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Automatic Road Tunnel Crack Inspection Based on Crack Area Sensing and Multiscale Semantic Segmentation

Computers, Materials & Continua 2024年第4期79卷 1679-1703页

作者： Dingping Chen Zhiheng Zhu Jinyang Fu Jilin He College of Mechanical and Electrical engineering Central South UniversityChangsha410083China Department of Geotechnical Guangdong Hualu Transportation Technology Company LimitedGuangzhou510000China national engineering research center of high-speed railway construction technology Changsha410075China

The detection of crack defects on the walls of road tunnels is a crucial step in the process of ensuring travel safetyand performing routine tunnel maintenance. The automatic and accurate detection of cracks on the surface of roadtunnels is the key to improving the maintenance efficiency of road tunnels. Machine vision technology combinedwith a deep neural network model is an effective means to realize the localization and identification of crackdefects on the surface of road *** propose a complete set of automatic inspection methods for identifyingcracks on the walls of road tunnels as a solution to the problem of difficulty in identifying cracks during manualmaintenance. First, a set of equipment applied to the real-time acquisition of high-definition images of walls inroad tunnels is designed. Images of walls in road tunnels are acquired based on the designed equipment, whereimages containing crack defects are manually identified and selected. Subsequently, the training and validationsets used to construct the crack inspection model are obtained based on the acquired images, whereas the regionscontaining cracks and the pixels of the cracks are finely labeled. After that, a crack area sensing module is designedbased on the proposed you only look once version 7 model combined with coordinate attention mechanism (CAYOLOV7) network to locate the crack regions in the road tunnel surface images. Only subimages containingcracks are acquired and sent to the multiscale semantic segmentation module for extraction of the pixels to whichthe cracks belong based on the DeepLab V3+ network. The precision and recall of the crack region localizationon the surface of a road tunnel based on our proposed method are 82.4% and 93.8%, respectively. Moreover, themean intersection over union (MIoU) and pixel accuracy (PA) values for achieving pixel-level detection accuracyare 76.84% and 78.29%, respectively. The experimental results on the dataset show that our proposed two-staged

关键词： Road tunnel crack inspection crack area sensing multiscale semantic segmentation CA-YOLO V7 DeepLab V3+

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基于贝叶斯自优化Bi-LSTM组合网络的高速铁路轨道-桥梁系统震后响应预测方法

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Journal of Central South University 2024年第3期31卷 965-975页

作者：彭康蒋丽忠周旺保余建向平吴凌旭 national engineering research center of high-speed railway construction technology Central South UniversityChangsha 410075China

中国高速铁路(HSR)规划建设逐渐向地震易发地区延伸,亟需一种及时、准确的灾后地震响应快速预测方法,以实现高速铁路系统运输生命线安全的快速评估。本文提出了一种基于贝叶斯自优化双向长短期记忆(Bi-LSTM)网络的快速预测方法,以经过... 详细信息

中国高速铁路(HSR)规划建设逐渐向地震易发地区延伸,亟需一种及时、准确的灾后地震响应快速预测方法,以实现高速铁路系统运输生命线安全的快速评估。本文提出了一种基于贝叶斯自优化双向长短期记忆(Bi-LSTM)网络的快速预测方法,以经过实验验证的高速铁路轨道-桥梁系统有限元模型地震动响应计算数据为样本,将预测地震响应和有限元计算结果进行比较,验证所提方法的精度和鲁棒性,表明该方法在预测高速铁路桥梁结构的非线性地震反应方面是有效的,且高速铁路轨道-桥梁系统的不同预测位置对预测精度的影响不明显;此外,为了降低神经网络训练数据量需求,提出了一种基于离散小波分解的分层聚类算法,结果表明,基于小波分解的分层聚类方法在保证预测精度的同时,有效地减少了训练地震集的输入数量。

关键词：高速铁路轨道-桥梁系统贝叶斯优化 Bi-LSTM神经网络离散小波分解聚类分析

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Debris Flow Susceptibility Evaluation in Meizoseismal Region:A Case Study in Jiuzhaigou,China

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Journal of Earth Science 2024年第1期35卷 263-279页

作者： Yongwei Li Linrong Xu Yonghui Shang Shuyang Chen School of Civil engineering Central South UniversityChangsha 410075China national engineering research center of high-speed railway construction technology Central South UniversityChangsha 410075China School of Civil engineering Central South University of Forestry and TechnologyChangsha 410004China

