Acoustic emission signal identification of different rocks based on SE-1DCNN-BLSTM network model

In order to study fracture mechanism of rocks in different brittle mineral contents,this study pro-poses a method to identify the acoustic emission signal released by rock fracture under different brittle miner-al content(BMC),and then determine the content of brittle matter in rock.To understand related interference such as the noises in the acoustic emission signals released by the rock mass rupture,a 1DCNN-BLSTM network model with SE module is constructed in this study.The signal data is processed through the 1DCNN and BLSTM networks to fully extract the time-series correlation features of the signals,the non-correlated features of the local space and the weak periodicity law.Furthermore,the processed signals data is input into the fully connected layers.Finally,softmax function is used to accurately identify the acoustic emission signals released by different rocks,and then determine the content of brittle minerals contained in rocks.Through experimental comparison and analysis,1DCNN-BLSTM model embedded with SE module has good anti-noise performance,and the recognition accuracy can reach more than 90 percent,which is better than the traditional deep network models and provides a new way of thinking for rock acoustic emission re-search.

Shear band evolution and acoustic emission characteristics of sandstone containing non-persistent flaws

Direct shear tests were conducted on sandstone specimens under different constant normal stresses to study the coalescence of cracks between non-persistent flaws and the shear sliding characteristics of the shear-formed fault.Digital image correlation and acoustic emission(AE)techniques were used to monitor the evolution of shear bands at the rock bridge area and microcracking behaviors.The experimental results revealed that the shear stresses corresponding to the peak and sub-peak in the stressdisplacement curve are significantly affected by the normal stress.Strain localization bands emerged at both the tip of joints and the rock bridge,and their extension and interaction near the peak stress caused a surge in the AE hit rate and a significant decrease in the AE b value.Short and curvilinear strain bands were detected at low normal stress,while high normal stress generally led to more microcracking events and longer coplanar cracks at the rock bridge area.Furthermore,an increase in normal stress resulted in a higher AE count rate and more energetic AE events during friction sliding along the shearformed fault.It was observed that the elastic energy released during the crack coalescence at the prepeak stage was much greater than that released during friction sliding at the post-peak stage.More than 75%of AE events were located in the low-frequency band(0e100 kHz),and this proportion continued to rise with increasing normal stress.Moreover,more AE events of low AF value and high RA value were observed in specimens subjected to high normal stress,indicating that greater normal stress led to more microcracks of shear nature.

Implications for identification of principal stress directions from acoustic emission characteristics of granite under biaxial compression experiments

The rock fracture characteristics and principal stress directions are crucial for prevention of geological disasters.In this study,we carried out biaxial compression tests on cubic granite samples of 100 mm in side length with different intermediate principal stress gradients in combination with acoustic emission(AE)technique.Results show that the fracture characteristics of granite samples change from‘sudden and aggregated’to‘continuous and dispersed’with the increase of the intermediate principal stress.The effect of increasing intermediate principal stress on AE amplitude is not significant,but it increases the proportions of high-frequency AE signals and shear cracks,which in turn increases the possibility of unstable rock failure.The difference of stress in different directions causes the anisotropy of rock fracture and thus leads to the obvious anisotropic characteristics of wave velocity variations.The anisotropy of wave velocity variations with stress difference is probable to identify the principal stress directions.The AE characteristics and the anisotropy of wave velocity variations of granite under two-dimensional stress are not only beneficial complements for rock fracture characteristic and principal stress direction identification,but also can provide a new analysis method for stability monitoring in practical rock engineering.

Characteristics of acoustic emission signals in damp cracking coal rocks

A uniaxial load experiment on coal rocks at different stress rates was carried out, based on the characteristics of acoustic emission (AE) signals in cracking coal rocks, decomposition, de-noising and reconstruction for the AE signals through wavelet packet transform for solving the current problems created by the presence of noise in AE signals and the existing problems in AE signal processing. The results show that the various characteristics of AE signals in coal rocks cracking under different situations can be clearly reflected, after the AE signals are de-noised by the wavelet packet. Compared to dry coal rocks, the number of AE occurrences in damp coal rocks was significantly reduced, as well as the average amplitude. The number of AE occurrences in damp and dry coal rocks clearly increased with increases in the loading rate, but the largest amplitude of the AE signals in damp coal rocks has been reduced. There is no clear evidence of change in dry coal rocks.

