Empirical Approach to Defect Detection Probability by Acoustic Emission Testing

2021 ◽  
Vol 11 (20) ◽  
pp. 9429
Author(s):  
Vera Barat ◽  
Artem Marchenkov ◽  
Valery Ivanov ◽  
Vladimir Bardakov ◽  
Sergey Elizarov ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Defect Detection ◽  
Probabilistic Models ◽  
Fatigue Cracks ◽  
A Priori ◽  
Empirical Approach ◽  
Empirical Generalization ◽  
Microstructure Parameters ◽  
A Priori Estimation ◽  
Ae Signals

Estimation of probability of defect detection (POD) is one of the most important problems in acoustic emission (AE) testing. It is caused by the influence of the material microstructure parameters on the diagnostic data, variability of noises, the ambiguous assessment of the materials emissivity, and other factors, which hamper modeling the AE data, as well as the a priori determination of the diagnostic parameters necessary for calculating POD. In this study, we propose an empirical approach based on the generalization of the experimental AE data acquired under mechanical testing of samples to a priori estimation of the AE signals emitted by the defect. We have studied the samples of common industrial steels 09G2S (similar to steel ANSI A 516-55) and 45 (similar to steel 1045) with fatigue cracks grown in laboratory conditions during cyclic testing. Empirical generalization of data using probabilistic models enables estimating the conditional probability of record emissivity and amplitudes of AE signals. This approach allows to eliminate the existing methodological gap and to build a comprehensive method for assessing the probability of fatigue cracks detection by the AE testing.

scholarly journals Proportional monitoring of the acoustic emission in crypto-conditions

2011 ◽  
Vol 59 (5) ◽  
pp. 31-38 ◽  
Author(s):  
Petr Dostál ◽  
Michal Černý ◽  
Jaroslav Lev ◽  
David Varner
Keyword(s):  
Acoustic Emission ◽  
Aluminum Alloys ◽  
Real Time ◽  
Fatigue Cracks ◽  
Current Status ◽  
Fatigue Properties ◽  
Material Degradation ◽  
Emission Method ◽  
Important Benefit ◽  
Ae Signals

The work is aimed at studying corrosion and fatigue properties of aluminum alloys by means of acoustic emission (AE). During material degradation are acoustic events scanned and evaluated. The main objective of the article is a description of behavior of aluminum alloys degraded in specific conditions and critical degradation stages determination. The first part of the article describes controlled degradation of the material in the crypto–conditions. The acoustic emission method is used for process analyzing. This part contains the AE signals assessment and comparing aluminium alloy to steel. Then the specimens are loaded on high-cyclic loading apparatus for fatigue life monitoring. Also, the synergy of fatigue and corrosion processes is taken into account.The aim is the description of fatigue properties for aluminum alloys that have already been corrosion-degraded. Attention is also focused on the structure of fatigue cracks. The main part of the article is aimed at corrosion degradation of aluminium alloys researched in real time by means of AE. The most important benefit of AE detection/recording is that it provides information about the process in real time. Using this measurement system is possible to observe the current status of the machines/devices and to prevent serious accidents.

scholarly journals Analytical Modeling of Acoustic Emission Signals in Thin-Walled Objects

2019 ◽  
Vol 10 (1) ◽  
pp. 279 ◽  
Author(s):  
Vera Barat ◽  
Denis Terentyev ◽  
Vladimir Bardakov ◽  
Sergey Elizarov
Keyword(s):  
Acoustic Emission ◽  
Data Processing ◽  
Defect Detection ◽  
Analytical Method ◽  
Analytical Modeling ◽  
Location Accuracy ◽  
Defect Location ◽  
Thin Walled ◽  
Noisy Background ◽  
Ae Signals

For the effective detection of acoustic emission (AE) impulses against a noisy background, the correct assessment of AE parameters, and an increase in defect location accuracy during data processing are needed. For these goals, it is necessary to consider the waveform of the AE impulse. The results of numerous studies have shown that the waveforms of AE impulses mainly depend on the properties of the waveguide, the path along which the signal propagates from the source to the sensor. In this paper, the analytical method for modeling of AE signals is considered. This model allows one to obtain model signals that have the same spectrum and waveform as real signals. Based on the obtained results, the attenuation parameters of the AE waves for various characteristics of the waveguide are obtained and the probability of defect detection at various distances between the AE source and sensor utilized for evaluation.

