Acoustic Emission Detection Research Articles

Research on the Evolution of Shield Segment Cracks Based on Acoustic Emission and CMOD.

In order to explore the cracking law and failure characteristics of segments, a model test of shield segment cracking was conducted. The microscopic and macroscopic crack evolution process of the segment is studied by using acoustic emission detection technology and crack opening displacement (CMOD). According to the acoustic emission signal and CMOD, characteristics generated in the process of segment cracking, in the form of numerical value, the evolution characteristics of each stage of segment cracking are directly reflected. Based on acoustic emission energy and CMOD, the segment cracking damage model was established to determine the segment fracture damage degree. The result shows that segment cracking can be divided into three stages, and the acoustic emission detection results and CMOD have different degrees of change in each cracking stage. This proves that both the acoustic emission acquisition results and CMOD can be used as evaluation indicators of damage degree. Acoustic emission can accurately identify the crack evolution process, and the yield strengthening is an important stage of crack damage evolution. The damage data points in this stage account for 76.83% of all the damage data points, the occurrence rate of damage data points is 0.225 s, and the density of data points in the damaged area is 3.219 × 10−4 mm3, which is larger than the other two stages. The segment cracking damage model can effectively reflect the segment cracking degree and provide a reference for the actual segment cracking assessment.

Magnetic-Acoustic Feature Extraction and Damage Fusion Evaluation of 45 Steel Specimens during Fatigue Process for Remanufacturing

To clarify the changes of the magnetic-acoustic features of 45 steel specimens during fatigue damage, an experimental platform was built to carry out magnetic memory and acoustic emission detection. The magnetic memory and acoustic emission signals of specimens in different damage states were collected, and the multi-scale entropy characteristics of magnetic memory signals, as well as the wavelet packet energy spectrum and singularity index characteristics of acoustic emission signals, were further extracted. A magnetic-acoustic feature fusion and damage assessment model was constructed by using Naive Bayes method. Results show that the average value of multi-scale entropy of normal magnetic field intensity Hp (y) increases gradually with the increase of fatigue cycles, and the average value of multi-scale entropy of magnetic field intensity gradient K gradually decreases. The cumulative ringing count and energy spectrum (proportion of frequency band 1) of acoustic emission signals decrease with the increase of fatigue cycles, while the amplitude singularity index gradually increases. The established model has high evaluation accuracy, and the conclusions of this paper can provide basic methods and data support for fatigue damage evaluation of remanufactured components.

High-Sensitivity Demodulation of Fiber-Optic Acoustic Emission Sensor Using Self-Injection Locked Diode Laser

We demonstrate the use of a self-injection locked distributed feedback (DFB) diode laser for high-sensitivity detection of acoustic emission (AE) using a fiber-coil Fabry-Perot interferometer (FPI) sensor. The FPI AE sensor is formed by two weak fiber Bragg gratings on the ends of a long span of coiled fiber, resulting in dense sinusoidal fringes in its reflection spectrum that allows the use of a modified phase-generated carrier demodulation method. The demodulation method does not require agile tuning capability of the laser, which makes the self-injection locked laser particularly attractive for the application. Experimental results indicate that the self-injection locked laser increases the signal-to-noise ratio by ∼33 dB compared with the free-running DFB laser. We studied the mode-hopping and laser instability of the self-injection locked laser and their effect on the demodulated signal and found that a mode hopping event causes an abrupt change in the laser intensity after the resonator inside the feedback loop. It manifests itself as a short transient signal in the output of the AE sensor system. With the identification of the mode-hopping events, the associated spurious signal can be identified and discarded in the signal processing without causing significant disruption to the sensor system. Experiment shows that the frequency of locked lasers could oscillate during unstable operations. The fundamental frequency is determined by the time delay of the feedback light and is typically much larger than the AE frequency. Therefore, the laser frequency oscillations have no negative effect on the performance of the sensor system. Finally, we show that the frequency of mode-hopping occurrence is related to the length of the feedback loop and reducing the loop length can effectively reduce the frequency of mode-hopping occurrence.

