Acoustic Emission Events Research Articles

Correlation between proprioception, functionality, patient-reported knee condition and joint acoustic emissions.

Non-invasive assessment of joint status using acoustic emissions (AE) is a growing research area that has the potential to translate into clinical practice. The purpose of this study is to investigate the correlation of the knee's AE with measures of proprioception, self-assessment, and performance, as it can be hypothesised that, AE parameters will correlate with joint function metrics due to AE being recorded during interaction of the articular surfaces. Threshold to detect passive motion (TTDPM), Knee Osteoarthritis Outcome Scores (KOOS) and 5 times sit-to-stand test (5STS) were collected from 51 participant. Knee AE were recorded during cycling with 30 and 60 rpm cadences using two sensors in different frequency ranges and three modes of AE event detection. Weak (0.297, p = 0.048) to moderate (0.475, p = 0.001) Spearman's correlations were observed between longer 5STS time and AE parameters (i.e. higher median absolute energy, signal strength, longer AE event rise time and duration). Similarly, AE parameters shown correlation with lower KOOS, especially in the "Function in Sports and Recreation" and "Activities of Daily Living" subscales with correlation coefficients for higher median amplitude up to 0.441, p = 0.001 and 0.403, p = 0.004, respectively. The correlation with the TTDPM was not detected for most of the AE parameters. Additionally, a lower frequency sensor and 60 rpm cadence AE recordings showed higher correlations. Considering that this study included subjects from the general population and the number of participants with KOOS <70 was relatively small, higher correlations might be expected for clinically confirmed OA cases. Additionally, different ICCs might be expected for alternative signal parameters and proprioception assessment methods. Overall, the study confirms that AE monitoring offers an additional modality of joint assessment that reflects interaction between cartilage surfaces and can complement orthopaedic diagnostics, especially in the context of remote monitoring, drug testing, and rehabilitation.

Experimental Investigation on Rock Failure Characteristics of Large-Span Goafs Using Digital Image Correlation Analysis and Acoustic Emission Monitoring

Rockmass in deep mining is highly susceptible to large-scale collapses under high stress and blast-induced disturbances, leading to casualties and economic losses. To investigate the evolution characteristics of goaf instability and the types of seismic sources that induce instability, an experiment on goaf instability was designed under uniaxial compression conditions based on actual mining operations. The entire experimental process was monitored using digital image correlation analysis and acoustic emission monitoring. By calculating the digital speckle field on the surface of the rock specimen during the experiment, the evolution characteristics of the deformation and strain fields from the beginning of loading to complete failure were analyzed. The study explored the dynamic behavior of cracks from initiation to propagation and eventually inducing large-scale collapse. The results show that the instability process of the goaf begins with the formation of tensile cracks. As stress increases, shear cracks occur in the specimen, leading to macroscopic failure. Furthermore, based on the differences in overall microfracture types measured by RA-AF characteristic parameters during specimen failure, large amplitude acoustic emission events corresponding to the formation of dominant macroscopic cracks were selected, and the focal mechanisms of these events were inverted. The results indicate that shear failure sources are significantly more prevalent than tensile failure sources in acoustic emission events leading to goaf instability. These findings can provide useful guidance for the support design and the prevention and control of rockmass instability disasters.

Uncovering the Fracturing Mechanism of Granite Under Compressive–Shear Loads for Sustainable Hot Dry Rock Geothermal Exploitation

