scholarly journals Analysis of the High-Frequency Content in Human QRS Complexes by the Continuous Wavelet Transform: An Automatized Analysis for the Prediction of Sudden Cardiac Death

Sensors ◽  
2018 ◽  
Vol 18 (2) ◽  
pp. 560 ◽  
Author(s):  
Daniel García Iglesias ◽  
Nieves Roqueñi Gutiérrez ◽  
Francisco De Cos ◽  
David Calvo
Keyword(s):  
Wavelet Transform ◽  
Sudden Cardiac Death ◽  
Continuous Wavelet Transform ◽  
High Frequency ◽  
Cardiac Death ◽  
Continuous Wavelet ◽  
Frequency Content ◽  
High Frequency Content

scholarly journals Wavelet-based Decomposition of Ground Acceleration for Efficient Calculation of Seismic Response in Elastoplastic Structures

2020 ◽  
Author(s):  
Reza Kamgar ◽  
Noorollah Majidi ◽  
Ali Heidari
Keyword(s):  
Wavelet Transform ◽  
Dynamic Analysis ◽  
Continuous Wavelet Transform ◽  
Nonlinear Dynamic ◽  
Nonlinear Dynamic Analysis ◽  
Continuous Wavelet ◽  
Frequency Content ◽  
Time Step ◽  
Integration Schemes ◽  
The Waves

The nonlinear dynamic analysis provides a more accurate simulation of the structural behavior against earthquakes. On the other hand, this analysis method is time-consuming since the time-step integration schemes are used to calculate the responses of the structure. Wavelet transform is also considered as one of the strong computing tools in studying the properties of the waves. The continuous wavelet transform is a time-frequency study and examines the frequency content of the waves while, the discrete wavelet transform is used to reduce sampling data and also to eliminate the noise of the waves. In this paper, the discrete and continuous wavelet transforms are used to reduce the wave sampling and therefore to reduce the required time for analysis. In this regard, eight near- and far- field earthquakes are studied. The frequency content of the earthquake is investigated by the Fourier spectrum and the continuous wavelet transform. The results show that the first five frequencies for the main earthquakes are similar to those values of earthquakes obtained by wavelet transform. Besides, it is shown that using wavelet transform for the main and decomposed earthquakes indicates that the duration of strong ground motion and the time of dominant frequency occur approximately in the same domain. Finally, it is concluded that the required calculation time reduces to about 80 % with an error less than 6 % when the main earthquake is decomposed by wavelet transform and the approximation waves are used in the nonlinear dynamic analysis.

Development of Spike Wavelet Analysis and Its Application to Damage Analysis on Gearbox

2006 ◽  
Vol 321-323 ◽  
pp. 1233-1236
Author(s):  
Sang Kwon Lee ◽  
Jang Sun Sim
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Gear System ◽  
Frequency Resolution ◽  
Linear Scaling ◽  
Continuous Wavelet ◽  
Vibration Signals ◽  
Gear Fault

Impulsive sound and vibration signals in gear system are often associated with their faults. Thus these impulsive sound and vibration signals can be used as indicators in condition monitoring of gear system. The traditional continuous wavelet transform has been used for detection of impulsive signals. However, it is often difficult for the continuous wavelet transform to identify spikes at high frequency and meshing frequencies at low frequency simultaneously since the continuous wavelet transform is to apply the linear scaling (a-dilation) to the mother wavelet. In this paper, the spike wavelet transform is developed to extract these impulsive sound and vibration signals. Since the spike wavelet transform is to apply the non-linear scaling, it has better time resolution at high frequency and frequency resolution at low frequency than that of the continuous wavelet transform respectively. The spike wavelet transform can be, therefore, used to detect fault position clearly without the loss of information for the damage of a gear system. The spike wavelet transform is successfully is applied to detection of the gear fault with tip breakage.

scholarly journals The continuous wavelet transform in processing data of high frequency electromagnetic prospecting

2016 ◽  
Vol 19 (2) ◽  
pp. 81-93
Author(s):  
Tin Quoc Chanh Duong ◽  
Dau Hieu Duong ◽  
Van Thanh Nguyen ◽  
Thuan Van Nguyen
Keyword(s):  
Wavelet Transform ◽  
Data Processing ◽  
Continuous Wavelet Transform ◽  
High Frequency ◽  
Theoretical Models ◽  
Vital Role ◽  
Continuous Wavelet ◽  
Ground Penetrating ◽  
Non Destructive ◽  
Shallow Structure

Ground Penetrating Radar (GPR), a high frequency electromagnetic prospecting method (10 to 3000 MHz) has been rapidly developed in recent decades. With many advantages such as non-destructive, fast data collection, high precision and resolution, this method is a useful means to detect underground targets. It is currently used in the research of studying the shallow structure for examples: forecast landslide, subsidence, mapping urban underground works, traffic, construction, archaeology and other various fields of engineering, GPR data processing is becoming increasingly urgent. Wavelet transform is one of the new signal analysis tools, plays a vital role in numerous domains like image processing, graphics, data compression, gravitational, electromagnetic and geomagnetic data processing, GPR and some others. In this study, we used the continuous wavelet transform (CWT) and multiscale edge detection (MED) with the wavelet functions which were appropriately selected to determine underground targets. The accuracy of this technique was tested on some theoretical models before being applied on experimental data. The obtained results showed that this was a feasible method that could be used to detect the size and position of the anomaly objects.

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