Application of the wavelet transform in filtering the noise of real earthquake accelerograms

2021 ◽  
pp. 19-27
Author(s):  
Svetlana V., Kharlanova ◽  
Vladimir L. Kharlanov
Keyword(s):  
Wavelet Transform ◽  
Comparative Analysis ◽  
Input Data ◽  
Dynamic Coefficient ◽  
Building Structures ◽  
Deterministic Analysis ◽  
Filtering Algorithm ◽  
Source Data ◽  
Real Earthquake ◽  
Earthquake Accelerograms

In the deterministic analysis of building structures, real accelerograms are used as input data. Very often, only instrumental recordings of accelerograms that are not cleared of noise are publicly available. Such accelerograms cannot be used directly in the analysis of building structures. Various broadband filters are used to adjust the instrumental recordings of accelerographs. This article discusses the possibility of applying filters based on the wavelet transform. The technique of the algorithm of filtering from the noise of the source data is considered. As an efficiency of this filtering algorithm, a comparative analysis of the dynamic coefficient and the energy criteria of the pulse and Arias for the corrected and instrumental accelerograms is carried out.

scholarly journals The comparative analysis of selected interactive data presentation techniques on the example of the land use structure in the commune of Tomice

2016 ◽  
Vol 48 (3) ◽  
pp. 115-127
Author(s):  
Karol Król ◽  
Barbara Prus
Keyword(s):  
Land Use ◽  
Information System ◽  
Comparative Analysis ◽  
Geographic Information System ◽  
Input Data ◽  
Technical Specification ◽  
Data Presentation ◽  
Land Use Structure ◽  
Programming Tools ◽  
Interactive Data

Abstract The authors present the results of a comparative analysis of selected techniques and programming tools for building interactive data presentation in the form of diagrams and maps generated in the browser. The results of an inventory of land use structure, which are a part of a geographic information system database of the commune of Tomice in district of Wadowice, were employed as input data. The research has shown that the tested tools have a similar design capacity; which makes it difficult to determine which of them is the best. Different factors contribute to choosing a particular tool. They include technical specification, project budget, license conditions, technical support and visualization possibilities.

scholarly journals Damage Detection on Sudden Stiffness Reduction Based on Discrete Wavelet Transform

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Bo Chen ◽  
Zhi-wei Chen ◽  
Gan-jun Wang ◽  
Wei-ping Xie
Keyword(s):  
Wavelet Transform ◽  
Damage Detection ◽  
Discrete Wavelet Transform ◽  
Sudden Change ◽  
Damage Index ◽  
Time Instant ◽  
Discrete Wavelet ◽  
Building Structures ◽  
Stiffness Reduction ◽  
Shear Building

The sudden stiffness reduction in a structure may cause the signal discontinuity in the acceleration responses close to the damage location at the damage time instant. To this end, the damage detection on sudden stiffness reduction of building structures has been actively investigated in this study. The signal discontinuity of the structural acceleration responses of an example building is extracted based on the discrete wavelet transform. It is proved that the variation of the first level detail coefficients of the wavelet transform at damage instant is linearly proportional to the magnitude of the stiffness reduction. A new damage index is proposed and implemented to detect the damage time instant, location, and severity of a structure due to a sudden change of structural stiffness. Numerical simulation using a five-story shear building under different types of excitation is carried out to assess the effectiveness and reliability of the proposed damage index for the building at different damage levels. The sensitivity of the damage index to the intensity and frequency range of measurement noise is also investigated. The made observations demonstrate that the proposed damage index can accurately identify the sudden damage events if the noise intensity is limited.

scholarly journals Comparative Analysis of Probabilistic Analysis and Deterministic Analysis by RESRAD Code

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1983
Author(s):  
Sang June Park ◽  
Jihyang Byon ◽  
Seokyoung Ahn
Keyword(s):  
United States ◽  
Comparative Analysis ◽  
South Korea ◽  
Probabilistic Analysis ◽  
The United States ◽  
Exposure Dose ◽  
Nuclear Facilities ◽  
Deterministic Analysis ◽  
Specific Concentration ◽  
Site Release

The decommissioning of nuclear facilities indicates that the site is finally released according to a limited or unlimited site reuse purpose. In this process, the assessment of exposure dose to decommissioning workers and nearby residents is essential. Based on MARSSIM, a widely used decommissioning guideline in the United States, derivation of the exposure dose and derived concentration guideline level (DCGL) is mandatory using the probabilistic analysis of the RESRAD code. Here, DCGL is the radionuclide-specific concentration that satisfies the site release criteria. By applying the priority 1 parameter, which has the greatest effect on the dose, the dose is derived through deterministic and probabilistic analyses. The results were compared and analyzed. The purpose of this study was to provide a basic database that can be applied to the development of parameter lists and distributions suitable for the characteristics of nuclear facilities in South Korea. In addition, the process of deriving the dose by applying the deterministic and probabilistic analyses of RESRAD was assessed.

scholarly journals Fall Detection Using Multiple Bioradars and Convolutional Neural Networks

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5569 ◽  
Author(s):  
Lesya Anishchenko ◽  
Andrey Zhuravlev ◽  
Margarita Chizh
Keyword(s):  
Wavelet Transform ◽  
Input Data ◽  
Detection Method ◽  
Fall Detection ◽  
Modern Medicine ◽  
Radar Signal ◽  
Continuous Wavelet ◽  
Time Frequency ◽  
Frequency Representation ◽  
Life Threatening

A lack of effective non-contact methods for automatic fall detection, which may result in the development of health and life-threatening conditions, is a great problem of modern medicine, and in particular, geriatrics. The purpose of the present work was to investigate the advantages of utilizing a multi-bioradar system in the accuracy of remote fall detection. The proposed concept combined usage of wavelet transform and deep learning to detect fall episodes. The continuous wavelet transform was used to get a time-frequency representation of the bio-radar signal and use it as input data for a pre-trained convolutional neural network AlexNet adapted to solve the problem of detecting falls. Processing of the experimental results showed that the designed multi-bioradar system can be used as a simple and view-independent approach implementing a non-contact fall detection method with an accuracy and F1-score of 99%.

A Variable Mode QR Decomposition Adaptive Filtering Algorithm for Acoustic Echo Cancellation

2014 ◽  
Vol 556-562 ◽  
pp. 3839-3843
Author(s):  
J.B. Li ◽  
C. Lu ◽  
Y. Zhou
Keyword(s):  
Adaptive Filtering ◽  
Input Data ◽  
Qr Decomposition ◽  
Echo Cancellation ◽  
Acoustic Echo Cancellation ◽  
Activity Detection ◽  
Filtering Algorithm ◽  
Acoustic Echo ◽  
Variable Mode ◽  
Voice Activity

This paper studies a new QR decomposition adaptive filtering algorithm for acoustic echo cancellation (AEC). Based on the p-TA-QR-LS algorithm [1] and an efficient voice activity detection technique, the proposed algorithm can distinguish the significant and insignificant input data periods. The resultant variable mode p-TA-QR-LS algorithm can work between two modes (p=1and N) and is thus suitable for AEC application where reusing significant input data can enhance convergence and the computation cost can be saved when the input is relatively weak.

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