Jiuzhaigou is situated on a mountain-canyon region and is famous for frequent tectonic *** abundance of loose co-seismic landslides and collapses were produced on gullies after the Jiuzhaigou Earthquake on August 8,2017,which was served as material source for debris flow in later *** flow appears frequently which are seriously endangering the safety of people's lives and *** the earliest debris flow appeared in areas where no case ever reported *** debris flow susceptibility evaluation(DFSE)is used for predicting the areas prone to debris flow,which is urgently required to avoid hazards and help to guide the strategy of preventive ***,this work employs debris flow in Jiuzhaigou to reveal the characteristics of disaster-pregnant environment and to explore the application of machine learning in *** new viewpoints are suggested:(i)Material density factor of debris flow is first adopted in this work,and it is proved to be a critical factor for triggering debris flows by sensitivity analysis method.(ii)Deep neural network and convolutional neural network(CNN)achieve relatively good area under the curve(AUC)values and are 0.021-0.024 higher than traditional machine learning methods.(iii)Watershed units combined with CNNbased model can achieve more accurate,reliable and practical susceptibility *** work provides an idea for prevention of debris flow in mountainous lands.

关键词： machine learning earthquakes debris flow susceptibility convolutional neural network deep neural network watershed unit

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Large eddy simulation study of 3D wind field in a complex mountainous area under different boundary conditions

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Journal of Zhejiang University-Science A(Applied Physics & engineering) 2024年第7期25卷 541-556页

作者： Yan LI Lei YAN Xuhui HE School of Civil engineering Central South UniversityChangsha410075China national engineering research center for high-speed railway construction Changsha410075China Hunan Provincial Key Laboratory for Disaster Prevention and Mitigation of Rail Transit engineering Structures Changsha410075China

Large eddy simulations generally are used to predict 3D wind field characteristics in complex mountainous *** simulation boundary conditions,such as the height and length of the computational domain or the characteristics of inflow turbulence,can significantly impact the quality of *** this study,we examined these boundary conditions within the context of the mountainous terrain around a long-span cable-stayed bridge using a wind tunnel *** sizes of computational domains and turbulent incoming wind velocities were used in large eddy *** results show that when the height of the computational domain is five times greater than the height of the terrain model,there is minimal influence from the top wall on the wind field characteristics in this complex mountainous *** the length of the wake region of the computational domain has negligible effects on the wind *** in the inlet boundary reduces the length of the wake region on a leeward hill with a low slope,but has less impact on the mean wind velocity of steep hills.

关键词： Large eddy simulation(LES) Spectral representation method Recycling method high mountainous canyon Wind characteristics Atmospheric boundary layer Computational domain

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An alternative approach to improve the compatibility of PCE in cement paste blend with coal gangue powder

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Waste Disposal and Sustainable Energy 2024年第1期6卷 139-150页

作者： Zonglin Xie Yuxuan Li Dahui Sun Yi Tian Jinyuan Hu Qiang Yuan Zheng Chen School of Civil engineering Central South UniversityChangshaChina China railway NO.9 Group CO. LTDShenyangChina national engineering research center for high-speed railway construction technology ChangshaChina Guangxi Key Laboratory of Disaster Prevention and engineering Safety Guangxi UniversityNanningChina

Coal gangue(CG)is an environmental waste that faces an urgent demand for disposal in *** utilization of CG in construction materials has broad application prospects and gained increasing ***,the poor compatibility of polycarboxylate superplasticizer(PCE)with CG powder hinders its efficiency in a wide range of ***,this paper attempts to improve the compatibility of PCE with CG powder in cement paste based on the regulation of aggregation and the adsorption behavior of *** light scattering(DLS)and fluorescence spectroscopy tests were carried out to understand the improved *** results indicated that the addition of CG powder increases the ionic strengths of the cement liquid phase,which makes PCE tend to aggregate at a lower concentration compared with no CG powder ***(CH_(3)COO)_(2)Cu is beneficial for enhancing the workability of cement paste by reducing PCE aggregation while maintaining the compressive strength of cement ***,(CH_(3)COO)_(2)Cu extra addition can be regarded as an effective and sustainable way to improve the workability of cement paste with CG powder.

