Application Of Acoustic Emission Research Articles

Coupled slow strain rate and acoustic emission tests for gaseous hydrogen embrittlement assessment of API X65 pipeline steel

Hydrogen embrittlement (HE) sensitivity of API X65 pipeline steel was evaluated in this study through the simultaneous application of slow strain rate tests (SSRT) and acoustic emission (AE) monitoring on hollow dog-bone samples. Exposure to hydrogen gas decreased the elongation to fracture percentage with a significant rise in embrittlement index for the higher pressure of 10 MPa. SEM images of the fracture surfaces demonstrated that the fracture mechanism changed from ductile to ductile–brittle under 1 MPa pressure, and to predominantly brittle with quasi-cleavage characteristic when testing under 10 MPa hydrogen gas. Classification of the AE events based on waveform analysis revealed a mainly shear mode fracture for 10 MPa nitrogen sample, while a dominant tensile mode fracture was identified for the hydrogen charged samples.

Dual-Use Strain Sensors for Acoustic Emission and Quasi-Static Bending Measurements.

In this paper, a MEMS piezoresistive ultrathin silicon membrane-based strain sensor is presented. The sensor's ability to capture an acoustic emission signal is demonstrated using a Hsu-Nielsen source, and shows comparable frequency content to a commercial piezoceramic ultrasonic transducer. To the authors' knowledge, this makes the developed sensor the first known piezoresistive strain sensor which is capable of recording low-energy acoustic emissions. The improvements to the nondestructive evaluation and structural health monitoring arise from the sensor's low minimum detectable strain and wide-frequency bandwidth, which are generated from the improved fabrication process that permits crystalline semiconductor membranes and advanced polymers to be co-processed, thus enabling a dual-use application of both acoustic emission and static strain sensing. The sensor's ability to document quasi-static bending is also demonstrated and compared with an ultrasonic transducer, which provides no significant response. This dual-use application is proposed to effectively combine the uses of both strain and ultrasonic transducer sensor types within one sensor, making it a novel and useful method for nondestructive evaluations. The potential benefits include an enhanced sensitivity, a reduced sensor size, a lower cost, and a reduced instrumentation complexity.

Influence of high temperature during tensile test for stainless steel using acoustic emission

AbstractThis paper explores the application of acoustic emission (AE) monitoring in mechanical and materials studies, specifically focusing on the detection of plastic deformation, fracture, and crack growth. However, the influence of high temperature on AE signals and its effects on mechanical properties are not fully understood due to the limitations of sensors in high‐temperature environments. To address this gap, the study investigates the impact of high temperatures on the mechanical properties of stainless steel SS304 using AE techniques during tensile testing. Two temperature conditions were tested: 600 and 700°C. AE sensors connected to specimens captured AE activity using a designated waveguide, and a Continuous Creep Monitoring Instrument (CCMi) recorded the responses. Sensitivity testing using the pencil‐lead break (PLB) technique ensured the sensor's capability. The proposed frequency‐based analysis method, fast Fourier transform amplitude (FFTA) analysis, was employed to effectively analyze the AE signals. The results revealed significant AE features and frequency distributions associated with elastic deformation, plastic deformation, and fracture regions. These findings establish a foundation for utilizing AE techniques in crack detection and monitoring under high‐temperature loading, contributing to equipment reliability and structural integrity.

Application of acoustic emission and digital image correlation for detecting diffusion interlayers in dissimilar welded joints

The paper investigates the possibility of using the acoustic emission (AE) method to detect carbide and decarburized interlayers formed in dissimilar welded joints of austenitic and pearlitic steels during welding and subsequent operation.

