Acoustic Emission Location Research Articles

Study on the acoustic and thermal response characteristics of coal samples with various prefabricated crack angles during loaded failure under uniaxial compression

In this study, uniaxial compression tests were conducted on coal samples with different-angle prefabricated cracks. Based on the test results, the effects of prefabricated crack angles on the mechanical properties, failure modes and acoustic and thermal characteristics of the samples during loaded failure were analyzed. The following research results were obtained: the prefabricated crack angle significantly influences the mechanical properties of coal samples. Both the peak stress and the peak strain increase with the increase of the prefabricated crack angle, and the relationships between them and the prefabricated crack angle satisfy quadratic functions. The fracture types of prefabricated fracture coal samples are wing-shaped cracks, inverse wing-shaped cracks and split fracture. For example, when α=90°, the coal sample experiences splitting failure. The infrared radiation temperature (IRT) and acoustic emission (AE) responses exhibit obviously distinct characteristics in different stages. The states of crack propagation in the loaded failure process can be clearly obtained by means of infrared thermal images and AE location. With the increase of the prefabricated crack angle, the change in average infrared radiation temperature and the peak AE counts vary in a similar trend, both decreasing first and increasing later.

Acoustic emission source location on a cylindrical shell structure through grouped sensors based analytical solution and data field theory

Cylindrical shell structures are widely used in the fields of mining engineering, tunneling engineering and material structures, where acoustic emission (AE) source location plays an important role in monitoring engineering fractures. The commonly used AE source location method for cylindrical shell structures has several shortcomings. First, it must select the shortest ray path from multiple possible ray paths, making it hard to derive an analytical solution and is inconvenient for iterative solutions. Moreover, a local optimal solution may be obtained through a single time event location. To address these issues, we propose an AE source location method, which combines grouped sensors based analytical solution and data field theory. Synthetic tests of 18,360 generated events with Gaussian noises (mean value = 0us, standard deviation = 2.5us) included for P-wave travel time show an average location error within 2 cm. Furthermore, the average location error of 53 pencil-lead breaks is 2.43 cm. Moreover, the results verify that it is necessary to remove the P-wave arrival time system error between sensors prior to AE event location. In conclusion, the proposed analytical solution is helpful for rapid AE location on a cylindrical shell structure, and the application of data field can overcome the local optimal problem of a single time location.

Novel method for detecting weak acoustic emission signals based on the similarity of time-frequency spectra

The acoustic emission (AE) technique has played a critical role in characterizing the fracturing process during laboratory rock mechanics experiments. However, this method is limited by low signal-to-noise ratio (S/N) because of significant noise in the measurement and environment and inaccurate AE location. Furthermore, it is difficult to distinguish two or more hits because their arrival times are very close when AE signals are mixed with strong background noise. Thus, we have developed a new method for detecting weak AE signals using the mathematical morphology (MM) character correlation of the time-frequency spectrum. The character in all hits of an AE event can be extracted from time-frequency spectra based on the theory of MM. Through synthetic and real data experiments, we determined that this method accurately identifies weak AE signals. Compared with conventional methods, our approach can detect AE signals with a lower S/N.

3-D Source Location by Neural Network for FBG Acoustic Emission Sensors

Fiber Bragg grating acoustic emission sensors have been used in many applications. In this paper, based on four fiber Bragg grating acoustic emission sensors, an acoustic emission location experiment is carried out on the surface of a cylindrical polymer-bonded explosive specimen. Due to the difference in the strain sensitivity of fiber Bragg grating in different directions, the traditional time-difference location method is not fit for fiber Bragg grating acoustic emission sensors. A 4-layer dense neural network for fiber Bragg grating acoustic emission sensors, together with a Bayesian regularization method is used to calculate the coordinates of the acoustic emission wave source. The experimental results show that the neural network location method is suitable for fiber Bragg grating acoustic emission sensors.

Acoustic emission control of tensile and compression defects for plastic carbon fiber samples reinforced with side girders

Tensile and compression tests of composite samples made of carbon fiber reinforced with side girders have been carried out. It was found that the area of active location of acoustic emission (AE) signals corresponds to the destruction of the composite, bolted and glued joints. Destruction of the carbon fiber-reinforced plastic material did not always occur in the area of the fasteners, but the sources of AE signals with the maximum total amplitude were registered in the destruction zones.

