Acoustic Emission Signal Parameters Research Articles

Detection of the Onset of Galling in Strip Reduction Testing Using Acoustic Emission

Galling is an important issue in metal forming of tribologically severe materials such as high strength steel, stainless steel, Al- or Ti-alloys, since it leads to poor surface quality of the formed components, production stops and possibly deterioration of tools. The onset of galling is difficult to detect, since it is either based on the operator's personal judgement or indirect measuring techniques. The application of acoustic emission measuring technique for characterization of onset of galling in sheet metal forming is discussed in the presented paper. The strip reduction test, which emulates the ironing process, has been examined in order to evaluate onset of galling and how this is related to the generated acoustic emission parameters. Preliminary investigations have shown that differences can be found in the acoustic emission signal parameters depending on the frictional conditions between the tool and the workpiece surfaces. A correlation to the severity of galling is found. This is inspected through observations of tested workpiece surfaces in SEM and measurements of the surface roughness. The acoustic emission measuring technique is found to possess promising aspects for online monitoring of galling in metal forming processes.

Mathematical Models for Interrelation of Characteristics of the Developing Defects with the Parameters of Acoustic Emission Signals

Mathematical models and mechanisms of acoustic emission signal generation are presented. It is shown that the reasons of acoustic emission signal origin are related to the local alterations of microstructure of materials and processes of movement of distribution at formation of tensions in solids. It is proved that the origination of signals is based on the analysis of acoustic wave energy released per load cycle and the work of the external forces at elastic deflection.

Acoustic emission monitoring for bond integrity evaluation of reinforced concrete under pull-out tests

This article presents the results of an experimental investigation on the application of acoustic emission technique for monitoring the steel-to-concrete bond integrity of reinforced concrete structures. A series of direct pull-out tests were performed on 54 reinforced concrete unconfined prism samples with variable rebar diameter (10, 20, and 35 mm), embedded length (50, 100, and 200 mm), and concrete cover (20, 30, and 40 mm). The samples were tested under incrementally increasing monotonic loading while being continuously monitored via attached acoustic emission sensors. These sensors were utilized to acquire different acoustic emission signal parameters emitted throughout the tests until failure. Also, an acoustic emission intensity analysis was implemented on acoustic emission signal strength data to quantify the damage resulting from loss of bond in all tested specimens. This analysis employed the signal strength of all recorded acoustic emission hits to develop two additional parameters: historic index ( H ( t)) and severity ( Sr). The results of bond behavior, mode of failure, and free end slip were compared with the recorded acoustic emission data. The results showed that the cumulative number of hits, cumulative signal strength, H ( t), and Sr had a good correlation with different stages of bond damage from de-bonding/micro-cracking until bond splitting failure and bar slippage, which caused cover cracking or delamination. The analysis of cumulative signal strength and H ( t) curves enabled early identification of two progressive stages of bond degradation (micro-cracking and macro-cracking) and recognized the various modes of failure of the tested specimens. The variations of bar diameter, concrete cover, and embedded length yielded significant impacts on both the bond behavior and acoustic emission activities. The results also presented developed intensity classification charts, based on H ( t) and Sr, to assess the bond integrity and to quantify the bond deterioration (micro-cracking, macro-cracking, and rebar slip) in reinforced concrete structures.

Acoustic emission monitoring of damaging of fiberglass

The results of studies on determining the nucleation moment of microcracks in fiberglass are presented on the basis of a full-strength glassfiber mat and vinyl ether binder by the acoustic emission method in uniaxial tension. The research was carried out by continuous monotonic loading of samples under uniaxial tension until failure with simultaneous recording of the parameters of acoustic emission signal. Qualitative dependences of the parameters of acoustic emission signals on the stress value in the sample are revealed. It is found that, at a stress value of about 40% of the ultimate strength of material (about 420 MPa), microfracture processes—cracking of the polymer matrix—begin.

