Acoustic Emission Research Articles

Acoustic Emission (AE) based health monitoring of RC beams strengthened with mechanically anchored hybrid Fiber Reinforced Cementitious Matrix (FRCM) system

The debonding between fabric and matrix/substrate hampers the strength and durability of fiber-reinforced cementitious matrix (FRCM) strengthened elements. One of the ways to improve the performance is to use mechanical anchorages. However, damage mechanisms associated with such systems are complex, and structural health monitoring of such systems is quite challenging. While earlier studies have concentrated on monitoring the health of FRCM coupons using acoustic emission techniques, they did not account for the effect of impregnation or use of mechanical anchorages. Also, very few studies are available on the health monitoring of full-scale FRCM-strengthened specimens. The current investigation employs AE-based health monitoring to classify the damage characteristics of reinforced concrete (RC) beams strengthened with FRCM. Two strengthening strategies, with and without mechanical anchorages, are employed. The non-anchored system involves conventional strengthening using two layers of pre-impregnated fabric, while the mechanically anchored method utilizes pre-impregnated fabric and a distributed anchorage system. The AE data is then analyzed using several parameters correlated with the digital image correlation (DIC) technique. Trends of sentry function, historical index, and cumulative signal strength (CSS) provide insights into major event occurrences and changes in the underlying damage modes. Three different b-values indicate a transition from micro to macro cracks during different loading stages. On the other hand, frequency content and RA-AF analysis are employed as qualitative tools to identify the source and type of damage. The strengthened RC beams with mechanical anchorages exhibited a 20.9 % increase in flexural capacity compared to those without, as evidenced by the AE parameters and DIC techniques. Overall, the study revealed that acoustic emission health monitoring could effectively evaluate the overall condition of the strengthened system, even with the complexity of a multi-part composite system.

Examining particle size growth in twin screw granulation up to steady state with acoustic emissions

The transient evolution of granules was studied to learn new details about the underlying mechanism for continuous wet granulation in a twin-screw extruder. Sieving and a new inline PAT for particle size development was used to gain these insights. The onset for steady state was established based on observing a consistent PSD, which occurred at five times the mean residence time of the process, over a range of degrees of fill (DF; 12–30 %). The early stages of startup for granulation were captured by the inline PAT, showing different stages of granule growth for particle sizes ranging from 102 to 2230 μm. The analysis found that conveying elements have a stronger influence on granule growth at a low DF whereas the kneading zone had a stronger influence on granule growth at a higher DF. This study presents new details on this black-box process while highlighting the unique value of PAT to twin-screw granulation.

Compressive and flexural properties and damage modes of aluminum foam/epoxy resin interpenetrating phase composites reinforced by silica powder

AbstractInterpenetrating phase composites (IPCs) can combine the advantages of each component and have a good application prospect. IPCs were prepared by combining open‐cell aluminum foam (AF) and epoxy resin (EP) in three‐dimensional space in this study. Different contents of silica powder (SP, 80, 100, 120, and 140 wt%) were added to EP to improve the compressive and three‐point bending properties of IPCs. In the bending test, acoustic emission (AE) was applied to track the bending deformation of the samples, and k‐means clustering algorithm was applied to identify the damage modes. The compressive and bending properties of IPCs increased first and then decreased with the increase of SP content, and reached the maximum when the SP content was 100 wt%, with a compressive yield strength of 74.6 MPa and a bending peak load of 1.96 kN. The performance degradation was mainly attributed to the AF/EP debonding due to SP distribution at the interface. The X‐type shear band and EP/AF debonding appeared in compression failures of AF and IPCs, respectively. The AE clustering results showed that under bending load, plastic deformation of matrix (60–200 kHz) and fracture failure (230–340 kHz) modes appeared in AF, while EP/AF debonding (60–120 kHz), EP failure (120–230 kHz) and plastic deformation of foam matrix (230–250 kHz) modes appeared in IPCs.Highlights Silica powder was added to improve compressive and bending properties of IPCs. Acoustic emission was used to monitor bending of foam and IPCs firstly. k‐means clustering was used to identify and classify bending damage patterns.

