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.

scholarly journals Analysis of the results of acoustic emission diagnostics of a structure during helicopter fatigue tests

Aviation ◽  
2018 ◽  
Vol 21 (2) ◽  
pp. 64-69 ◽  
Author(s):  
Aleksandrs URBAHS ◽  
Kristine CARJOVA ◽  
Jurijs FESCUKS
Keyword(s):  
Acoustic Emission ◽  
Measurement Data ◽  
Fatigue Tests ◽  
Parameter Analysis ◽  
Inspection Method ◽  
Characteristic Structure ◽  
Ae Signal ◽  
Diagnostic Measurement ◽  
Non Destructive ◽  
Ae Signals

The study is devoted to a perspective diagnostic method, which makes it possible to deal with diagnostic tasks – the acoustic non-destructive inspection method based on acoustic emission (AE) signal parameter analysis. The practical use of this method is related to the interpretation of diagnostic measurement data. The parameters of acoustic emission (AE) signals were measured during bench tests of the tail boom structure and fin, as well as the joint areas of the fin, tail boom, and fuselage of the helicopter (joint area No.1 and No.19, frames of the tail boom and fuselage respectively).The analysis of fatigue damage kinetics was carried out in several stages for groups of bolts and for characteristic structure loading intervals. Bolt fracture was predicted at least 26 to 44 flight hours before the actual collapse. Using the AE parameters, the micro crack origin intervals identified when the bolt bearing capacity after the occurrence of the damage reached 96%.

scholarly journals Determining the Characteristics of Acoustic Emission in the Fatigue Crack Growth of Aluminum Alloy 2025 for Online Structural Monitoring

2021 ◽  
Author(s):  
Javad Sharifi Ghaderi
Keyword(s):  
Acoustic Emission ◽  
Aluminum Alloy ◽  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Crack Growth ◽  
Fatigue Cracks ◽  
Structural Monitoring ◽  
Acoustic Emission Method ◽  
Emission Method ◽  
Non Destructive

In the use of metals, due to industrial advances and the application of more dynamic loads, it is necessary to pay more attention to the fatigue issue. Non-destructive inspection methods are used to condition and health monitoring of structures at the time of production and even during the service life of parts. Among non-destructive methods, the acoustic emission method has become a standard and reliable method in recent years. In this project, the characteristics of acoustic emission in the fatigue crack growth of aluminum alloy 2025 for online structural monitoring have been investigated and determined. Acoustic emission tests have been performed in two parts: bending fatigue test with the aim of initiation of fatigue cracks in aluminum alloy 2025 specimens and following tensile tests with the aim of growth of fatigue cracks. The acoustic emission signals and parameters sent by the acoustic emission sensor during both tests were received and recorded by the acoustic emission software. According to the received acoustic emission information, various diagrams are plotted. Analyzing the results from online acoustic emission monitoring showed, the acoustic emission method can be considered as a suitable and reliable technique for detecting crack initiation and crack growth in aluminum alloy 2025.

scholarly journals Estimation of Fatigue Crack AE Emissivity Based on the Palmer–Heald Model

2019 ◽  
Vol 9 (22) ◽  
pp. 4851
Author(s):  
Vera Barat ◽  
Artem Marchenkov ◽  
Sergey Elizarov
Keyword(s):  
Acoustic Emission ◽  
Fatigue Crack ◽  
Fatigue Cracks ◽  
Experimental Studies ◽  
Steel Structures ◽  
Random Variable ◽  
Probability Of Detection ◽  
Materials Testing ◽  
Distribution Law ◽  
Maximum Value

This article is devoted to materials testing by the acoustic emission (AE) method, which is the analysis of models and diagnostic parameters to assess the probability of detection of a defect in steel structures. The paper proposes to evaluate the emissivity of the material quantitatively by the number and dynamics of the accumulation of acoustic emission impulses. Experimental studies were carried out on pearlitic structural steels, including the loading of samples with fatigue cracks. It was established that the number of AE impulses emitted during loading of an object with a fatigue crack is a random variable corresponding to the normal distribution law. The results show that an estimate of the number of AE impulses emitted during the loading of samples with fatigue cracks can be obtained by distributing the multiplicative parameter D of the Palmer-Heald model by taking into account the maximum value of the applied load.

