Passive Acoustic Emission Research Articles

Evaluation of Concrete Fatigue Damage with Elastic Wave-based Measurement Techniques

Fatigue damage is a progressive and permanent change in the internal material structure due to cyclic loading. The cyclic loads can be due to wind, waves, temperature variation, and traffic loads. Each cyclic load application introduces micro-damages that accumulate to induce failure. Detecting these micro-damages requires sensitive measuring techniques. Hence this research compares the sensitivity of different measuring techniques applied to fatigue experiments of concrete. The applied NDT are the passive acoustic emission technique (AET) and active ultrasonic measurements. In addition, linear variable differential transformers (LVDTs) are applied as a reference measurement. Accordingly in this research, cylindrical concrete samples are subjected to monotonic and cyclic Brazilian splitting tests. The cylinders are 100 mm in diameter and 150 mm in length. The cyclic load is applied to these samples with a loading frequency of 5 Hz. During the tests, the damage evolution is monitored with AET, ultrasonic measurements and LVDTs. There are eight AE sensors attached to the sample. The two LVDTs are positioned at the center of the sample's front and back side. Besides passively monitoring the acoustic emissions, the AET sensors are also used to do active ultrasonic measurements. The research reports the comparison conducted on the deformations and cracks measured with the LVDTs, the damage growth identified with the AET, and the change in the ultrasonic pulse velocity measurements. In addition, the study also presents the damage analysis capacity of the methods across different types of loading: monotonic, constant amplitude, and stepped fatigue loading. The comparison shows that combination of AET and ultrasonic velocity measurement is a sensitive indicator for damage growth.

Passive wall thickness monitoring using acoustic emission excitation

Erosion-corrosion is a problematic damage mechanism for the oil and gas industry. To manage the risk of erosion-corrosion networks of particle impact monitoring systems have been installed on pipelines in order to detect acoustic emission from abrasive sand particles impacting the inside surface of the pipe. It would be of value if the existing network of particle impact monitoring systems were not only capable of detecting particle impact, but also sizing the remaining wall thickness. Particle impact monitoring systems are passive and are not generally equipped for excitation. This paper explores the feasibility of using passive acoustic emission transducers for wall thickness measurement, utilizing the fact that active pulse-echo measurements can be approximated by autocorrelating diffuse acoustic waves, such as those generated by particle impact. Two measurement modalities are presented: a) time-of-flight measurements and b) resonant ultrasound spectroscopy measurements. The more usual time-of-flight based measurement is limited by the fact that acoustic emission transducers typically have sensitive bandwidths limited to <1 MHz. The relatively low frequency operation limits the use to thick wall components where the component thickness ≫ ultrasonic wavelength. In thinner walled components a resonant ultrasound spectroscopy approach is required. Experimental measurements are shown that are truly passive (with no purposeful excitation at all), and semi-passive, utilizing acoustic emission from sand impact or compressed air as the excitation source. Results show very good agreement with active measurements.

Precursors of rock failure under cyclic loading and unloading: From the perspective of energy and acoustics

The precursor characteristics of rock failure under cyclic loading and unloading are crucial to the prevention of underground engineering disasters. Taking sandstone as an example, this work conducted rock failure experiments under uniaxial cyclic loading and unloading combined with active wave velocity and passive acoustic emission (AE). The damage evolution process of rock was analyzed from the perspectives of energy, AE, and wave velocity. The results show that as the cyclic load stress level increases, the rigidity of the rock continuously increases, the proportion of elastic energy may reach a peak, and there will be an extreme time difference between the wave velocity and stress. The occurrence of the peak point of elastic energy proportion is a sufficient and unnecessary condition for the precursor characteristics of rock failure. The appearance of numerous AE events with high amplitude and high count is an effective precursor characteristic of rock failure. The stress continues to increase while wave velocity decreases is a key precursor characteristic of rock failure. There is a clear linear relationship between wave velocity drop and dissipated energy, it implies that both the which can quantitatively evaluate the rock damage under cyclic loading and unloading. The variation of wave velocity exhibits obvious anisotropic characteristics. This paper is not only a beneficial supplement to the theoretical system of rock failure precursors, but also provides new ideas and methods for rock stability monitoring and failure disaster early warning in underground engineering.

