and Charisma Classic materials a mixed type of fracture is characteristic. Conclusions. Analysis of the parameters of the AE signals showed that the signals had the highest amplitude and energy when the Tetric N-Ceram composite was destroyed, and the lowest – Latelux. All dental composites are dominated by high-energy ductile-brittle and brittle fracture, which indicates the spread of micro- and macrocracks of various sizes in materials. Key words: polymer composites, strength, acoustic emission method.

NONLINEAR CHARACTERISTICS OF ACOUSTIC EMISSION DURING THE HEATING PROCESS OF COAL AND ROCK

Fractals ◽  
2018 ◽  
Vol 26 (04) ◽  
pp. 1850046 ◽  
Author(s):  
ZHIBO ZHANG ◽  
ENYUAN WANG ◽  
ENLAI ZHAO ◽  
SHUAI YANG
Keyword(s):  
Acoustic Emission ◽  
Hurst Exponent ◽  
Multifractal Spectrum ◽  
Heating Process ◽  
Nonlinear Characteristics ◽  
Rock Samples ◽  
Spectrum Width ◽  
Multifractal Theory ◽  
Ae Signal ◽  
Temperature Levels

In this paper, acoustic emission (AE) signal of coal and rock samples during the heating process are measured. The results show that AE energy of coal samples is higher than that of rock samples. Based on the multifractal theory, the multifractal characteristics of AE signal are researched. The multifractal spectrum width ([Formula: see text]) of coal samples is wider than that of rock samples, which means AE signal of coal samples is more complex than AE signal of rock samples during the heating process. Multifractal parameter ([Formula: see text]) is more than zero, illustrating that small AE signal is dominate. The time-varying multifractal characteristics are analyzed, and the change trend of multifractal spectrum width ([Formula: see text]) of coal and rock samples is consistent. At the stage of 40–50[Formula: see text]C, multifractal spectrum width ([Formula: see text]) gets the maximum value, whereas multifractal spectrum width ([Formula: see text]) gets the minimum value at the stage of 80–100[Formula: see text]C. For coal samples, multifractal parameter ([Formula: see text] is more than zero except at the stage of 40–50[Formula: see text]C. However, multifractal parameter ([Formula: see text] of rock samples is always more than zero during the entire heating process. By [Formula: see text] analytical method, Hurst exponent of AE signal is calculated. The results show that Hurst exponent of coal and rock samples are more than 0.5, which indicate that AE signal presents persistence, and there is a positive correction between AE signal and temperature. In different temperature levels, Hurst exponent curve presents an increase trend after the initial decrease.

scholarly journals Study on the Mechanical Behavior and Acoustic Emission Properties of Granite under Triaxial Compression

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Jiaqi Guo ◽  
Pengfei Liu ◽  
Junqi Fan ◽  
Hengyuan Zhang
Keyword(s):  
Acoustic Emission ◽  
Crack Initiation ◽  
Triaxial Compression ◽  
Testing Machine ◽  
Confining Pressure ◽  
High Energy ◽  
Granite Sample ◽  
Initiation Point ◽  
Granite Samples ◽  
Ae Signals

To study the rock mechanical behaviors and damage process mechanism of granite samples under triaxial stress, conventional triaxial compression tests were carried out on an RMT-150B rock mechanics testing machine and acoustic emission detector. The test results show that the strength of the granite sample has a good linear relationship with the confining pressure, the cohesion force c of the granite samples is 29.37 MPa, and the internal friction angle is 54.23° by calculation based on the Mohr-Coulomb strength criterion. The larger the initial confining pressure of the rock sample is, the larger the crack initiation stress ( σ ci ) and dilatancy stress ( σ cd ) of the granite specimen are, the larger the energy values at the crack initiation point and dilatancy point are, and the larger the peak energy storage and energy release rate at the failure are. In the case of a small initial confining pressure, the AE ringdowning counts and the cumulative AE ringing counts increase to their maximum instantaneously at the peak stress point, and the damage of the sample develops rapidly. While the initial confining pressure is high, the AE ringing counts and the cumulative AE ringing counts of the granite specimens increase evenly, and the deformation damage of the granite specimens is slow. Before the crack initiation point, AE signals are mainly low-energy and low-frequency friction-type AE events, while after the dilatation point, AE signals of samples are mainly high-frequency and high-energy fracture-type AE events. The failure mode of granite samples judged by acoustic emission parameters according to the distribution of characteristic values of AE parameters RA and AF is consistent with the reality. The AE b value of the granite sample is large when the confining pressure is low, and there will be a sudden drop, the decrease time is late, and the decrease rate is large. Under the same stress level, the larger the confining pressure is, the larger the damage variable D is.

