Mechanical properties and acoustic emission characteristics of soft rock with different water contents under dynamic disturbance

Uniaxial compression tests and cyclic loading acoustic emission tests were conducted on 20%,40%,60%,80%,dry and saturated muddy sandstone by using a creep impact loading system to investigate the mechanical properties and acoustic emission characteristics of soft rocks with different water contents under dynamic disturbance.The mechanical properties and acoustic emission characteristics of muddy sandstones at different water contents were analysed.Results of experimental studies show that water is a key factor in the mechanical properties of rocks,softening them,increasing their porosity,reducing their brittleness and increasing their plasticity.Under uniaxial compression,the macroscopic damage characteristics of the muddy sandstone change from mono-bevel shear damage and‘X’type conjugate bevel shear damage to a roadway bottom-drum type damage as the water content increases.Dynamic perturbation has a strengthening effect on the mechanical properties of samples with 60%and less water content,and a weakening effect on samples with 80%and more water content,but the weakening effect is not obvious.Macroscopic damage characteristics of dry samples remain unchanged,water samples from shear damage and tensile–shear composite damage gradually transformed into cleavage damage,until saturation transformation monoclinic shear damage.The evolution of acoustic emission energy and event number is mainly divided into four stages:loading stage(Ⅰ),dynamic loading stage(Ⅱ),yield failure stage(Ⅲ),and post-peak stage(Ⅳ),the acoustic emission characteristics of the stages were different for different water contents.The characteristic value of acoustic emission key point frequency gradually decreases,and the damage degree of the specimen increases,corresponding to low water content—high main frequency—low damage and high water content—low main frequency—high damage.

Predicting microseismic,acoustic emission and electromagnetic radiation data using neural networks

Microseism,acoustic emission and electromagnetic radiation(M-A-E)data are usually used for predicting rockburst hazards.However,it is a great challenge to realize the prediction of M-A-E data.In this study,with the aid of a deep learning algorithm,a new method for the prediction of M-A-E data is proposed.In this method,an M-A-E data prediction model is built based on a variety of neural networks after analyzing numerous M-A-E data,and then the M-A-E data can be predicted.The predicted results are highly correlated with the real data collected in the field.Through field verification,the deep learning-based prediction method of M-A-E data provides quantitative prediction data for rockburst monitoring.

Identifying the real fracture hidden in rock microcrack zone by acoustic emission energy

Identifying the real fracture of rock hidden in acoustic emission(AE)source clusters(AE-depicted microcrack zone)remains challenging and crucial.Here we revealed the AE energy(representing dissipated energy)distribution rule in the rock microcrack zone and proposed an AE-energy-based method for identifying the real fracture.(1)A set of fracture experiments were performed on granite using wedgeloading,and the fracture process was detected and recorded by AE.The microcrack zone associated with the energy dissipation was characterized by AE sources and energy distribution,utilizing our selfdeveloped AE analysis program(RockAE).(2)The accumulated AE energy,an index representing energy dissipation,across the AE-depicted microcrack zone followed the normal distribution model(the mean and variance relate to the real fracture path and the microcrack zone width).This result implies that the nucleation and coalescence of massive cracks(i.e.,real fracture generation process)are supposed to follow a normal distribution.(3)Then,we obtained the real fracture extension path by joining the peak positions of the AE energy normal distribution curve at different cross-sections of the microcrack zone.Consequently,we distinguished between the microcrack zone and the concealed real fracture within it.The deviation was validated as slight as 1–3 mm.

Mechanical anisotropy associated with beddings in shale under Brazilian test conditions:Insights from acoustic emission statistics

A comprehensive understanding of shale’s bedding anisotropy is crucial for shale-related engineering activities,such as hydraulic fracturing,drilling and underground excavation.In this study,seven Brazilian tests were conducted on shale samples at different bedding orientations with respect to the loading direction(0°,45°and 90°)and the disc end face(0°,45°and 90°).An acoustic emission(AE)system was employed to capture the evolution of damage and the temporal-spatial distribution of microcracks under splitting-tensile stress.The results show that the Brazilian tensile strength decreases with increasing bedding inclination with respect to the disc end face,while it increases with the angle between bedding and loading directions.Increasing the bedding inclination with respect to the end face facilitates the reduction in b value and enhances the shale’s resistance to microcrack growth during the loading process.Misalignment between the bedding orientation and the end face suppresses the growth of mixed tensile-shear microcracks,while reducing the bedding angle relative to the loading direction is beneficial for creating mixed tensile-shear and tensile cracks.The observed microscopic failure characteristics are attributed to the competing effects of bedding activation and breakage of shale matrix at different bedding inclinations.The temporal-spatial distribution of microcracks,characterized by AE statistics including the correlation dimension and spatial correlation length,illustrates that the fractal evolution of microcracks is independent of bedding anisotropy,whereas the spatial distribution shows a stronger correlation.The evolution features of correlation dimension and spatial correlation length could be potentially used as precursors for shale splitting failure.These findings may be useful for predicting rock mass instability and analyzing the causes of catastrophic rupture.