The Use of Acoustic Emission Intensity Analysis for the Assessment of Cover Crack Growth in Corroded Concrete Structures

In this paper, acoustic emission (AE) intensity analysis was utilized to assess the concrete cover cracking due to steel corrosion in reinforced concrete structures. A total of 30 reinforced concrete prism samples were tested under an accelerated corrosion test coupled with continuous AE monitoring using attached AE sensors. The samples were cast with three concrete cover thicknesses (20, 30 and 40 mm) around steel bars and were exposed to five percentages of steel mass loss: 1, 2, 3, 4, and 5 %. The cover cracking was monitored daily by visual inspection to detect and measure crack widths. Different AE signal parameters were continuously recorded during the tests, including number of hits, signal strength, energy, and amplitude. The acquired AE events were subjected to an intensity analysis of signal strength to estimate historic index (H (t)) and severity (\(S_r)\). In addition, a b value analysis was conducted on all AE data and the results were compared to those obtained from the intensity analysis. The results showed that increasing the cover thickness had no significant impact on AE parameters (number of hits, cumulative signal strength, cumulative energy, amplitude, H (t), and \(S_{r})\) at similar values of crack growth. Nonetheless, varying the cover thickness from 20 to 40 mm resulted in lower crack widths and slightly higher b values at the same levels of steel mass loss. It was also found that both H (t) and \(S_r\) showed a more evident correlation with the values of crack growth than did b values, regardless of cover thickness or percentage of steel mass loss. Finally, an intensity classification chart was developed to quantify the cover crack growth based on the values of H (t) and \(S_{r}\).

Failure strength prediction of glass/epoxy composite laminates from acoustic emission parameters using artificial neural network

The ageing effect of glass/epoxy composite laminates exposed to seawater environment for different periods of time was investigated using acoustic emission (AE) monitoring. The mass gain ratio and flexural strength of glass fiber reinforced plastic (GFRP) composite laminates were examined after the seawater treatment. The flexural strength of the seawater treated GFRP specimens showed a decreasing trend with increasing exposure time. The degradation effects of seawater are studied based on the changes in AE signal parameters for various periods of time. The significant AE parameters like counts, energy, signal strength, absolute energy and hits were considered as training data input. The input data were taken from 40% to 70% of failure loads for developing the radial basis function neural network (RBFNN) and generalised regression neural network (GRNN) models. RBFNN model was able to predict the ultimate failure strength and could be validated with the experimental results with the percentage error well within 0.5–7.2% tolerance, whereas GRNN model was able to predict the ultimate failure strength with the percentage error well within 0.5–4.4% tolerance. The prediction accuracy of GRNN model is found to be better than RBFNN model.

Burr formation and correlation with cutting force and acoustic emission signals

The principle objective of this work is to present a methodology to evaluate the correlation between burr size attributes (thickness and height) and information computed from acoustic emission and cutting forces signals. In the proposed methodology, cutting force and acoustic emission signals were recorded in each cutting test, and each recorded original acoustic emission signal was segmented into two sections that correspond to steady-state cutting process (cutting signal) and cutting tool exit from the work part (exit signal). The dominant acoustic emission signal parameters including AEmax and AErms were computed from each segmented acoustic emission signal. The maximum values of directional cutting forces (FX, FY and FZ) were also measured in each trial. The experimental verification was conducted on slot milling operation which has relatively more complicated burr formation mechanism than that in many other traditional machining operations. Among slot milling burrs, the top-up milling side burrs and exit burrs along up milling side were largest and thickest burrs which were studied in this work. To evaluate the correlation between signal information and burr size, the computed signal information (5 parameters) and their interaction effects (10 parameters) were used to construct the input parameters of the multiple regression fitted models. Statistical methods were then used to assess the adequacy of individual input parameters and signal information. Using the acoustic emission and cutting force signals information in the input layer of multiple regression models, a high correlation was observed between the predicted and observed values of burr size. It was exhibited that due to complex burr formation mechanism in milling operation and strong interaction effects between cutting process parameters, no systematic relationship can be formulated between the milling burrs.

