scholarly journals Wavelet Energy Accumulation Method Applied on the Rio Papaloapan Bridge for Damage Identification

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 422
Author(s):  
Jose M. Machorro-Lopez ◽  
Juan P. Amezquita-Sanchez ◽  
Martin Valtierra-Rodriguez ◽  
Francisco J. Carrion-Viramontes ◽  
Juan A. Quintana-Rodriguez ◽  
...  
Keyword(s):  
Bridge Deck ◽  
Damage Identification ◽  
Area Under The Curve ◽  
Economic Losses ◽  
Civil Structures ◽  
Vibration Signals ◽  
Energy Accumulation ◽  
Damage Location ◽  
Wavelet Energy ◽  
Accumulation Method

Large civil structures such as bridges must be permanently monitored to ensure integrity and avoid collapses due to damage resulting in devastating human fatalities and economic losses. In this article, a wavelet-based method called the Wavelet Energy Accumulation Method (WEAM) is developed in order to detect, locate and quantify damage in vehicular bridges. The WEAM consists of measuring the vibration signals on different points along the bridge while a vehicle crosses it, then those signals and the corresponding ones of the healthy bridge are subtracted and the Continuous Wavelet Transform (CWT) is applied on both, the healthy and the subtracted signals, to obtain the corresponding diagrams, which provide a clue about where the damage is located; then, the border effects must be eliminated. Finally, the Wavelet Energy (WE) is obtained by calculating the area under the curve along the selected range of scale for each point of the bridge deck. The energy of a healthy bridge is low and flat, whereas for a damaged bridge there is a WE accumulation at the damage location. The Rio Papaloapan Bridge (RPB) is considered for this research and the results obtained numerically and experimentally are very promissory to apply this method and avoid accidents.

scholarly journals EMD-Shannon Entropy-Based Methodology to Detect Incipient Damages in a Truss Structure

2018 ◽  
Vol 8 (11) ◽  
pp. 2068 ◽  
Author(s):  
Alejandro Moreno-Gomez ◽  
Juan Amezquita-Sanchez ◽  
Martin Valtierra-Rodriguez ◽  
Carlos Perez-Ramirez ◽  
Aurelio Dominguez-Gonzalez ◽  
...  
Keyword(s):  
Shannon Entropy ◽  
Early Stage ◽  
Economic Losses ◽  
Civil Structures ◽  
Vibration Signals ◽  
Mode Decomposition ◽  
Damage Condition ◽  
Stage 1 ◽  
Diameter Reduction ◽  
Emd Method

Truss-type designs are widely used in civil structures. Despite the fact that they are robust and reliable structures, different kinds of damage can appear. In order to avoid human and economic losses, the development and application of damage-detection methodologies are paramount. In this work, a methodology based on the empirical mode decomposition (EMD) method and the Shannon Entropy Index (SEI) to detect incipient damages associated with corrosion in a 3D 9-bay truss-type bridge is presented. As different EMD methods are presented in literature, the most representative methods are investigated in order to evaluate their performance for this task. To this end, the vibration signals generated in the truss-type bridge at different conditions are analyzed. For the damage condition, four severity levels of simulated corrosion (1 mm, 3 mm, 5 mm, and 8 mm of diameter reduction) generated into the elements of truss-type bridge are considered. Results demonstrate the effectiveness of the proposal in terms of detecting corrosion in its very early stage (1 mm of reduction in the element).

Simulation Study of Damage Identification Method Based on Lamb Wave Scattering in Aluminium Plate

2012 ◽  
Vol 433-440 ◽  
pp. 2611-2618
Author(s):  
Zhen Hua Tian ◽  
Hong Yuan Li ◽  
Hong Xu
Keyword(s):  
Energy Distribution ◽  
Lamb Wave ◽  
Damage Identification ◽  
Optimization Method ◽  
Propagation Path ◽  
Transient Dynamic Analysis ◽  
Time Frequency ◽  
Damage Location ◽  
Identification Method ◽  
Short Time

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.