Detection and Monitoring of Fatigue Cracks in Metallic Structures Using Acoustic Emission: Routes to Quantification of Probability of Detection

2014 ◽  
Vol 891-892 ◽  
pp. 1268-1274 ◽  
Author(s):  
Daniel Gagar ◽  
Peter Foote ◽  
Phil E. Irving
Keyword(s):  
Acoustic Emission ◽  
Fatigue Crack ◽  
Fatigue Cracks ◽  
Failure Process ◽  
Probability Of Detection ◽  
Metallic Structures ◽  
Final Failure ◽  
Ae Signal ◽  
Non Destructive ◽  
Ae Signals

The performance and reliability of Structural Health Monitoring (SHM) techniques remain largely unquantified. This is in contrast to the probability of detection (POD) and sensitivity of manual non destructive inspection methods which are well characterised. In this study factors influencing the rates of emission of Acoustic Emission (AE) signals from propagating fatigue cracks were investigated. Fatigue crack growth experiments were performed in 2014 T6 aluminium sheet to observe the effects of changes in crack length, loading spectrum and sample geometry on rates of emission and the probability of detecting and locating the fatigue crack. Significant variation was found in the rates of AE signal generation during crack progression from initiation to final failure. AE signals at any point in the failure process were found to result from different failure mechanisms operating at particular stages in the failure process.

Characterization of acoustic emission signals from fatigue fracture

2000 ◽  
Vol 214 (9) ◽  
pp. 1141-1149 ◽  
Author(s):  
Z Shi ◽  
J Jarzynski ◽  
S Bair ◽  
S Hurlebaus ◽  
L. J. Jacobs
Keyword(s):  
Acoustic Emission ◽  
Transfer Functions ◽  
Fatigue Cracks ◽  
Experimental Program ◽  
Fracture Mechanisms ◽  
Torsional Fatigue ◽  
Quantitative Understanding ◽  
Critical Components ◽  
Ae Signals ◽  
Geometric Effects

This paper discusses a comprehensive study that is developing a quantitative understanding of the acoustic emission (AE) signals that emanate from fatigue cracks. Two critical components of this study are the development of a transfer function that quantifies and removes geometric effects from a measured AE waveform and an experimental program that monitors and identifies AE signals that occur during the fatigue of cylindrical stainless steel specimens under torsion. Typical waveforms are collected during torsional fatigue and correlated with fracture mechanisms from different stages of testing. Three stages of fatigue are identified by AE waveform characterization and confirmed by microscopic replica observation. The other portion of this study demonstrates the effectiveness of using laser ultrasonic techniques to develop transfer functions to quantify and remove geometric effects from measured acoustic emission waveforms.

Использование амплитудного анализа сигналов акустической эмиссии при циклическом и статическом нагружении стальных образцов

2021 ◽  
pp. 18-26
Author(s):  
Л.Н. Степанова ◽  
М.М. Кутень ◽  
А.Л. Бобров
Keyword(s):  
Acoustic Emission ◽  
Carbon Steel ◽  
Fatigue Cracks ◽  
Low Carbon Steel ◽  
Research Data ◽  
Combined Loading ◽  
Low Carbon ◽  
Amplitude Analysis ◽  
Sensitivity Level ◽  
Ae Signals

The results of amplitude analysis of discrete acoustic emission signals from developed sources such as fatigue cracks are presented. A combined loading of low-alloy and low-carbon steel samples with stress concentrators was carried out. The analysis of the probability density of the distribution of the registered AE signals from one source by amplitudes was made. A power-behaved dependence of the frequency of distribution of the amplitude of signals with a high correlation coefficient for AE sources has been established. The research data made it possible to develop a method for restoring the total number of acoustic emission acts from a source at a given sensitivity level.

scholarly journals Analysis of Acoustic Emission (AE) Signals for Quality Monitoring of Laser Lap Microwelding

2021 ◽  
Vol 11 (15) ◽  
pp. 7045
Author(s):  
Ming-Chyuan Lu ◽  
Shean-Juinn Chiou ◽  
Bo-Si Kuo ◽  
Ming-Zong Chen
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Frequency Domain ◽  
Monitoring System ◽  
Welding Quality ◽  
Steel Sheets ◽  
Signal Features ◽  
Ae Signal ◽  
Laser Microwelding ◽  
Ae Signals