Parameters of Acoustic Emission Signals Obtained During the Setting and Hardening of Concrete Mixtures with Different Water-Cement Ratio

Concrete hardening and setting processes are the most critical phases during construction work, influencing the properties of concrete structure. For this reason applying non-destructive testing in the early age of concrete lifetime can be useful. Acoustic emission method is a powerful tool for determination of lifetime concrete structures. Nevertheless, its application in civil engineering area is not easy because many building structures are inhomogeneous. This method can describe material changes during concrete lifetime. Acoustic Emission Method monitors concrete structure continuously. Changes in the whole concrete structure are recorded. The acoustic emission phenomenon is directly associated with nucleation of cracks in building materials, therefore the changes result from the volumetric expansion causing formation micro and macro cracking in structure, which we can recognize. Application of Acoustic Emission Method during concrete hardening and setting with different water-cement ratio will be the aim of this article and his influence on parameters of acoustic emission. A comprehension of microstructure-performance relationships is the key to true understanding of material behaviour.

Использование АЭ метода при продлении срока службы стальных деталей сложной конструкции

The author has developed way to extend the life of cast components of freight car bogies using acoustic emission method. The proposed modified integral method of the determination state of the cast parts truck freight wagons in the parameters of acoustic emission signals the most loaded sections. Present a study at developing criteria for assessing the state of the cast parts and the results of the application on real details.

Assessment of concrete-to-steel bond behaviour of reinforced concrete structures using acoustic emission intensity analysis

Abstract. An experimental study was performed to utilize acoustic emission (AE) intensity analysis for the assessment of the concrete-to-steel bond behaviour of reinforced concrete structures. A total of 18 reinforced concrete unconfined prism samples were tested in a direct pullout test setup under incrementally increasing monotonic loading as being constantly monitored with attached AE sensors. The samples were cast using variable bar diameter (10, 20, 35 mm) and bar embedded length (50, 100, 200 mm). Different AE signals parameters were recorded throughout the tests until failure including rise time, counts, number of hits, signal strength, energy, amplitude, duration, and frequency values. Moreover, an AE intensity analysis was applied on AE signal strength results to produce two additional AE parameters: historic index (H (t)) and severity (Sr). Results demonstrated that cumulative signal strength (CSS) correlated well with different degrees of loss of bond from micro-cracking till bond splitting failure, which resulted in cover cracking or delamination. The review of CSS, H (t), and Sr curves allowed the detection of two progressive stages of bond deterioration (micro-cracking and macro-cracking) in all tested specimens. Intensity analysis parameters (H (t) and Sr) were employed to create bond damage classification chart to evaluate the concrete-to-steel bond condition in reinforced concrete structures.

Optimized statistical parameters of acoustic emission signals for monitoring of rolling element bearings

Acoustic emission (AE) signal generated from artificial defects in rolling element bearings are investigated using experimental measurements in this paper. Rolling element bearings are crucial parts of many machines and there has been an increasing demand to find effective and reliable health monitoring technique and advanced signal processing to detect and diagnose the size and location of incipient defects. Condition monitoring of rolling element bearings, comprises four main stages which are, statistical analysis, faults diagnostics, defect size calculation, and prognostics. In this paper, the effect of defect size, operating speed, and loading conditions on statistical parameters of AE signals, using design of experiment method, have been investigated to select the most sensitive parameters for diagnosing incipient faults and defect growth on rolling element bearings.

Roller bearing acoustic signature extraction by wavelet packet transform, applications in fault detection and size estimation

Continuous online monitoring of rotating machines is necessary to assess real-time health conditions so as to enable early detection of operation problems and thus reduce the possibility of downtime. Rolling element bearings are crucial parts of many machines and there has been an increasing demand to find effective and reliable health monitoring technique and advanced signal processing to detect and diagnose the size and location of incipient defects. Condition monitoring of rolling element bearings, comprises four main stages which are, statistical analysis, fault diagnostics, defect size calculation, and prognostics. In this paper the effect of defect size, operating speed, and loading conditions on statistical parameters of acoustic emission (AE) signals, using design of experiment method (DOE), have been investigated to select the most sensitive parameters for diagnosing incipient faults and defect growth on rolling element bearings. A modified and effective signal processing algorithm is designed to diagnose localized defects on rolling element bearings components under different operating speeds, loadings, and defect sizes. The algorithm is based on optimizing the ratio of Kurtosis and Shannon entropy to obtain the optimal band pass filter utilizing wavelet packet transform (WPT) and envelope detection. Results show the superiority of the developed algorithm and its effectiveness in extracting bearing characteristic frequencies from the raw acoustic emission signals masked by background noise under different operating conditions. To experimentally measure the defect size on rolling element bearings using acoustic emission technique, the proposed method along with spectrum of squared Hilbert transform are performed under different rotating speeds, loading conditions, and defect sizes to measure the time difference between the double AE impulses. Measurement results show the power of the proposed method for experimentally measuring size of different fault shapes using acoustic emission signals.