A first step towards the detection of damage processes in endodontic Ni-Ti alloy files, using acoustic emission

Despite major instrumental developments over the last decade, endodontic files are still not infallible. It is well known that NiTi rotary files can break without any visible sign of deformation. Instrument breakage under combined flexion-torsion loading is still common in clinical practice. Unfortunately, breakage of this type of instrument mainly occurs in narrow canals, through pinching in the apical region. When such an incident occurs, the endodontist must adopt a debris retrieval strategy that is both stressful and not guaranteed success. This study proposes a new method for experimental damage detection leading to the fracture of Ni-Ti shape memory alloy endodontic files. It is based on the acoustic emission (AE) technique and mechanical parameters measured in real-time and image analysis. It has been shown that the AE results correlate with the damage observations and torque and force measurements recorded during the tests.Having carried out numerous root canal treatment on resin blocks, it appears that this new detection and analysis technique can be used to analyze and anticipate the first signs of damage leading to endodontic file failure. The technological development of such a method, at the level of the engine itself, associated with the act in service procedure, would constitute a revolution in the field of endodontics.

Experimental study on acoustic emission damage in precast reinforced concrete interior joints containing disc springs

To address the inferior performance of precast reinforced concrete beam-column joints compared to cast-in-place joints during earthquakes, this study designed a precast concrete frame beam-column interior joint incorporating disc springs. The disc springs, installed based on grouted sleeve connections, aimed to enhance structural ductility and mitigate seismic forces on the joints. Five joints, including one cast-in-place joint, two ordinary precast joints, and two precast joints with disc springs, were tested quasi-statically and monitored using acoustic emission technology. The precast joints had axial compression ratios of 0.2 and 0.4. Parameters such as energy, count, and b-value from acoustic emission monitoring were analyzed. The Gaussian mixture model was employed for the clustering analysis of RA-AF parameters, and a damage model was developed to evaluate performance differences among the joints in the quasi-static tests. The results indicate that precast joints with the same axial compression ratio can achieve performance similar to cast-in-place joints, with more rapid damage development at higher axial compression ratios. Installing disc springs decelerates damage progression in the later stages of loading, maintaining joint integrity for a certain period even after reaching maximum load, thereby demonstrating improved ductility. At higher axial compression ratios, the b-value curve of joints with disc springs more closely resembles that of ordinary joints. Disc springs' positive effect is more pronounced in clustering analysis and damage models, such as their lower proportion of shear fractures.

Insight into wave propagation in polyimide films and resistive grid sandwich structures towards a hybrid monitoring of hypervelocity impact

Micro-Meteoroid and Orbital Debris pose a significant threat to the safe operation of orbiting spacecraft, potentially leading to mission failure in space exploration. Quantitative characterization of hypervelocity impact (HVI) is crucial to ensure the safety and successful completion of on-orbit missions. Firstly, this study designed a three-layer sandwich structure of polyimide film with orthogonally laid resistive wires, combined with piezoelectric and resistive wire sensors, for the simultaneous acquisition of acoustic emission (AE) signals generated by HVI and measurement of perforation dimensions. Secondly, a semi-analytical finite element (SAFE) analysis of wave dispersion properties in the periodic sandwich structure is conducted with Bloch’s theorem, together with a hybrid model based on three-dimensional smoothed particle hydrodynamics and finite element methods (SPH-FEM) to comprehensively understand the AE waves and damage characteristics induced by HVI. The resulting anisotropic wave propagation characteristics with SAFE and SPH-FEM are closely matched. Thirdly, a time delay-multiplication (TDM) imaging algorithm considering wave velocity anisotropy is proposed for accurate real-time “visualization” of HVI locations. Lastly, correlations are established between projectile and perforation dimensions. The proposed algorithm for HVI multi-parameter quantification and damage detection helps evaluate the space HVI environment and HVI-induced damage to spacecraft.

Rate‐dependent mechanical properties and acoustic emission characteristic of recycled aggregate concrete under four‐point bending

AbstractThe application of recycled aggregate is crucial for waste concrete recycling, while the loading rate significantly influences the fracture behavior of recycled aggregate concrete. Herein, we investigate the effect of loading rate on the flexural and fracture behaviors of recycled aggregate concrete, along with associated acoustic emission characteristics. Results show that the flexural strength and energy absorption capacity maximum increase by 15.18% and 38.39%, respectively, as the loading rate rises. As the loading rate increases from 0.05 to 1 mm/min, peak frequency is primarily clustered in 0 ~ 75 kHz and 75 ~ 225 kHz and tends to be dense, while the b value decreases by 19.28%, 23.30%, and 30.17%, respectively. Additionally, the proportion of shear failure also decreases, which relates to the high energy release rate. Further, the multifractal spectrum α − f(α) resembles a quadratic distribution, with both multifractal intensity ∆f and spectrum width ∆α showing a downward trend as the loading rate rises.