PARAMETERS OPTIMIZATION OF CONTINUOUS WAVELET TRANSFORM AND ITS APPLICATION IN ACOUSTIC EMISSION SIGNAL ANALYSIS OF ROLLING BEARING

Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform （CWT） has been successfully used in the field of fault diagnosis. The principle of scale selection in CWT is discussed. Based on genetic algorithm, an optimization strategy for the waveform parameters of the mother wavelet is proposed with wavelet entropy as the optimization target. Based on the optimized waveform parameters, the wavelet scalogram is used to analyze the simulated acoustic emission （AE） signal and real AE signal of rolling bearing. The results indicate that the proposed method is useful and efficient to improve the quality of CWT.

Mechanical responses and acoustic emission behaviors of coal under compressive differential cyclic loading(DCL):a numerical study via 3D heterogeneous particle model

The stability of coal walls(pillars)can be seriously undermined by diverse in-situ dynamic disturbances.Based on a 3D par-ticle model,this work strives to numerically replicate the major mechanical responses and acoustic emission(AE)behaviors of coal samples under multi-stage compressive cyclic loading with different loading and unloading rates,which is termed differential cyclic loading(DCL).A Weibull-distribution-based model with heterogeneous bond strengths is constructed by both considering the stress-strain relations and AE parameters.Six previously loaded samples were respectively grouped to indicate two DCL regimes,the damage mechanisms for the two groups are explicitly characterized via the time-stress-dependent variation of bond size multiplier,and it is found the two regimes correlate with distinct damage patterns,which involves the competition between stiffness hardening and softening.The numerical b-value is calculated based on the mag-nitudes of AE energy,the results show that both stress level and bond radius multiplier can impact the numerical b-value.The proposed numerical model succeeds in replicating the stress-strain relations of lab data as well as the elastic-after effect in DCL tests.The effect of damping on energy dissipation and phase shift in numerical model is summarized.

Moment tensor and stress inversion solutions of acoustic emissions during compression and tensile fracturing in crystalline rocks

We investigate the accuracy and robustness of moment tensor(MT)and stress inversion solutions derived from acoustic emissions(AEs)during the laboratory fracturing of prismatic Barre granite specimens.Pre-cut flaws in the specimens introduce a complex stress field,resulting in a spatial and temporal variation of focal mechanisms.Specifically,we consider two experimental setups:(1)where the rock is loaded in compression to generate primarily shear-type fractures and(2)where the material is loaded in indirect tension to generate predominantly tensile-type fractures.In each test,we first decompose AE moment tensors into double-couple(DC)and non-DC terms and then derive unambiguous normal and slip vectors using k-means clustering and an unstructured damped stress inversion algorithm.We explore temporal and spatial distributions of DC and non-DC events at different loading levels.The majority of the DC and the tensile non-DC events cluster around the pre-cut flaws,where macro-cracks later develop.Results of stress inversion are verified against the stress field from finite element(FE)modeling.A good agreement is found between the experimentally derived and numerically simulated stress orientations.To the best of the authors’knowledge,this work presents the first case where stress inversion methodologies are validated by numerical simulations at laboratory scale and under highly heterogeneous stress distributions.

Identification of acoustic emission signal in aluminum alloys spot welding based on fractal theory

The acoustic emission signal of aluminum alloys spot welding includes the information of forming nugget and is one of the important parameters in the quality control. Due to the nonlinearity of the signals, classic Euclidean geometry can not be applied to depict exactly. The fractal theory is implemented to quantitatively describe the characteristics of the acoustic emission signals. The experiment and calculation results show that the box counting dimension of acoustic emission signal, between 1 and 2, are distinctive from different nugget areas in AC spot welding. It is proved that box counting dimension is an effective characteristic parameter to evaluate spot welding quality. In addition, fractal theory can also be applied in other spot welding parameters, such as voltage, current, electrode force and so on, for the purpose of recognizing the spot welding quality.