Concrete damage constitutive relation based on characteristic parameters of acoustic emission

Based on the experiments, the parameters of acoustic emission signals regarding cracks, expansion, and instability of concrete are discussed in this paper. The relationship between different acoustic emission signals of concrete was established on damage constitutive relation. A new method was provided by damage assessment for hydraulic structures.

The dependence of local deformations and internal stress fields on welding technique for grade VSt3sp structural steel: I. The influence of welding technique on the mechanical characteristics and acoustic emission parameters of grade VSt3sp steel

A staging analysis was carried out for deformation curves and the evolution of local deformation fields in defective and defect-free specimens of welded joints of grade VSt3sp steel that were made using manual arc and manual pulsed arc welding. Stages of elasticity, microplasticity, nucleation and motion of Chernov–Luder’s bands, and parabolic deformation strengthening were considered. The parameters of acoustic-emission signals during tension of specimens with a welded seam were analyzed.

Influence of Aeration of Concrete on Acoustic Emission and Fracture Mechanical Parameters Obtained from Three-Point Bending Tests

This paper examines the analysis of acoustic emission signals captured during three-point bending fracture tests of concrete specimens with similar water-cement ratio, but one set of specimens was prepared from aerated concrete. The acoustic emission method is an experimental tool well suited for monitoring fracture processes in material. The typical parameters of acoustic emission signals were identified from the acoustic emission records for two different concrete mixtures to further describe the under-the-stress behaviour and failure development. An understanding of microstructure–performance relationships is the key to true understanding of material behaviour. The crack growth was continuously monitored using four acoustic emission sensors mounted on the specimen. The acoustic emission results are accompanied by selected fracture mechanical parameters determined via evaluation of load versus displacement diagrams recorded during three-point bending fracture tests.

Оценка степени герметичности шаровых кранов DN800, установленных на компрессорной станции «Портовая»

Leak integrity guaranteeing is the main requirement to shut-off valves. Possibilities to prolong an operation life as well as real activities on leaktightness restoration depend on leakage value at valve’s closing element. The leakage value can be efficiently and quantitatively evaluated by recording acoustic signals. The levels of acoustic signals are different at different testing conditions. In order to determine the correspondence between different levels of acoustic signals and different leakage values, it is necessary to carry out some experiments on real tested objects. Since 2011 “Lenorgenergogaz” together with “INTERYUNIS” have been devising a technique for leak integrity evaluation of shut-off valves at gas-compressor stations. A large amount of experiments on more than 130 units of shut-off valves installed both on ground and underground was carried out. The algorithm for leakage detection in case a typical “leakage” signal is received has been developed; empirical dependences for leakage evaluation on the basis of acoustic emission signal parameters have been obtained for main types of shut-off valves installed at “Gasprom Transgas St. Petersburg” objects. The article presents the results of research work on leak integrity evaluation of valves at “Portovaya” gas-compressor station. The stabbing valves DN800 mm installed at a segment of a reverse pipeline were the object of the research. Leak integrity test was carried out using both a manometric and an acoustic technique with quantitative leakage evaluation for every closing element. The results of each method have agreed with an error no more than 20%. Visual inspection of stabbing valves inner parts has shown that seat guide firming are damaged; this fact indirectly confirms the quantitative evaluation of shut-off valves leaktightness. Conclusions made on the basis of obtained results can serve as a foundation for acoustic emission leak integrity evaluation technique for shut-off valves.

