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CONTENTS
Volume 54, Number 2, April 2015
 

Abstract
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Key Words
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Address
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Abstract
This paper presents the non-destructive evaluation of a high-speed railway bridge using train-induced strain responses. Based on the train-track-bridge interaction analysis, the strain responses of a high-speed railway bridge under moving trains with different operation status could be calculated. The train induced strain responses could be divided into two parts: the force vibration stage and the free vibration stage. The strain-displacement relationship is analysed and used for deriving critical displacements from theoretical stain measurements at a forced vibration stage. The derived displacements would be suitable for the condition assessment of the bridge through design specifications defined indexes and would show certain limits to the practical application. Thus, the damage identification of high-speed railways, such as the stiffness degradation location, needs to be done by comparing the measured strain response under moving trains in different states because the vehicle types of high-speed railway are relatively clear and definite. The monitored strain responses at the free vibration stage, after trains pass through the bridge, would be used for identifying the strain modes. The relationship between and the degradation degree and the strain mode shapes shows certain rules for the widely used simply supported beam bridges. The numerical simulation proves simple and effective for the proposed method to locate and quantify the stiffness degradation.

Key Words
condition assessment; train-induced responses; high=speed railway bridges; strin modes; structural health monitoring

Address
Zhonglong Li, Shunlong Li and Hui Li: School of Transportation Science and Engineering, Harbin Institute of Technology, 73 Huanghe Road, Nangang District, Harbin 150090, People\'s Republic of China
Jia Lv: Harbin Municipal Engineering Design Institute, Building 217, Dafangli, Daowai District, Harbin 150000, People\'s Republic of China

Abstract
An integrated method is proposed for structural nonlinear damage detection based on time series analysis and the higher statistical moments of structural responses in this study. It combines the time series analysis, the higher statistical moments of AR model residual errors and the fuzzy c-means (FCM) clustering techniques. A few comprehensive damage indexes are developed in the arithmetic and geometric mean of the higher statistical moments, and are classified by using the FCM clustering method to achieve nonlinear damage detection. A series of the measured response data, downloaded from the web site of the Los Alamos National Laboratory (LANL) USA, from a three-storey building structure considering the environmental variety as well as different nonlinear damage cases, are analyzed and used to assess the performance of the new nonlinear damage detection method. The effectiveness and robustness of the new proposed method are finally analyzed and concluded.

Key Words
structural damage detection; nonlinear damage detection; time series analysis; higher statistical moments

Address
Ling Yu: College of Civil Engineering and Architecture, China Three Gorges University, Yichang 443002, China
Ling Yu and Jun-Hua Zhu: MOE Key Lab of Disaster Forecast and Control in Engineering, Jinan University, Guangzhou 510632, China
Science and Technology on Reliability Physics and Application Technology of Electronic Component Laboratory, Guangzhou 510610, China

Abstract
An adaptive-scale damage detection strategy based on a wavelet finite element model (WFEM) for thin plate structures is established in this study. Equations of motion and corresponding lifting schemes for thin plate structures are derived with the tensor products of cubic Hermite multi-wavelets as the elemental interpolation functions. Sub-element damages are localized by using of the change ratio of modal strain energy. Subsequently, such damages are adaptively quantified by a damage quantification equation deduced from differential equations of plate structure motion. WFEM scales vary spatially and change dynamically according to actual needs. Numerical examples clearly demonstrate that the proposed strategy can progressively locate and quantify plate damages. The strategy can operate efficiently in terms of the degrees-of-freedom in WFEM and sensors in the vibration test.

Key Words
adaptive-scale damage detection; plate structure; modal strain energy; wavelet finite element model

Address
Wen-Yu He: Department of Civil Engineering, Hefei University of Technology, Hefei, Anhui Province, 230009, China
Wen-Yu He and Songye Zhu: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China