关键词： Coal gangue powder Polycarboxylate superplasticizer Compatibility Aggregation

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WT-FCTGN:A wavelet-enhanced fully connected time-gated neural network for complex noisy traffic flow modeling

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Chinese Physics B 2024年第7期33卷 652-664页

作者：廖志芳孙轲刘文龙余志武刘承光宋禹成 School of Computer Science and engineering Central South UniversityChangsha 410083China national engineering research center of high-speed railway construction technology Changsha 410075China School of Civil engineering Central South UniversityChangsha 410075China School of Traffic&Transportation engineering Central South UniversityChangsha 410083China

Accurate forecasting of traffic flow provides a powerful traffic decision-making basis for an intelligent transportation system. However, the traffic data's complexity and fluctuation, as well as the noise produced during collecting information and summarizing original data of traffic flow, cause large errors in the traffic flow forecasting results. This article suggests a solution to the above mentioned issues and proposes a fully connected time-gated neural network based on wavelet reconstruction(WT-FCTGN). To eliminate the potential noise and strengthen the potential traffic trend in the data, we adopt the methods of wavelet reconstruction and periodic data introduction to preprocess the data. The model introduces fully connected time-series blocks to model all the information including time sequence information and fluctuation information in the flow of traffic, and establishes the time gate block to comprehend the periodic characteristics of the flow of traffic and predict its flow. The performance of the WT-FCTGN model is validated on the public Pe MS data set. The experimental results show that the WT-FCTGN model has higher accuracy, and its mean absolute error(MAE), mean absolute percentage error(MAPE) and root mean square error(RMSE) are obviously lower than those of the other algorithms. The robust experimental results prove that the WT-FCTGN model has good anti-noise ability.

关键词： traffic flow modeling time-series wavelet reconstruction

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Age of Information Based User Scheduling and Data Assignment in Multi-User Mobile Edge Computing Networks:An Online Algorithm

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China Communications 2024年第5期21卷 153-165页

作者： Ge Yiyang Xiong Ke Dong Rui Lu Yang Fan Pingyi Qu Gang School of Computer and Information technology Beijing Jiaotong UniversityBeijing 100044China engineering research center of Network Management technology for high speed railway of Ministry of Education Beijing 100044China Beijing engineering research center of high-speed railway Broadband Mobile Communications Beijing 100044China Department of Electronic engineering Tsinghua UniversityBeijing 100084China Beijing national research center for Information Science and technology Tsinghua UniversityBeijing 100084China Department of Electrical and Computer engineering College ParkMarylandUSA

This paper investigates the age of information(AoI)-based multi-user mobile edge computing(MEC)network with partial offloading *** weighted sum AoI(WSA)is first analyzed and derived,and then a WSA minimization problem is formulated by jointly optimizing the user scheduling and data *** to the non-analytic expression of the WSA *** optimization variables and the unknowability of future network information,the problem cannot be solved with known solution ***,an online Joint Partial Offloading and User Scheduling Optimization(JPOUSO)algorithm is proposed by transforming the original problem into a single-slot data assignment subproblem and a single-slot user scheduling sub-problem and solving the two sub-problems *** analyze the computational complexity of the presented JPO-USO algorithm,which is of O(N),with N being the number of *** results show that the proposed JPO-USO algorithm is able to achieve better AoI performance compared with various baseline *** is shown that both the user’s data assignment and the user’s AoI should be jointly taken into account to decrease the system WSA when scheduling users.

关键词： age of information(aoi) mobile edge computing(mec) user scheduling

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A method for support stiffness failure identification in a steel spring floating slab track of urban railway: a case study in China

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Journal of Zhejiang University-Science A(Applied Physics & engineering) 2024年第3期25卷 206-222页

作者： Junyuan ZHENG Caiyou ZHAO Duojia SHI Ping WANG Jian WANG Bolong JIANG Xi SHENG Key Laboratoryof high-speed railway engineering Ministry of EducationSouthwest Jiaotong UniversityChengdu 60031China School of Civil engineering Southwest Jiaotong UniversityChengdu 610031China 01 DYNA(Qingdao)Test&Data Co. Ltd.Qingdao 266000China Rail Transit Digital construction and Measurement technology national engineering research center China Railway Design CorporationTianjin300308China Institute of Urban Smart Transportation&Safety Maintenance Shenzhen UniversityShenzhen 518060China