一种ALMAE-SWSupAE裂纹声发射信号识别算法研究

针对裂纹声发射信号的识别问题,基于大边缘自编码器(LMAE)和堆叠融合监督自编码器(SFSupAE)设计了自适应大边缘堆叠权重监督自编码(ALMAE-SWSupAE)算法。针对LMAE中的固定k值问题,引入自适应k值算法,修改h(s)运算方法解决数据溢出问题;在SFSupAE中引入子分类器的性能权重优化分配策略,并设计新的权重函数;使用铝合金试件进行拉伸裂纹实验,识别采集到的声发射信号。研究结果表明:所提出的ALMAE-SWSupAE算法法识别准确率达到98.89%,相较于SSAE、SDAE、CAE、StAE和SAE方法性能具有明显提升,并在消融实验中证明了其改进有效性。

A robust triaxial localization method of AE source using refraction path

Acoustic emission(AE)localization algorithms based on homogeneous media or single-velocity are less accurate when applied to the triaxial localization experiments.To the end,a robust triaxial localization method of AE source using refraction path is proposed.Firstly,the control equation of the refraction path is established according to the sensor coordinates and arrival times.Secondly,considering the influence of time-difference-of-arrival(TDOA)errors,the residual of the governing equation is calculated to estimate the equation weight.Thirdly,the refraction points in different directions are solved using Snell’s law and orthogonal constraints.Finally,the source coordinates are iteratively solved by weighted correction terms.The feasibility and accuracy of the proposed method are verified by pencil-lead breaking experiments.The simulation results show that the new method is almost unaffected by the refraction ratio,and always holds more stable and accurate positioning performance than the traditional method under different ratios and scales of TDOA outliers.

Chaos analysis of acoustic emission signals in spot welding process

Based on chaos time series and fractal theory, acoustic emission signals were studied in the process of spot welding. According to calculating 8 welding parameters using phase space reconstruction method, the largest Lyapunov exponents were positive values and chaos characteristics were firstly discovered from acoustic emission signals in spot welding. In order to evaluate acoustic emission signal, Hausdorff dimension is put forward to analyze and estimate chaos characteristics. The experiment and calculation results indicate that the Hausdorff dimension of acoustic emission signal is significantly distinguishable in the nuggets with different welding parameters. This research provides a new method for measuring the resistance spot welding quality.

Prediction of fracture and dilatancy in granite using acoustic emission signal cloud

The invisibility of fracture network evolution in the rock under triaxial compression seriously restricts the correlation modeling between dilatancy behavior and fracture interconnectivity.The key to solving such a challenge is strongly dependent on the accurate modeling of the spatial correlation in fracture network,which could be indirectly re-constructed by the acoustic emission(AE)signal cloud.Considering the interaction of local fractures,a cube cluster approach is established to describe the spatial correlation.The evolutional cube clusters effectively present the geometric characteristics induced by the increasing dilatancy of fracture.Two descriptors(i.e.three-axis length sum and pore fraction)are introduced to correlate cluster model with dilatancy behavior.Most fitting results support the linear correlation between two descriptors and volumetric strain,which verifies the sensitiveness of the cube cluster model to dilatancy.More importantly,by the statistical analysis of cluster structure,the cluster model shows the potential of calculating fracture angle.Moreover,a comparison between dilatancybased damage and porosity-based damage is made not to prove the best but provide an AE-based prediction of local damage evolution.Finally,four classical models for calculating fracture angle are compared.The deviations prove the huge difficulty of describing the development of the fracture network uniquely dependent on a fracture angle.The proximity of measured angle and cluster-based angle supports the effectiveness of predication by the cube cluster approach.

Study of hydraulic fracture growth behavior in heterogeneous tight sandstone formations using CT scanning and acoustic emission monitoring

Tortuous hydraulic fractures(HFs) are likely to be created in heterogeneous formations such as conglomerates, which may cause sand plugging, ultimately resulting in poor stimulation efficiency. This study aims to explore HF growth behavior in conglomerate through laboratory fracturing experiments under true tri-axial stresses combined with computed tomography scanning and acoustic emission(AE) monitoring. The effects of gravel size, horizontal differential stress, and AE focal mechanisms were examined. Especially, the injection pressure and the AE response features during HF initiation and propagation in conglomerate were analyzed. Simple HFs with narrow microfractures are created in conglomerate when the gravels are considerably smaller than the specimen, whereas complex fractures are created when the gravels are similar in size to the specimen, even under high horizontal differential stresses. Breakdown pressure and AE rates are high when a HF is initiated from the high-strength gravel. A large pressure decline after the breakdown may indicate the creation of a planar and wide HF. Analyzing the focal mechanism indicates that the shear mechanism generally dominates with an increase in the HF complexity. Tensile events are likely to occur during HF initiation and are located around the wellbore. Shear events occur mainly around the nonplanar and complex matrix/gravel interfaces.

