Development of Features for Early Detection of Defects and Assessment of Bridge Decks

Damage detection is an important area with growing interest in mechanical and structural engineering.One of the critical issues in damage detection is how to determine indices sensitive to the structural damage and insensitive to the surrounding environmental variations.Current damage identification indices commonly focus on structural dynamic characteristics such as natural frequencies,mode shapes,and frequency responses.This study aimed at developing a technique based on energy Curvature Difference,power spectrum density,correlation-based index,load distribution factor,and neutral axis shift to assess the bridge deck condition.In addition to tracking energy and frequency over time using wavelet packet transform,in order to further demonstrate the feasibility and validity of the proposed technique for bridge condition assessment,experimental strain data measured from two stages of a bridge in the different intervals were used.The comparative analysis results of the bridge in first and second stage show changes in the proposed feature values.It is concluded,these changes in the values of the proposed features can be used to assess the bridge deck performance.

Comparative Analysis of Wavelet Transform for Time-Frequency Analysis and Transient Localization in Structural Health Monitoring

A critical problem facing data collection in structural health monitoring,for instance via sensor networks,is how to extract the main components and useful features for damage detection.A structural dynamic measurement is more often a complex time-varying process and therefore,is prone to dynamic changes in time-frequency contents.To extract the signal components and capture the useful features associated with damage from such nonstationary signals,a technique that combines the time and frequency analysis and shows the signal evolution in both time and frequency is required.Wavelet analyses have proven to be a viable and effective tool in this regard.Wavelet transform(WT)can analyze different signal components and then comparing the characteristics of each signal with a resolution matched to its scale.However,the challenge is the selection of a proper wavelet since various wavelets with varied properties that are to analyze the same data may result in different results.This article presents a study on how to carry out a comparative analysis based on analytic wavelet scalograms,using structural dynamic acceleration responses,to evaluate the effectiveness of various wavelets for damage detection in civil structures.The scalogram’s informative time-frequency regions are examined to analyze the variation of wavelet coefficients and show how the frequency content of a signal changes over time to detect transient events due to damage.Subsequently,damage-induced changes are tracked with time-frequency representations.Towards this aim,energy distribution and sharing information are investigated.The undamaged and damaged simulated comparative results of a structure reveal that the damaged structure were shifted from the undamaged structure.Also,the Bump wavelet shows the best results than the others.

Reaching law based sliding mode control for a frame structure under seismic load

Implementation of efficient vibration control schemes for seismically excited structures is becoming more and more important in recent years.In this study,the influence of different control schemes on the dynamic performance of a frame structure excited by El Centro wave,with an emphasis on reaching law based control strategies,is examined.Reaching law refers to the reachable problem and criteria for the sliding state of a control system.Three reaching laws are designed to present different sliding mode control strategies by incorporating a state space model that describes structural dynamic characteristics of a frame structure.Both intact and damaged structures are studied by using the aforementioned control strategies.The influence of different structural damage extents,control locations and reaching law based control methods are further investigated.The results show that the structure can be well controlled using the sliding mode strategy when the induced structural damage extent does not exceed the standard percentage for considering the structure was damaged,which is 20%reduction in structure stiffness,as reported in the literature.The control effectiveness is more satisfactory if the control location is the same as the direction of external excitation.Furthermore,to study the chattering phenomenon of the sliding mode control method,approximation and detail components extracted from the phase plots of the sliding mode control system are compared via wavelet transform at different scales.The results show that for the same type of control law,the system behaves with similar chattering phenomenon.

An Exact Solution for Acoustic Simulation Based Transmission Loss Optimization of Double-Chamber Silencer

The optimization of the acoustic silencer volume is very important to develop it and to get high-performance,the importance of the silencer was appeared in industrial field to eliminate the noise of the duct by efficient and economical method.The main goal of this research is to optimize the transmission loss(TL)by analytical method of the Double-Chamber Silencer(DCS),the TL has been selected as the main parameter in silencer because it does not based on the source or the termination impedances.First we calculated the power transmission coefficient(PTC)and the TL of an acoustic silencer,then used the Lagrange method to optimize the silencer length.All calculation of silencer data is obtained by solving the governing equations in commercial software Matlab®.A several calculations for different silencer length at many frequency ranges were performed simultaneously.Finally,this research supports the efficient and rapid techniques for DCS optimal design under narrow space.The results show that the acoustic TL is maximized at the desired frequency.