Shear-dominated hazards, such as induced earthquakes, pose an escalating threat to the sustainability and safety of the geothermal exploitation. Variations in fault orientations and compression–shear stress ratios exert a profound influence on the failure processes underlying these disasters. To better understand these effects on the shear failure mechanisms of hot dry rocks, mode-II fracturing tests on granites were conducted at varying loading angles (specifically, 55°, 60°, 65°, and 70°). These tests were accompanied by a comprehensive analysis of the mechanical properties, energy dissipation behavior, acoustic emission (AE) responses, and digital image correlation (DIC)-extracted displacement fields. The tensile–shear properties of stress-induced microcracks were discerned via AE characteristic parameter analysis and DIC displacement decomposition, and the mode-II fracture energy release rate was quantitatively characterized. The results reveal that with increasing compression–shear loading angles, the mechanical properties of granites are weakened, and the elastic strain energy at peak stress gradually decreases, while the slip-related dissipated energy increases. Throughout the fracturing process, the AE count progressively climbs and reaches a peak near catastrophic failure, with an upsurge in low-frequency and high-amplitude AE events. Microcrack distribution concentrates aggregation along the shear plane, reflecting the emergent displacement discontinuities evident in DIC contours. Both the AE characteristic parameter analysis and DIC displacement decomposition demonstrate that shear-sliding constitutes the paramount mechanism, and the fraction of shear-oriented microcracks and the ratio of tangential versus normal displacement escalate with increases in shear stress. This analysis is supported by the heightened propensity for transgranular microcracking events observed through scanning electron microscopy. As the shear-to-compression stress increases, the energy concentration along the shear band intensifies, with the gradient of the fitting line between cumulative AE energy and slip displacement steepening, indicative of a heightened mode-II energy release rate. These results contribute to a deeper understanding of the mode-II fracture mechanism of rocks, thereby providing a foundational basis for early warnings of shear-dominant geomechanical disasters, and improving the safety and sustainability of subsurface rock engineering.

Magnitude Clustering During Stick‐Slip Dynamics on Laboratory Faults

AbstractWe present an analysis of magnitude clustering of microfractures inferred from acoustic emissions (AEs) during stick‐slip (SS) dynamics of faulted Westerly granite samples in frictional sliding experiments, with and without fluids, under triaxial loading with constant displacement rate. We investigate magnitude clustering in time across periods during, preceding and after macroscopic slip events on laboratory faults. Our findings reveal that magnitude clustering exists such that subsequent AEs tend to have more similar magnitudes than expected. Yet, this clustering only exists during macroscopic slip events and is strongest during major slip events in fluid‐saturated and dry samples. We demonstrate that robust magnitude clustering arises from variations in frequency‐magnitude distributions of AE events during macroscopic slip events. These temporal variations indicate a prevalence of larger AE events right after (0.3–3 s) the SS onset. Hence, magnitude clustering is a consequence of non‐stationarities.

A hierarchical multistage holistic model for acoustic emission source monitoring in composites

Abstract This paper introduces a multistage smart structural health monitoring (SHM) model for carbon-fiber composites, with a focus on multiple types of acoustic emission (AE) source localization and classification. The SHM model uses time-frequency data from various AE events (such as tool drops, impact, and artificial debonding) across different zones of a composite structure. The SHM strategy demonstrates a robust smart monitoring of composites with high accuracy. Further, a hypothesis testing has been carried out that supports the superiority of a 2-stage identification process, revealing statistically significant higher accuracy and confidence intervals across all zones and AE source types. This research establishes a novel framework for solving a hierarchical multistage holistic damage source identification problem, offering robustness in identifying various damage scenarios and quantifying associated prediction uncertainties.&amp;#xD;

Characteristics of Deformation and Damage and Acoustic Properties of Sandstone in Circular Tunnel Morphology under Varying Inundation Depths

When water damage occurs in a mine, variations in the immersion levels of tunnels at different burial depths can be observed. There is a significant relationship between the stability of the surrounding rock and the depth of immersion. Therefore, studying the deformation and damage characteristics of sandstone with circular holes at varying immersion depths, along with their acoustic properties, plays a crucial role in maintaining the stability of water-rich roadways. The TAW-2000 press and static strain system were utilized to investigate the mechanical properties, crack evolution, and deformation field distribution of sandstone with circular holes at varying immersion depths. Additionally, this study analyzed the impact of immersion depth on the characteristic parameters of acoustic emission. The results indicate that immersion depth is negatively correlated with the compressive strength and modulus of elasticity of sandstone; as immersion depth increases, the duration of the compression and yield phases of the rock samples also increases, while the duration of the elastic phase remains relatively unaffected. Furthermore, greater immersion depths correspond to a decrease in the total number of cracks, although the proportion of tensile cracks increases, making the formation of secondary cracks less likely. The frequency of acoustic emission events (transient elastic waves generated by the formation, extension, or closure of tiny cracks within the rock) shows a closely correlated dynamic with the stress–time curve of the rock sample. The acoustic emission ringing counts generated by rock samples under submerged water conditions tend to stabilize with a slight increase before signs of rupture appear. Additionally, the cumulative total energy of acoustic emissions from the rock samples decreases as the water level rises. These research findings provide significant reference value for addressing issues related to water immersion and the extent of water saturation in roadways within rock engineering.