Experimental Investigation of Progressive Failure Processes Using 3D Acoustic Emission Tomography

In this paper, the potential of 3D acoustic emission (AE) tomography technique in demonstrating fracture development and delineating stress conditions was examined. Brazilian tests and uniaxial compression tests were monitored by 3D AE tomography. AE counts, AE source locations and 3D tomographic images of locally varying velocity distributions were analyzed along with stress and strain measurements. Experimental results revealed two distinct failure processes between Brazilian tests and uniaxial compression tests indicated by differences in AE counts, source locations and the temporal variation of velocity. Furthermore, the development of micro-cracks showed by the results correlated well with theoretical analysis and experimental observations. Additionally, stress patterns, failure modes and final failure planes were indicated by AE locations and velocity tomography. Three-dimensional velocity tomographic images indicated the anisotropy of samples caused by stresses as well. These results confirm the usefulness of AE tomography as a method to monitor stress induced failure and the potential of AE tomography for delineating stress conditions and predicting rock failure.

Laser structural training, artificial intelligence-based acoustic emission localization and structural/noise signal distinguishment in a thick FCEV fuel tank

Acoustic emission (AE) is present when transient elastic waves from structures are generated by various causes, such as structural cracks, fiber breakage, debonding of fibers and matrix, temperature changes, and fatigue. In AE-based structural health monitoring, the simple event counting method is unable to determine where AE occurs, so it is possible to discard a structure even if it is safe or not discard it when it is not safe. Much research on AE localization has been conducted to solve these problems. However, most of the methods have limitations with respect to isotropic material or near field conditions and cannot be applied when there is a change in the boundary conditions of the structure or obstacles. Thus, to solve these problems, a Q-switched laser capable of generating elastic waves has been used to scan and train the structures. Although this method worked effectively on thin specimens, a more advanced method is required for thick and complex structures, such as a fuel tank of a fuel cell electric vehicle (FCEV). Therefore, we propose a novel method based on artificial intelligence (AI) that can be applied to a real FCEV fuel tank fabricated with a filament winding composite. More specifically, this technique modulates the difference in characteristics between AE and laser-induced elastic waves in the frequency domain with AI. AE is simulated by a pencil lead break of the Hsu-Nielsen source. Then, AE localization is performed through cross-correlation in the time⋅frequency domains between a generated AE signal and modulated laser-induced signals obtained from AI. In addition, an experiment conducted to localize the AE that occurs at arbitrary points in real time confirms that AE localization can be performed within 2 s. Finally, an AI algorithm is proposed to distinguish between structural AE and unwanted noise to consider real-world applications and visualize the features of these two types of signals.

Characterization of damage processes in Montney siltstone under triaxial compression using acoustic emission and diagnostic imaging

SUMMARY Crack nucleation and rock failure processes in a fine-grained siltstone (Montney Formation) under triaxial compression are investigated using combined diagnostic techniques, including ultrasonic-wave measurement, acoustic-emission (AE) monitoring, computed tomography (CT) scanning, and thin-section imaging. The sample displays a weak-to-moderate inherent seismic anisotropy and noticeable stress-induced anisotropy prior to failure. No AE event was detected until the applied axial stress reached 95 per cent of the peak value. The signal-to-noise ratio is relatively low, however, and detectable AE events are more diffuse than those observed in highly brittle rocks. The AE locations correlate with a shear fracture zone imaged by CT scanning. AE moment-tensor analysis reveals that events with larger relative magnitudes are characterized by high volumetric (tensile or compressive) components, and the initiation of the failure zone is dominated by combined shear-tensile (ST) failure. Stress inversion of the AE events with high tensile components is in good agreement with the known applied stress. Microscopic imaging of thin sections from the failed sample shows that the failure zone is an en echelon structure consisting of a major fracture with branching micro and minor cracks. This failure mechanism is consistent with a ST source mechanism and is interpreted to be associated with the fine granular structure and mineral composition of Montney siltstone.

