scholarly journals Seismic Damage Identification Method for Curved Beam Bridges Based on Wavelet Packet Norm Entropy

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 239
Author(s):  
Tongfa Deng ◽  
Jinwen Huang ◽  
Maosen Cao ◽  
Dayang Li ◽  
Mahmoud Bayat

Curved beam bridges, whose line type is flexible and beautiful, are an indispensable bridge type in modern traffic engineering. Nevertheless, compared with linear bridges, curved beam bridges have more complex internal forces and deformation due to the curvature; therefore, this type of bridge is more likely to suffer damage in strong earthquakes. The occurrence of damage reduces the safety of bridges, and can even cause casualties and property loss. For this reason, it is of great significance to study the identification of seismic damage in curved beam bridges. However, there is currently little research on curved beam bridges. For this reason, this paper proposes a damage identification method based on wavelet packet norm entropy (WPNE) under seismic excitation. In this method, wavelet packet transform is adopted to highlight the damage singularity information, the norm entropy of wavelet coefficient is taken as a damage characteristic factor, and then the occurrence of damage is characterized by changes in the damage index. To verify the feasibility and effectiveness of this method, a finite element model of Curved Continuous Rigid-Frame Bridges (CCRFB) is established for the purposes of numerical simulation. The results show that the damage index based on WPNE can accurately identify the damage location and characterize the severity of damage; moreover, WPNE is more capable of performing damage location and providing early warning than the method based on wavelet packet energy. In addition, noise resistance analysis shows that WPNE is immune to noise interference to a certain extent. As long as a series of frequency bands with larger correlation coefficients are selected for WPNE calculation, independent noise reduction can be achieved.

2015 ◽  
Vol 9 (1) ◽  
pp. 570-576 ◽  
Author(s):  
Can He ◽  
Jianchun Xing ◽  
Juelong Li ◽  
Wei Qian ◽  
Xun Zhang

Excitation makes a great influence on the wavelet energy distribution of the response signal, this deficiency leads that the traditional structural damage identification method based on wavelet energy has a low precision. In order to solve this problem, a new structural damage identification method based on wavelet packet energy entropy (WPEE) of impulse response is presented in this paper. Firstly, natural excitation technique (NExT) is adopted to extract structural impulse response. Then, WPEE of the impulse response is computed, and the change rate of WPEE is used to construct the structural damage index. An experiment of damage identification on a pile structure is provided to verify the effectiveness of the proposed method. Experiment results show that this method can accurately identify the single damage and multi-damage.


2014 ◽  
Vol 680 ◽  
pp. 374-378
Author(s):  
Chun Cheng Liu ◽  
Shang Yu Hou ◽  
Wen Qiang Li ◽  
Zhao Wen He

In order to study the damage problem caused by the transmission tower fatigue cracks and bolt pretightening force loss ,this paper proposes a transmission tower damage identification method based on concurrent multi-scale model, namely establish solid model on nodes of fatigue crack and bolt looseness based on large scale model., subdividing elements size. Take a practical engineering 500kV transmission towers as an example to establish a concurrent multi-scale models. This paper simulates 8 kinds of conditions including bolt pretightening force loss and angle steel crack, research shows that the sum of wavelet packet energy curvature difference can effectively identify minute damage, and then get the function relation between damage level and damage index with no noise interference, also this provides a theoretical basis for it as actual damage monitoring indicators index.


Vibration ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 422-445
Author(s):  
Md Riasat Azim ◽  
Mustafa Gül

Railway bridges are an integral part of any railway communication network. As more and more railway bridges are showing signs of deterioration due to various natural and artificial causes, it is becoming increasingly imperative to develop effective health monitoring strategies specifically tailored to railway bridges. This paper presents a new damage detection framework for element level damage identification, for railway truss bridges, that combines the analysis of acceleration and strain responses. For this research, operational acceleration and strain time-history responses are obtained in response to the passage of trains. The acceleration response is analyzed through a sensor-clustering-based time-series analysis method and damage features are investigated in terms of structural nodes from the truss bridge. The strain data is analyzed through principal component analysis and provides information on damage from instrumented truss elements. A new damage index is developed by formulating a strategy to combine the damage features obtained individually from both acceleration and strain analysis. The proposed method is validated through a numerical study by utilizing a finite element model of a railway truss bridge. It is shown that while both methods individually can provide information on damage location, and severity, the new framework helps to provide substantially improved damage localization and can overcome the limitations of individual analysis.