Crack propagation behavior and failure prediction of rocks with non-parallel conjugate flaws: Insights from the perspective of acoustic emission and DIC

Rock-like containing non-parallel conjugate flaws specimens (NPCFS) were prepared and uniaxial compression crack propagation tests were conducted employing acoustic emission (AE) and digital image correlation (DIC) techniques. The results show that: the angle of conjugate unilateral cracks increases, the average load-bearing capacity of the rock rises. Dominant frequencies from different conjugate defect angles exhibit distinct bimodal characteristics (low-frequency: 80–140 kHz, intermediate-frequency: 260–320 kHz). The concept of AE dominant frequency ratio β is proposed and introduced to quantify the strength of macro-scale failure of the specimens. The AE multiparameter is proposed to predict the failure load, and the mean value of failure load is predicted to be in the range of 86–93 % (failure load), the prediction interval of Ib value is in the range of 95–99 %, the prediction interval of critical slowing down variance value is in the range of 90–95 %, while the prediction interval of autocorrelation coefficient is in the range of 83–90 %. A favorable correlation was observed between AE events in NPCFS and surface deformations observed through DIC technology. Both ends of the conjugate flaw cannot propagate simultaneously; once one extends, the other ceases further expansion, forming a primary failure line that propagates towards the direction of the primary compressive stress.

Macro-micro fracture mechanism and acoustic emission characteristics of brittle rock induced by loading rate effect

The deterioration and deformation of brittle rock generally appear in railway tunnels with the operation of large buried deep tunnel. To investigate the macro-micro fracture and acoustic emission evolution characteristics of brittle rock, this paper conducted the uniaxial compression, scanning electron microscope (SEM), and acoustic emission (AE) signal monitoring under different loading rates. The results showed that the loading rate has an obvious enhancement effect on mechanical parameters. The increased loading rate extends the elastic deformation and improves the bearing strength, elastic modulus and deformation modulus. The fracture patterns include shear fracture, composite fracture, and tension fracture. The oblique shear fracture is transformed into composite fracture and tension fracture with the loading rate increasing. The microscopic fracture shows that increasing loading rate inhibits the evolution of oblique shear fractures and promotes the expansion of tensile fractures. The roughness level of tensile fractures is significantly lower than that of oblique shear fracture and composite fracture. The AE parameters and deformation behavior are characterized by simultaneous evolution. The AE amplitude changes from low-level and low-density distribution to high-level and high-density distribution as the loading rate increases. The AE activity intensity of tensile fracture is significantly greater than that of oblique shear fracture and composite fracture. The warning timeliness of cumulative AE events and cumulative AE energy is generally earlier than the AE b-value under the same loading rate, and the early warning timeliness of cumulative AE events is similar to that of cumulative AE energy.

An Experimental Assessment Using Acoustic Emission Sensors to Effectively Detect Surface Deterioration on Steel Plates

Acoustic emission (AE) testing is used for the continuous evaluation of structural integrity and the monitoring of damage evolution in structural components and materials. During operation, the environmental and loading conditions of metal structures can result in corrosion and surface wear damage. The early detection of surface degradation flaws is crucial, as they can serve as local stress concentration points, leading to crack initiation and failure. In this work, the effectiveness of AE in monitoring corrosion and surface wear flaw formation was experimentally evaluated. AE sensors were installed on steel test plates during the artificial induction of corrosion and surface wear in order to detect and record the generated AE signals. Corrosion-related AE signals typically exhibit low amplitude, count, and energy values. The direct detection of active corrosion can be challenging in noisy environments, but it can be carried out under certain conditions using dedicated AE sensor groups. Surface-wear-related AE signals exhibit high amplitude, energy, and count values, with long duration values that are associated with wear and grinding conditions. It was found that AE sensors can be utilised to detect corrosion and surface degradation events. The effectiveness of the AE method in detecting surface degradation in noisy environments can be improved by implementing a filtering methodology. This will limit the recording of noise-related signals that can mask out actual surface degradation AE events.

