© 2015 Elsevier B.V. All rights reserved. Locating the sources of elastic waves during rapid local stress relaxation in solids under load is a central element in acoustic emission non-destructive testing, seismology, etc. The location problem relies heavily on the accuracy of arrival time detection. To increase the reliability of real time signal detection and to ensure precise phase picking of transient waveforms of a low amplitude, we propose a novel Wavelet transform-based algorithm. Benefiting strongly from the neighboring concepts in the wavelet theory, the shortcomings of conventional amplitude threshold-based and Short Term Average/Long Term Average methods are addressed. The proposed method was validated in a variety of acoustic emi...
Many seismology applications such as earthquake hypocenter determination, source mechanism analysis...
Onset detection of P-wave in seismic signals is of vital importance to seismologists because it is n...
In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective math...
© 2015 Elsevier B.V. All rights reserved. Locating the sources of elastic waves during rapid local s...
This paper investigates the development of an in situ impact detection monitoring system able to ide...
This paper investigates the development of an in situ impact detection monitoring system able to ide...
Acoustic emission (AE) monitoring is carried out during proof pressure testing of pressurevessels to...
In Part 2, the same finite-element-generated database of acoustic emission (AE) signals was used, as...
Accurately determined acoustic emission (AE) locations provide significant information on fracture s...
A novel methodology is proposed to enhance the reliability of detection of low amplitude transients ...
A commonality in the many applications and domains where signal processing (SP)is applied is the det...
Acoustic Emission (AE) monitoring can be used to detect the presence of damage as well as determine ...
We report a new method using a time delay neural network to transform acoustic emission (AE) wavefor...
This paper deals with acoustic event detection (AED), such as screams, gunshots, and explosions, in ...
The discrete time wavelet transform has been used to develop software that detects seismic P and S-p...
Many seismology applications such as earthquake hypocenter determination, source mechanism analysis...
Onset detection of P-wave in seismic signals is of vital importance to seismologists because it is n...
In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective math...
© 2015 Elsevier B.V. All rights reserved. Locating the sources of elastic waves during rapid local s...
This paper investigates the development of an in situ impact detection monitoring system able to ide...
This paper investigates the development of an in situ impact detection monitoring system able to ide...
Acoustic emission (AE) monitoring is carried out during proof pressure testing of pressurevessels to...
In Part 2, the same finite-element-generated database of acoustic emission (AE) signals was used, as...
Accurately determined acoustic emission (AE) locations provide significant information on fracture s...
A novel methodology is proposed to enhance the reliability of detection of low amplitude transients ...
A commonality in the many applications and domains where signal processing (SP)is applied is the det...
Acoustic Emission (AE) monitoring can be used to detect the presence of damage as well as determine ...
We report a new method using a time delay neural network to transform acoustic emission (AE) wavefor...
This paper deals with acoustic event detection (AED), such as screams, gunshots, and explosions, in ...
The discrete time wavelet transform has been used to develop software that detects seismic P and S-p...
Many seismology applications such as earthquake hypocenter determination, source mechanism analysis...
Onset detection of P-wave in seismic signals is of vital importance to seismologists because it is n...
In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective math...