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.

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.

scholarly journals Identification of Deformation Stage and Crack Initiation in TC11 Alloys Using Acoustic Emission

2020 ◽  
Vol 10 (11) ◽  
pp. 3674
Author(s):  
Jiaoyan Huang ◽  
Zhiheng Zhang ◽  
Cong Han ◽  
Guoan Yang
Keyword(s):  
Acoustic Emission ◽  
Titanium Alloy ◽  
Crack Initiation ◽  
Peak Frequency ◽  
Identification Accuracy ◽  
Energy Ratio ◽  
Frequency Bands ◽  
Mode Decomposition ◽  
Tc11 Titanium Alloy ◽  
Ae Signals

The Acoustic Emission (AE) is a widely used real-time monitoring technique for the deformation damage and crack initiation of areo-engine blades. In this work, a tensile test for TC11 titanium alloy, one of the main materials of aero-engine, was performed. The AE signals from different stages of this test were collected. Then, the AE signals were decomposed by the Variational Mode Decomposition (VMD) method, in which the signals were divided into two different frequency bands. We calculated the engery ratio by dividing the two different frequency bands to characterize TC11′s degree of deformation. The results showed that when the energy ratio was −0.5 dB, four stages of deformation damage of the TC11 titanium alloy could be clearly identified. We further combined the calculated Partial Energy Ratio (PER) and Weighted Peak Frequency (WPF) to identify the crack initiation of the TC11 titanium alloy. The results showed that the identification accuracy was 96.33%.

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.

Monitoring of Failure Mechanisms in Fiber Reinforced Composites During Cryogenic Cooling by Acoustic Emission

2003 ◽  
Vol 17 (08n09) ◽  
pp. 1763-1769 ◽  
Author(s):  
Nak Sam Choi ◽  
Sung Choong Woo ◽  
Tae Won Kim ◽  
Kyong Y. Rhee
Keyword(s):  
Acoustic Emission ◽  
High Frequency ◽  
Composite Laminates ◽  
Low Frequency ◽  
Cryogenic Cooling ◽  
Reinforced Composites ◽  
Frequency Bands ◽  
Initial Stage ◽  
The Matrix ◽  
Ae Signals

Microfractures in composite laminates during cryogenic cooling were monitored employing thermo-acoustic emission(AE). During the initial stage of cryogenic cooling, very strong AE signals with low and high frequency bands were dominantly detected showing a development of large cracks accompanying fiber breakages. After that, weak emissions with low frequency bands became prevalent indicating the propagation of microfractures in the matrix and/or fiber-matrix interface. It was concluded that the breakage of bridged-fibers hindering the macroscopic cracking in the initial stage might be the representative cryogenic damage of composite laminates.

ACOUSTIC EMISSION CONTROL OF THE PROCESS OF DESTRUCTION OF SAMPLES FROM CARBON PLASTIC DURING STATIC LOAD, POSITIVE AND NEGATIVE TEMPERATURES

2019 ◽  
pp. 34-41 ◽  
Author(s):  
L. N. Stepanova ◽  
V. V. Chernova
Keyword(s):  
Acoustic Emission ◽  
Static Load ◽  
Tensile Load ◽  
Dominant Frequency ◽  
Carbon Plastic ◽  
Strength Tests ◽  
Partial Energy ◽  
Static Tensile ◽  
Geometrical Dimensions ◽  
Ae Signals

Strength tests of T800 carbon-fiber specimens with geometrical dimensions 100×600×0.9 mm were performed. The CFRP material used a stacking of nine mono-layers [±45/90/03/90/±45]. In the central part of the samples, a stress concentrator was placed in the form of a hole with a diameter of 12 mm. The loading with a static tensile load was carried out by the loading machine MTS-100 with hydraulic grips. Simultaneously with static loading, the sample was affected by positive (+20; +100 °С) or negative (–20; –40; –60 °С) temperatures. Registration information was carried out using the method of acoustic emission (AE). In the process of loading the samples, the effect of static load and temperature on the main informative parameters (amplitude, dominant frequency, structural coefficient) of AE signals recorded during the loading of samples was studied. The structure coefficient, reflecting the energy at one frequency, and the coefficient, calculated as a partial energy, were compare.

Acoustic Emission Signal Analysis for Tool Condition Monitoring in Microendmilling of Aluminium Alloy

2014 ◽  
Vol 984-985 ◽  
pp. 25-30
Author(s):  
Muniyandi Prakash ◽  
P. Ravisankar ◽  
Mani Kanthababu
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Aluminium Alloy ◽  
Condition Monitoring ◽  
Dominant Frequency ◽  
Tool Condition Monitoring ◽  
Tool Condition ◽  
Ae Energy ◽  
Ae Signal ◽  
Ae Signals

In this study, the effect of tool wear is correlated with acoustic emission (AE) signal during microendmilling of aluminium alloy (AA 1100). The AE signals were acquired using Kistler make AE sensor and the signal features are analyzed in time domain (root mean square (RMS)) and frequency domain (dominant frequency and amplitude). The dominant frequency of the AE signal shows increasing trend with increase in the tool wear, where as AERMSshow uneven trend. The discrete wavelet transformation technique (DWT) has also been carried out by decomposing the required AE signal in different frequency bands. The AERMSand specific AE energy were computed for the decomposed AE signals. From the specific AE energy, it is observed that shearing occurs during microendmilling and also found to be similar that of macro-regieme endmilling. The result demonstrated that the AE signals are potential indicator for tool condition monitoring in microendmilling.

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.

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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