Early detection of structural damage in UHPFRC structures through the combination of acoustic emission and ultrasonic stress wave monitoring

Ultra-High-Performance Fiber-Reinforced Cementitious Composite (UHPFRC) offers several advantages compared to concrete, notably due to the strain hardening behavior under tensile actions. Structures made of this composite material are lightweight and highly durable, thanks to the UHPFRC waterproofing quality. Nonetheless, the tensile behavior leads to a different cracking pattern than conventional concrete that is not fully understood yet. This paper presents an innovative monitoring approach that combines passive acoustic emission and active ultrasonic stress wave to localize and quantify damage on a full-scale UHPFRC beam during the loading protocol. This monitoring technique involves 24 transducers that are embedded throughout a UHPFRC t-shape beam of 4.2 meters. Continuous monitoring using this unique passive and active approach enables accurate location events, such as micro-cracking within the beam. Moreover, this sensor network is able to determine the location of the macro-crack that is linked to the structural collapse just after the end of the elastic domain. This novel sensor network opens new possibilities to monitor the structural behavior and detect damage on UHPFRC structures before they affect the structural behavior in terms of deflection and strain.

Pre-Failure Strain Localization in Siliclastic Rocks: A Comparative Study of Laboratory and Numerical Approaches

We combined novel laboratory techniques and numerical modeling to investigate (a)seismic preparatory processes associated with deformation localization during a triaxial failure test on a dry sample of Berea sandstone. Laboratory observations were quantified by measuring strain localization on the sample surface with a distributed strain sensing (DSS) array, utilizing optical fibers, in conjunction with both passive and active acoustic emission (AE) techniques. A physics-based computational model was subsequently employed to understand the underlying physics of these observations and to establish a spatio-temporal correlation between the laboratory and modeling results. These simulations revealed three distinct stages of preparatory processes: (i) highly dissipative fronts propagated towards the middle of the sample correlating with the observed acoustic emission locations; (ii) dissipative regions were individuated in the middle of the sample and could be linked to a discernible decrease of the P-wave velocities; (iii) a system of conjugate bands formed, coalesced into a single band that grew from the center towards the sample surface and was interpreted to be representative for the preparation of a weak plane. Dilatative lobes at the process zones of the weak plane extended outwards and grew to the surface, causing strain localization and an acceleration of the simulated deformation prior to failure. This was also observed during the experiment with the strain rate measurements and spatio-temporally correlated with an increase of the seismicity rate in a similar rock volume. The combined approach of such laboratory and numerical techniques provides an enriched view of (a)seismic preparatory processes preceding the mainshock.

Study on acoustic characteristics of bubble interaction

Abstract Bubble flow exists widely in various hydraulic systems. The shape and size of the initial bubble deformed from a nozzle/orifice have a significant effect on the dynamic characteristics of the rising processes. In the monitoring of the sound signal of the bubble flow, it is found that the bubble will produce the sound signal when it detaches and rises, and the bubble flow pattern is related to the acoustic signal. In order to better understand the physical mechanism of passive acoustic emission, the acoustic characteristics of different nozzle arrays and gas flow rates were studied. The bubble acoustic statistical characteristics are obtained by filtering. The spectrogram based on time-frequency analysis is used to count the formation of individual bubbles and also to show the transient behaviour of bubble acoustics. Synchronous analysis is applied to study the image information and acoustic signal characteristics, the corresponding relationship between the flow pattern and the acoustic texture feature is established. This will provide a reference for predicting flow patterns through acoustic signals, and is significant for improving work efficiency and detecting faults.

Combined acoustic methods in monitoring the crack development in granite

Detecting cracks of various sizes is crucial for monitoring and predicting rock failure. This study combines two acoustic methods—the passive acoustic emission (AE) and the active ultrasonic P-wave velocity to investigate the cracking process from initiation to propagation and coalescence of rocks containing pre-existing flaws, which simulate the intrinsic defects in natural rocks or rock masses, across different scales in three-dimensional space. The resultant AE activity is found sensitive to microcracks even in the early loading stage and can be divided into three stages: quiet, stable, and high growth periods. The positions of the microcracks can be obtained with the assistance of several AE sensors. It is also found that the P-wave velocity attenuation is more sensitive to macrocracks but less sensitive to microcracks. The results indicate that combining the AE and active ultrasonic-wave methods can provide comprehensive information to evaluate the damage levels and localize the internal cracks with multiple scales in the entire cracking process of rocks. The study also indicates the potential for predicting crack coalescence and failure based on the combination of these two nondestructive methods. In addition, the findings can also be applicable in the monitoring and prediction of failure in other brittle materials.