Experimental and Numerical Assessment on Seismic Performance of Earth Adobe Walls

Earth buildings are common types of structures in most rural areas in all developing countries.Catastrophic failure and destruction of these structures under seismic loads always result in loss of human lives and economic losses.Wall is an important load-bearing component of raw soil buildings.In this paper,a novel approach is proposed to improve the strength and ductility of adobe walls.Three types of analyses,material properties,mechanical properties,and dynamic properties,are carried out for the seismic performance assessment of the adobe walls.These performed studies include that,material properties of the earth cylinder block,mechanical properties of adobe walls under quasi-static loads,and dynamic performance of adobe walls excited by seismic waves.On investigation of material properties,eighteen cylindrical specimens with a diameter of 100 mm and a height of 110 mm were divided into three groups for compressive,tensile,and split pull strength tests,respectively.The results of the three groups of tests showed that the yield strength ratios of compressive,tensile,and shear strength were about 1:0.3:0.2.In order to study the performance of structural components,three 1/3 scale model raw soil walls with a dimension of 1,200 mm in width,1,000 mm in height,and 310 mm in thickness were tested under cyclic loading.The average wall capacity of the wall obtained by the test was about 13.5 kN and the average displacement angle was about 1/135.The numerical simulation experiment is used to explore the mechanism of structural failure.A three-dimensional finite element model is established by choosing the material parameters based on the above test outcomes.The accuracy of the numerical simulation experiment is verified by simulation and comparison of the above quasi-static test results.Further,the collapse process of raw soil wall under a seismic wave is simulated for exploring the response and damage mechanism of structure.Based on those systematically analyzed,some useful suggested guidelines are provided for improving the seismic performance of raw soil buildings.

A Fatigue Damage Model for FRP Composite Laminate Systems Based on Stiffness Reduction

This paper introduces a stiffness reduction based model developed by the authors to characterize accumulative fatigue damage in unidirectional plies and(0/θ/0)composite laminates in fiber reinforced polymer(FRP)composite laminates.The proposed damage detection model is developed based on a damage evolution mechanism,including crack initiation and crack damage progress in matrix,matrix-fiber interface and fibers.Research result demonstrates that the corresponding stiffness of unidirectional composite laminates is reduced as the number of loading cycles progresses.First,three common models in literatures are presented and compared.Tensile viscosity,Young’s modulus and ultimate tensile stress of composites are incorporated as key factors in this model and are modified in accordance with temperature.Four types of FRP composite property parameters,including Carbon Fiber Reinforced Polymer(CFRP),Aramid Fiber Reinforced Polymer(AFRP),Glass Fiber Reinforced Polymer(GFRP),and Basalt Fiber Reinforced Polymer(BFRP),are considered in this research,and a comparative parameter study of FRP unidirectional composite laminates with different off-angle plies using control variate method are discussed.It is concluded that the relationship between the drop in stiffness and the number of cycles also shows three different regions,following the mechanism of damage of FRP composites and the matrix is the dominant factor determined by temperature,while fiber strength is the dominant factor that determine the reliability of composite.

Applying Neural Networks for Tire Pressure Monitoring Systems

A proof-of-concept indirect tire-pressure monitoring system is developed using artificial neural networks to identify the tire pressure of a vehicle tire.A quarter-car model was developed with MATLAB and Simulink to generate simulated accelerometer output data.Simulation data are used to train and evaluate a recurrent neural network with long short-term memory blocks(RNN-LSTM)and a convolutional neural network(CNN)developed in Python with Tensorflow.Bayesian Optimization via SigOpt was used to optimize training and model parameters.The predictive accuracy and training speed of the two models with various parameters are compared.Finally,future work and improvements are discussed.

A Deep Learning Based Approach for Response Prediction of Beam-like Structures

Beam-like structures arde a class of common but important structures in engineering.Over the past few centuries,extensive research has been carried out to obtain the static and dynamic response of beam-like structures.Although build-ing the finite element model to predict the response of these structures has proven to be effective,it is not always suitable in all the application cases because of high computational time or lack of accuracy.This paper proposes a novel approach to predict the deflection response of beam-like structures based on a deep neural net-work and the governing differential equation of Euler-Bernoulli beam.The Prandtl-Ishlinskii model is introduced as an element of prediction model to simu-late the plasticity of this beam structure.Finally the application of the proposed approach is demonstrated through four numerical examples including linear elastic/ideal plastic beam under concentrated/sinusoidal load and elastic/plastic continues beam under seismic load to demonstrate a proof of concept for the effectiveness of this AI-based approach.