Laboratory acoustic emission study for earthquake generation process

Since the similarity in size distribution of earthquakes and acoustic emissions （AE） was found in the 1960s, many laboratory studies have been motivated by the need to provide tools for the prediction of mining failures and natural earthquakes. This paper aims, on the one hand, to draw an outline of laboratory AE studies in the last 50 years, which have addressed seismological problems. Topics include the power laws in which the similarity between AEs and earthquakes is involved and progress that has been made in AE technology and laboratory AE study. On the other hand, this study will highlight some key issues intensively discussed, especially in the last three decades, such as aspects related to the pre-failure damage evolution, fault nucleation and growth in brittle rocks and discuss factors governing these processes.

A laboratory acoustic emission experiment and numerical simulation of rock fracture driven by a high-pressure fluid source

In order to improve our understanding of rock fracture and fault instability driven by high-pressure fluid sources, the authors carried out rock fracture tests using granite under a confining pressure of 80 MPa with fluid injection in the laboratory. Furthermore, we tested a number of numerical models using the FLAC;modeling software to find the best model to represent the experimental results. The high-speed multichannel acoustic emission（AE） waveform recording system used in this study made it possible to examine the total fracture process through detailed monitoring of AE hypocenters and seismic velocity.The experimental results show that injecting high-pressure oil into the rock sample can induce AE activity at very low stress levels and can dramatically reduce the strength of the rock. The results of the numerical simulations show that major experimental results, including the strength, the temporal and spatial patterns of the AE events, and the role of the fluid can be represented fairly well by a model involving（1） randomly distributed defect elements to model pre-existing cracks,（2） random modification of rock properties to represent inhomogeneity introduced by different mineral grains, and（3）macroscopic inhomogeneity. Our study, which incorporates laboratory experiments and numerical simulations, indicates that such an approach is helpful in finding a better model not only for simulating experimental results but also for upscaling purposes.

Acoustic emission characterization of microcracking in laboratory-scale hydraulic fracturing tests

Understanding microcracking near coalesced fracture generation is critically important for hydrocarbon and geothermal reservoir characterization as well as damage evaluation in civil engineering structures. Dense and sometimes random microcracking near coalesced fracture formation alters the mechanical properties of the nearby virgin material. Individual microcrack characterization is also significant in quantifying the material changes near the fracture faces （i.e. damage）. Acoustic emission （AE） monitoring and analysis provide unique information regarding the microcracking process temporally, and infor- mation concerning the source characterization of individual microcracks can be extracted. In this context, laboratory hydraulic fracture tests were carried out while monitoring the AEs from several piezoelectric transducers. In-depth post-processing of the AE event data was performed for the purpose of under- standing the individual source mechanisms. Several source characterization techniques including moment tensor inversion, event parametric analysis, and volumetric deformation analysis were adopted. Post-test fracture characterization through coring, slicing and micro-computed tomographic imaging was performed to determine the coalesced fracture location and structure. Distinct differences in fracture characteristics were found spatially in relation to the openhole injection interval. Individual microcrack AE analysis showed substantial energy reduction emanating spatially from the injection interval. It was quantitatively observed that the recorded AE signals provided sufficient information to generalize the damage radiating spatially away from the injection wellbore.

Application of quantum neural networks in localization of acoustic emission

Due to defects of time-difference of arrival localization,which influences by speed differences of various model waveforms and waveform distortion in transmitting process,a neural network technique is introduced to calculate localization of the acoustic emission source.However,in back propagation（BP） neural network,the BP algorithm is a stochastic gradient algorithm virtually,the network may get into local minimum and the result of network training is dissatisfactory.It is a kind of genetic algorithms with the form of quantum chromosomes,the random observation which simulates the quantum collapse can bring diverse individuals,and the evolutionary operators characterized by a quantum mechanism are introduced to speed up convergence and avoid prematurity.Simulation results show that the modeling of neural network based on quantum genetic algorithm has fast convergent and higher localization accuracy,so it has a good application prospect and is worth researching further more.