Monitoring fatigue delamination growth in a wind turbine blade using passive thermography and acoustic emission

Damage monitoring is an essential step to understand fatigue damage growth in composite wind turbine blades and for reliable lifetime prediction. The current study is an experimental investigation of fatigue delamination induced by an intentionally embedded defect in the spar cap of a 31 m wind turbine blade. A constant cyclic flap-wise bending was applied to the blade for 320,000 cycles. Delamination growth is identified and measured by visual inspection, acoustic emission (AE), and infrared thermography of the blade surface. It was observed that the area of delaminated regions grew faster during the early cycles, then their growth rates decreased, and the interlayer cracks reached stable growth. The experiment shows fatigue delamination develops gradually in the spar cap and allows monitoring of the damage before reaching a critical stage. The ability of AE and thermography methods to detect subsurface damage is demonstrated by the identification of steady delamination growth during cyclic load. Damage localization by both methods is in good agreement with the delamination location. Most acoustic activities are spotted in the boundaries of delaminated regions, and the position of a significant number of acoustic activities with the highest energy content correlates with the location of delamination crack fronts. It is shown that the surface temperature distribution contour indicates the shape of the largest delaminated region, and the growth of the hot region area correlates with damage propagation. However, multiple delaminations through the thickness cannot be discriminated from the thermal images.

Active-Passive Joint Acoustic Emission Monitoring Test Considering the Heterogeneity of Concrete.

The heterogeneity of concrete is a major challenge for acoustic emission monitoring. A method of active-passive joint acoustic emission monitoring considering the heterogeneity of concrete is presented herein, and the time-frequency-space multi-parameter response characteristics of active and passive acoustic emission signals were studied in relation to the damage evolution of concrete. This method provides an idea of evaluating the damage state of concrete more actively and quantitatively than traditional methods. The results show that the microscopic damage model of concrete based on the acoustic emission penetrating wave velocity and amplitude is in agreement with the damage process of concrete. The standard deviation of the wave velocity up to 1000 m/s and the change rate of the amplitude up to -0.66 can be adopted as two signs that the load of concrete reached 70% of the ultimate load. The time-of-arrival localization based on variable velocity was used to correct the acoustic emission localization results, and the localization accuracy was increased by 44.74%. The damage process of concrete undergoes diverse changes; that is, the distribution of damage changes from heterogeneous to homogeneous and then back to heterogeneous. Hence, it is necessary for researchers to consider the heterogeneity of concrete when using acoustic emission monitoring. The active-passive joint acoustic emission monitoring is an effective method.

Monitoring Rheological Changes Using Acoustic Emissions for Complex Formulated Fluids Manufacturing

AbstractThe measurement capabilities of a newly developed in‐situ rheometric device based on a single passive acoustic emission sensor and machine learning algorithms were investigated. Two surfactant structured fluids demonstrating complex non‐Newtonian rheology (Power‐law and Herschel‐Bulkley models) were examined. Furthermore, a static evaluation on the laboratory scale in comparison to dynamic processing on the pilot scale was conducted. The results indicate that the machine learning algorithms of this technology can identify, in &gt; 90 % of scenarios, the correct type of rheology or the manufacturing process step across both scales. This identification is based on solving a classification problem using quadratic support vector machine learning algorithms, which have proven to deliver the most robust predictions across a choice of 24 different algorithms tested. Additionally, a new format of in situ rheology display was introduced, referred to as RRF™ factor.

Using transient energy release measurements for the in‐line characterization of non‐Newtonian fluids and fluid state in pipe flow

AbstractAlberini et al. have developed a new technology based on a passive acoustic emission (AE) sensing system that uses only a single sensor, with the goal of providing live and in‐situ measurement of rheology. For this study, three different types of fluids were selected to represent common rheological behaviours: Newtonian behaviour, non‐Newtonian behaviour with power law, and non‐Newtonian behaviour with Herschel–Bulkley relationship. By analyzing the transient energy released during the interaction between the probe and the fluid, distinct acoustic fingerprints were identified in the frequency domain. These acoustic fingerprints were found to be characteristic of the different fluids and their rheology, and were validated in triplicate. Furthermore, the results showed that the intensity of the acoustic emissions increased with higher flow rates (30 to 50 L/min). To test the correlation between flow rate and acoustic response, a neural network regression test was conducted, which demonstrated a direct correlation between AE peaks and flow rate. The neural network used was nonlinear autoregressive network with exogenous inputs (NARX), and the test involved a stepwise regression with 70% training and 30% network validation. The study also introduced the Rheology‐AE quotient, which maps fluid constituents against the acoustic signal. Results showed that this was a reliable means of deriving live rheology from a fluid's frequency domain. Finally, the results obtained from this study were validated using an offline rotational rheometer.