Experimental Study of Source Localization in Acoustic Emission using Triangulation Method

Conventional repair and rehabilitation techniques have proven effective only to treat damage and arrest it. Hence, the need to prevent the damage, to know the growing damage before a complete collapse is necessary. Thus, acoustic emission is a proven method for structural health monitoring, to find and rectify the damage at its early stage. The Acoustic emission technique could be directly applied for monitoring large structures made of concrete, aircrafts & bridges. It helps in recognition of structural damage prior, which helps in avoiding catastrophic failure. The proper and efficient detection of damage makes structure safer for the public. This is a low-cost & less intricate technique than conventional methods. Quantitative criteria of acoustic sensing will provide efficient diagnosis and prognosis of structural damage. This paper surmounts the triangulation method of source localization of acoustic emission. The data is gathered by the sensors and then used to know the location of damage/source and respective characteristics of the wave. MATLAB is used for defining the energy of the signals captured by the sensors. Thus, the signal parameter’s study and verification of the source’s location using sensors is justified to be correct in the acoustic emission technique.

What Controls the Presence and Characteristics of Aftershocks in Rock Fracture in the Lab?

AbstractAftershock cascades are a characteristic feature of natural seismicity, but underlying mechanisms remain debated. Here, we experimentally explore the presence or absence of aftershocks during failure of intact rock and slip on newly created laboratory faults. We show that the overall activity increase and spatial localization of acoustic emission (AE) events during fracture nucleation occurs without temporal (Omori‐type) correlations. Our analysis shows that this absence of aftershock sequences occurs even beyond peak stress and also when a macroscopic fracture has formed post peak‐stress and propagates. Instead, aftershock triggering does occur during post‐fracture stress relaxation along the newly created lab‐fault and in the presence of large‐scale stress heterogeneities, for example, imposed by a saw‐cut notch. The detected aftershocks in these cases can be described by standard seismological relationships such as a modified Omori‐Utsu relation and its associated inter‐event time distribution and productivity relation. Moreover, AE within all experiments follow the Gutenberg‐Richter relation, with smaller ‐values for triggered events compared to non‐triggered events. Performing full‐moment tensor inversions, we find that seismic events with significant isotropic, compaction components play an important role for aftershock triggering. The resulting triggered events tend to have focal mechanisms similar to their trigger. Seismic events with predominant tensile components, on the other hand, show little evidence for aftershock triggering. This opens up a new perspective on aftershocks, going beyond not only the rate‐and‐state paradigm limited to purely frictional sliding or shear events but also the mainshock attribute paradigm where mainshock attributes control aftershock patterns.

Проблемы локации источников акустической эмиссии

The accuracy of the location of acoustic emission (AE) sources in the concentrator zones (central holes 5 mm in diameter) located at a distance of 40 mm from the receiving transducers during tensile tests of steel, aluminum alloy and composite flat specimens with dimensions of 550x50x4 mm was evaluated. Calculated speed dependence of propagation of pulses on the level of their amplitude and the partial energy of the high-frequency components of the spectrum is studied. With the threshold method of signal registration, the error in the location of AE event sources arising in the near zone of the receiving transducers at a distance 𝛥L<0.1 m can significantly exceed 10% relative to the base size (B) of the location area, when B<0.5 m. Moreover, with a decrease in the distance 𝛥L<0.05 m, the level of possible error will increase, reaching 20-30% relative to the basic size of the antenna array, when recording pulses with an amplitude level um<60 dB and a fraction of the energy of high-frequency spectrum components not exceeding 10%.

Detection of source locations in RC columns using machine learning with acoustic emission data

Detecting and monitoring the damage locations of in-service reinforced concrete (RC) structures is difficult as they exhibit more complex geometries and consist of composite materials. In this study, a new method for detecting the source location of acoustic emission (AE) signals in RC structures using machine learning was introduced and tested on an in-service RC column. An impulse response test was conducted using an AE testing system to gather data regarding the source locations. Meanwhile, the source locations on the test column were generated through manual hits. The corresponding AE data were collected using a AE data acquisition system. The significant AE parameters were determined using neighborhood component analysis for feature selection to obtain a dataset for machine learning. Further, a support vector machine classifier was adopted to classify the source locations of the columns for three sensor groups. Furthermore, the source locations were predicted using feedforward backpropagation neural networks. This study validated the detectability of AE signals in RC columns and proposed a novel detection method, which can be employed to perform continuous nondestructive tests on in-service RC columns.