Propagation of Elastic Waves in Homogeneous Media: 2D Numerical Simulation for a Concrete Specimen

This paper addresses the theoretical foundation of a localization method for crack detection in a concrete sample based on the time of arrival of the elastic wave generated by the crack formation to a group of sensors positioned on the boundary of the sample. The equations of motion for the elastic waves are carefully presented, including a body force term which accounts for the sudden formation of a crack. Then, a localization method based on the detection of acoustic emissions, and specifically on their arrival times, is described. Finally, a discretization scheme for the 2D equations of elasticity is developed, and some numerical experiments are performed to assess the validity of the method.

Design of a novel fiber grating acoustic emission sensor based on coupling cone structure

A novel fiber Bragg grating (FBG) acoustic emission (AE) sensor based on coupling cone structure is proposed in this paper, which is flexible and reusable. The sensor is fabricated by additive manufacturing technology. The numerical modeling of the coupling cone structure was performed using finite element analysis. The influence of the coupling cone angle and material on the AE detection performance was studied. The main parameters of the coupling cone structure are determined. The AE detection of material tensile tests was studied by edge-filter-demodulation of spectrum technology. The experimental results demonstrated that the coupling cone FBG AE (Cone-FBG-AE) sensor has advantages of high sensitivity, flexibility and adjustable positioning, and can be reused. It realizes real-time monitoring of AE signals in the tensile process of the specimen, which is consistent with the effect of the resonant AE sensor. The Cone-FBG-AE sensor has great application value in the fields of health monitoring, such as aero-engines, microcracks of structural defects.

Acoustic emission based grinding wheel wear monitoring: Signal processing and feature extraction

Surface grinding, being one of the later stages of a manufacturing process, is crucial to achieve the desired workpiece quality by maintaining proper wheel condition. Machine learning and acoustic emission (AE) detection have demonstrated potentials for developing an effective on-line wheel wear monitoring system. However there are inconsistencies among existing studies regarding to signal sampling and feature extraction methods. In the present paper, surface grinding experiments using medium carbon steel workpieces were conducted to determine the effects of using different signal analysis window lengths, feature types, and AE sensor bandwidths on the wheel wear detection performances. In addition, the use of AE transient spikes occurred during wheel entry and exit were analyzed. Feature were extracted from time domain (TD), frequency domain (FD), and time–frequency domain (TFD) representations of the measured AE signals, which were then refined using sequential floating forward selection (SFFS) algorithm to reduce feature redundancy. Support vector machine (SVM) algorithm with linear kernel was used for pattern classification. A number of insights for future monitoring system development were obtained. Firstly, while the lower frequency AE sensor (below 100 kHz) provided adequate classification performances, the higher frequency AE sensor (above 100 kHz) produced more robust results. Secondly, 100% classification rate was achievable using features derived from Fast Fourier Transform (FFT) in combination with descriptive statistics. Thirdly, it was determined that a window length as short as 1 ms (1000 data points) could capture enough signal information using FFT with the higher frequency AE sensor. Lastly, the choice sampling instance did not significantly impact classification outcomes.

Application of Nondestructive Testing Technology in Quality Evaluation of Plain Concrete and RC Structures in Bridge Engineering: A Review

The development and application of nondestructive testing technology for prestressed reinforced concrete structures in the field of infrastructure construction were summarized in this study via the analysis of relevant literature worldwide. The detection methods, detection principles, and detection instruments in quality evaluation of prestressed reinforced concrete structures were analyzed and compared, based on which, acoustic emission detection technology, impact echo detection technology, ultrasonic detection technology, infrared thermography detection technology, ground-penetrating radar detection technology, piezoelectric transducer detection technology, and X-ray detection technology were summarized. Additionally, the advantages, disadvantages, and application scope of each detection method were focused upon and analyzed comparatively. It is indicated that further improvement in the detection visualization, accuracy, and efficiency for most nondestructive testing technologies is available by optimizing the algorithm and combining artificial intelligence technology with neural network deep learning, precise positioning, and imaging analysis of the quality defects in prestressed reinforced concrete structures. The results of this study can provide technical reference for the further application and research of nondestructive testing technologies in the quality inspection of prestressed reinforced concrete structures.

