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12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

作者： Luo, Wenfeng Yu, Ling Jinan Univ Dept Mech & Civil Engn Guangzhou 510632 Guangdong Peoples R China Jinan Univ MOE Key Lab Disaster Forecast & Control Engn Guangzhou 510632 Guangdong Peoples R China

ISBN: (纸本)9781509040933

In this study, the finite element (FE) model updating method and particle swarm optimization (PSO) algorithm are combined to identify joint equivalent parameters by converting the inverse problem into an optimization problem. First, the natural frequency and frequency response function (FRF) of assembled structures are regarded as an index of the dynamic characteristics. The objective function is defined by minimizing index relative errors between FE model and assembled structures. And then the PSO algorithm is used to solve the optimization problem. The noise effect on the method is also considered. The illustrated numerical simulation results show that the proposed method can identify the equivalent parameters with a good robustness to noises as well as with a high efficiency.

关键词： bolted joints equivalent parameters finite element (FE) model updating particle swam optimization (PSO) frequency response function (FRF)

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Structural Damage Prognosis on Truss Bridges with End Connector Bolts

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JOURNAL OF engineering MECHANICS 2017年第3期143卷

作者： Yu, Ling Zhu, Jun Hua Jinan Univ Minist Educ Key Lab Disaster Forecast & Control Engn 601 West Huangpu Ave Guangzhou 510632 Guangdong Peoples R China China Three Gorges Univ Coll Civil Engn & Architecture Yichang 443002 Peoples R China CEPREI Sci & Technol Reliabil Phys & Applicat Technol El Guangzhou 510610 Guangdong Peoples R China

The successful development of structural damage prognosis (SDP) capability requires the further development and integration of many technology areas, such as hardware, software, modeling capabilities, and so forth. By combining the damage-sensitive feature extraction, the higher statistical moments of structural responses and the fuzzy c-means (FCM) clustering algorithm with the traditional time-series analysis-based SDP method, an integrated method is proposed for the SDP of a truss bridge model with end connector bolts under environmental and operational variability simulated in laboratory. The theoretical formulation of the integrated method is developed first. A six-bay truss bridge model is then designed and fabricated in laboratory for assessing the performance of the proposed method. Various damage cases are simulated by partially or completely loosening some end connecter bolts of the truss bridge under the environmental variability. The performance of the integrated SDP method is assessed based on the time-series acceleration response data measured at 16 ball nodes of the truss bridge model in each reference state and test state. The illustrated results show that the proposed integrated SDP method can effectively identify the damages of a truss bridge with end connector bolts. The introduction of higher statistical moments can provide a beneficial supplement to the traditional damage-sensitive indexes. (C) 2016 American Society of Civil Engineers.

关键词： Structural damage prognosis (SDP) Truss bridge Time-series analysis Higher statistical moments Structural health monitoring (SHM)

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Moving Force Identification based on Particle Swarm Optimization 12

Moving Force Identification based on Particle Swarm Optimiza...

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12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

作者： Liu, Huanlin Yu, Ling Jinan Univ Dept Mech & Civil Engn Guangzhou 510632 Guangdong Peoples R China Jinan Univ MOE Key Lab Disaster Forecast & Control Engn Guangzhou 510632 Guangdong Peoples R China

ISBN: (纸本)9781509040933

Moving force is very important for bridge design, structural analysis and structural health monitoring. Some studies on moving force identification (MFI) attract extensive attentions in the past decades. A novel two-step MFI method is proposed based on particle swarm optimization (PSO) and time domain method (TDM) in this study. The new proposed MFI method includes two steps. In the first step, the PSO is used to identify the constant loads without matrix inversion. In the second step, the conventional TDM is employed to estimate the rest time-varying loads where the Tikhonov regularization and general cross validation (GCV) are introduced to improve the MFI accuracy and to select optimal regularization parameters, respectively. A simply supported beam bridge subjected to moving forces is taken as a numerical simulation example to assess the performance of the proposed method. The illustrated results show that the new two-step MFI method can more effectively identify the moving forces compared to the conventional TDM and the improved Tikhonov regularization method, the proposed new method can provide more accurate MFI results on two moving forces under eight combinations of bridge responses.