Monitoring of damage evolution in carbon fiber reinforced polymer composites by electrical impedance tomography

Electrical impedance tomography (EIT) has been widely investigated as a nondestructive testing method for carbon fiber reinforced polymer (CFRP) composites. However, the performance of EIT method on the damage process monitoring of the composites is lack of investigation. Herein, quasi-static indentation tests were utilized to introduce damage on CFRP laminates. The damage evolution process was monitored by EIT, while the potential of distinguishing the elastic deformation stage from the plastic stage was analyzed with the aid of acoustic emission. It was found that the changes in conductivity first appeared in the non-central region. With the accumulation of damage, the conductivity changes gradually extended to the center region. The reconstructed damage images were in the crossover shape, which was consist with the micro-CT results that showed the fracture of fibers in ±45° direction. This work further promotes the application of EIT in damage process monitoring of CFRP components.

Acoustic emission and multiscale computation-guided tensile damage identification in woven composite laminates at cryogenic temperatures as low as 20 K

For laminated composite structures as key components of storage tanks serving at cryogenic temperature, it is crucial to identify the damage mechanisms for evaluating their mechanical properties and guiding structural design. In this work, the cryogenic tensile damage behavior of a thin-walled woven composite laminate was investigated through the acoustic emission (AE) monitoring and multiscale finite element (FE) computation at typical low temperatures of 153 K, 77 K and 20 K. We first established temperature-dependent constitutive laws for the microscale and mesoscale constituents of such composites based on experimental data, followed by the development of a hierarchical computational framework for modeling multiscale damage characteristics at different low temperatures. A fiber-optic acoustic emission measurement system was constructed to provide online monitoring of tensile damage of the woven composite laminates at cryogenic temperatures as low as 20 K. The comparations were made between the predicted cryogenic damage characteristics and in-situ AE signal analysis, assisted by scanning electron microscope (SEM) observations. The computed cryogenic damage evolution closely matched the AE signal identification results. The results indicate that fiber breakage and matrix cracking are the dominant cryogenic damage modes, and that the different low temperatures exert significant effects on the properties of the epoxy matrix, yarns and composite laminates. The combination of the AE monitoring system and the computational scheme provides a valuable tool for evaluating structural integrity and guiding the microstructural design of composite laminates used in cryogenic environments.

A Method for the Pattern Recognition of Acoustic Emission Signals Using Blind Source Separation and a CNN for Online Corrosion Monitoring in Pipelines with Interference from Flow-Induced Noise.

As a critical component in industrial production, pipelines face the risk of failure due to long-term corrosion. In recent years, acoustic emission (AE) technology has demonstrated significant potential in online pipeline monitoring. However, the interference of flow-induced noise seriously hinders the application of acoustic emission technology in pipeline corrosion monitoring. Therefore, a pattern-recognition model for online pipeline AE monitoring signals based on blind source separation (BSS) and a convolutional neural network (CNN) is proposed. First, the singular spectrum analysis (SSA) was employed to transform the original AE signal into multiple observed signals. An independent component analysis (ICA) was then utilized to separate the source signals from the mixed signals. Subsequently, the Hilbert-Huang transform (HHT) was applied to each source signal to obtain a joint time-frequency domain map and to construct and compress it. Finally, the mapping relationship between the pipeline sources and AE signals was established based on the CNN for the precise identification of corrosion signals. The experimental data indicate that when the average amplitude of flow-induced noise signals is within three times that of corrosion signals, the separation of mixed signals is effective, and the overall recognition accuracy of the model exceeds 90%.