Defect detection of ferromagnetic rail using EMAE-based peak-to-peak method and confidence probability indicator

Rail defect detection holds a vital role in bolstering the safety, improving operational efficiency, and optimizing the lifespan of infrastructures in railway transportation systems. This paper proposes an electromagnetic acoustic emission-based peak-to-peak (EMAE-PTP) method along with a dedicated confidence probability indicator (CPI) for ferromagnetic rail defect detection. Firstly, a comprehensive simulation model that blends Lorentz forces with magnetostrictive effects is built up, affirming the theoretical practicability of the proposed EMAE-PTP method in ferromagnetic rail defect detection. Taking into consideration of the contingency and difference in actual signals acquisition, a special indicator, namely CPI, is formulated as the defect evaluation threshold. Based on the Chebyshev inquality and the time-domain characteristic of acquired signals, this CPI delineates the range of peak-to-peak amplitudes related to non-defective state, with a confidence level up to 96%. By doing so, the numerically segregation of defect signals can be accomplished with ease. In addition, according to the detection coefficient calculated from CPI, the suitable excitation conditions for electromagnetic acoustic emission application are determined. In conclusion, the efficacy of the proposed approach for ferromagnetic rails defect detection is substantiated, encompassing a holistic assessment of both its theoretical underpinnings and experimental manifestations.

Piezoelectric Wafer Active Sensor Transducers for Acoustic Emission Applications.

Piezoelectric materials are defined by their ability to display a charge across their surface in response to mechanical strain, making them great for use in sensing applications. Such applications include pressure sensors, medical devices, energy harvesting and structural health monitoring (SHM). SHM describes the process of using a systematic approach to identify damage in engineering infrastructure. A method of SHM that uses piezoelectric wafers connected directly to the structure has become increasingly popular. An investigation of a novel pitch-catch method of determining instrumentation quality of piezoelectric wafer active sensors (PWASs) used in SHM was conducted as well as an investigation into the effects of defects in piezoelectric sensors and sensor bonding on the sensor response. This pitch-catch method was able to verify defect-less instrumentation quality of pristinely bonded PWASs. Additionally, the pitch-catch method was compared with the electromechanical impedance method in determining defects in piezoelectric sensor instrumentation. Using the pitch-catch method, it was found that defective instrumentation resulted in decreasing amplitude of received and transmitted signals as well as changes in the frequency spectrums of the signals, such as the elimination of high frequency peaks in those with defects in the bonding layer and an increased amplitude of around 600 kHz for a broken PWAS. The electromechanical impedance method concluded that bonding layer defects increase the primary frequency peak's amplitude and cause a downward frequency shift in both the primary and secondary frequency peaks in the impedance spectrum, while a broken sensor has the primary peak amplitude reduced while shifting upward and nearly eliminating the secondary peak.

Application of Acoustic Emission as Damage Assessment Technique for Performance Evaluation of Concrete Structures: A Review

A significant increase in existing inspection efforts and the creation of more resilient structures using built-in sensors and systems is essential for accurate and reliable assessment and monitoring of structural conditions in order to minimize the risk of catastrophic failure. The acoustic emission (AE) technique could immensely benefit the damage assessment, real-time checking of structural integrity under operating conditions, and identification of the operational risk factors along with the causes of initiation and development of flaws. Therefore, this article presents a comprehensive overview of AE as a potential damage assessment and localization technique to determine the performance and behavior of reinforced concrete (RC) members along with an overview of the latest research in computational AE damage modeling and machine learning tools to optimize the accurate interpretation of voluminous AE data. The primary aim of this review is to identify specific gaps in the literature pertaining to concrete structures that need immediate attention of the researchers working in this domain. The identification of damage mechanisms based on AE events and parameters covered in this review would enable researchers to identify damage sources nondestructively in situ and produce large data sets for detailed statistical analyses of the effects of small-scale local damages in large-scale concrete structures. This review will also be helpful for practicing engineers to choose between different available AE parameters based on the limitations and advantages of these parameters for specific inspection and maintenance requirements of various types of RC structural elements, loading conditions, and failure.