Broadband Fiber-Optic Acoustic Sensors

A broadband fiber-optic acoustic sensing system is proposed and demonstrated, which is configured by a fiber Bragg grating (FBG) and an erbium-doped fiber (EDF) ring laser. As the acoustic waves can shift the FBG reflective spectrum, the wavelength of the laser output shifts accordingly and this shift is subsequently converted into a corresponding phase shift and demodulated by an unbalanced fiber-optic Mach-Zehnder interferometer (MZI). The sensitivity of the presented sensing system is also investigated, which is a function of the optical path difference of the MZI and the linewidth of the FBG. Due to the adaptability and high sensitivity of the system, it can detect signals with frequencies from tens of hertz to hundreds of kilohertz, which shows the potential for acoustic emission detection in real applications.

Safety Monitoring of Bearing Replacement for a Concrete High-Speed Railway Bridge Based on Acoustic Emission

As an important part of a bridge, bearings easily suffer damage when exposed to various loading and environmental changes during their lifetime. Bearing replacement should be performed in a timely manner if damage occurs to high-speed railway (HSR) bridges. The unique structural form and strict operation requirements mean that bearing replacements of HSR bridges are much more difficult than those of highway bridges. However, compared with bearing replacements of highway bridges, far fewer scientific and engineering studies have been conducted to guide the bearing replacement of HSR bridges. In this paper, based on a three-span continuous concrete box girder HSR bridge, an innovative bearing replacement method using reverse disassembly and assembly techniques is proposed and was implemented at a location under operating HSRs. In addition, safety monitoring measures were undertaken to guarantee the safety of the bridge during bearing replacement. In contrast to the usual monitoring practice focusing on the displacement and the external strain of the structure, this monitoring work adopted the acoustic emission (AE) detection technique to explore the internal structural damage formed in the process of construction. The results suggest that the proposed bearing replacement method, which requires the girder to be jacked up by no more than 9 mm, is a promising practice for this complicated construction, and the start time and evolution of damage in the concrete of a bridge during construction can be captured accurately by AE detection with a parameter-based analysis method. All practices presented in this case study can guide future bearing replacements in similar projects.

Propagation characteristics of acoustic emission waves in liquid media in near-field

Acoustic emission (AE) detection through a liquid medium is a simple and effective method that can be widely applied to AE diagnosis for rotating machinery. As AE diagnosis is performed by correlating the signal intensity with the failure level and the frequency characteristics with the failure type, it is important to clarify the propagation characteristics of AE waves in liquid media to enable accurate AE diagnosis using a simpler system that utilizes AE propagation in a liquid medium. Therefore, in this study, systematic experiments were conducted focusing on the liquid medium type and the propagation distance as factors affecting the propagation characteristics of AE waves. As the area where AE waves propagate, we mainly focused on the near-field, where AE waves do not spread and are not attenuated with the propagation distance. First, we investigated the propagation and attenuation characteristics of AE waves in the near-field using an artificial AE source in liquid media such as purified water, cutting fluid solution, and lubricating oil. Differences in attenuation characteristics with the liquid medium were observed. Moreover, the propagation distance affected the attenuation characteristics, i.e., the signal intensity decreased with increasing propagation distance in a manner depending on the viscosity of the liquid medium, especially in the frequency bandwidth range from 1.5 to 3.0 MHz. Second, we theoretically verified some of the experimental results from the viewpoint of ultrasonic propagation in a liquid medium. As a result, the observed differences in attenuation characteristics with liquid medium were explained by the acoustic impedances of the liquid media, and the attenuation of the signal intensity of AE waves with increasing propagation distance was caused by the increasing absorption coefficient with increasing viscosity of the liquid medium.