Laboratory visualization of damage asymmetry formation of rock fracture via acoustic emission and digital imaging correlation

Rock fracture mechanics and accurate characterization of rock fracture are crucial for understanding a variety of phenomena interested in geological engineering and geoscience.These phenomena range from very large-scale asymmetrical fault structures to the scale of engineering projects and laboratory-scale rock fracture tests.Comprehensive study can involve mechanical modeling,site or post-mortem investigations,and inspection on the point cloud of the source locations in the form of earthquake,microseismicity,or acoustic emission.This study presents a comprehensive data analysis on characterizing the forming of the asymmetrical damage zone around a laboratory mixed-mode rock fracture.We substantiate the presence of asymmetrical damage through qualitative analysis and demonstrate that measurement uncertainties cannot solely explain the observed asymmetry.The implications of this demonstration can be manifold.On a larger scale,it solidifies a mechanical model used for explaining the contribution of aseismic mechanisms to asymmetrical fault structures.On a laboratory scale,it exemplifies an alternative approach to understanding the observational difference between the source location and the in situ or post-mortem inspection on the rock fracture path.The mechanical model and the data analysis can be informative to the interpretations of other engineering practices as well,but may face different types of challenges.

Characteristic stress variation and microcrack evolution of granite subjected to uniaxial compression using acoustic emission methods

The size of mineral grain has a significant impact on the initiation and propagation of microcracks within rocks.In this study,fine-,medium-,and coarse-grained granites were used to investigate microcrack evolution and characteristic stress under uniaxial compression using the acoustic emission(AE),digital image correlation(DIC),and nuclear magnetic resonance(NMR)measurements.The experimental results show that the characteristic stress of each granite decreased considerably with increasing grain sizes.The inflection points of the b-value occurred earlier with an increase in grain sizes,indicating that the larger grains promote the generation and propagation of microcracks.The distribution characteristics of the average frequency(AF)and the ratio of rise time to amplitude(RA)indicate that the proportion of shear microcracks increases with increasing grain size.The NMR results indicate that the porosity and the proportion of large pores increased with increasing grain size,which may intensify the microcrack evolution.Moreover,analysis of the DIC and AE event rates suggests that the high-displacement regions could serve as a criterion for the degree of microcrack propagation.The study found that granites with larger grains had a higher proportion of high-displacement regions,which can lead to larger-scale cracking or even spalling.These findings are not only beneficial to understand the pattern of microcrack evolution with different grain sizes,but also provide guidance for rock monitoring and instability assessment.

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.

Enhancing microseismic/acoustic emission source localization accuracy with an outlier-robust kernel density estimation approach

Monitoring sensors in complex engineering environments often record abnormal data,leading to significant positioning errors.To reduce the influence of abnormal arrival times,we introduce an innovative,outlier-robust localization method that integrates kernel density estimation(KDE)with damping linear correction to enhance the precision of microseismic/acoustic emission(MS/AE)source positioning.Our approach systematically addresses abnormal arrival times through a three-step process:initial location by 4-arrival combinations,elimination of outliers based on three-dimensional KDE,and refinement using a linear correction with an adaptive damping factor.We validate our method through lead-breaking experiments,demonstrating over a 23%improvement in positioning accuracy with a maximum error of 9.12 mm(relative error of 15.80%)—outperforming 4 existing methods.Simulations under various system errors,outlier scales,and ratios substantiate our method’s superior performance.Field blasting experiments also confirm the practical applicability,with an average positioning error of 11.71 m(relative error of 7.59%),compared to 23.56,66.09,16.95,and 28.52 m for other methods.This research is significant as it enhances the robustness of MS/AE source localization when confronted with data anomalies.It also provides a practical solution for real-world engineering and safety monitoring applications.

Study on Joint Method of 3D Acoustic Emission Source Localization Simplex and Grid Search Scanning

Acoustic emission(AE)source localization is a fundamental element of rock fracture damage imaging.To improve the efficiency and accuracy of AE source localization,this paper proposes a joint method comprising a three-dimensional(3D)AE source localization simplex method and grid search scanning.Using the concept of the geometry of simplexes,tetrahedral iterations were first conducted to narrow down the suspected source region.This is followed by a process of meshing the region and node searching to scan for optimal solutions,until the source location is determined.The resulting algorithm was tested using the artificial excitation source localization and uniaxial compression tests,after which the localization results were compared with the simplex and exhaustive methods.The results revealed that the localization obtained using the proposed method is more stable and can be effectively avoided compared with the simplex localization method.Furthermore,compared with the global scanning method,the proposed method is more efficient,with an average time of 10%–20%of the global scanning localization algorithm.Thus,the proposed algorithm is of great significance for laboratory research focused on locating rupture damages sustained by large-sized rock masses or test blocks.

