Wavelet analysis of acoustic emission signals and quality control in laser welding

2001 ◽  
Vol 13 (4) ◽  
pp. 167-173 ◽  
Author(s):  
Hao Zeng ◽  
Zude Zhou ◽  
Youping Chen ◽  
Hong Luo ◽  
Lunji Hu
Keyword(s):  
Quality Control ◽  
Acoustic Emission ◽  
Wavelet Analysis ◽  
Laser Welding

Online quality control of laser welding using supporting line-shaped IR detection

1999 ◽  
Author(s):  
Hans K. Toenshoff ◽  
Ferdinand von Alvensleben ◽  
Andreas Ostendorf ◽  
Oliver Hillers ◽  
Matthias Stallmach
Keyword(s):  
Quality Control ◽  
Laser Welding ◽  
Supporting Line ◽  
Online Quality Control ◽  
Ir Detection

WAVELET ANALYSIS OF ACOUSTIC EMISSION SIGNALS BASED ON ALGEBRAIC WAVELETS

2016 ◽  
pp. 34-43
Author(s):  
K. O. Osipov ◽  
R. V. Zagidulin ◽  
T. R. Zagidulin
Keyword(s):  
Acoustic Emission ◽  
Wavelet Analysis

Study of Acoustic Emission of Wheel Passivation for Cermet Based on Super-Speed Grinding

2011 ◽  
Vol 328-330 ◽  
pp. 796-800
Author(s):  
Li Guo ◽  
Hou Bin Du ◽  
Xiao Min Sheng ◽  
Ke Li Peng ◽  
Tan Jin ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Wavelet Analysis ◽  
Monitoring Method ◽  
Wavelet Energy ◽  
Grinding Conditions ◽  
Nonlinear Relation ◽  
Relation Model ◽  
On Line ◽  
Viable Method ◽  
Table Speed

In this paper, there are two kinds of material (cermet and cemented carbide) to be used. Different grinding conditions were performed for evaluation of RMS of acoustic emission(AE) signals and understanding the effect of each grinding parameter on AE RMS during grinding process. A kind of on-line monitoring method based on wavelet analysis and acoustic emission was raised and the nonlinear relation model between AE RMS,wavelet energy coefficients and wheel passivation state was built. During the process,the wavelet analysis method was used to decompose the original signals for extracting wavelet energy coefficients. The results of experiments indicates that AE RMS increases with increasing table speed;The corresponding relation between AE RMS and table speed is good and could take the table speed as the main parameter for studying wheel passivation state. As a result, the nonlinear relation model can monitor the wheel passivation degree on-line accurately through training. This provides a kind of viable method which has very high practical value for confirming the wheel dressing cycle.

Theoretic description of the nature of acoustic emission in laser welding

2001 ◽  
Author(s):  
Vitaliy A. Lopota ◽  
Gleb A. Turichin ◽  
E. A. Valdaytzeva ◽  
Ernst-Wolfgang Kreutz ◽  
Wolfgang Schulz
Keyword(s):  
Acoustic Emission ◽  
Laser Welding ◽  
Theoretic Description

Research and Analysis on Rock Acoustic Emission Wave Characteristics

2014 ◽  
Vol 638-640 ◽  
pp. 534-537
Author(s):  
Jian Ping He
Keyword(s):  
Acoustic Emission ◽  
Wavelet Analysis ◽  
Laboratory Tests ◽  
Low Frequency ◽  
Development Trend ◽  
Signal Wave ◽  
Original Signal ◽  
Great Efficiency ◽  
Wave Characteristics ◽  
Ae Signal

Analyzing wave behavior on acoustic emission laboratory tests from relationship between stress and AE rate , the rock AE signal wave in laboratory is decomposed into high and low frequency elements. Analysis and compare with the details elements include, the approximation elements and original AE wave, the results show that rock AE wave characteristics are not same in the course of transform fracture on stages, found AE wave characteristics storehouse, it is a matter of great significance for utilizing monitoring and prediction regularity and development trend in the course of fracture transform. The error between the original signal and the signal of wave coefficient of the approximation elements reconstructed is minor to, wavelet analysis makes accuracy and reliability of rock AE wave characteristics monitoring and prediction improved, States that wavelet analysis is a great efficiency method.

scholarly journals STUDY ON PROPAGATION LAW OF ACOUSTIC EMISSION SIGNALS ON ANISOTROPIC WOOD SURFACE

Wood Research ◽  
2021 ◽  
Vol 66 (4) ◽  
pp. 517-527
Author(s):  
TINGTING DENG ◽  
SHUANG JU ◽  
MINGHUA WANG ◽  
MING LI
Keyword(s):  
Acoustic Emission ◽  
Wavelet Analysis ◽  
Wood Surface ◽  
Propagation Velocity ◽  
Quadratic Function ◽  
Propagation Direction ◽  
Mode Decomposition ◽  
Propagation Law ◽  
Ae Signals ◽  
Obvious Feature

In order to explore the influence of wood’s anisotropic characteristics on Acoustic Emission (AE) signals’ propagation, the law of AE signals’ propagation velocity along different directions was studied. First, The center of the specimen’s surface was took as the AE source,then 24 directions were chose one by one every 15º around the center,and 2 AE sensors were arranged in each direction to collect the original AE signals. Second, the wavelet analysis was used to denoise the original AE signals, then the AE signals were reconstructedby Empirical Mode Decomposition (EMD). Finally, time difference location method was utilized to calculate AE signals’ propagation velocity. The results demonstrate that AE signals’ propagation velocity has obvious feature of quadratic function. In the range of 90º, as the angle of propagation direction increases, the propagation velocity of the AE signals presents a downward trend.

Sign in / Sign up

Export Citation Format

Share Document