A Novel Two-Stage Structural Damage Identification Method Based on Superposition of Modal Flexibility Curvature and Whale Optimization Algorithm

2021 ◽  
pp. 2150169
Author(s):  
Minshui Huang ◽  
Xihao Cheng ◽  
Zhigang Zhu ◽  
Jin Luo ◽  
Jianfeng Gu
Keyword(s):  
Optimization Algorithm ◽  
Damage Identification ◽  
Whale Optimization Algorithm ◽  
Two Stage ◽  
Simply Supported ◽  
Damage Location ◽  
Flexibility Matrix ◽  
Modal Flexibility ◽  
Whale Optimization ◽  
The Impact

A novel two-stage method is proposed to properly identify the location and severity of damage in plate structures. In the first stage, a superposition of modal flexibility curvature (SMFC) is adopted to locate the damage accurately, and the identification index of modal flexibility matrix is improved. The low-order modal parameters are used and a new column matrix is formed based on the modal flexibility matrix before and after the structure is damaged. The difference of modal flexibility matrix is obtained, which is used as a damage identification index. Meanwhile, based on SMFC, a method of weakening the “vicinity effect” is proposed to eliminate the impact of the surrounding elements to the damaged elements when damage identification is carried out for the plate-type structure. In the second stage, the objective function based on the flexibility matrix is constructed, and according to the damage location identified in the first stage, the actual damage severity is determined by the enhanced whale optimization algorithm (EWOA). In addition, the effects of 3% and 10% noise on damage location and severity estimation are also studied. By taking a simply supported beam and a four-side simply supported plate as examples, the results show that the method can accurately estimate the damage location and quantify the damage severity without noise. When considering noise, the increase of noise level will not affect the assessment of damage location, but the error of quantifying damage severity will increase. In addition, damage identification of a steel-concrete composite bridge (I-40 Bridge) under four damage cases is carried out, and the results show that the modified method can evaluate the damage location and quantify 5%–92% of the damage severity.

The Behavior of Tiled Laminate GFRP Composites, a Class of Robust Materials for Civil Applications

2019 ◽  
Author(s):  
Wouter De Corte ◽  
Jordi Uyttersprot ◽  
Wim Van Paepegem
Keyword(s):  
Crack Propagation ◽  
Numerical Simulations ◽  
Bridge Deck ◽  
Fatigue Loading ◽  
Structural Behavior ◽  
Gfrp Composites ◽  
Civil Structures ◽  
Laminate Composites ◽  
Deck Panels ◽  
Highly Loaded

<p>This paper focuses on the structural behavior of tiled laminate composites. Such laminates, in which the plies are not parallel to the outer surfaces are found in GFRP bridge deck panels. The technology is developed for the construction of robust GFRP panels useful in highly loaded structures such as bridges or lock gates. In civil structures, the drawback in traditional FRP sandwich structures has always been debonding of skin and core. Such a debonding problem may occur after unintentional impact, followed by fatigue loading. Through the concept of using overlapping Z-shaped and two-flanged web laminates, alternating with polyurethane foam cores, debonding is no longer possible in vacuum infused GFRP bridge deck panels. In such panels, the fibers in the upper and lower skins as well as in the vertical webs run in all directions, rendering a resin-dominated crack propagation impossible. As a result of the integration of core and skin reinforcement, a skin material is created in which the reinforcement is not parallel to the outer surfaces, but tiled. Based on experimental results and numerical simulations the relevance of tiled laminates for civil applications is demonstrated.</p>

scholarly journals Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Yazmin Alcala-Canto ◽  
Juan Antonio Figueroa-Castillo ◽  
Froylán Ibarra-Velarde ◽  
Yolanda Vera-Montenegro ◽  
María Eugenia Cervantes-Valencia ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Environmental Variables ◽  
Control Strategies ◽  
Integrated Control ◽  
Area Under The Curve ◽  
Entropy Method ◽  
Distribution Model ◽  
Economic Losses ◽  
Precipitation Seasonality ◽  
Epidemiological Risk

The tick genus Ripicephalus (Boophilus), particularly R. microplus, is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of Rhipicephalus spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks’ distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of Rhipicephalus spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that Rhipicephalus has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using Rhipicephalus records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies.

Circumference Damage Identification in a Pipe Using Mode Conversion of Longitudinal Guided Wave

2013 ◽  
Vol 395-396 ◽  
pp. 787-791
Author(s):  
Jing Wu ◽  
Wei Wei Zhang
Keyword(s):  
Damage Detection ◽  
Damage Identification ◽  
Mode Conversion ◽  
Guided Wave ◽  
Symmetric Mode ◽  
Axially Symmetric ◽  
Mode Transformation ◽  
Damage Location

This paper aims to develop a method to identify the damage location in circumference direction of a pipe using mode transformation of longitudinal guided wave. The corrosion-like damage in bimetal pipe is considered. Case study that damage detection for a bimetal pipe is used to show the validity and advantage of the proposed method. It can be found that the axially symmetric mode guided wave encounter the damage and the three modes were received in reflection. The damage location in circumferential directions could be identified by conversed modes measured at one position. The simulation shows a good performance.