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.

Identification of Stability Domains for Flow Parameters in Fused Filament Fabrication Using Acoustic Emission

In Fused Filament Fabrication(FFF),the state of material flow significantly influences printing outcomes.However,online monitoring of these micro-physical processes within the extruder remains challenging.The flow state is affected by multiple parameters,with temperature and volumetric flow rate(VFR)being the most critical.The study explores the stable extrusion of flow with a highly sensitive acoustic emission(AE)sensor so that AE signals generated by the friction in the annular region can reflect the flow state more effectively.Nevertheless,the large volume and broad frequency range of the data present processing challenges.This study proposes a method that initially selects short impact signals and then uses the Fast Kurtogram(FK)to identify the frequency with the highest kurtosis for signal filtration.The results indicate that this approach significantly enhances processing speed and improves feature extraction capabilities.By correlating AE characteristics under various parameters with the quality of extruded raster beads,AE can monitor the real-time state of material flow.This study offers a concise and efficient method for monitoring the state of raster beads and demonstrates the potential of online monitoring of the flow states.

Study on Acoustic Emission Characteristics of Deformation Damage Process of Zirconia Ceramics

Zirconia ceramics have become increasingly widely used in recent years and are favored by relevant enterprises. From the traditional dental field to aerospace, parts manufacturing has been used, but there is limited research on the deformation and damage process of zirconia ceramics. This article analyzes the acoustic emission characteristics of each stage of ceramic damage from the perspective of acoustic emission, and explores its deformation process characteristics from multiple perspectives such as time domain, frequency, and EWT modal analysis. It is concluded that zirconia ceramics exhibit higher brittleness and acoustic emission strength than alumina ceramics, and when approaching the fracture, it tends to generate lower frequency acoustic emission signals.

Combined optical fiber interferometric sensors for the detection of acoustic emission

A type of combined optical fiber interferometric acoustic emission sensor is proposed. The sensor can be independent on the laser source and make light interference by matching the lengths of two arms,so it can be used to monitor the health of large structure. Theoretical analyses indicate that the system can be equivalent to the Michelson interferometer with two optical fiber loop reflectors,and its sensitivity has been remarkably increased because of the decrease of the losses of light energy. PZT is powered by DC regulator to control the operating point of the system,so the system can accurately detect feeble vibration which is generated by ultrasonic waves propagating on the surface of solid. The amplitude and the frequency of feeble vibration signal are obtained by detecting the output light intensity of interferometer and using Fourier transform technique. The results indicate that the system can be used to detect the acoustic emission signals by the frequency characteristics.

Three-dimensional analytical solution of acoustic emission source location for cuboid monitoring network without pre-measured wave velocity

To find analytical solutions of nonlinear systems for locating the acoustic emission/microseismic（AE/MS） source without knowing the wave velocity of structures, the sensor location coordinates were simplified as a cuboid monitoring network. Different locations of sensors on upper and lower surfaces were considered and used to establish nonlinear equations. Based on the proposed functions of time difference of arrivals, the analytical solutions were obtained using five sensors under three networks. The proposed analytical solutions were validated using authentic data of numerical tests and experiments. The results show that located results are consistent with authentic data, and the outstanding characteristics of the new solution are that the solved process is not influenced by the wave velocity knowledge and iterated algorithms.

Effects of sonic speed on location accuracy of acoustic emission source in rocks

To quantitatively study the location errors induced by deviation of sonic speed, the line and plane location tests were carried out. A broken pencil was simulated as acoustic emission source in the rocks. The line and plane location tests were carried out in the granite rod using two sensors and the cube of marble using four sensors, respectively. To compare the position accuracy between line and plane positions, the line poison test was also carried out on the marble surface. The results show that for line positioning, the maximum error of absolute distance is about 0.8 cm. With the speed difference of 200 m/s, the average value of absolute difference from the position error is about 0.4 cm. For the plane positioning, in the case of the sensor array of 30 cm, the absolute positioning distance is up to 8.7 cm. It can be seen that the sonic speed seriously impacts on the plane positioning accuracy. The plane positioning error is lager than the line positioning error, which means that when the line position can satisfy the need in practical engineering, it is better to use the line position instead of the plane location. The plane positioning error with the diagonal speed is the minimum one.