From Labquakes to Megathrusts: Scaling Deep Learning Based Pickers Over 15 Orders of Magnitude

AbstractThe application of machine learning techniques in seismology has greatly advanced seismological analysis, especially for earthquake detection and seismic phase picking. However, machine learning approaches still face challenges in generalizing to data sets that differ from their original training setting. Previous studies focused on retraining or transfer‐learning models for these scenarios, but require high‐quality labeled data sets. This paper demonstrates a new approach for augmenting already trained models without the need for additional training data. We propose four strategies—rescaling, model aggregation, shifting, and filtering—to enhance the performance of pre‐trained models on out‐of‐distribution data sets. We further devise various methodologies to ensemble the individual predictions from these strategies to obtain a final unified prediction result featuring prediction robustness and detection sensitivity. We develop an open‐source Python module quakephase that implements these methods and can flexibly process input continuous seismic data of any sampling rate. With quakephase and pre‐trained ML models from SeisBench, we perform systematic benchmark tests on data recorded by different types of instruments, ranging from acoustic emission sensors to distributed acoustic sensing, and collected at different scales, spanning from laboratory acoustic emission events to major tectonic earthquakes. Our tests highlight that rescaling is essential for dealing with small‐magnitude seismic events recorded at high sampling rates as well as larger magnitude events having long coda and remote events with long wave trains. Our results demonstrate that the proposed methods are effective in augmenting pre‐trained models for out‐of‐distribution data sets, especially in scenarios with limited labeled data for transfer learning.

Experimental study on mechanical and acoustic emission characteristics of red sandstone containing combined flaws of hole-fissure under biaxial compression

To investigate the mechanical behaviour and failure mechanism of flawed rock masses under biaxial stress conditions, a series of biaxial compression experiments are conducted on red sandstone specimens containing combined flaws of the circular hole and perforated symmetric fissure combined with acoustic emission (AE) technology in this work. The results show a close association between the stress-strain curve morphology and confining stress, both the biaxial compression strength and elastic modulus exhibit an upward trend with increasing fissure angle and confining stress. The maximum AE energy and cumulative AE energy both increase with higher confining stress. The crack types in the specimens are identified by analyzing the AF/RA value distribution, revealing a gradual decrease in the percentage of tensile cracks with increasing fissure angle. An AE localization algorithm based on the least absolute value method is applied to pinpoint AE events during biaxial compression, and AE events distribution is analyzed through the Kernel density estimation (KDE). The crack extension behaviour is described based on the movement of the maximum kernel density points, which initially exhibits a progression from both ends of the specimen towards the central region and subsequently from the central fissure tip towards the two ends.

Acoustic Emission Measurements During a Four-Point Bending Test on a Reinforced Concrete Specimen

Acoustic emission (AE) measurements were carried out during a four-point bending test to in-vestigate the influence of the shear load-bearing capacity of reinforced concrete beams (so-called Leonhardt beam) with shear reinforcement. The results of AE measurements show that the AE activity begins immediately after starting loading. During the test approximately 3.500 AE events could be automatically located using longitudinal and transverse wave arrival times. Most AE events are in the central region of the specimen within the sensor network. Therefore, only the flexural tensile cracks are represented through AE locations. The transverse shear crack that occurred during the ultimate failure of the specimen is outside the sensor arrangement and has not been detected. Due to the localization error, the AE events are distributed in a cloud-like manner, and as a result, they do not sharply depict the macroscopic flexural tensile cracks. Ra-ther, acoustic emission indicates that a crack network of many small microscopic cracks formed in the tensile area, resulting in a very rough and fragmented crack morphology. Additional to the conventional source location, we applied the so-called collapsing method to highlight structures already inherent within the unfocused AE events clouds.

Classification of Crack Coordinates through Wavelet - Analysis and CNN: Analysis of Data Preparation and Network Structure

For the two-dimensional localization of acoustic emission events (AE), artificial intelligence (AI) was applied. AE events were generated by breaking pencil leads on a granite plate measuring with dimensions of 50 cm × 50 cm × 6 cm. A total of 128 measurements were carried out at each of the 81 positions on the top surface of the granite plate. The recorded signals with 16 channels were processed using continuous wavelet transformation (CWT). The resulting RGB images served as input data for a convolutional neural network (CNN). The transformed images of the measured AE signals were converted into a four-dimensional input by considering them as deeper input, allowing for improved data capture. The result was analysed using a binary classifier according to the one-versus-all method. However, due to limited computational capacity, processing the four-dimensional data posed a challenge, resulting in significant programming effort. The results of this investigation provide insights into the potential of using AI for the localization of AE events.