In this study, the correlation between welding quality and features of acoustic emission (AE) signals collected during laser microwelding of stainless-steel sheets was analyzed. The performance of selected AE features for detecting low joint bonding strength was tested using a developed monitoring system. To obtain the AE signal for analysis and develop the monitoring system, lap welding experiments were conducted on a laser microwelding platform with an attached AE sensor. A gap between the two layers of stainless-steel sheets was simulated using clamp force, a pressing bar, and a thin piece of paper. After the collection of raw signals from the AE sensor, the correlations of welding quality with the time and frequency domain features of the AE signals were analyzed by segmenting the signals into ten 1 ms intervals. After selection of appropriate AE signal features based on a scatter index, a hidden Markov model (HMM) classifier was employed to evaluate the performance of the selected features. Three AE signal features, namely the root mean square (RMS) of the AE signal, gradient of the first 1 ms of AE signals, and 300 kHz frequency feature, were closely related to the quality variation caused by the gap between the two layers of stainless-steel sheets. Classification accuracy of 100% was obtained using the HMM classifier with the gradient of the signal from the first 1 ms interval and with the combination of the 300 kHz frequency domain signal and the RMS of the signal from the first 1 ms interval.

scholarly journals Acoustic Emission Testing and Ib-Value Analysis of Ultraviolet Light-Irradiated Fiber Composites

2021 ◽  
Vol 11 (14) ◽  
pp. 6550
Author(s):  
Doyun Jung ◽  
Wonjin Na
Keyword(s):  
Acoustic Emission ◽  
Irradiation Time ◽  
Tensile Load ◽  
Failure Behavior ◽  
Value Analysis ◽  
Emission Testing ◽  
Final Failure ◽  
Acoustic Emission Testing ◽  
Woven Glass Fiber ◽  
Ae Signals

The failure behavior of composites under ultraviolet (UV) irradiation was investigated by acoustic emission (AE) testing and Ib-value analysis. AE signals were acquired from woven glass fiber/epoxy specimens tested under tensile load. Cracks initiated earlier in UV-irradiated specimens, with a higher crack growth rate in comparison to the pristine specimen. In the UV-degraded specimen, a serrated fracture surface appeared due to surface hardening and damaged interfaces. All specimens displayed a linearly decreasing trend in Ib-values with an increasing irradiation time, reaching the same value at final failure even when the starting values were different.

Acoustic Emission Monitoring of Leaks in Pipes for Transport of Liquid and Gaseous Media: A Model Experiment

2006 ◽  
Vol 13-14 ◽  
pp. 351-356 ◽  
Author(s):  
Andreas J. Brunner ◽  
Michel Barbezat
Keyword(s):  
Acoustic Emission ◽  
Model Experiment ◽  
Structural Integrity ◽  
Fiber Composite ◽  
Leak Testing ◽  
Pipe Segment ◽  
Potential Applications ◽  
Gaseous Media ◽  
The Media ◽  
Ae Signals

In order to explore potential applications for Active Fiber Composite (AFC) elements made from piezoelectric fibers for structural integrity monitoring, a model experiment for leak testing on pipe segments has been designed. A pipe segment made of aluminum with a diameter of 60 mm has been operated with gaseous (compressed air) and liquid media (water) for a range of operating pressures (between about 5 and 8 bar). Artificial leaks of various sizes (diameter) have been introduced. In the preliminary experiments presented here, commercial Acoustic Emission (AE) sensors have been used instead of the AFC elements. AE sensors mounted on waveguides in three different locations have monitored the flow of the media with and without leaks. AE signals and AE waveforms have been recorded and analysed for media flow with pressures ranging from about 5 to about 8 bar. The experiments to date show distinct differences in the FFT spectra depending on whether a leak is present or not.

scholarly journals A Principal Component Analysis of Acoustic Emission Signals from a Landing Gear Component

2008 ◽  
Vol 13-14 ◽  
pp. 41-47 ◽  
Author(s):  
Rhys Pullin ◽  
Mark J. Eaton ◽  
James J. Hensman ◽  
Karen M. Holford ◽  
Keith Worden ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Acoustic Emission ◽  
Background Noise ◽  
Principal Component ◽  
Component Analysis ◽  
Landing Gear ◽  
Fracture Detection ◽  
Artificial Fracture ◽  
High Level ◽  
Ae Signals

This work forms part of a larger investigation into fracture detection using acoustic emission (AE) during landing gear airworthiness testing. It focuses on the use of principal component analysis (PCA) to differentiate between fracture signals and high levels of background noise. An artificial acoustic emission (AE) fracture source was developed and additionally five sources were used to generate differing AE signals. Signals were recorded from all six artificial sources in a real landing gear component subject to no load. Further to this, artificial fracture signals were recorded in the same component under airworthiness test load conditions. Principal component analysis (PCA) was used to automatically differentiate between AE signals from different source types. Furthermore, successful separation of artificial fracture signals from a very high level of background noise was achieved. The presence of a load was observed to affect the ultrasonic propagation of AE signals.

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