Classification of acoustic emission sources produced by carbon/epoxy composite based on support vector machine

Carbon/epoxy specimens were made and stretched to fracture. In the process, acoustic emission (AE) signals were collected and their parameters were set as the input parameters of the neural network. Results show that using support vector machine (SVM) network can recognize the difference of AE sources more accurately than using the BP neural network. In addition, the accuracy of the SVM increases when the number of the training set increases. It is proved that using AE signal parameters and SVM network can recognize the AE sources’ pattern well.

Identification of damage mode in AZ31 magnesium alloy under tension using acoustic emission

In order to characterize different damage modes, real-time detection of the tensile cracking process for AZ31 magnesium alloy was performed using acoustic emission (AE) technique. Results showed that elastic deformation, plastic deformation, microcracking, stable and unstable propagation occurred during crack damage. Four damage modes were determined using AE multiparameter analysis. Dislocation motion signals with amplitudes <70 dB and twinning signals with 70–100 dB were found. Microcrack signal energy was concentrated from 2400 aJ to 4100 aJ, mainly at a rise time of less than 800 μs. A stable crack propagation signal had high peak to counts in the 20 to 50 range, whereas its ring count was in the 20 to 2000 range. The average frequency of unstable propagation signals was approximately 100 kHz, with duration from 2000 μs to 105 μs. The damage mechanisms and AE resources from different crack propagation steps were discussed. Various damage modes could be characterized by different AE signal parameters when they appeared simultaneously during crack propagation.

Monitoring of Tool Vibration for Magnetorheological Fluid Controlled Bar During Turning ff Hardened Aisi4340 Steel

Abstract In recent times, the concept of hard turning has gained awareness in metal cutting as it can apparently replace the traditional process cycle of turning, heat treating, and finish grinding for assembly of hard, wear-resistant steel parts. The major apprehension in hard turning is the tool vibration, which affects the surface finish of the work piece, has to be controlled and monitored. In order to control tool vibration in metal cutting, a magnetorheological fluid damper which has received great attention in suppressing tool vibration was developed and used. Also an attempt has been made in this study to monitor tool vibration using the skewness and kurtosis parameters of acoustic emission (AE) signal for the tool holder with and without magnetorheological damper. Cutting experiments were conducted to arrive at a set of operating parameters that can offer better damping characteristics to minimize tool vibration during turning of AISI4340 steel of 46 HRC using hard metal insert with sculptured rake face. From the results, it was observed that the presence of magnetorheological damper during hard turning reduces tool vibration and there exist a strong relationship between tool vibration and acoustic emission (AERMS) signals to monitor tool condition. This work provides momentous understanding on the usage of magnetorheological damper and AE sensor to control and monitor the tool condition during turning of hardened AISI4340 steel

Monitoring Rock Failure Processes Using the Hilbert–Huang Transform of Acoustic Emission Signals

Rock fracturing generates acoustic emission (AE) signals that have statistical parameters referred to as AE signal parameters (AESP). Identification of rock fracturing or the failure process stage using such data raises several challenges. This study proposes a Hilbert–Huang transform-based AE processing approach to capture the time–frequency characteristics of both AE signals and AESP during rock failure processes. The damage occurring in tested rock specimens can be illustrated through analysis using this method. In this study, the specimens were 25 × 60 × 150 mm3 in size and were compressed at a displacement rate of 0.05 mm/min until failure. The recorded data included force and displacement, AE signals, and AESP. The AESP in the last third of the strain range period and 14 typical moments of strong AE signals were selected for further investigation. These results show that AE signals and AESP can be jointly used for identification of deformation stages. The transition between linear and nonlinear deformation stages was found to last for a short period in this process. The instantaneous frequency of the AE effective energy rate increased linearly from 0.5 to 1.5 Hz. Attenuation of elastic waves spreading in rock samples developed with deformation, as illustrated in the Hilbert spectra of AE signals. This attenuation is frequency dependent. Furthermore, AE signals in the softening process showed a complex frequency distribution attributed to the mechanical properties of the tested specimen. The results indicate that rock failure is predictable. The novel technology applied in this study is feasible for analysis of the entire deformation process, including softening and failure processes.