Damage Detection of Steel Domes Subjected to Earthquakes by Using Wavelet Transform

2010 ◽  
Vol 150-151 ◽  
pp. 1580-1583 ◽  
Author(s):  
Jin Zheng ◽  
Bo Chen ◽  
Chun Yang Ye
Keyword(s):  
Wavelet Transform ◽  
Damage Detection ◽  
Time Instant ◽  
Discrete Wavelet ◽  
Acceleration Response ◽  
Sudden Loss ◽  
Detection Approach ◽  
Time Histories ◽  
The Time Domain ◽  
Detection Quality

The degradation of a steel dome due to strong earthquake may lead to a sudden loss of structural stiffness in a structure and cause a discontinuity in acceleration response time histories recorded in the vicinity of damage location at damage time instant. A damage detection approach based on discrete wavelet transform is developed and implemented in this paper to detect the damage time instant and location of a steel dome due to sudden seismic damage. To examine the feasibility of the wavelet-based detection approach, parameter studies are carried out to investigate the detection quality for different noise intensities. The time instant and location of sudden damage event are detected through the distribution of discrete wavelet coefficients in the time domain and spatial distribution along the structural span.

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.

Generation of Wave-Field Time Histories by the Modulated Discrete Fourier Transformation

2003 ◽  
Author(s):  
Yousun Li
Keyword(s):  
Wave Field ◽  
Fourier Transformation ◽  
Time Instant ◽  
Discrete Fourier Transformation ◽  
Fast Fourier Transformation ◽  
Structural Members ◽  
Random Waves ◽  
Offshore Structure ◽  
Time Histories ◽  
The Time Domain

In the time domain simulation of the response of an offshore structure under random waves, the time histories of the wave field should be generated as the input to the dynamic equations. Herein the wave field is the wave surface elevation, the water particle velocities and accelerations at structural members. The generated time histories should be able to match the given wave-field spectral descriptions, to trace the structural member motions if it is a compliant offshore structure, and be numerically efficient. Most frequently used generation methods are the direct summation of a limited number of cosine functions, the Fast Fourier Transformation, and the digital filtering model. However, none of them can really satisfy all the above requirements. A novel technique, called the Modulated Discrete Fourier Transformation, has been developed. Under this method, the wave time histories at each time instant is a summation of a few time-varying complex functions. The simulated time histories have continuous spectral density functions, and the motions of the structural members are well included. This method seems to be superior to all the conventional methods in terms of the above mentioned three requirements.

ON-LINE HEALTH MONITORING AND DAMAGE DETECTION OF STRUCTURES BASED ON THE WAVELET TRANSFORM

2008 ◽  
Vol 08 (03) ◽  
pp. 367-387 ◽  
Author(s):  
B. ZHU ◽  
A. Y. T. LEUNG ◽  
C. K. WONG ◽  
W. Z. LU
Keyword(s):  
Wavelet Transform ◽  
Damage Detection ◽  
Discrete Wavelet Transform ◽  
Health Monitoring ◽  
Continuous Wavelet Transform ◽  
Abrupt Change ◽  
Discrete Wavelet ◽  
Continuous Wavelet ◽  
Random Decrement Technique ◽  
On Line

Presented herein is an experiment that aims to investigate the applicability of the wavelet transform to damage detection of a beam–spring structure. By burning out the string that is connected to the cantilever beam, high-frequency oscillations are excited in the beam–spring system, and there results an abrupt change or impulse in the discrete-wavelet-transformed signal. In this way, the discrete wavelet transform can be used to recognize the damage at the moment it occurs. In the second stage of damage detection, the shift of frequencies and damping ratios is identified by the continuous wavelet transform so as to ensure that the abrupt change or impulse in the signal from the discrete wavelet transform is a result of the damage and not the noise. For the random forced vibration, the random decrement technique is used on the original signal to obtain the free decaying responses, and then the continuous wavelet transform is applied to identify the system parameters. Some developed p version elements are used for the parametric studies on the first stage of health monitoring and to find the damage location. The results show that the two-stage method is successful in damage detection. Since the method is simple and computationally efficient, it is a good candidate for on-line health monitoring and damage detection of structures.

scholarly journals Eliminated aliasing effect on wavelet transform based multiresolution analysis

2016 ◽  
Vol 55 (3) ◽  
Author(s):  
Ernesto González-Flores ◽  
José Oscar Campos-Enríquez ◽  
Erick Camacho-Ramírez ◽  
David Ernesto Rivera-Recillas
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Multiresolution Analysis ◽  
Synthetic Data ◽  
Seismic Signal ◽  
Discrete Wavelet ◽  
Frequency Bands ◽  
Analysis Technique ◽  
The Time Domain ◽  
Seismic Signal Processing