关键词： particle swarm optimization (PSO) moving force identification (MFI) time domain method (TDM) Tikhonov regularization general cross validation (GCV)

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Theory and calculation of stress transfer between fiber and matrix

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Applied Mathematics and Mechanics(English Edition) 2015年第6期36卷 815-826页

作者： Jiayu WU Hong YUAN Renhuai LIU MOE Key Laboratory of Disaster Forecast and Control in Engineering Institute of Applied Mechanics Jinan University

For the better use of composites and a deeper insight into the fracture propa- gation and stress transfer of the interface between fiber and matrix, a theoretical solution of closed form is presented with the assumed bilinear local bond-slip law and a parabolic shear stress distribution along the thickness of the matrix. The load-displacement re- lationship and interfacial shear stress are obtained for four loading stages. Finally, the effects of Young＇s modulus of fiber （matrix） and bond length on the performance of the interface are illustrated.

关键词： shear-lag method composite material interfacial mechanics

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Analysis of the key points for increasing passenger traffic efficiencies based on measurements of traffic through ticket gates in 3 cities

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International Journal of Simulation: Systems, Science and Technology 2016年第24期17卷

作者： Tang, Jian Key Lab of Disaster Forecast and Control in Engineering Ministry of Education of the People’s Republic of China Jinan University GuangzhouGuangdong China

By 2012, the passenger traffic capacity for rail transport in Guangzhou reached the highest level of all the cities in China. A questionnaire survey of commuters revealed that 42% of those interviewed in Guangzhou thought the ticket Automatic Gate Machine (AGM) was the most time-consuming aspect of the rail transport system, and its capacity could not meet commuter demand. Therefore, this research focused on the ticket gate machine and its effect on passenger traffic. In addition, concentrating on the sensor area of the ticket gate machine and investigating the machines in Guangzhou, Shenzhen and Hong Kong regions, the optimized key points for increasing passenger traffic efficiencies were found. These were whether the sensor areas lay flat or oblique and whether raised or not, and the color design of the sensor area. © 2016, UK Simulation Society. All rights reserved.

关键词： Efficiency

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Data-Driven Damage Detection for Beam-Like Structures under Moving Loads Using Quasi-Static Responses

Data-Driven Damage Detection for Beam-Like Structures under ...

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International Conference on Fuzzy System and Data Mining (FSDM)

作者： Lin, Yi-Zhou Zhao, Zhan Nie, Zhen-Hua Ma, Hong-Wei Jinan Univ Minist Educ Key Lab Disaster Forecast & Control Engn Dept Mech & Civil Engn Guangzhou 510632 Guangdong Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian Shan Xi Peoples R China

ISBN: (纸本)9781614996194;9781614996187

Due to safety problems of modern structures continuously becoming more serious, structural health monitoring (SHM) systems are attracting increasing attention. The huge amounts of data being generated by SHM systems every day are challenging to analyze. Due to data-driven methods only considering the changes in signals, they are well-suited for this problem. This study considered an application of a data-driven method, moving principal component analysis (MPCA), for damage detection and location for moving-load quasi-static responses of a beam. The MPCA is an adaption version of principal component analysis (PCA) in which a fixed-length window is used to limit the data length so that it has some advantages in adapting to damage detection. Both finite element model and experimentation were used to prepare the time series for detection. It was noted that the MPCA algorithm showed good performances on both numerical and experimental data.

关键词： Damage detection Moving principal component analysis Bridges

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Cloud Computing-Based Time Series Analysis for Structural Damage Detection

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JOURNAL OF engineering MECHANICS 2017年第1期143卷

作者： Yu, Ling Lin, Jing-Chun Jinan Univ Minist Educ Key Lab Disaster Forecast & Control Engn 601 West Huangpu Ave Guangzhou 510632 Guangdong Peoples R China China Three Gorges Univ Coll Civil Engn & Architecture Yichang 443002 Peoples R China Jinan Univ Dept Mech & Civil Engn 601 West Huangpu Ave Guangzhou 510632 Guangdong Peoples R China