Revealing the interaction mechanism of pulsed laser processing with the application of acoustic emission

The mechanisms of interaction between pulsed laser and materials are complex and indistinct, severely influencing the stability and quality of laser processing. This paper proposes an intelligent method based on the acoustic emission (AE) technique to monitor laser processing and explore the interaction mechanisms. The validation experiment is designed to perform nanosecond laser dotting on float glass. Processing parameters are set differently to generate various outcomes: ablated pits and irregular-shaped cracks. In the signal processing stage, we divide the AE signals into two bands, main and tail bands, according to the laser processing duration, to study the laser ablation and crack behavior, respectively. Characteristic parameters extracted by a method that combines framework and frame energy calculation of AE signals can effectively reveal the mechanisms of pulsed laser processing. The main band features evaluate the degree of laser ablation from the time and intensity scales, and the tail band characteristics demonstrate that the cracks occur after laser dotting. In addition, from the analysis of the parameters of the tail band very large cracks can be efficiently distinguished. The intelligent AE monitoring method was successfully applied in exploring the interaction mechanism of nanosecond laser dotting float glass and can be used in other pulsed laser processing fields.Graphical

Sound Range AE as a Tool for Diagnostics of Large Technical and Natural Objects.

Application of acoustic emission of the sound frequency range is under consideration. This range is of current interest for the diagnostics of the stability of mountain slopes, glaciers, ice covers, large technical constructions (bridges, dams, etc.) as well as for the detection of rock deformation anomalies preceding earthquakes. Acoustic sensors, which can be used to record and to determine the directivity of acoustic emission of the sound frequency range, are under consideration. The structure of the system for acoustic emission recording, processing and analysis is described. This system makes it possible to determine the direction to the acoustic emission source using one multi-component sensor. We also consider the algorithms for detection of acoustic emission pulses in a noisy background, and for the analysis of their structure using the Adaptive Matching Pursuit algorithm. A method for the detection of the direction to an acoustic emission signal source based on multi-component sensors is described. The results of application of sound range acoustic emission for the detection of the intensification of rock deformations, associated with earthquake preparation and development in the seismically active region of Kamchatka peninsula, are presented.

Acoustic emission monitoring of the textile reinforced cement (trc)-to-masonry shear bond

This study focuses on the potential of Textile Reinforced Cementitious (TRC) composites with alkali-resistant glass textile to reinforce masonry structures. In particular, a better identification of the debonding mechanisms is a crucial point for a more efficient use of these composites. Twelve single-lap shear bond tests are performed to investigate four strengthening configurations - two matrices and two reinforcement ratios. This paper discusses the applicability of acoustic emission to assess the damage state of TRC during adherence testing. The flexibility of the matrix used and the amount of reinforcement of the TRC affect the cumulative amplitude distributions. The accumulation of the partial frequency associated with high frequency (above 400 kHz) is a precursor of a strong contribution of the textile in the load transfer.

Analytical solution of acoustic emission in soft material with cracks by using reciprocity theorem

Special property in soft materials manifests itself as slight external action may occur significant changes in structure or performance followed by crack initiation and propagation. Characterizing the transition from a crack-free to a cracked soft material remains one of the most challenging problems in structural changes. New methods are needed to predict when and how these soft materials will fail due to defects. In this context, we explored the acoustic emission phenomenon of a crack generation with micro-nanometer size in rubber seal rings. We found through the reciprocity theorem and equivalent body forces that this tiny structural change is defined by the opening crack time function, crack opening body and elastic constant. We take rubber as an example and analyze the new application of acoustic emission and propose a methodology for near surface crack detection of soft materials. Additionally, we discuss the contributions of the opening crack time function, cyclic frequency and elastic constant. The present ‘acoustic emission applications’ strategy offers an effective pathway to observe soft materials' structural changes.

Development of accelerated comparative assessment of contact fatigue strength based on the analysis of acoustic emission of friction units

The article presents the results of theoretical and experimental research of acoustic emission of friction units during rolling-sliding friction contact. The purpose of this study is the development of a method of accelerated assessment of contact fatigue strength with the application of acoustic emission during friction contact. The application of acoustic emission method reveals periods of energy state of the material: the activation, the damage accumulation, the transition to the initial fatigue damage. Pulse loading up to the maximum possible value was used for activation of damage accumulation process on the friction surfaces. Specific destructive energy for one load cycle was used as the fatigue strength assessment criterion. The developed technique allows to quantify the fatigue strength in analogy with the methods of such evaluation with the help of fatigue machines for testing at cyclic loads.