Localization of AE sources in rocks improved by enhanced arrival time localization

Accurate localization of Acoustic Emission (AE) events in rock structures is crucial for investigating rock failure mechanisms. This paper presents a comprehensive analysis of 3D AE localization in basalt-type rock samples, utilizing a novel combination of three powerful techniques: the Simulated Annealing Algorithm (SAA), an innovative AIC-EEMD picking method, and a velocity-free approach to wave propagation. We employed a localized Hsu–Nielsen source to generate elastic waves, which were captured by six AE sensors strategically placed on the rock surface. To address challenges in identifying P-wave arrivals, particularly in noisy or spurious data, we developed an innovative technique that integrates the Akaike Information Criterion (AIC) with Empirical Ensemble Mode Decomposition (EEMD) to enhance signal clarity. The performance of our proposal was validated achieving an average absolute distance error of 3.74 mm. Compared to traditional methods, our technique demonstrates superior accuracy and offers enhanced robustness in the presence of noise.

Signal detection

Acoustic emission (AE) occurring in concrete fracture process is a combination of concrete fracture at local material level and the propagation of induced elastic waves at structural level. Simulation of the fracture-induced AE in concrete needs a model that is able to address the fracture behavior and the wave propagation at the same time. However, to date, no available modelling tools can simulate the whole fracture-induced AE process. Among others, the lattice models have the potential to achieve the simulation of the whole fracture-induced AE process. However, the lattice models are currently restricted to statistical analysis of AE events in fracture process. This paper investigates the feasibility and limitation of lattice model for the simulation of elastic wave propagation process. Several simulation cases are performed considering the propagation of both plane waves and point-source waves. The simulation results, in terms of wave velocity and geometric spreading loss of wave amplitudes, agree well with the analytical solutions. This study represents the first step for the simulation of complete fracture-induced AE waves in concrete.

Experimental investigation on the influence of weak interlayers on sandstone rockburst and associated microcracking mechanism

Weak interlayers (WI) are common in sedimentary rock masses in deep coal mines. The qualitative effect of the WI on rockbursts is widely acknowledged; however, its influence mechanism still needs further investigation. In the present study, true triaxial unloading rockburst tests of sandstone with WI and calcite veins (CV) were conducted to explore their influence mechanisms. To explore the impact of WI, the rockburst stress, failure modes, acoustic emission (AE) parameters (energy, entropy, and b-value), and spatial energy characteristics of AE events were analyzed. The influence of the area ratio of WI and their distribution patterns (centralization and dispersion) on rockburst were further investigated. The results indicate that the rockburst stress (peak of maximum principal stress) decreased by 4 % for every 1 % increase in the sandstone's dispersion WI area ratio (1.9%–9.3 %). Namely, rockburst is more likely to occur when there is appropriate WI distributed in the sandstone because WI exacerbates the microcrack activities and energy release. The CV will reduce the weakening effect of WI on rockburst stress and can enhance the rockburst intensity, especially in samples with dispersion WI. Moreover, the more considerable AE energy is released around CV for the sandstone with dispersion WI. The interface between WI and matrix is prone to rockburst for the sandstone with centralized WI because of the concentrated energy release. The results of this paper can provide a reference for the prevention and control of rockbursts in mine sedimentary rocks containing WI and CV.

A lattice modelling framework for fracture-induced acoustic emission wave propagation in concrete

To date, there is no comprehensive approach available that can explicitly model the complete transient waveforms of acoustic emissions (AE) induced by fracture processes in brittle and quasi-brittle materials like concrete. The complexity of AE modelling arises from the intricate coupling between the local discontinuity of material fracturing and the global continuity of elastic wave propagation in solids. Among others, the lattice type models are promising approaches, as they are known to be a matured modelling approach to simulate the fracturing process in concrete-like materials. Nevertheless, like other discrete element methods (DEM), they are currently limited to describing the number and rate of AE events (broken elements) in the fracture process and cannot explicitly model wave generation and propagation. In this study, we propose a lattice modeling framework to simulate the propagation of complete waveforms of fracture-induced AE signals in concrete. A proportional-integral-derivative (PID) control algorithm is incorporated in an explicit time integration procedure to reduce dynamic noise from spurious oscillations. Additionally, a Rayleigh damping-based calculation method and corresponding calibration procedure are proposed to model the attenuation of AE signals due to material damping. Using the developed approach, we systematically investigate the feasibility of lattice models for elastic wave propagation simulation, the dependence of lattice mesh sizes and the choice of numerical damping parameters. These results lead to a systematic framework which can be employed in simulating wave propagation with attenuation using DEM models in general including lattice models.