Evaluation and classification of rock heterogeneity based on acoustic emission detection

Evaluation and classification of rock heterogeneity based on acoustic emission detection

High-speed train wheel set bearing fault diagnosis and prognostics: Research on acoustic emission detection mechanism

Acoustic emission (AE) technology is suitable for the condition monitoring and fault diagnosis of high-speed train wheel set bearings (HSTWSB) owing to its high frequency and high sensitivity. However, there has been no research on the mechanism of the relationship between HSTWSB state and AE signal. Therefore, this study explores the AE detection mechanism of HSTWSB state. First, based on the structure and load characteristics of HSTWSB, combined with the Hertz contact theory, a force analysis of the whole, local, and single roller is performed. Second, based on the assumption of random distribution of asperities, a contact model of the rough surface of the bearing is established, and the elastic deformation analysis of the asperities under load is performed based on the theory of elasticity. The corresponding relationship between the asperity deformation energy and root mean square (RMS) of the AE signal is obtained. Meanwhile, considering the influence of elastohydrodynamic lubrication (EHL) and signal attenuation on the deformation energy, an AE mathematical model of the HSTWSB is established. Accordingly, based on the characteristics of HSTWSB with different damage types, the influences of the load, deformation, speed, and defect morphology on the AE signals are thoroughly analyzed, and the improved models corresponding to different damage types are established, which extends the AE model to greater freedom. Finally, taking different damage types of the outer ring fault bearings as examples, the correctness of the proposed models is verified by comparing the theoretically calculated and experimental results. The proposed models can provide theoretical support for the application of AE to bearing condition monitoring.

Acoustic emission and computed tomography investigation on fatigue failure of fissure‐contained hollow‐cylinder granite: Cavity diameter effect

AbstractThis work aims to investigate the influence of cavity diameter on fracture behaviors for fissure‐contained hollow‐cylinder granite subjected to multistage cyclic loads, using acoustic emission detection, and post‐test computed tomography (CT) scanning. The influence of the cavity diameter on rock fracture was revealed in terms of volumetric deformation, stiffness degradation, AE output activities, hole spalling, and crack coalescence pattern. The testing results show the both the volumetric strain and AE b value decrease with increasing cavity diameter. An increase of volumetric strain and a decrease of AE b value are found during rock failure and their relationship was established. In addition, damage is quantificationally characterized by the released energy, and a damage evolution model is defined to characterize rock damage process. Moreover, post‐test CT visualization highlights the communication between the hole and fissures at the rock bridge segment, and it is suggested that failure severity decreases with the increase of hole diameter.

Modified Model of Sound Velocity with Different Saturation in Fractured Sandstone

The hazards of surrounding rock sheeting, collapse and rock explosion during the excavation of underground projects can be regarded as the macroscopic dynamics of the evolutionary development of their internal fractures, mostly accompanied by acoustic emission phenomena. The application of acoustic emission detection technology can quickly determine the existence of fissures in the surrounding rock and predict their approximate location and spatial spread. Therefore, considering the effect of fissures on the sound velocity propagation law. In this work, experiments on the identification of acoustic emission signal paths in solid media with different void states are carried out, and the path propagation law of acoustic emission signals is explored and studied. A comparative analysis of acoustic emission source localization in fractured sandstone with different sensor arrays at different saturation levels was carried out using water as the coupling agent. The acoustic emission source 3D localization results are optimized by correcting the time difference model. The results show that the acoustic emission signal propagation conforms to the shortest distance principle. In the localization of 3D cylindrical AE sources, it is suitable to select a combined array of spatial tetrahedral sensors for better localization. As the saturation increases the positioning effect gets closer to the actual value. The sound source localization effect of the sound velocity correction model based on the time difference method is closer to the actual lead break position. In actual engineering, water as a benign coupling agent can better improve the accuracy of AE source localization in fracture-containing sandstone, which can provide some guiding suggestions for related engineering.

Plastic instabilities explored via acoustic emission during spherical nanoindentation

The plastic instabilities of a silicon iron single crystal (Fe single crystal doped with 3 wt% of Si) were explored via spherical nanoindentation coupled with an acoustic emission detection at nano/micro-scale. Three possible scenarios were identified (gradually developing plasticity without detectable AE activity, sudden onset of plasticity with strong AE event, and an elastic response with frequent AE activity both during loading and unloading). Beside the irreversible dislocation slip, the reversible microstructural changes were identified that in turn provokes to extend the common definition of acoustic emission from a phenomenon caused by the sudden irreversible microstructural changes by including also reversible atomic reorganization. AE activity at nano/micro-scale was for the first time observed during both the loading and the unloading for purely elastic indentations suggesting an action of reversible twinning. Critical indentation stresses representing the onset of AE activity during loading and its termination during unloading were identified. The unambiguous classification of AE events and irregularities on the indentation curve showed a direct correlation between the depth excursion and AE hit parameters. Acoustic emissions proved to be a very powerful and complementary method for the examination and classification of different deformation mechanisms (slip and twinning) observed during indentation loading.

