scholarly journals Application of Acoustic Emission Technique to the Evaluation of Coal Seam Hydraulic Flushing Effect

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1705 ◽  
Author(s):  
Rongxi Shen ◽  
Xuan Zhang ◽  
Enyuan Wang ◽  
Hongru Li ◽  
Xu Han ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Coal Seam ◽  
Gas Flow ◽  
Damage Mechanics ◽  
Water Pressure ◽  
Quantitative Relationship ◽  
Practical Significance ◽  
Effect Evaluation ◽  
Permeability Enhancement ◽  
Ae Signals

Hydraulic flushing has the advantages of reducing coal stress and improving coal seam permeability, so it is widely used in high gas outburst coal seams in China. However, the effect evaluation of stress relief and permeability enhancement will be necessary before coal mining. In this paper, an acoustic emission (AE) experiment system of coal seam hydraulic flushing was established, and the AE characteristics of coal during hydraulic flushing were studied. The results show that the changes in AE signals are basically consistent with those in load and water pressure. In addition, the quantitative relationship between the signals and the damage of coal around the borehole is revealed by the theory of damage mechanics. The in-situ AE test of hydraulic flushing was performed in the Liangbei Coal Mine, by measuring gas flow and coal stress simultaneously. The variation of AE activities and the effect evaluation of hydraulic flushing were analyzed. The results reveal that the changes in coal seam stress are basically consistent with those of AE signals. After the flushing has been completed for 1–3 h, the coal seam stress decreases rapidly, and the AE counts and intensity reach the peak. Therefore, this study proposes a new method for evaluating the effect of coal seam hydraulic flushing by AE, which has a very important practical significance.

Quantitative Relationship between Strain and Acoustic Emission Response in Monitoring Fatigue Damage

2013 ◽  
Vol 66 (1) ◽  
Author(s):  
M. Mohammad ◽  
S. Abdullah ◽  
N. Jamaludin ◽  
O. Innayatullah
Keyword(s):  
Acoustic Emission ◽  
Failure Mechanism ◽  
Fatigue Failure ◽  
Quantitative Relationship ◽  
Steel Specimen ◽  
Cyclic Fatigue ◽  
Steel Component ◽  
Specific Data ◽  
The Relationship ◽  
Ae Signals

This study was carried out to investigate the relationship between the strain and acoustic emission (AE) signals, thus, to confirm the capability of AE technique to monitor the fatigue failure mechanism of a steel component. To achieve this goal, strain and AE signals were captured on the steel specimen during the cyclic fatigue test.  Both signals were collected using specific data acquisition system by attaching the strain gauge and AE piezoelectric transducer simultaneously at the specimen during the test. The stress loading used for the test was set at 600 MPa, and the specimens were fabricated using the SAE 1045 carbon steel.  The related parameters for both signals were determined at every 2000 seconds until the specimen failed.  It was found that a meaningful correlation of all parameters, i.e. amplitude, kurtosis and energy, was established. Finally, all AE parameters are correlated with the damage values, which have been estimated using the Coffin-Manson model.  Hence, it was suggested that the AE technique can be used as a monitoring tool for fatigue failure mechanism in a steel component.

scholarly journals Quantitative Damage and Fracture Mode of Sandstone under Uniaxial Load Based on Acoustic Emission

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ying Xu ◽  
Qiangqiang Zheng ◽  
Xin Gao ◽  
Rongzhou Yang ◽  
Xian Ni ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Fracture Mechanism ◽  
Damage Mechanics ◽  
Shear Failure ◽  
Rock Fracture ◽  
Damage Model ◽  
Damage Models ◽  
Uniaxial Load ◽  
Damage And Fracture ◽  
Ae Signals

The damage degree and fracture mechanism of the rock are important to the bearing performance of the rock mass and the stability of the overlying structure. Most of the existing damage models for characterizing rock damage exclude the range of postpeak stress or do not consider the compaction and closure stage of the fracture, and the description of the quantitative damage of sandstone is not accurate enough. In addition, the description of the rock fracture mechanism under load is not exact enough. Aiming at the problem of quantitative damage and fracture mechanism of the loaded rock, this paper adopts acoustic emission (AE) to monitor the loading process of sandstone under uniaxial loading. In accordance with the characteristics of the AE signal, the loading stage of sandstone under uniaxial load is divided into three stages: initial hit stage, hit stability stage, and hit instability stage. By modifying the traditional damage model and combining the AE signals of the sandstone under the load, a modified damage mechanics model is obtained, which can fully express the entire loading stage. Furthermore, through the analysis of AE signals, the fracture mechanism of sandstone under uniaxial load is studied. The results show that the modified damage model can quantitatively describe the damage at different loading stages which include two areas including the fracture compaction closure stage and the postpeak stress stage. The failure and instability of sandstone under uniaxial load is mainly shear failure. The research results can provide a reference for the nondestructive testing of sandstone and engineering reliability in geotechnical engineering.

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.

Grinding Acoustic Emission Classification in Terms of Mechanical Behaviours

2007 ◽  
Vol 329 ◽  
pp. 15-20 ◽  
Author(s):  
Xun Chen ◽  
James Griffin
Keyword(s):  
Neural Network ◽  
Acoustic Emission ◽  
Material Removal ◽  
Grinding Process ◽  
Short Time Fourier Transform ◽  
Fundamental Investigation ◽  
Mechanical Behaviours ◽  
Wavelets Transform ◽  
Short Time ◽  
Ae Signals

The material removal in grinding involves rubbing, ploughing and cutting. For grinding process monitoring, it is important to identify the effects of these different phenomena experienced during grinding. A fundamental investigation has been made with single grit cutting tests. Acoustic Emission (AE) signals would give the information relating to the groove profile in terms of material removal and deformation. A combination of filters, Short-Time Fourier Transform (STFT), Wavelets Transform (WT), statistical windowing of the WT with the kurtosis, variance, skew, mean and time constant measurements provided the principle components for classifying the different grinding phenomena. Identification of different grinding phenomena was achieved from the principle components being trained and tested against a Neural Network (NN) representation.

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.

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