Application of acoustic emission and scleroscopy for the analysis of carbon fiber-reinforced plastic samples with different degrees of matrix curing

Samples made of a 1.6 mm thick carbon fiber-reinforced plastic sheet with different curing modes were loaded in the elastic region according to the cantilever bending scheme. Acoustic emission was recorded using an oscilloscope. The microhardness characteristics were used as criteria evaluating the degree of matrix curing which was evaluated on the face surface of the samples and in its cross section at fixed distances from the face surface. Dependences of the frequency, amplitude of acoustic signals, temperature, deflection value and distance to the sample surface on the matrix microhardness were established. The studies showed that the value of matrix microhardness is a relevant criterion evaluating the influence of the mode of carbon fiber-reinforced plastic molding.

A Review on Application of Acoustic Emission in Coal—Analysis Based on CiteSpace Knowledge Network

Based on CiteSpace software, this paper reviews and analyzes the application articles of acoustic emission in coal from 2010 to 2020. In this paper, CiteSpace software visualizes 453 articles collected in the Web of Science core database. The cooperation networks between different countries, institutions, and authors are used to determine the connection of knowledge in papers. The keyword co-occurrence, keyword co-occurrence time zone map, and keyword clustering are used to determine the hot topics in the field. The cited collaborative network analysis reveals the important literature and the contribution of prominent authors in this area. In the future, for the research of acoustic emission in coal mining, compression tests will still be the main test methods. In terms of time domain parameters of acoustic emission, the application of ring counting, energy, waveform, and signal strength are very mature. The principal problem of acoustic emission location operation will become a focus in the future. The most widely used patterns in the determination of ruptures are the signal intensity fractal dimension, the acoustic emission number, and the b-value. In practical engineering problems, there is little research on the deformation activity law of steeply inclined coal seams and surrounding rock. The mining of steeply inclined coal seams is still a difficult problem. There are immature technologies in coal mining, rockburst early warning, and coal and gas outburst. In terms of the intellectualization and accuracy based on experience, there is room for improvement in the future. Scholars will continue a deeper exploration on the application of the numerical simulation.

Study on Splitting Damage Characteristics of a Rock–Shotcrete Interface Subjected to Corrosive Water

Splitting tensile real time acoustic emission tests were carried out on rock–shotcrete binary specimens under the action of different corrosive waters in different periods. The effect of corrosion on the damage process of the binary interface was studied from a mesoscopic point of view. The results showed that the physical and chemical properties of the binary specimens were changed due to corrosion, resulting in a decrease in the tensile strength. Moreover, the corrosion effect of the acid solution is relatively strong throughout the whole corrosion cycle. It can be seen that the acoustic emission signal can reflect the interface microcrack propagation and inoculation process from the stress–strain curve, the ringing count, and the cumulative energy correspondence. Furthermore, the peak point of each parameter decreases with deepening the corrosion degree in different corrosive environments. The same-step variation in numerical value can provide certain early warning information. The application of acoustic emission B value indicates that the failure mode of the interface of the binary body develops from the failure of large internal cracks to the failure of continuous small cracks as the corrosion intensifies. The damage model established based on acoustic emission cumulative ringing count can better characterize the coupling relationship between corrosion-load-damage of the binary.

Damage Modes Recognition of Wood Based on Acoustic Emission Technique and Hilbert–Huang Transform Analysis

Identifying the different damage modes of wood is of great significance for monitoring the occurrence, development, and evolution of wood material damage. This paper presents the research results of the application of acoustic emission (AE) technology to analyze and evaluate the mapping relationship between the damage pattern of wood in the fracture process and the AE signal. For the three-point bending specimen with pre-crack, the double cantilever beam specimen, the single fiber tensile specimen, and the uniaxial compression specimen, the bending tensile compression test and the AE monitoring were performed, respectively. After the post-processing and analysis of the recorded AE signal, the results show that the peak frequency of AE is an effective parameter for identifying different damage modes of wood. In this study, the empirical mode decomposition (EMD) of the AE signal can separate and extract a variety of damage modes contained in the AE signal. The Hilbert–Huang transform (HHT) of the AE signal can clearly describe the frequency distribution of intrinsic mode function (IMF) components in different damage stages on the time scale, and can calculate instantaneous energy accurately, which provides a basis for damage mode recognition and lays a foundation for further accurate evaluation of the wood damage process.