scholarly journals Damage Identification of Multi-span Bridge Structure Based on the Recognition of Influence Line

2021 ◽  
Vol 233 ◽  
pp. 03002
Author(s):  
Zhang Yunkai ◽  
Xie Qingli ◽  
Li Guohua ◽  
Ye Yuntao
Keyword(s):  
Information Fusion ◽  
Damage Identification ◽  
Sensory Information ◽  
Bridge Structure ◽  
Damage Site ◽  
Damage Location ◽  
Influence Line ◽  
Before And After ◽  
Bridge Damage ◽  
Combining Information

The stress and deflection effects of the line changes before and after the bridge damage are used as indicators to evaluate the bridge damage and the initial damage site. Then a method of combining information is proposed to improve the accuracy of the damage site. Three-span continuous reinforced concrete was used in the analysis. According to the test, the effectiveness of damage identification based on the damage change of the influence line and the feasibility of the damage location method based on multi-sensory information fusion are confirmed.

A Bayesian fusion method for composite damage identification using Lamb wave

2020 ◽  
pp. 147592172094500
Author(s):  
Haode Huo ◽  
Jingjing He ◽  
Xuefei Guan
Keyword(s):  
Lamb Wave ◽  
Composite Plate ◽  
Damage Identification ◽  
Reconstruction Algorithm ◽  
Damage Location ◽  
Numerical Studies ◽  
Composite Damage ◽  
Bayesian Fusion ◽  
Novel Method ◽  
Reliability And Robustness

This study presents a novel method for composite damage identification using Lamb wave. A probabilistic integration of the elliptical loci method and the RAPID (reconstruction algorithm for probabilistic inspection of defects) in a Bayesian framework is proposed. The proposed method allows for the incorporation of multiple damage sensitive features in a rational manner to improve the reliability and robustness for a given array of sensors. Numerical studies are performed to verify the effectiveness of the proposed method and to compare its accuracy with existing methods. Experimental investigation using a realistic composite plate is made to further validate the proposed method. The influence of damage location and the number of participating sensors on the performance of the proposed method is discussed. Results indicate that the proposed method yields more accurate and reliable results comparing with existing methods.

scholarly journals A Neural-Wavelet Technique for Damage Identification in the ASCE Benchmark Structure Using Phase II Experimental Data

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
Mahmoud M. Reda Taha
Keyword(s):  
Damage Detection ◽  
Damage Identification ◽  
Damage Classification ◽  
Integrated Method ◽  
Damage Recognition ◽  
Wavelet Energy ◽  
Challenging Tasks ◽  
Damage States ◽  
Artificial Neural Network Ann ◽  
American Society

Damage pattern recognition research represents one of the most challenging tasks in structural health monitoring (SHM). The vagueness in defining damage and the significant overlap between damage states contribute to the challenges associated with proper damage classification. Uncertainties in the damage features and how they propagate during the damage detection process also contribute to uncertainties in SHM. This paper introduces an integrated method for damage feature extraction and damage recognition. We describe a robust damage detection method that is based on using artificial neural network (ANN) to compute the wavelet energy of acceleration signals acquired from the structure. We suggest using the wavelet energy as a damage feature to classify damage states in structures. A case study is presented that shows the ability of the proposed method to detect and pattern damage using the American Society of Civil Engineers (ASCEs) benchmark structure. It is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy to varying levels of damage.

Application of BP Neural Network in Structural Damage Diagnosis of Bridge behind Abutment

2016 ◽  
Vol 847 ◽  
pp. 440-444 ◽  
Author(s):  
Yu Hui Zhang
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Bp Neural Network ◽  
Structural Damage ◽  
Damage Identification ◽  
Current Knowledge ◽  
Horizontal Displacement ◽  
Structural Deformation ◽  
Bp Network ◽  
Damage Location

BP neural network is introduced and applied to identify and diagnose both location and extent of bridge structural damage; static load tests and dynamic calculations are also made on bridge structural damage behind abutment. The key step of this method is to design a reasonably perfect BP network model. According to the current knowledge, three BP neural networks are designed with horizontal displacement rate and inherent frequency rate as damage identification indexes. The neural networks are used to identify the measurement of structure behind abutment and the calculation of damage location and extent, at the same time, they can also be used to compare and analyze the results. The test results show that: taking the two factors (static structural deformation rate and the change rate of natural frequency in dynamic response) as input vector, the BP neural network can accurately identify the damage location and extent, implying a promising perspective for future applications.

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