Damage source localisation in complex geometries using acoustic emission and acousto-ultrasonic techniques: an experimental study on clear aligners

Passive non-destructive evaluation tools such as acoustic emission (AE) testing and acousto-ultrasonics (AU) approach present a complex problem in damage localisation in complex and nonhomogeneous geometries. A novel AU-guided AE frequency interpretation approach is proposed in this research work which aims at overcoming this limitation. For the experimental evaluation, the damage sources from a geometrically complex clear dental aligners are tested under cyclic compression load and their origins are evaluated. Despite the rapid worldwide diffusion of the clear aligners, their mechanical behaviour is poorly investigated. In this work, the frequency characteristics of the artificially simulated stress wave, generated from different dental positions of the clear aligners, are studied using the AU approach. These frequency characteristics are then used to analyse the AE signals generated by these aligners when subjected to cyclic compressive loading. In addition, the time domain characteristics of the AE signals are studied using their Time of Arrival (ToA). The Akaike Information Criterion (AIC) is used to estimate the ToA. These frequency and time domain characteristics of the AE signals are used to estimate the local damage origin in the clear dental aligners. This will help in identifying localised damage sources during the usage period of the aligners. Experimental results revealed significant damages in the left maxillary premolar and right maxillary third molar of the aligners.

Summary of Rock Damage Mechanics Classification

As an important means to study the mechanical properties and failure mechanism of rock materials and engineering mechanics, damage mechanics is often used to assist in the analysis of the failure process and mechanism of rock, metal, and other materials in the current research. In the use of damage mechanics to study the properties of rock materials and explore the deformation and failure law of rock, important research results have been achieved. The research methods of damage mechanics can be roughly divided into three types: statistical damage model, mesoscopic damage model, and continuous damage model. Based on the existing literature in hand, according to the division of damage mechanics research methods in the academic community, this paper collates and considers that the existing damage model construction can be summarized from the mechanical point of view. The pure theory is derived or fitted from the mathematical point of view. One of them is derived from the mechanism point of view, and the other is derived from the phenomenon point of view. The stress, strain, acoustic emission, and other data are analyzed and reconstructed, and both have advantages and disadvantages.

Fracture propagation characteristics of layered shale oil reservoirs with dense laminas under cyclic pressure shock fracturing

Forming a fracture network through fracturing stimulation is significant to efficiently developing shale oil resources. However, the complex lithological characteristics and dense laminas of continental shale oil strongly shield fracture propagation. The concept of "cyclic fluid injection induces rock fatigue" was introduced into shale oil fracturing technology, and the cyclic pressure shock fracturing method was designed. The horizontal well fracturing simulation experiments used prepared shale rock samples from the Permian Lucaogou Formation shale oil reservoir outcrop in Jimusar Sag, Junggar Basin. Two pressurization states were obtained through constant injection and rapid release of accumulated high pressure, corresponding to conventional and pressure shock conditions. The characteristics of fracture propagation under different fracturing methods were analyzed by combining acoustic emission monitoring and injection pressure curve response. Research has found that the dense laminas with a certain original width near the wellbore significantly inhibit the vertical propagation of hydraulic fractures (HFs), and conventional constant-rate fracturing methods make it difficult to stimulate the reservoir effectively. Fatigue fracturing can increase the complexity of near-wellbore fractures, but the HFs still tend to be arrested by the laminas. The bottom hole pressure (BHP) is artificially increased to a value far exceeding the rock breakdown pressure near the wellbore by applying the cyclic pressure shock fracturing method. It can avoid the communication between micro-cracks and horizontal laminas during the BHP constant rate increase process and overcome the inhibition of weak layers on vertical propagation. Besides, the fracture height and number of activated laminas positively correlate with the number of cycles. When the shock pressure is about 30 MPa, the fracture height of the three cycles increases by 50% compared to a single shock. In addition, the shock pressure has a more significant effect on the fracture height, and the fracture height increases significantly with the increase of shock pressure. The shock pressure increased by about 57%, and the fracture height increased by 60%. High-pressure shock has a certain effect on the naturally weak surface of the far well, which may cause the slip of the weak surface to produce AE signals. This provides a new approach for improving fracture complexity and control volume in layered shale oil reservoirs with dense laminas.