Three-dimensional analytical solution of acoustic emission or microseismic source location under cube monitoring network

To find the analytical solution of the acoustic emission/microseismic(AE/MS) source location coordinates, the sensor location coordinates were optimized and simplified. A cube monitoring network of sensor location was selected, and the AE/MS source localization equations were established. A location method with P-wave velocity by analytical solutions (P-VAS) was obtained with these equations. The virtual location tests show that the relocation results of analytical method are fully consistent with the actual coordinates for events both inside and outside the monitoring network; whereas the location error of traditional time difference method is between 0.01 and 0.03 m for events inside the sensor array, and the location errors are larger, which is up to 1080986 m for events outside the sensor array. The broken pencil location tests were carried out in the cross section of 100 mm×98 mm, 350 mm-length granite rock specimen using five AE sensors. Five AE sources were relocated with the conventional method and the P-VAS method. For the four events outside monitoring network, the positioning accuracy by P-VAS method is higher than that by the traditional method, and the location accuracy of the larger one can be increased by 17.61 mm. The results of both virtual and broken pencil location tests show that the proposed analytical solution is effective to improve the positioning accuracy. It can locate the coordinates of AE/MS source only using simple four arithmetic operations, without determining the fitting initial value and iterative calculation, which can be solved by a conventional calculator or Microsoft Excel.

APPLICATION OF ACOUSTIC EMISSION SENSOR IN DETECTING TOOL BREAKAGE IN MICRO-MILLING

Acoustic emission （AE） sensors are used to monitor tool conditions in micro-milling operations. Together with the microphone, the AE sensor can detect the tool breakage more accurately and more effectively by applying the wavelet analysis. The processed tool breakage technique by AE sensor is used to perform the wavelet analysis on the experimental data. Results indicate the feasibility of using the AE signals for monitoring the tool condition in micro-milling.

Acoustic emission source identification based on harmonic wavelet packet and support vector machine

In order to solve the fatigue damage identification problem of helicopter moving components, a new approach for acoustic emission （AE） source type identification based on the harmonic wavelet packet （HWPT） feature extraction and the hierarchy support vector machine （H-SVM） classifier is proposed. After a four-level decomposition of the HWPT, the energy feature of AE signals in different frequency bands is extracted, which overcomes the shortcomings of the traditional wavelet packet including energy leakage, and inflexible frequency band selection and different frequency resolutions on different levels. The H-SVM classifier is trained with a subset of the experimental data for known AE source types and tested using the remaining set of data. The results of pressure-off experiments on the specimens of carbon fiber materials indicate that the proposed approach can effectively implement the AE source type identification, and has a better performance in terms of computational efficiency and identification accuracy than the wavelet packet （WPT） feature extraction.

Space-time evolution rules of acoustic emission location of unloaded coal sample at different loading rates

By using MTS815 rock mechanics test system,a series of acoustic emission(AE) location experiments were performed under unloading confining pressure,increasing the axial stress.The AE space-time evolution regularities and energy releasing characteristics during deformation and failure process of coal of different loading rates are compared,the influence mechanism of loading rates on the microscopic crack evolution were studied,combining the AE characteristics and the macroscopic failure modes of the specimens,and the precursory characteristics of coal failure were also analyzed quantitatively.The results indicate that as the loading rate is higher,the AE activity and the main fracture will begin earlier.The destruction of coal body is mainly the function of shear strain at lower loading rate and tension strain at higher rate,and will transform from brittleness to ductility at critical velocities.When the deformation of the coal is mainly plasticity,the amplitude of the AE ringing counting rate increases largely and the AE energy curves appear an obvious ''step'',which can be defined as the first failure precursor point.Statics of AE information shows that the strongest AE activity begins when the axial stress level was 92-98%,which can be defined as the other failure precursor point.As the loading rate is smaller,the coal more easily reaches the latter precursor point after the first one,so attention should be aroused to prevent dynamic disaster in coal mining when the AE activity reaches the first precursor point.

Analysis of Dynamic Tensile Process of Fiber Reinforced Concrete by Acoustic Emission Technique

The fiber reinforced concrete has good dynamic mechanical properties. But corresponding research lacks the dynamic damage characteristics of the polypropylene fiber（fiber of low elastic modulus） and steel fiber（fiber of high elastic modulus） reinforced concrete under medium strain rate（10-6 s-1-10-4 s-1）. In order to study the effect of strain rate on the damage characteristics of fiber reinforced concrete during the full curve damage process, the real time dynamic acoustic emission（AE） technique was applied to monitor the damage process of fiber reinforced concrete at three strain rates. The AE wavelet energy spectrum in ca8 frequency band and average AE peak frequency at three strain rates were analyzed. With the accumulation of damage, the AE wavelet energy spectrum in ca8 frequency band increased first and then decreased, and the average AE peak frequency increased gradually. With the increase of strain rate, the AE wavelet energy spectrum in ca8 frequency band and average AE peak frequency decreased gradually. The polypropylene fiber content has more obvious effect on the Dynamic increase factor（DIF） of the peak stress than the steel fiber content. The theoretical basis was provided for the monitoring of dynamic damage of fiber reinforced concrete based on the AE technique.