Sonothrombolysis with an acoustic net-assisted boiling histotripsy: A proof-of-concept study

Whilst sonothrombolysis is a promising and noninvasive ultrasound technique for treating blood clots, bleeding caused by thrombolytic agents used for dissolving clots and potential obstruction of blood flow by detached clots (i.e., embolus) are the major limitations of the current approach. In the present study, a new sonothrombolysis method is proposed for treating embolus without the use of thrombolytic drugs. Our proposed method involves (a) generating a spatially localised acoustic radiation force in a blood vessel against the blood flow to trap moving blood clots (i.e., generation of an acoustic net), (b) producing acoustic cavitation to mechanically destroy the trapped embolus, and (c) acoustically monitoring the trapping and mechanical fractionation processes. Three different ultrasound transducers with different purposes were employed in the proposed method: (1) 1-MHz dual focused ultrasound (dFUS) transducers for capturing moving blood clots, (2) a 2-MHz High Intensity Focused Ultrasound (HIFU) source for fractionating blood clots and (3) a passive acoustic emission detector with broad bandwidth (10 kHz to 20 MHz) for receiving and analysing acoustic waves scattered from a trapped embolus and acoustic cavitation. To demonstrate the feasibility of the proposed method, in vitro experiments with an optically transparent blood vessel-mimicking phantom filled with a blood mimicking fluid and a blood clot (1.2 to 5 mm in diameter) were performed with varying the dFUS and HIFU exposure conditions under various flow conditions (from 1.77 to 6.19 cm/s). A high-speed camera was used to observe the production of acoustic fields, acoustic cavitation formation and blood clot fragmentation within a blood vessel by the proposed method. Numerical simulations of acoustic and temperature fields generated under a given exposure condition were also conducted to further interpret experimental results on the proposed sonothrombolysis. Our results clearly showed that fringe pattern-like acoustic pressure fields (fringe width of 1 mm) produced in a blood vessel by the dFUS captured an embolus (1.2 to 5 mm in diameter) at the flow velocity up to 6.19 cm/s. This was likely to be due to the greater magnitude of the dFUS-induced acoustic radiation force exerted on an embolus in the opposite direction to the flow in a blood vessel than that of the drag force produced by the flow. The acoustically trapped embolus was then mechanically destructed into small pieces of debris (18 to 60 μm sized residual fragments) by the HIFU-induced strong cavitation without damaging the blood vessel walls. We also observed that acoustic emissions emitted from a blood clot captured by the dFUS and cavitation produced by the HIFU were clearly distinguished in the frequency domain. Taken together, these results can suggest that our proposed sonothrombolysis method could be used as a promising tool for treating thrombosis and embolism through capturing and destroying blood clots effectively.

Laboratory investigation of hydraulic fracturing in granitic rocks using active and passive seismic monitoring

SUMMARY Knowledge of the fracturing processes can be important for the optimization of pressurized fluid injection operations in the deep underground rock mass. Active and passive seismic monitoring techniques have been used in the field for tracking or mapping the propagating hydraulic fracture. Although both these monitoring techniques provide valuable information about the generated fracture network, it is difficult for either technique to comprehensibly identify the different processes associated with hydraulic fracturing. The combined active and passive monitoring has the potential for better characterization of the complex hydraulic fracturing phenomena. In this study, laboratory hydraulic fracturing experiments with combined active and passive seismic monitoring were conducted on true triaxially loaded Barre granite cubes with different fluid injection rates. The seismic inelastic fracturing was detected by 16 passive acoustic emission sensors, where 3678 and 2370 seismic source events were detected for the high and low injection rate experiments, respectively. For active monitoring, strong variations in the attributes of signals were observed which were transmitted through four source–receiver pairs, placed both perpendicular and parallel to the generated hydraulic fracture. Positive velocity changes were observed for active sensor pairs with ray paths passing through the generated hydraulic fracture indicating fluid permeation, whereas isolated dry deformation was characterized by a slight but permanent velocity decrease. Compared to velocity, the energy of the active signals was 1–2 orders of magnitude more sensitive to different hydraulic fracturing processes. However, the sensitivity and signatures of the active signal attributes were found to be dependent on the frequency range and direction of ray path with respect to the location of the generated fracture network. Using the coupled evaluation of the active and passive signals we were able to systematically identify various hydraulic fracturing processes including: (1) aseismic deformation, (2) fracture initiation and fluid permeation, (3) pressure build-up, (4) fracture propagation and (5) pressure release and leak-off. The results of this study showed that combining the respective advantages of active and passive seismic techniques and using both of them to monitor the failure processes can facilitate a more comprehensive understanding and better control of the hydraulic stimulations in subsurface operations.