The structural damage detection (SDD) and on-line integrity assessment is one of the fundamental objectives in the field of structural health monitoring (SHM). Unfortunately, some of the existed SDD methodologies are time-consuming, and more efficient methods are needed as some large complex structures are assessed in practice. In this study, the cloud computing (CC) technology is introduced into the SDD domain for saving the computation cost and for improving the computation efficiency. The CC definition and application are introduced. Then MapReduce is described as its core technology and Hadoop platform adopted as its open source as well. The traditional time series analysis is separated into map and reduce function modules. In combination with the Hadoop, a new CC-based time series analysis method is proposed for SDD by combining CC technology with time series analysis and further by defining damage-sensitive feature (DSF). The performance and efficiency of the proposed CC-based SDD method is assessed by some numerical simulations for single and multiple damages of a two-story rigid frame, further by a series experimental data downloaded from the web site of the Los Alamos National laboratory (LANL), United States, for damage detection of a three-story building model under the linear and nonlinear damage conditions of structures. The illustrated results show that the new CC-based SDD method can effectively locate the structural damage and quantify the damage severity to some extent. It can save the computation cost and enhance the computing efficiency of SDD implementation. The more the damage cases are, the more significant the speedup ratio is. It is more beneficial to the analysis and processing of the mega data measured on site in the SHM field. (C) 2015 American Society of Civil Engineers.

关键词： Structural damage detections (SDD) Structural health monitoring (SHM) Time series analysis Cloud computing

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Rheological Behaviors of Fresh Cement Pastes with Polycarboxylate Superplasticizer

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Journal of Wuhan University of Technology(Materials Science) 2016年第2期31卷 286-299页

作者：张艳荣孔祥明高亮 WANG Jiaxin State Key Lab of Rail Traffic Control and Safety School of Civil Engineering beijing Jiaotong University beijing 100044 China Department of Civil Engineering Tsinghua University Beijing 100084 China beijing Key Laboratory of Track Engineering beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention Beijing Jiaotong University Beijing 100044 China

The rheologicalbehaviors of fresh cement paste with polycarboxylate superplasticizer were systematically *** including superplasticizer to cement ratio（Sp/C）,water to cement ratio（w/c）,temperature,and time were *** cement pastes with Sp/Cs in the range of 0 to 2.0% and varied W/Cs from 0.25 to 0.5 were prepared and tested at 0,20 and 40 °C,*** and rheologicaltests on cement pastes were conducted to characterize the development of the rheologicalbehavior of fresh cement pastes over *** exprimentalresults indicate that the initialflowability and flowability retention over shelf time increase with the growth in superplasticizer dosage due to the plasticizing effect and retardation effect of *** temperature usually leads to a sharper drop in initialflowability and flowability ***,for the cement paste with high Sp/C or w/c,the flowability is slightly affected by *** stress and plastic viscosity show similar variation trends to the flowability under the abovementioned influentialfactors at low Sp/*** the case of high Sp/C,yield stress and plastic viscosity start to decline over shelf time and the decreasing rate descends at elevated ***,two equations to roughly predict yield stress and plastic viscosity of the fresh cement pastes incorporating Sp/C,w/c,temperature and time are developed on the basis of the existing models,in which experimentalconstants can be extracted from a database created by the rheologicaltest results.

关键词： cement paste flowability yield stress plastic viscosity model

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New damage-sensitive feature for structures with bolted joints

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Journal of Physics: Conference Series 2017年第1期842卷

作者： W F Luo L Yu School of Mechanics and Construction Engineering Jinan University Guangzhou 510632 China MOE Key Lab of Disaster Forecast and Control in Engineering Jinan University Guangzhou 510632 China

Compared with riveted and welded joints, bolted joints have advantages of easily dismantled, high load carrying and load-transferring capacity. However, bolted joints are also weaker components of assembled structures. Structural damage detection (SDD) on bolted joints is much required in the field of structural health monitoring (SHM). A new SDD method is proposed for damage identification of structures with bolted joints based on residual error of AR model in time series analysis. Firstly, a new data standardization process is defined to maintain the information of damage location. Then, a new structural damage feature sensitive to structural damage is developed based on the standard deviation of AR model residual errors. To verify the proposed method, a bolted joint structure is designed and fabricated in laboratory, connection damages of structures are simulated by loosening the bolted joints. The acceleration responses of structures with bolted joints under healthy and damage cases are acquired. Finally, the SDD is performed by traditional DSF and the new DSF. The illustrated results show that the proposed method is a hybrid tool for the bolted joint damage detection with the new damage-sensitive feature. In addition, some related issues will be discussed as well.

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Moving force identification based on particle swarm optimization

Moving force identification based on particle swarm optimiza...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Huanlin Liu Ling Yu Department of Mechanics and Civil Engineering Jinan University Guangzhou China MOE Key Lab of Disaster Forecast and Control in Engineering Jinan University Guangzhou China

ISBN: (纸本)9781509040940

关键词： Bridges Force Time division multiplexing Acceleration Particle swarm optimization Time-domain analysis Numerical simulation

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