Investigation on damage behaviors of carbon fiber‐reinforced nylon 6 thermoplastic composite laminates using acoustic emission and digital image correlation techniques

Investigation on damage behaviors of carbon fiber‐reinforced nylon 6 thermoplastic composite laminates using acoustic emission and digital image correlation techniques

Experimental study of postcritical deformation stage realization in layered composites during tension using digital image correlation and acoustic emission

Experimental study of postcritical deformation stage realization in layered composites during tension using digital image correlation and acoustic emission

Acoustic emission-based delamination investigation in drilled GFRP under mixed tensile and bending cyclic loading

The drilling process can cause various defects in glass fiber-reinforced polymer (GFRP), such as delamination, which ultimately leads to damage progression, especially under fatigue loading. Therefore, the current study aims to investigate the progression of failure in drilled composites subjected to cyclic bending and tensile loads using acoustic emission (AE), image processing, and mechanical behavior monitoring. The results show tyhat the fatigue diagram consists of three stages associated with resistance of fibers and matrix against delamination propagation, stable delamination progression, and ultimate spread of failure which are accurately identified by AE and mechanical methods. Additionally, the pattern and procedure of all fatigue diagrams under all loading conditions were similar and independent of loading parameters. Results from this study provide a strategy for real-time structural health monitoring (SHM) of delamination propagation in GFRPs under multi-axial fatigue loading.

Research on failure mechanism of landslide with retaining-wall-like locked segment and instability prediction by inverse velocity method

The locked segment is critical for determining the stability of locked segment-type landslides. Research indicates that the volume expansion point marks the transition from the secondary creep stage to the tertiary creep stage in a landslide’s evolution, and also separates the stable crack growth stage from the unstable crack growth stage in the locked segment. Identifying the volume expansion point is essential for early warning and predicting locked segment-type landslides. A series of instruments (resistance strain gauges, acoustic emission system, piezoelectric acceleration sensors, etc.) were used to conduct physical model tests of the landslide with retaining-wall-like locked segment under external load on the landslide’s trailing edge. The evolution process of this landslide was analyzed through changes in slope shape and stress response characteristics. The experimental results reveal the failure mechanism of the landslide with retaining-wall-like locked segment: the upper part of the landslide thrusts and slides, the middle part squeezes and uplifts, the retaining-wall-like locked segment produces a locking effect, and compression-shear fracture of the retaining-wall-like locked segment leads to landslide failure. Based on the deformation and acoustic emission characteristics of the locked segment, a method for identifying the volume expansion point was established. This point was used as the onset of acceleration point in the inverse velocity method to predict the failure time of the locked segment-type landslides, incorporating the three-stage creep model and Fukumoto’s theory.

Research on On-Line Monitoring of Grinding Wheel Wear Based on Multi-Sensor Fusion.

The state of a grinding wheel directly affects the surface quality of the workpiece. The monitoring of grinding wheel wear state can allow one to efficiently identify grinding wheel wear information and to timely and effectively trim the grinding wheel. At present, on-line monitoring technology using specific sensor signals can detect abnormal grinding wheel wear in a timely manner. However, due to the non-linearity and complexity of the grinding wheel wear process, as well as the interference and noise of the sensor signal, the accuracy and reliability of on-line monitoring technology still need to be improved. In this paper, an intelligent monitoring system based on multi-sensor fusion is established, and this system can be used for precise grinding wheel wear monitoring. The proposed system focuses on titanium alloy, a typical difficult-to-process aerospace material, and addresses the issue of low on-line monitoring accuracy found in traditional single-sensor systems. Additionally, a multi-eigenvalue fusion algorithm based on an improved support vector machine (SVM) is proposed. In this study, the mean square value of the wavelet packet decomposition coefficient of the acoustic emission signal, the grinding force ratio of the force signal, and the effective value of the vibration signal were taken as inputs for the improved support vector machine, and the recognition strategy was adjusted using the entropy weight evaluation method. A high-precision grinding machine was used to carry out multiple sets of grinding wheel wear experiments. After being processed by the multi-sensor integrated precision grinding wheel wear intelligent monitoring system, the collected signals can accurately reflect the grinding wheel wear state, and the monitoring accuracy can reach more than 92%.

Online Vibration Detection in High-Speed Robotic Milling Process Based on Wavelet Energy Entropy of Acoustic Emission

Online Vibration Detection in High-Speed Robotic Milling Process Based on Wavelet Energy Entropy of Acoustic Emission

A study of diamond grinding wheel wear condition monitoring based on acoustic emission signals

A study of diamond grinding wheel wear condition monitoring based on acoustic emission signals