Spatio-temporal evolution and precursory indicators of rock failure processes using acoustic emission tomography

The characterization of stress and crack development plays important part in monitoring disasters. To capture the instability enlightenment from the spatio-temporal evolution of rock damage, this paper constructs the velocity field of key nodes in the rock failure process with the active and passive collaborative acoustic emission (AE) tomography method. It realizes the exploration of the micro-crack propagation law and its potential connection with the stress environment, combining the velocity field, the AE density field, and the energy field. Furthermore, from the spatial integrity and directional evolution of the velocity field, the mutation trend coefficient (MTC) and deformation coefficient (DC) of the velocity field are proposed as precursor indicators of rock instability, respectively. Results show that the anisotropy of the velocity field increases with the aggravation of rock damage, and the stress environment controls the spatial heterogeneity of the velocity field. The most important feature of spatial heterogeneity is that there are the continuous decrease and extension of low-velocity regions and the transformation from the high velocity to the low velocity. Real-time acoustic emission monitoring of the velocity field with MTC and DC can early identify rock instability precursors and principal stress direction, which provides vital pre-alarm information for geotechnical engineering.

Flow regime identification in aerated stirred vessel using passive acoustic emission and machine learning

AbstractSmart at‐ or online process sensors, which employ machine learning (ML) to process data, have been the subject of extensive research in recent years, due to their potential for real‐time process control. In this paper, a passive acoustic emission process sensor has been used to detect gas–liquid regimes within a stirred, aerated vessel using novel ML approaches. Pressure fluctuations (acoustic emissions) in an air‐water system were recorded using a piezoelectric sensor installed on the external wall of three identical cylindrical tanks of diameter, T = 160 mm, filled to a volume of 5 L (height, H = 1.5 T). The tanks were made of either glass, steel, or aluminium, and each tank was equipped with a Rushton turbine of diameter, D = 0.35 T. The investigated flow regimes, flooding, loading, complete dispersion, and un‐gassed, were obtained by changing the air feed flow rates and by varying the impeller speed. The acoustic spectra obtained were processed to select an optimal number of features characterizing each of the regimes, and these were used to train three different ML algorithms. The pre‐processing includes a principal component analysis (PCA) step, which reduces the volume of data fed to the ML algorithms, saving computational time up to a factor of 5. The algorithms (decision tree, k‐nearest neighbour, and support vector machines) were challenged to use these features to identify the correct flow regime. Accurate predictions of the three gas–liquid regimes of interest have been achieved. The accuracy of the prediction ranges from 90% to 99%, and this difference is related to the material used for the vessel.

Cooperative P-Wave Velocity Measurement with Full Waveform Moment Tensor Inversion in Transversely Anisotropic Media.

Precise stochastic approaches to quantitatively calculate the source uncertainties offers the opportunity to eliminate the influence of anisotropy on moment tensor inversion. The effects of ignoring anisotropy were tested by using homogeneous Green’s functions. Results indicate the influence of anisotropy and noise on fault plane rotation is very small for a pure shear source whether it is restricted to double couple solution or full moment tensor solution. Green’s functions with different prior rough anisotropy information were tested, indicating that the complex source is more sensitive to velocity models than the pure shear source and the fault plane rotation caused by full moment tensor solution is larger than the pure double couple solution. Collaborative P-wave velocity inversion with active measurements and passive acoustic emission data using the fast-marching method were conducted, and new Green’s functions established based on the tomography results. The resolved fault plane solution rotated only 3.5° when using the new Green’s functions, but the presence of spurious isotropic and compensated linear vector dipole components was not completely eliminated. It is concluded that the cooperative inversion is capable of greatly improving the accuracy of the fault plane solutions and reducing the spurious components in the full moment tensor solution.

Signal Analysis of Characteristics Using Passive Acoustic Emission Technique in Gas‐Solid Pipeline Flows

This paper investigates a case study of the use of a passive acoustic sensor for online measurement of the dilute phase gas‐solid pipeline flows. The acoustic emission sensor is mounted externally on a stainless steel line conveying silica powders. For different experimental conditions, including the solid to air mass ratios from 0.6 to 1.4 and the gas volume flows from 160 to 240 m3/h, the sound signals in the pipeline are discussed using the wavelet transform technique. The measured values of transmission mechanism of two different lengths, 25 mm and 35 mm, are analyzed. The results show that the variation tendency of standard deviations is consistent and that the noninvasive, online acoustic detect technique can be regarded as a satisfactory tool in gas‐solid flows.