2012 ◽  
Vol 433-440 ◽  
pp. 2611-2618
Author(s):  
Zhen Hua Tian ◽  
Hong Yuan Li ◽  
Hong Xu

The propagation of scattering Lamb wave in plate was simulated using transient dynamic analysis in ANSYS. In order to extract the characteristic information of received signal for damage identification, the short time Fourier transform based on time-frequency analysis was utilized, and then the energy distribution and envelop of received signal were obtained. Based on the displacement contour of simulation and energy distribution, the propagation of scattering wave in plate with a through hole was examined. Also, a mathematic relationship between damage location and scattering signal was developed, with the help of wave propagation path through actuator, damage and sensor. A nonlinear optimization method was applied on the mathematic relationship to obtain the damage location. The damage identification method using scattering Lamb wave was therefore established.


2016 ◽  
Vol 16 (1) ◽  
pp. 3-23 ◽  
Author(s):  
Yongfeng Xu ◽  
Weidong Zhu

Mode shapes (MSs) have been extensively used to detect structural damage. This paper presents a new non-model-based damage identification method that uses measured MSs to identify damage in plates. A MS damage index (MSDI) is proposed to identify damage near regions with consistently high values of MSDIs associated with MSs of different modes. A MS of a pseudo-undamaged plate can be constructed for damage identification using a polynomial of a properly determined order that fits the corresponding MS of a damaged plate, if the associated undamaged plate is geometrically smooth and made of materials that have no stiffness and mass discontinuities. It is shown that comparing a MS of a damaged plate with that of a pseudo-undamaged plate is better for damage identification than with that of an undamaged plate. Effectiveness and robustness of the proposed method for identifying damage of different positions and areas are numerically investigated using different MSs; effects of crucial factors that determine effectiveness of the proposed method are also numerically investigated. Damage in the form of a machined thickness reduction area was introduced to an aluminum plate; it was successfully identified by the proposed method using measured MSs of the damaged plate.


2009 ◽  
Vol 413-414 ◽  
pp. 71-78
Author(s):  
Xiao Qiang Chen ◽  
Hong Ping Zhu ◽  
Dan Sheng Wang

In this paper, a new time-domain method for detecting structural local damage has been developed, which is based on the measured strain signals. The “pseudo strain energy density (PSED)” is defined and used to build two major damage indexes, the “average pseudo strain energy density” (APSED) and the “average pseudo strain energy density changing rate” (APSEDR). A probability and mathematical statistics technique is utilized to derive a standardized damage index. Afterwards, these indexes are used to establish the damage identification strategies for beam structures and plate structures respectively. Furthermore, the wavelet packet transform is used to pre-process the measured dynamic strain signals. Then, the effectivity of the new damage identification method is confirmed by numerical simulations. Finally, a laboratory beam model experiment is conducted to verify this method examine the feasibility and applicability of the new method.


2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Qian Xu

To eliminate the influence of excitation on the wavelet packet frequency band energy spectrum (ES), ES is acquired via wavelet packet decomposition of a virtual impulse response function. Based on ES, a character frequency band vector spectrum and damage eigenvector spectrum (DES) are created. Additionally, two damage identification indexes, the energy ratio standard deviation and energy ratio variation coefficient, are proposed. Based on the damage index, an updated damage identification method for retaining wall structures is advanced. The damage state of a retaining wall can be diagnosed through DES, the damage location can be detected through the damage index trend surface, and the damage intensity can be identified by establishing a quantitative relationship between the damage intensity and damage index. To verify the feasibility and validity of this damage identification method, a vibration test on a pile plate retaining wall is performed. Test results demonstrate that it can distinguish whether the retaining wall is damaged, and the location of partial damage within the retaining wall can be easily detected; in addition, the damage intensity of the wall can also be identified validly. Consequently, this damage identification theory and method may be used to identify damage within retaining wall structures.


2005 ◽  
Vol 293-294 ◽  
pp. 727-734
Author(s):  
José L. Zapico ◽  
María P. González

This article deals with a method for seismic damage identification in buildings with steel moment-frame structure. The damage identification is based on artificial neural networks and natural frequencies. A simplified finite element model is used to obtain the data needed for training the nets. The method is simulated on a four-storey building under conditions as close as possible to reality. The robustness of the method and its sensitivity to the variations of the mass with time and the influence of the data errors is addressed. The statistical analysis of the results is successful, but it reveals that the predictions are quite sensitive to the data errors.


2013 ◽  
Vol 347-350 ◽  
pp. 107-110
Author(s):  
Sen Wu ◽  
Bin Wang ◽  
Hai Hua Zhang

In view of the defects of the traditional damage identification method based on vibration,the damage identification method based on vibration transmissibility is put forward. The feasibility of the vibration transmissibility applied to structural damage identification is analyzed by the numerical simulation experiment of a cantilever beam, the analysis results show that, vibration transmissibility contains the structure damage severity, damage location and other useful information, and all the information is favor of the damage identification.


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