Investigation of active vibration drilling using acoustic emission and cutting size analysis

This paper describes an investigation of active bit vibration on the penetration mechanisms and bit-rock interaction for drilling with a diamond impregnated coring bit. A series of drill-off tests(DOTs) were conducted where the drilling rate-of-penetration(ROP) was measured at a series of step-wise increasing static bit thrusts or weight-on-bits(WOBs). Two active DOTs were conducted by applying 60 Hz axial vibration at the bit-rock interface using an electromagnetic vibrating table mounted underneath the drilling samples, and a passive DOT was conducted where the bit was allowed to vibrate naturally with lower amplitude due to the compliance of the drilling sample mountings. During drilling, an acoustic emission(AE) system was used to record the AE signals generated by the diamond cutter penetration and the cuttings were collected for grain size analysis. The instrumented drilling system recorded the dynamic motions of the bit-rock interface using a laser displacement sensor, a load cell, and an LVDT(linear variable differential transformer) recorded the dynamic WOB and the ROP, respectively. Calibration with the drilling system showed that rotary speed was approximately the same at any given WOB, facilitating comparison of the results at the same WOB. Analysis of the experimental results shows that the ROP of the bit at any given WOB increased with higher amplitude of axial bit-rock vibration, and the drill cuttings increased in size with a higher ROP. Spectral analysis of the AEs indicated that the higher ROP and larger cutting size were correlated with a higher AE energy and a lower AE frequency. This indicated that larger fractures were being created to generate larger cutting size. Overall, these results indicate that a greater magnitude of axial bit-rock vibration produces larger fractures and generates larger cuttings which, at the same rotary speed, results in a higher ROP.

Acoustic emission monitoring of rockbursts during TBM-excavated headrace tunneling at Jinping Ⅱ hydropower station

To better understand the mechanical properties of marble at Jinping II hydropower station, this paper examines the changes of brittle rocks in excavation damaged zones(EDZs) before and after excavation of tunnel with the tunnel boring machine(TBM). The paper attempts to employ the acoustic emission(AE) to study the AE characteristics and distribution of rockburst before and after TBM-excavated tunnel. It is known that the headrace tunnel #2, excavated by the drill-and-blast(D&B) method, is ahead of the headrace tunnel #3 that is excavated by TBM method. The experimental sub-tunnel #2–1, about 2000 m in depth and 13 m in diameter, between the two tunnels is scheduled. In the experimental sub-tunnel #2–1, a large number of experimental boreholes are arranged, and AE sensors are installed within 10 m apart from the wall of the headrace tunnel #3. By tracking the microseismic signals in rocks, the location, frequency, quantity, scope and intensity of the microseismic signals are basically identifed. It is observed that the AE signals mainly occur within 5 m around the rock wall, basically lasting for one day before tunnel excavation and a week after excavation. Monitoring results indicate that the rockburst signals are closely related to rock stress adjustment. The rock structure has a rapid self-adjustment capacity before and after a certain period of time during tunneling. The variations of rock stresses would last for a long time before reaching a fnal steady state. Based on this, the site-specifc support parameters for the deep tunnels can be accordingly optimized.

Fracture propagation in sandstone and slateeLaboratory experiments, acoustic emissions and fracture mechanics

Fracturing of highly anisotropic rocks is a problem often encountered in the stimulation of unconventional hydrocarbon or geothermal reservoirs by hydraulic fracturing. Fracture propagation in isotropic material is well understood but strictly isotropic rocks are rarely found in nature. This study aims at the examination of fracture initiation and propagation processes in a highly anisotropic rock, specifically slate. We performed a series of tensile fracturing laboratory experiments under uniaxial as well as triaxial loading. Cubic specimens with edge lengths of 150 mm and a central borehole with a diameter of13 mm were prepared from Fredeburg slate. An experiment using the rather isotropic Bebertal sandstone as a rather isotropic rock was also performed for comparison. Tensile fractures were generated using the sleeve fracturing technique, in which a polymer tube placed inside the borehole is pressurized to generate tensile fractures emanating from the borehole. In the uniaxial test series, the loading was varied in order to observe the transition from strength-dominated fracture propagation at low loading magnitudes to stress-dominated fracture propagation at high loading magnitudes.