Multiresolution analysis, based on the discrete wavelet transform, is here incorporated in seismic signal processing. This analysis technique enables decomposing a seismic signal, in different frequency bands, and thus to analyze the information contained in these frequency bands. Multiresolution analysis allows visualizing in the time domain the information contained in the frequency bands. Wavelets commonly used in the discrete wavelet transform present an overlay between scales, this constitutes an aliasing effect that gives rise to spurious effects. Vaidyanathan wavelet minimizes the overlay between scales. We applied this wavelet to synthetic data and to a 3D seismic cube. Accordingly, spurious effects from aliasing generated by overlay between scales are minimized with the Vaidyanathan wavelet.

scholarly journals Short-term Load Forecasting for Microgrids Based on Discrete Wavelet Transform and BP Neural Network

2014 ◽  
Vol 8 (1) ◽  
pp. 738-742 ◽  
Author(s):  
Chong Gao ◽  
sheng Huang ◽  
Hai-feng Wang
Keyword(s):  
Wavelet Transform ◽  
Load Forecasting ◽  
Discrete Wavelet ◽  
Short Term ◽  
Short Term Load Forecasting ◽  
Micro Grid ◽  
Grid Load ◽  
The Time Domain ◽  
National Economies ◽  
Better Than

Electricity is of great vital and indispensable to national economies. A new short-term load forecasting for micro grid is proposed in this paper. After comparing and analyzing all load characteristic in the time domain and frequency domain, we apply wavelet transform to decompose the load signal. After that, the training set and text set are selected in consideration of the effects generated by the temperature and day type. At length, BP natural network is employed you forecast the micro grid load. The final result proves that the forecasting precision of the method we propose is obviously better than the traditional ones. What’s more, our method has Strong adaptability and good generalization ability.

scholarly journals Multiscale Analysis of GPS Time Series from Non-decimated Wavelet to Investigate the Effects of Ionospheric Scintillation

2015 ◽  
Vol 16 (2) ◽  
pp. 119 ◽  
Author(s):  
Gabriela De Oliveira Nascimento Brassarote ◽  
Eniuce Menezes de Souza ◽  
João Francisco Galera Monico
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Artificial Satellite ◽  
Stationary Time Series ◽  
Ionospheric Scintillation ◽  
Discrete Wavelet ◽  
The Time Domain ◽  
Gps Time Series ◽  
Redundant Discrete Wavelet Transform

Due to the numerous application possibilities, the theory of wavelets has been applied in several areas of research. The Discrete Wavelet Transform is the most known version. However, the downsampling required for its calculation makes it sensitive to the origin, what is not ideal for some applications,mainly in time series. On the other hand, the Non-Decimated Discrete Wavelet Transform (or Maximum Overlap Discrete Wavelet Transform, Stationary Wavelet Transform, Shift-invariant Discrete Wavelet Transform, Redundant Discrete Wavelet Transform) is shift invariant, because it considers all the elements of the sample, by eliminating the downsampling and, consequently, represents a time series with the same number of coefficients at each scale. In the present paper, the objective is to present the theorical aspects of the a multiscale/multiresolution analysis of non-stationary time series from non-decimated wavelets in terms of its implementation using the same pyramidal algorithm of the decimated wavelet transform. An application with real time series of the effect of the ionospheric scintillation on artificial satellite signals is investigated. With this analysis some information and hidden patterns which can not be detected in the time domain, may therefore be explained in the space-frequency domain.

scholarly journals Connection Damage Detection of Double Beam System under Moving Load with Genetic Algorithm

Mechanika ◽  
2021 ◽  
Vol 27 (1) ◽  
pp. 80-87
Author(s):  
Hougui ZHANG ◽  
Ruixiang SONG ◽  
Jie YANG ◽  
Dan WU ◽  
Yingjie WANG
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Response ◽  
Damage Detection ◽  
Moving Load ◽  
Acceleration Response ◽  
Damage Pattern ◽  
Load Model ◽  
Beam System ◽  
Detection Approach ◽  
Double Beam

In this paper, a novel damage detection approach for the spring connection of the double beam system using the dynamic response of the beam and genetic algorithm is presented. The double beam system is regarded as both Bernoulli-Euler beams with simply supported ends, the upper and lower beams are connected by a series of linear springs with certain intervals. With the genetic algorithm, the dynamic acceleration response of double beam system under moving load, which can be solved by the Newmark-β integration procedure, is used as the input data to detect the connection damage. Thus the dynamic response of the double beam system with a certain damage pattern can be calculated employing the moving load model. If the calculated result is quite close to the recorded response of the damaged bridge, this damage pattern will be the solution. The connection damage detection process of the proposed approach is presented herein, and its feasibility is studied from the numerical investigation with simple and multiple damages detection. It is concluded that the sophisticated damage conditions need much longer time to detect successfully.

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