Acoustic emission and digital image correlation for damage evolution in brittle rocks under time-dependent tensile loading

Time-dependent rock deformation is considered to precede dynamic failure in many rock-engineering projects and natural geohazards. In order to understand long-term performance of brittle rocks, we gather mechanical load, strain, acoustic emission (AE) and digital image correlation (DIC) data to describe the evolution of damage and cracking in response to tensile loading during multi-stage relaxation experiments on inverted single edge notch bending (iSENB) specimens. The source locations of the AEs correspond to a process zone ahead and around the notch indicating the evolution of the microcracks. The results showed that the cracks first start aseismicaly under subcritical growth until 10mm from the tip of the notch and then they grow seismically by showing seismic signals in the form of acoustic emissions. It was observed that the process zone obtained by DIC is smaller than the cloud of the AE locations. This can be partially because DIC only shows surface deformation and partially because of the errors associated with the AE source locations such as ignoring anisotropic velocity, sampling rate, sensor locations, etc. Moment tensor analyses of the AE signals showed that both tensile and shear cracks are involved in the micro-scale although in the macroscopic scale the damage process is mostly considered as tensile. The results showed that microcracks start as tensile, and then continue as shear, especially at the end of the crack where the specimen experiences compression loading.

On tensile fracture of a brittle rock

Three-point bending experiments were performed to observe mode-I fracture in a series of geometrically similar, center-notched rectangular beams composed of Sioux quartzite, a stiff, hard rock with flexural tensile strength σt = 32 MPa. Acoustic emission (AE) were recorded and microcrack locations were determined to track crack growth. Digital image correlation (DIC) was used to augment the acoustic emission data. Detailed observations indicate that (i) subsize specimens of Sioux quartzite follow a size effect law, and (ii) linear elastic fracture mechanics (LEFM) can be used to explain crack growth for large specimens of Sioux quartzite, with fracture toughness KIc = 2.2 MPa m. In particular, crack lengths based on compliance from LEFM are in good agreement with those obtained from AE and DIC suggesting a small process zone for specimens with beam depth >20 times the characteristic length = (KIc/σt)2. Further, crack velocities predicted from LEFM matched those estimated from AE locations of crack tip position with time. For sufficiently sized specimens, these observations indicate that LEFM can be used to describe fracture in this stiff, hard rock.

Influence of temperature on acoustic emission source location accuracy in underground structure

An acoustic emission (AE) experiment was carried out to explore the AE location accuracy influenced by temperature. A hollow hemispherical specimen was used to simulate common underground structures. In the process of heating with the flame, the pulse signal of constant frequency was stimulated as an AE source. Then AE signals received by each sensor were collected and used for comparing localization accuracy at different temperatures. Results show that location errors of AE keep the same phenomenon in the early and middle heating stages. In the later stage of heating, location errors of AE increase sharply due to the appearance of cracks. This provides some beneficial suggestions on decreasing location errors of structural cracks caused by temperature and improves the ability of underground structure disaster prevention and control.

Identification of Similar Seismic Waves Using the Phase-Only Correlation Function and Wavelet Transform

Accurately determined acoustic emission (AE) locations provide significant information on fracture systems, such as the orientation of fractures in a geothermal reservoir. To determine the relative source locations among a group of seismic events, similar AE waveforms must be detected and the relative arrival times of the P and S waves must be determined. In this paper, a method to identify similar AE waveforms is proposed, in which wavelet transform scalograms are used to determine the phase-only correlation function. The proposed method was applied to arbitrarily selected seismic waveforms, and its feasibility was evaluated by comparing the results with those obtained when the phase-only correlation function was obtained by using Fourier transform results.