Quantifying the Progressive Fracture Damage of Granite Rocks by Stress–Strain, Acoustic Emission, and Active Ultrasonic Methods

The accurate identification and quantification of rock damage are important for the reliable safety assessment of rock engineering. In this paper, stress-strain behavior, passive acoustic emission (AE), and active ultrasonic transmission were measured simultaneously under uniaxial compression to characterize the fracture damage of granites. The deformation and acoustic behaviors with respect to crack initiation and crack damage thresholds were analyzed. Meanwhile, irreversible damage was quantified using different methods. The results show that the marked increase in the AE rate and the average hit energy coincide with the crack initiation stress, ranging from 0.41σc–0.45σc (uniaxial compressive strength), which occurs earlier than the decrease of the P-wave velocity and onset of the rock dilation. The moment in which the average hit energy and ratio of low-frequency AEs start to increase rapidly corresponds to the crack damage stress of 0.71σc–0.74σc. In addition, the fracture damage was quantified by the crack volumetric strain, dissipated energy, modulus loss, AE characteristics, b value (defined as the log-linear slope of the frequency-magnitude distribution of AEs), and ultrasonic properties. It is revealed that the majority of rock damage accumulates after the crack damage stress, corresponding to the appearance of most high-magnitude hypocenters. Rock damage quantified by dissipated energy and AE energy with clear physical meaning is more reasonable and less subjective. Moreover, the precipitous reduction of the b value, a sharp increase in AE energy, and the ratio of low-frequency AEs prior to peak failure is a perfect precursor of potentially brittle failure.

Identification of suspension state using passive acoustic emission and machine learning in a solid–liquid mixing system

Solid–liquid mixing is a core operation in many manufacturing processes in the food, cosmetics, pharmaceutical and chemical industries.This work aims to develop an accurate and reliable sensing methodology using passive acoustic emission (PAE) coupled with supervised machine learning (ML) algorithms, to allow identifying and predicting solid–liquid suspension state.Using PAE in process monitoring is beneficial because it is affordable, sensitive, non-intrusive, and suitable for on-line applications. PAE equipment includes a piezoelectric sensor, placed in contact with the system, an amplifier, a filter, an oscilloscope to record the signal and a computer.Experiments were carried out in a fully baffled, flat bottom glass vessel equipped with a PBT impeller. Acoustic signals were recorded with sampling frequency of 750 kHz, impeller speed range 50–1000 rpm and varying solid features, i.e., particle size (dp range 0.250–6 mm), solid loading and solid density (acryl-glass particles).For each classification run, sampled data were pre-processed using Fast Fourier Transform (FFT) to reveal any detailed spectral characteristics of the signal in the frequency domain. Spectra have been filtered and then reduced by selecting the highest variance frequencies. As labelling, established optical measurements were used to classify the acoustic frequency spectra.The frequency data set has been split in training (60%), cross validation (20%) and test (20%) sets and were used, respectively, to build the model, identify the best model parameters (optimisation step), and finally to check the accuracy (test step).The developed technique has shown excellent results in recognizing spectra corresponding to different classes with observed accuracy greater than 99.72%.

Laboratory characterisation of anisotropic and heterogeneous damage of rock sample using acoustic emission and ultrasonic monitoring technologies

Rock damage characterisation of Gosford sandstone samples under triaxial loading was achieved using an integrated approach, combing passive acoustic emission (AE) and active ultrasonic wave monitoring. The location of AE events is firstly obtained using isotropic wave velocity field measured by continuous ultrasonic wave. Then, passive AE tomography is conducted to progressively-update the anisotropy and heterogenous P-wave velocity field of rock samples. According to the variance in P-wave velocity, damage induced anisotropy and heterogeneity can be identified. The results suggest that the inhomogeneous damage evolution highly dependent on the loading stages and can well reflect the microcrack behaviour. Anisotropic damage variable along the whole loading process is also analysed, by a second order damage tensor with a transversely anisotropy assumption. It is observed that the lateral component of damage is much higher than the axial component. This is mainly due to the dilation behaviour of rock sample. This paper will cast more light on anisotropic and heterogenous damage characterisation using acoustic/ultrasonic lab experiments.