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.

Guided Wave Acoustic Emission from Fatigue Crack Growth in Aluminium Plate

2006 ◽  
Vol 13-14 ◽  
pp. 23-28 ◽  
Author(s):  
C.K. Lee ◽  
Jonathan J. Scholey ◽  
Paul D. Wilcox ◽  
M.R. Wisnom ◽  
Michael I. Friswell ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Crack Growth ◽  
Elastic Waves ◽  
Fatigue Cracks ◽  
Guided Wave ◽  
Experimental Results ◽  
Multiple Reflections ◽  
Alloy Plate

Acoustic emission (AE) testing is an increasingly popular technique used for nondestructive evaluation (NDE). It has been used to detect and locate defects such as fatigue cracks in real structures. The monitoring of fatigue cracks in plate-like structures is critical for aerospace industries. Much research has been conducted to characterize and provide quantitative understanding of the source of emission on small specimens. It is difficult to extend these results to real structures as most of the experiments are restricted by the geometric effects from the specimens. The aim of this work is to provide a characterization of elastic waves emanating from fatigue cracks in plate-like structures. Fatigue crack growth is initiated in large 6082 T6 aluminium alloy plate specimens subjected to fatigue loading in the laboratory. A large specimen is utilized to eliminate multiple reflections from edges. The signals were recorded using both resonant and nonresonant transducers attached to the surface of the alloy specimens. The distances between the damage feature and sensors are located far enough apart in order to obtain good separation of guided-wave modes. Large numbers of AE signals are detected with active fatigue crack propagation during the experiment. Analysis of experimental results from multiple crack growth events are used to characterize the elastic waves. Experimental results are compared with finite element predictions to examine the mechanism of AE generation at the crack tip.

Experiment on Surface Roughness and Acoustic Emission Signal in Infeed Period of Cylindrical Plunge Grinding

2013 ◽  
Vol 690-693 ◽  
pp. 2442-2445 ◽  
Author(s):  
Hao Lin Li ◽  
Hao Yang Cao ◽  
Chen Jiang
Keyword(s):  
Surface Roughness ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Feed Rate ◽  
Grinding Process ◽  
Experiment Research ◽  
Plunge Grinding ◽  
Emission Signal ◽  
Ae Signal ◽  
Ae Signals

This work presents an experiment research on Acoustic emission (AE) signal and the surface roughness of cylindrical plunge grinding with the different infeed time. The changed infeed time of grinding process is researched as an important parameter to compare AE signals and surface roughnesses with the different infeed time in the grinding process. The experiment results show the AE signal is increased by the increased feed rate. In the infeed period of the grinding process, the surface roughness is increased at first, and then is decreased.

Research on Feature Extraction Method Based on Rub-Impact Acoustic Emission Signals of Mechanical Seal End Faces

2010 ◽  
Vol 36 ◽  
pp. 68-74
Author(s):  
Chuan Jun Liao ◽  
Shuang Fu Suo ◽  
Wei Feng Huang
Keyword(s):  
Acoustic Emission ◽  
Feature Extraction ◽  
Extraction Methods ◽  
Mechanical Seal ◽  
Mechanical Seals ◽  
Feature Extraction Method ◽  
Different Types ◽  
Ae Signal ◽  
Feature Information ◽  
Ae Signals

Acoustic emission (AE) techniques are put forward to monitor rub-impacts between rotating rings and stationary rings of mechanical seals by this paper. By analyzing feature extraction methods of the typical rub-impact AE signal, the method combining of wavelet scalogram and power spectrum is found useful, and can used to attribute the feature information implicated in rub-impact AE signals of mechanical seal end faces. Both simulations and experimental research prove that the method is effective, and are used successfully to identify the typical features of different types of rub-impacts of mechanical seal end faces.

