Acoustic emission source locating in two-layer plate using wavelet packet decomposition and wavelet-based optimized residual complexity

2017 ◽  
Vol 25 (1) ◽  
pp. e2048 ◽  
Author(s):  
Amir Mostafapour ◽  
Saman Davoodi
Keyword(s):  
Acoustic Emission ◽  
Wavelet Packet ◽  
Emission Source ◽  
Wavelet Packet Decomposition ◽  
Acoustic Emission Source ◽  
Residual Complexity

Acoustic Emission Source Localization in Ring Gears from Wind Turbine Planetary Gearboxes

2019 ◽  
Vol 83 (1) ◽  
pp. 43-52 ◽  
Author(s):  
Felix Leaman ◽  
Steffen Hinderer ◽  
Ralph Baltes ◽  
Elisabeth Clausen ◽  
Brian Rieckhoff ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Wind Turbine ◽  
Source Localization ◽  
Emission Source ◽  
Acoustic Emission Source

scholarly journals Single-Sensor Acoustic Emission Source Localization in Plate-Like Structures Using Deep Learning

Aerospace ◽  
2018 ◽  
Vol 5 (2) ◽  
pp. 50 ◽  
Author(s):  
Arvin Ebrahimkhanlou ◽  
Salvatore Salamone
Keyword(s):  
Acoustic Emission ◽  
Deep Learning ◽  
Source Localization ◽  
Emission Source ◽  
Acoustic Emission Source ◽  
Single Sensor

Near-field beamforming analysis for acoustic emission source localization

Ultrasonics ◽  
2012 ◽  
Vol 52 (5) ◽  
pp. 587-592 ◽  
Author(s):  
Tian He ◽  
Qiang Pan ◽  
Yaoguang Liu ◽  
Xiandong Liu ◽  
Dayong Hu
Keyword(s):  
Acoustic Emission ◽  
Source Localization ◽  
Near Field ◽  
Emission Source ◽  
Acoustic Emission Source

Adaptive multisensor data fusion for acoustic emission source localization in noisy environment

2012 ◽  
Vol 12 (1) ◽  
pp. 59-77 ◽  
Author(s):  
Ehsan Dehghan Niri ◽  
Alireza Farhidzadeh ◽  
Salvatore Salamone
Keyword(s):  
Acoustic Emission ◽  
Data Fusion ◽  
Source Localization ◽  
Emission Source ◽  
Noisy Environment ◽  
Multisensor Data Fusion ◽  
Acoustic Emission Source ◽  
Multisensor Data

Quality Testing of the Chrome Coating Based on Acoustic Emission Technology

2012 ◽  
Vol 253-255 ◽  
pp. 399-402
Author(s):  
Xing Guo Wang
Keyword(s):  
Acoustic Emission ◽  
Assessment Method ◽  
Emission Source ◽  
Uniform Motion ◽  
Emission Testing ◽  
Acoustic Emission Source ◽  
Quality Testing ◽  
Testing Technology ◽  
Chrome Coating ◽  
Acoustic Emission Testing

A assessment method on quality detected system was developed on cylinders inner wall coating through the hydraulic radial expansive load system and acoustic emission testing technology,. Put double probes linear position principle and uniform motion of load system together, and make curved positioning come true based on the technical principle of locating acoustic emission source. The disadvantage was solved that double probes can’t make acoustic emission source planar positioning. The result showed that this system can provide a precise identification and location; it has fast testing velocity and portable device.

Acoustic emission source location in composite structure by Voronoi construction using geodesic curve evolution

2009 ◽  
Vol 126 (5) ◽  
pp. 2324-2330 ◽  
Author(s):  
R. Gangadharan ◽  
G. Prasanna ◽  
M. R. Bhat ◽  
C. R. L. Murthy ◽  
S. Gopalakrishnan
Keyword(s):  
Acoustic Emission ◽  
Composite Structure ◽  
Source Location ◽  
Emission Source ◽  
Curve Evolution ◽  
Geodesic Curve ◽  
Acoustic Emission Source

scholarly journals Time–Frequency Domain Characteristics of Acoustic Emission Signals and Critical Fracture Precursor Signals in the Deep Granite Deformation Process

2021 ◽  
Vol 11 (17) ◽  
pp. 8236
Author(s):  
Le Zhang ◽  
Hongguang Ji ◽  
Liyuan Liu ◽  
Jiwei Zhao
Keyword(s):  
Acoustic Emission ◽  
Frequency Domain ◽  
High Frequency ◽  
Wavelet Packet ◽  
Confining Pressure ◽  
Wavelet Packet Decomposition ◽  
Evolution Law ◽  
Time Frequency ◽  
Characteristic Signal ◽  
Failure Precursor

To study the crack evolution law and failure precursory characteristics of deep granite rocks in the process of deformation and failure under high confining pressure, granite samples obtained from a depth of 1150 m are tested using a TAW-2000 triaxial hydraulic servo testing machine and a PCI-II acoustic emission monitoring system. Based on the stress–strain curve and IET function, the loading process of the sample is divided into five stages: crack closure, linear elastic deformation, microcrack generation and development, macroscopic fracture generation and energy surge, and post-peak failure. The evolution trend and fracture evolution law of the acoustic emission signal event interval function in different stages are analyzed. In particular, the signals with an amplitude greater than 85 dB, a peak frequency greater than 350 kHz, and a frequency centroid greater than 275 kHz are defined as the failure precursor signals before the rock reaches the peak stress. The defined precursor signal conditions agree well with the experimental results. The time–frequency analysis and wavelet packet decomposition of the precursor signal are performed on the extracted characteristic signal of the failure precursor. The results show that the time-domain signal is in the form of a continuous waveform, and the frequency-domain waveform has multi-peak coexistence that is mainly concentrated in the high-frequency region. The energy distribution obtained by the wavelet packet decomposition of the characteristic signal is verified with the frequency-domain waveform. The energy distribution of the signal is mainly concentrated in the 343.75–375 kHz frequency band, followed by the 281.25–312.5 kHz frequency band. The energy proportion of the high-frequency signal increases with the confining pressure.

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