An Approach to Calculate Source Locations for Thicker Plates when Acoustic Emission Signals are Dominated by Trailing Waves

In many acoustic emission (AE) applications, signal arrival times from an array of sensors are coupled with an appropriate velocity to calculate the source location of AE events. To date, the AE signals present in these applications are Lamb and/or Rayleigh waves. In a previous publication [1], finite element modeled (FEM) AE signals in thicker plates were dominated by trailing wave (TW) packets, when no Rayleigh wave was present. The typical character of the TW dominated signals was described as a spaced-in-time train of short-in-time wave packets. Further, it was pointed out, that when TW dominate the signals, it is not clear how arrival times for source location calculations might be obtained along with an appropriate propagation velocity. The goal of this work is to develop a source location approach for cases of dominant TWs in the AE signals in thicker plates. The FEM-signal database from the previous publication was used for this study. The database consisted of in-plane dipole sources at five different depths and four different steel plate thicknesses (50, 75, 100 and 125 mm). Bottom-surface out-of-plane displacement signals versus time for propagation distances from 250 to 1500 mm were examined. The FEM signals were frequency filtered to examine a broadband case of 80 to 500 kHz and a narrowband case of 100 to 300 kHz. To study the potential source location accuracy, a total of seven four-sensor arrays were employed. The study results describe a process to select appropriate arrival times and obtain a propagation “velocity.” This information was used to calculate source locations for the sensor arrays. The location errors were shown to be less than the plate thickness.

Optical fiber sensors for acoustic emission monitoring

Acoustic emission sensors are most of the time based on piezoelectric sensors, which may not be suited for harsh environments or be too bulky to integrate a large number of them. We present here a system based on Fiber Bragg gratings on optical fibers to measure acoustic emission events. The use of such sensors enables a low intrusivity and measurements in extreme environments. The system is designed to enable measurements under varying environmental conditions, enabling its use in real applications.

Experimental study of type-I crack propagation in rock monitored by fiber Bragg grating

The occurrence of rock mass engineering disasters can be reduced significantly by obtaining the key information in the process of rock internal fracture accumulation and evolution through advanced monitoring means and taking certain preventive measures. Through fiber Bragg grating monitoring tests of the type-I crack propagation in rock, the spectral characteristics of the fiber Bragg grating in the process of rock failure were analyzed, the bandwidth expansion was extracted to characterize the local tensile strain during the crack propagation process, and the damage variable based on the bandwidth expansion was calculated to describe the type-I crack propagation process. The research results showed the following: (1) The fiber Bragg grating generated a non-uniform local tensile strain during type-I crack propagation. The bandwidth expansion of the wave spectrum was positively correlated with the local tensile strain. The change in the characteristics of the wave spectrum could provide the local real strain in the process of crack propagation. (2) During the steady propagation of the type-I crack, the bandwidth increased obviously, while the number of acoustic emission events was relatively small, and most of them were in the process zone. The gentle increase in the bandwidth corresponded to the unstable growth stage of the type-I crack, which could be used as a precursor of rock sample instability. During loading, the maximum tensile strain of the type-I crack was 6 %, while the maximum shear strain reached 1.8 %, primarily attributed to tensile failure. The average value of fracture toughness KIC, based on the equivalent linear elastic fracture mechanics model, was determined to be 1.21 MPa·m1/2, and the average value of fracture energy Gf was calculated as 57.7 N/m. The variation of peak reflectivity in fiber Bragg grating was associated with the closure of pre-existing defects and the propagation of microcracks in rocks, resulting in unstable shear strain at crack extension sites. (3) The damage variable D defined by the bandwidth broadening began to become concentrated and accumulated in the crack steady growth stage, and it increased slowly in the crack intensification and evolution stage. The grating was sensitive to changes when it was pasted to the surface at 90°, but it could easily fracture or become unable to capture spectral signals in time. Based on a comprehensive comparison, the monitoring effect was the best when the grating was pasted at 60° relative to the crack.