On the potential applications of acoustic emission in friction stir welding

In friction stir welding (FSW), only a few studies related to acoustic emission (AE) signals analysis have been conducted. In this work, the potential application of AEs in FSW is explored from a phenomenological and monitoring point of view. In static tests, with the tool only rotating without advancing, the information hidden behind AEs concerning the tool-workpiece interaction was investigated. Additionally, the sensors' positioning analysis is considered by comparing the signals' features obtained by placing the sensor on the welding plate or the support. Then in the second part, the effective capability of detecting internal defects during friction stir welding through AE signals monitoring is addressed. The experimental tests were performed on aluminum alloys of two different heat treatable families. Differences in the material plastic behavior depending on the aluminum alloys and the rotational speed were revealed by AEs features such as the amplitude and the absolute energy. In addition, internal defect occurrence was correlated with a shift in the signal centroid frequency. The results are auspicious for employing AE signals to deepen the tool-workpiece interaction and identify internal defects.

Application of acoustic emission to the analysis of phase transformations in 27MnCrB5-2 steel tests during continuous cooling

Application of acoustic emission to the analysis of phase transformations in 27MnCrB5-2 steel tests during continuous cooling

An Investigation of the Redox Stability of an Anode-Supported SOFC Stack Using Acoustic Emission Monitoring

The current interest in solid oxide fuel cells (SOFC) technology lies mainly in its high power generation/conversion efficiency and its low or zero emissions. Their application in stationary power generation systems indicate their maturity to date. However, the stability and performance of the cells or stacks could be affected due to the adverse conditions to which they are exposed. One of the most concerning conditions for Ni-based anode-supported cells (ASC) is when the stack is subjected to unplanned reduction-oxidation (Redox) cycles, which can lead to irreversible damage to the cell. During a Redox cycle, the anode undergoes changes in its volume, due to the oxidation of nickel (Ni) to nickel oxide (NiO), which causes microstructural damages to the anode itself or to the electrolyte or to both. Previous study has shown that the cell performance decreased after redox cycling above 600 °C, mainly based on voltage-current curve or electrochemical impedance measurements. However, there is little information on the application of acoustic emission (AE) techniques in the study of redox cycling. Therefore, the purpose of this work is to investigate the redox process and stability of a SOFC stack through the application of the AE monitoring. The research will include the analysis of the AE signals, the AE cumulative energy as well as an analysis in the frequency domain. This is expected to contribute to the understanding of the redox process inside stack and failure modes of the cell.

On the application of machine learning for defect detection in L-PBF additive manufacturing

This paper investigates the performance of several Machine Learning (ML) techniques for online defect detection in the Laser Powder Bed Fusion (L- PBF) process. The research aims to improve the consistency in product quality and process reliability. The applications of acoustic emission (AE) sensor to receive elastic waves during the printing process is a cost-effective way of materializing such a demand. In this study, the process parameters were intentionally adjusted to create three different levels of defects in H13 tool steel samples. The first class was printed with minimum defects, the second class had only intentional cracks, and the last class included both intentional cracks and porosities. The AE signals were acquired during the samples' manufacturing, and three different machine learning (ML) techniques were applied to analyze and interpret the dataset. First, a hierarchical K-means clustering is employed for labeling the data, followed by a supervised deep learning neural network (DL) to match acoustic signal with defect type. Second, a principal component analysis (PCA) was used to reduce the dimensionality of the dataset. A Gaussian Mixture Model (GMM) was then employed to enable fast defect detection suitable for online monitoring. Third, a variational auto-encoder (VAE) approach is used to obtain a general feature of the signal that could be an input for the classifier. A supervised DL trained on the H13 tool steel dataset successfully detected quality trends in AE signals collected from 316L samples. The VAE approach presents a novel method to detect defects in L-PBF processes that eliminate the need for model training in different materials.