Non-Destructive Testing for Cavity Damages in Automated Machines Based on Acoustic Emission Tomography

Damage detection is important for the maintenance of automated machines. General non-destructive testing techniques require static equipment and complex analysis processes, which restricts the maintenance of automated machines. Therefore, this paper proposes an acoustic emission (AE) tomography method for detecting cavity damage in automated machines, combining the fast sweeping method (FSM) and the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method. This approach overcomes the limitations of real-time AE detection for cavity damage in continuous and homogeneous materials. The proposed method has been applied in numerical and laboratory experiments to validate its feasibility. The results show that the inversed low-velocity regions correspond to the actual cavity regions, and the sources of cavity damage can be effectively detected. This paper provides a new perspective for AE testing technologies, and also lays the foundation for other non-destructive testing techniques, in terms of cavity damage detection.

Study on Delamination Damage of CFRP Laminates Based on Acoustic Emission and Micro Visualization.

This study investigated the mechanism of delamination damage in the double cantilever beam (DCB) standard test by the use of the strain energy release rate. The curve of the strain energy release rate was verified by the Rise Angle (RA) method. For this purpose, 24-layer carbon fiber/epoxy multidirectional laminates with interface orientations of 0°, 30°, 45°, and 60° were fabricated according to the standard ASTM D5528(13). In the course of this test, acoustic emission (AE) was used for real-time monitoring, and combined with micro visualization, the damage mechanism of composite multidirectional laminates was studied at multiple scales. Combining the AE detection results with micro visualization, it is found that the AE parameters and the damage to multidirectional laminates could realize a one-to-one correspondence. Through the study of the variation of the RA value, load, and strain energy release rate with the crack length, it is proved that the AE parameters can effectively characterize the initiation of delamination damage.

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.

Acoustic Emission Damage Detection during Three-Point Bend Testing of Short Glass Fiber Reinforced Composite Panels: Integrity Assessment

In this study, an acoustic emission (AE) technique was used as a passive non-destructive tool to detect the damage progress in short glass fiber-reinforced composite panels. AE detection was conducted during three-point bend tests, thus illustrating the flexural damage accumulation for composite panels with different sizes and fiber volume content. To demonstrate the universality of the employed integrity assessment methodology, AE data was detected using different timing parameters and two different transducer types, i.e., medium-band and wide-band frequency sensors. The AE waveform classification presented in this study is based on peak frequency distributions. Frequency bands that are associated with certain failure mechanisms, including matrix micro-cracking, fiber debonding, delamination, and fiber breakage, were obtained from the technical literature. Through this investigation, the concept of cumulative signal strength (CSS) and cumulative rise time versus peak amplitude ratio (CRA) as AE output parameters are shown to facilitate integrity assessment for the employed complex composite material system. Significant jumps in CSS and CRA curves could be correlated to critical strain levels and distinct damage events in the composite panels subjected to flexural loading.

An Efficient Method for Wheel-Flattened Defects Detection Based on Acoustic Emission Technique.

Recent research studies show that acoustic emission (AE) technologies have great potential in detecting the flattened defects of wheel; however, the wheel-rail rolling interference (WRRI) significantly influences the accuracy of wheel defect detection. Aiming to solve the above-mentioned problem, a novel detection method, which combines an improved synthesized health index (ISHI) with a time adaptive threshold (time-ATH), is proposed in this article. In order to obtain the defect information from the signals generated by the wheels, a completed feature set that contains many types of features is extracted from AE signals. Then, the ISHI is fused by several effective features that are selected from the completed feature set, according to detection rate and accuracy. Besides, a time-ATH calculation is proposed to detect the defective signals of wheels and reduce the influence of the WRRI. The method is fully verified in actual datasets, and the results show that the proposed method achieves a better detection rate and accuracy. Moreover, it provides an effective way for the AE detection of wheel-flattened defects under strong and numerous WRRI.