Reciprocating compressor valve damage estimation under varying speeds through the acoustic emission technique

2019 ◽  
Vol 10 (5) ◽  
pp. 621-633
Author(s):  
Hoi-Yin Sim ◽  
Rahizar Ramli ◽  
Ahmad Saifizul
Keyword(s):  
Acoustic Emission ◽  
Regression Analysis ◽  
Flow Rate ◽  
Reciprocating Compressor ◽  
Damage Estimation ◽  
Content Type ◽  
Air Compressor ◽  
Ae Signal ◽  
Valve Opening ◽  
Ae Signals

Purpose The purpose of this paper is to examine the effect of reciprocating compressor speeds and valve conditions on the roor-mean-square (RMS) value of burst acoustic emission (AE) signals associated with the physical motion of valves. The study attempts to explore the potential of AE signal in the estimation of valve damage under varying compressor speeds. Design/methodology/approach This study involves the acquisition of AE signal, valve flow rate, pressure and temperature at the suction valve of an air compressor with speed varrying from 450 to 800 rpm. The AE signals correspond to one compressor cycle obtained from two simulated valve damage conditions, namely, the single leak and double leak conditions are compared to those of the normal valve plate. To examine the effects of valve conditions and speeds on AE RMS values, two-way analysis of variance (ANOVA) is conducted. Finally, regression analysis is performed to investigate the relationship of AE RMS with the speed and valve flow rate for different valve conditions. Findings The results showed that AE RMS values computed from suction valve opening (SVO), suction valve closing (SVC) and discharge valve opening (DVO) events are significantly affected by both valve conditions and speeds. The AE RMS value computed from SVO event showed high linear correlation with speed compared to SVC and DVO events for all valve damage conditions. As this study is conducted at a compressor running at freeload, increasing speed of compressor also results in the increment of flow rate. Thus, the valve flow rate can also be empirically derived from the AE RMS value through the regression method, enabling a better estimation of valve damages. Research limitations/implications The experimental test rig of this study is confined to a small pressure ratio range of 1.38–2.03 (free-loading condition). Besides, the air compressor is assumed to be operated at a constant speed. Originality/value This study employed the statistical methods namely the ANOVA and regression analysis for valve damage estimation at varying compressor speeds. It can enable a plant personnel to make a better prediction on the loss of compressor efficiency and help them to justify the time for valve replacement in future.

scholarly journals An Experimental Investigation of Moisture-Induced Softening Mechanism of Marble Based on Quantitative Analysis of Acoustic Emission Waveforms

2019 ◽  
Vol 9 (3) ◽  
pp. 446
Author(s):  
Huang Yiming ◽  
Deng Jianhui ◽  
Zhu Jun
Keyword(s):  
Acoustic Emission ◽  
Dominant Frequency ◽  
Uniaxial Compression Test ◽  
Test Results ◽  
Frequency Bands ◽  
Softening Mechanism ◽  
Final Failure ◽  
Shear Failures ◽  
Microcosmic Mechanism ◽  
Ae Signals

The decrease of strength after saturation of rocks is known as moisture-induced softening. To date, there are numerous studies on the mechanism of moisture-induced softening of different rocks. However, due to a lack of effective observational methods, the microcosmic mechanism of moisture-induced softening still needs to be understood. We collected and processed acoustic emission (AE) signals during the uniaxial compression test of marble specimens. The results of spectral and statistical analysis show that two dominant frequency bands of AE waveforms exist regardless of the specimen’s water content. Additionally, for the AE signals from the saturated specimens, the ranges of the low and high frequency bands are wider than dried rock samples. Besides, since the tensile and shear failures in the rock release low and high dominant frequency AE signals, respectively, the test results of this paper show that micro-shear and micro-tensile failures dominate the final failure of dried and saturated rocks, respectively.

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