The extensive use of steel spring floating slab tracks has effectively addressed the challenge of alleviating the environmental vibrations induced by urban rail transit ***,under the combined action of train dynamic loads and complex environmental factors,problems,such as the fracture of steel spring vibration isolators and suspension vibrations induced by the uneven settlement of the base,often *** failure of isolator support stiffness is often hidden in its early stages and is challenging to identify by conventional detection *** the same time,it will aggravate the wheel-rail interaction,accelerate the deterioration of track structure,and even affect the driving *** study first establishes a detailed coupled train-floating slab track-foundation analytical *** the influence of the vibration isolator support stiffness failure on the dynamic indices of the floating slab track system response is analyzed.A set of defect identification methods that can detect the number of failed steel springs,severity of damage,and their location is ***,an intelligent monitoring system for support stiffness of floating slab track is built by combining the density-based spatial clustering of applications with noise algorithm and statistical data analysis and is applied to a rail line in southern *** a three-year monitoring campaign,a suspension failure and a fracture of a steel spring were each successfully detected and detailed failure information was *** investigation results were consistent with the damage identification *** repair,the track structure dynamic response returned to the average pre-damage level and further deterioration had been *** proposed damage identification methods and monitoring system provide an approach for intelligent identification of track structure support stiffness failures.

关键词： Floating slab track Support stiffness Detailed analytical model Failure identification Monitoring system

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Vibration-Based Fault Diagnosis for railway Point Machines Using VMD and Multiscale Fluctuation-Based Dispersion Entropy

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Chinese Journal of Electronics 2024年第3期33卷 803-813页

作者： Yongkui SUN Yuan CAO Peng LI Guo XIE Tao WEN Shuai SU national engineering research center of Rail Transportation Operation and Control System Beijing Jiaotong University School of Electronic and Information engineering Beijing Jiaotong University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Frontiers Science center for Smart high-speed railway System Beijing Jiaotong University

As one of the most important railway signaling equipment,railway point machines undertake the major task of ensuring train operation *** fault diagnosis for railway point machines becomes a hot *** the advantage of the anti-interference characteristics of vibration signals,this paper proposes an novel intelligent fault diagnosis method for railway point machines based on vibration signals.A feature extraction method combining variational mode decomposition(VMD) and multiscale fluctuation-based dispersion entropy is developed,which is verified a more effective tool for feature ***,a two-stage feature selection method based on Fisher discrimination and ReliefF is proposed,which is validated more powerful than single feature selection ***,support vector machine is utilized for fault *** comparisons show that the proposed method performs *** diagnosis accuracies of normal-reverse and reverse-normal switching processes reach 100% and 96.57% ***,it is a try to use new means for fault diagnosis on railway point machines,which can also provide references for similar fields.

关键词： Fault diagnosis Vibrations Support vector machines Diversity reception Switches Feature extraction Rail transportation

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基于Seed-PCG法的列车-轨道-地基土三维随机振动GPU并行计算方法

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Journal of Central South University 2024年第1期31卷 302-316页

作者：朱志辉冯杨杨啸李昊邹有 national engineering research center of high-speed railway construction technology Changsha 410075China School of Civil engineering Central South UniversityChangsha 410075China School of Computer Science and engineering Center South UniversityChangsha 410083China Information and Network center Central South UniversityChangsha 410083China

为了解决列车-轨道-地基土三维有限元模型随机多样本计算效率低的问题,本文提出了一种基于Seed-PCG法的高效并行计算方法。基于有限元法和虚拟激励法建立轨道不平顺激励下的三维列车-轨道-地基土耦合随机振动分析模型;针对车致地基土随... 详细信息

为了解决列车-轨道-地基土三维有限元模型随机多样本计算效率低的问题,本文提出了一种基于Seed-PCG法的高效并行计算方法。基于有限元法和虚拟激励法建立轨道不平顺激励下的三维列车-轨道-地基土耦合随机振动分析模型;针对车致地基土随机振动分析产生的多右端项线性方程组求解问题,采用Seed-PCG方法进行求解。通过PCG方法求解种子系统得到的Krylov子空间进行投影,以改进其余线性方程组的初始解和对应的初始残量,有效提高了PCG法的收敛速度,最后,在MATLABCUDA混合平台上开发了并行计算程序。数值算例表明:相同计算平台下的该方法相比多点同步算法获得了104.2倍的加速;相比PCG法逐个求解方案减少了18%的迭代次数,获得了1.21倍的加速。

关键词： Seed-PCG法多右端项线性方程组随机振动 GPU并行计算列车-轨道-地基土耦合模型

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