All-phase fast Fourier transform and multiple cross-correlation analysis based on Geiger iteration for acoustic emission sources localization in complex metallic structures

Nowadays, the localization and identification of acoustic emission (AE) source is widely utilized to structural health monitoring (SHM) of complex metallic structures. However, traditional AE source localization methods are generally difficult to localize and characterize AE sources in plate-like structure that has complex geometric features. To alleviate the problem, a novel AE source localization method based on all-phase fast Fourier transform and multiple cross-correlation analysis is proposed in this article. Moreover, least squares and Geiger iteration algorithm are applied to determine the coordinates of AE sources. In addition, an improved Bayesian information criterion (BIC) version named autoregressive BIC (i.e., AR-BIC) is presented to increase the accuracy of source localization. To validate the performance of the proposed approach, the classical pencil lead break tests are carried out on a 316 L stainless steel with 10 laser cladding layers. Experimental waveforms are generated from AE sources near laser cladding layers, the surface of the structure, and on its edges. Additionally, to evaluate the performance of the proposed approach in three-dimensional AE source localization, an industrial storage tank is used to acquire three-dimensional AE sources through manually striking. Finally, to further verify the effectiveness of the proposed approach, comparisons with conventional AE source location methods (i.e., PAC or SAMOS AE acquisition system, Newton’s method, and multiple cross-correlation based on Geiger algorithm) and two representative approaches (i.e., deep learning and Bayesian methodology) for localizing AE sources generated by complex metallic structures are conducted. The comparative results demonstrate the effectiveness and superiority of the proposed method in AE-based SHM of complex metallic structures.

Acoustic emission source location from P-wave arrival time corrected data and virtual field optimization method

Acoustic emission (AE) event location plays an important role in structural safety assessments. However, accurately locating an AE event is usually difficult, especially for a small structure. Interestingly, a pencil-lead break (PLB) experiment shows that the P-wave arrival time of a sensor is always significantly different (~260 µs) from that of the other sensors. This time difference is much greater than the P-wave travel time in the range of the experimental sample. Therefore, it can be inferred that there is a P-wave arrival time system error (PATSE) for each sensor. The PATSE may be due to a combined result of the sensor site effect and signal transfer delay time from the sensor to the signal storage. To handle this, a Bayesian inversion framework was built to estimate PATSEs. A synthetic test demonstrated the effectiveness of the proposed Bayesian method for noisy P-wave arrival time data. Then, Bayesian inversion was applied to 15 PLB events, which confirmed the existence of PATSE in an AE experiment for the first time. The average PATSE reached 1.47 µs without considering the P-wave arrival time significantly different sensor. The average location error of 25 PLB events was 14.30 mm and 6.58 mm for PATSE unremoved and removed data, respectively. To achieve this, a high-precision virtual field optimization location method (VFOM) was used. This demonstrates the necessity of removing the PATSEs. Finally, the AE event location performance for the PATSE unremoved and removed data was compared, where the AE events were obtained from the uniaxial compression of a red sandstone sample. The results indicated that there was a higher location detection success rate for the corrected data. The AE locations based on the corrected data were in a better correlation with the rock sample failure mode than that without correction. Moreover, increase the signal sampling frequency for AE event identification, use a real-time inverted 3D velocity model and update the PATSEs in real time could be used to further improve the AE event location accuracy.

Defect localization on rolling element bearing stationary outer race with acoustic emission technology

Accurate rotational speed information is typically required to diagnose bearing failures under variable speed conditions. This paper proposes a fault localization method to obtain the defect position on a bearing based on the spatial localization of acoustic emission (AE). Firstly, a localization model independent of accurate wave propagation velocity is established for the annular structure of the bearing. Secondly, the Akaike Information Criterion method is used to calculate the arrival time of the AE signal; the characteristic function is used for the measured signal with low signal-to-noise ratio to improve the calculation accuracy of the arrival time. Lastly, the effectiveness of the method in the fault diagnosis of rolling bearings is verified by pencil lead break tests and dynamic tests using a thrust rolling bearing. The results of the experiments demonstrate that this method can locate AE sources. Future work will involve the implementation of the proposed method on larger bearings and verification of the accuracy in industrial machines.

Acoustic emission location analysis and microcracks’ nature determination of uniaxially compressed calcitic marble hollow plates

Acoustic emission location analysis and microcracks’ nature determination of uniaxially compressed calcitic marble hollow plates