Real-Time Detection of Cracks on Concrete Bridge Decks Using Deep Learning in the Frequency Domain

This paper presents a vision-based crack detection approach for concrete bridge decks using an integrated one-dimensional convolutional neural network(1D-CNN)and long short-term memory(LSTM)method in the image frequency domain.The so-called 1D-CNN-LSTM algorithm is trained using thousands of images of cracked and non-cracked concrete bridge decks.In order to improve the training efficiency,images are first transformed into the frequency domain during a preprocessing phase.The algorithm is then calibrated using the flattened frequency data.LSTM is used to improve the performance of the developed network for long sequence data.The accuracy of the developed model is 99.05%,98.9%,and 99.25%,respectively,for training,validation,and testing data.An implementation framework is further developed for future application of the trained model for large-scale images.The proposed 1D-CNN-LSTM method exhibits superior performance in comparison with existing deep learning methods in terms of accuracy and computation time.The fast implementation of the 1D-CNN-LSTM algorithm makes it a promising tool for real-time crack detection.

Numerical investigation of temperature gradient-induced thermal stress for steel–concrete composite bridge deck in suspension bridges

A3D finite element model(FEM)with realistic field measurements of temperature distributions is proposed to investigate the thermal stress variation in the steel–concrete composite bridge deck system.First,a brief literaturereview indicates that traditional thermal stress calculation in suspension bridges is based on the2D plane structure with simplified temperature profiles on bridges.Thus,a3D FEM is proposed for accurate stress analysis.The focus is on the incorporation of full field arbitrary temperature profile for the stress analysis.Following this,the effect of realistic temperature distribution on the structure is investigated in detail and an example using field measurements of Aizhai Bridge is integrated with the proposed3D FEM model.Parametric studies are used to illustrate the effect of different parameters on the thermal stress distribution in the bridge structure.Next,the discussion and comparison of the proposed methodology and simplified calculation method in the standard is given.The calculation difference and their potential impact on the structure are shown in detail.Finally,some conclusions and recommendations for future bridge analysis and design are given based on the proposed study.

Enhanced air-coupled impact echo technique by phase analysis of signals from multiple sensors

This paper presents an air-coupled impact echo(IE)technique that relies on the phase spectrum of the collected data to find the frequencies corresponding to the reflections from delaminations.The proposed technique takes advantage of the fact that the IE compression wave is not a propagating wave,but it is the 1st order symmetrical(S1)mode Lamb wave at zero group velocity(S1-ZGV).Therefore,it searches the phase spectra of the data collected by multiple sensors to locate the frequency corresponding to the lowest phase difference.As a result,the technique reduces the effect of propagating waves,including the direct acoustic wave and ambient noise.It is named the Constant Phase IE(CPIE).The performance of the CPIE is experimentally compared with the regular amplitude spectrum-based IE technique and two other multisensor IE techniques.The CPIE shows a performance advantage,especially in a noisy environment.