The Method of Fault Feature Extraction from Acoustic Emission Signals Using Wigner-Ville Distribution

2011 ◽  
Vol 216 ◽  
pp. 732-737 ◽  
Author(s):  
G.F. Bin ◽  
C.J. Liao ◽  
Xue Jun Li
Keyword(s):  
Acoustic Emission ◽  
Fault Diagnosis ◽  
High Energy ◽  
Frequency Resolution ◽  
Time Frequency ◽  
Fault Features ◽  
Very High Energy ◽  
Ae Signal ◽  
Experimental Data Analysis ◽  
Ae Signals

Wigner-Ville distribution (WVD) has the characteristics of very high-energy accumulation and excellent time-frequency resolution. It is a good way to extract fault feature of acoustic emission (AE) signals due to mechanical component broken. The characteristics of typical AE signals initiated by damages are analyzed. Based on the extracting principle of AE signals from damaged components, the WVD analysis method of AE signal is developed. WVD method is employed to the fault diagnosis of rolling bearings with AE technique. The fault features reading from experimental data analysis are clear, accurate and intuitionistic, meantime, the validity and accuracy of WVD method proposed are nice from the experimental results. Therefore, WVD method is useful for condition monitoring and fault diagnosis in conjunction with AE technique.

scholarly journals Analysis of Acoustic Emission (AE) Signals for Quality Monitoring of Laser Lap Microwelding

2021 ◽  
Vol 11 (15) ◽  
pp. 7045
Author(s):  
Ming-Chyuan Lu ◽  
Shean-Juinn Chiou ◽  
Bo-Si Kuo ◽  
Ming-Zong Chen
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Frequency Domain ◽  
Monitoring System ◽  
Welding Quality ◽  
Steel Sheets ◽  
Signal Features ◽  
Ae Signal ◽  
Laser Microwelding ◽  
Ae Signals

In this study, the correlation between welding quality and features of acoustic emission (AE) signals collected during laser microwelding of stainless-steel sheets was analyzed. The performance of selected AE features for detecting low joint bonding strength was tested using a developed monitoring system. To obtain the AE signal for analysis and develop the monitoring system, lap welding experiments were conducted on a laser microwelding platform with an attached AE sensor. A gap between the two layers of stainless-steel sheets was simulated using clamp force, a pressing bar, and a thin piece of paper. After the collection of raw signals from the AE sensor, the correlations of welding quality with the time and frequency domain features of the AE signals were analyzed by segmenting the signals into ten 1 ms intervals. After selection of appropriate AE signal features based on a scatter index, a hidden Markov model (HMM) classifier was employed to evaluate the performance of the selected features. Three AE signal features, namely the root mean square (RMS) of the AE signal, gradient of the first 1 ms of AE signals, and 300 kHz frequency feature, were closely related to the quality variation caused by the gap between the two layers of stainless-steel sheets. Classification accuracy of 100% was obtained using the HMM classifier with the gradient of the signal from the first 1 ms interval and with the combination of the 300 kHz frequency domain signal and the RMS of the signal from the first 1 ms interval.

scholarly journals Acoustic Emission Testing and Ib-Value Analysis of Ultraviolet Light-Irradiated Fiber Composites

2021 ◽  
Vol 11 (14) ◽  
pp. 6550
Author(s):  
Doyun Jung ◽  
Wonjin Na
Keyword(s):  
Acoustic Emission ◽  
Irradiation Time ◽  
Tensile Load ◽  
Failure Behavior ◽  
Value Analysis ◽  
Emission Testing ◽  
Final Failure ◽  
Acoustic Emission Testing ◽  
Woven Glass Fiber ◽  
Ae Signals

The failure behavior of composites under ultraviolet (UV) irradiation was investigated by acoustic emission (AE) testing and Ib-value analysis. AE signals were acquired from woven glass fiber/epoxy specimens tested under tensile load. Cracks initiated earlier in UV-irradiated specimens, with a higher crack growth rate in comparison to the pristine specimen. In the UV-degraded specimen, a serrated fracture surface appeared due to surface hardening and damaged interfaces. All specimens displayed a linearly decreasing trend in Ib-values with an increasing irradiation time, reaching the same value at final failure even when the starting values were different.

Acoustic Emission Monitoring of Leaks in Pipes for Transport of Liquid and Gaseous Media: A Model Experiment

2006 ◽  
Vol 13-14 ◽  
pp. 351-356 ◽  
Author(s):  
Andreas J. Brunner ◽  
Michel Barbezat
Keyword(s):  
Acoustic Emission ◽  
Model Experiment ◽  
Structural Integrity ◽  
Fiber Composite ◽  
Leak Testing ◽  
Pipe Segment ◽  
Potential Applications ◽  
Gaseous Media ◽  
The Media ◽  
Ae Signals

In order to explore potential applications for Active Fiber Composite (AFC) elements made from piezoelectric fibers for structural integrity monitoring, a model experiment for leak testing on pipe segments has been designed. A pipe segment made of aluminum with a diameter of 60 mm has been operated with gaseous (compressed air) and liquid media (water) for a range of operating pressures (between about 5 and 8 bar). Artificial leaks of various sizes (diameter) have been introduced. In the preliminary experiments presented here, commercial Acoustic Emission (AE) sensors have been used instead of the AFC elements. AE sensors mounted on waveguides in three different locations have monitored the flow of the media with and without leaks. AE signals and AE waveforms have been recorded and analysed for media flow with pressures ranging from about 5 to about 8 bar. The experiments to date show distinct differences in the FFT spectra depending on whether a leak is present or not.

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