Abstract
Shear connectors are generally used to link the slab and girders together in slab-on-girder bridge structures. Damage of shear connectors in such structures will result in shear slippage between the slab and girders, which significantly reduces the load-carrying capacity of the bridge. Because shear connectors are buried inside the structure, routine visual inspection is not able to detect conditions of shear connectors. A few methods have been proposed in the literature to detect the condition of shear connectors based on vibration measurements. This paper proposes a different dynamic condition assessment approach to identify the damage of shear connectors in slab-on-girder bridge structures based on power spectral density transmissibility (PSDT). PSDT formulates the relationship between the auto-spectral densities of two responses in the frequency domain. It can be used to identify shear connector conditions with or without reference data of the undamaged structure (or the baseline). Measured impact force and acceleration responses from hammer tests are analyzed to obtain the frequency response functions at sensor locations by experimental modal analysis. PSDT from the slab response to the girder response is derived with the obtained frequency response functions. PSDT vectors in the undamaged and damaged states can be compared to identify the damage of shear connectors. When the baseline is not available, as in most practical cases, PSDT vectors from the measured response at a reference sensor to those of the slab and girder in the damaged state can be used to detect the damage of shear connectors. Numerical and experimental studies on a concrete slab supported by two steel girders are conducted to investigate the accuracy and efficiency of the proposed approach. Identification results demonstrate that damages of shear connectors are identified accurately and efficiently with and without the baseline. The proposed method is also used to evaluate the conditions of shear connectors in a real composite bridge with in-field testing data.

Key Words
condition assessment; shear connectors; power spectral density transmissibility; structural monitoring; slab-on-girder bridge; frequency response function

Address
Jun Li, Hong Hao: Department of Civil Engineering, School of Civil and Mechanical Engineering, Curtin University, Bentley, WA 6102, Australia
Yong Xia: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, People\'s Republic of China
Hong-ping Zhu: School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, Hubei, People\'s Republic of China

Abstract
Compared with the identification of linear structures, it is more challenging to conduct identification of nonlinear structure systems, especially when the locations of structural nonlinearities are not clear in structural systems. Moreover, it is highly desirable to develop methods of parametric identification using partial measurements of structural responses for practical application. To cope with these issues, an identification method is proposed in this paper for the detection and parametric identification of structural nonlinear restoring forces using only partial measurements of structural responses. First, an equivalent linear structural system is proposed for a nonlinear structure and the locations of structural nonlinearities are detected. Then, the parameters of structural nonlinear restoring forces at the locations of identified structural nonlinearities together with the linear part structural parameters are identified by the extended Kalman filter. The proposed method simplifies the identification of nonlinear structures. Numerical examples of the identification of two nonlinear multi-story shear frames and a planar nonlinear truss with different nonlinear models and locations are used to validate the proposed method.

Key Words
nonlinear structural systems; parametric identification; nonlinear restoring force; extended Kalman filter; partial measurements

Address
Ying Lei, Wei Hua, Sujuan Luo and Mingyu He: Department of Civil Engineering, Xiamen University, Xiamen 361005, China

Abstract
Optimal sensor placement (OSP) is an integral component in the design of an effective structural health monitoring (SHM) system. This paper describes the implementation of a novel collaborative-climb monkey algorithm (CMA), which combines the artificial fish swarm algorithm (AFSA) with the monkey algorithm (MA), as a strategy for the optimal placement of a predefined number of sensors. Different from the original MA, the dual-structure coding method is adopted for the representation of design variables. The collaborative-climb process that can make the full use of the monkeys\' experiences to guide the movement is proposed and incorporated in the CMA to speed up the search efficiency of the algorithm. The effectiveness of the proposed algorithm is demonstrated by a numerical example with a high-rise structure. The results show that the proposed CMA algorithm can provide a robust design for sensor networks, which exhibits superior convergence characteristics when compared to the original MA using the dual-structure coding method.

Key Words
optimal sensor placement; monkey algorithm; artificial fish swarm algorithm; collaborative -climb; modal assurance criterion

Address
Ting-Hua Yi, Hong-Nan Li and Xu-Dong Zhang: School of Civil Engineering, Dalian University of Technology, Dalian 116023, China
Guang-Dong Zhou: College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China

Abstract
Life cycle performance of corrosion affected RC structures is an important and challenging issue for effective infrastructure management. The accurate condition assessment of corroded RC structures mainly depends on the effective evaluation of deterioration occurring in the structures. Structural performance deterioration caused by reinforcement corrosion is a complex phenomenon which is generally uncertain and non-decreasing. Therefore, a stochastic modelling such as the gamma process can be an effective tool to consider the temporal uncertainty associated with performance deterioration. This paper presents a time-dependent reliability analysis of corrosion affected RC structures associated bond strength degradation. Initially, an analytical model to evaluate cracking in the concrete cover and the associated loss of bond between the corroded steel and the surrounding cracked concrete is developed. The analytical results of cover surface cracking and bond strength deterioration are examined by experimental data available. Then the verified analytical results are used for the stochastic deterioration modelling, presented here as gamma process. The application of the proposed approach is illustrated with a numerical example. The results from the illustrative example show that the proposed approach is capable of assessing performance of the bond strength of concrete structures affected by reinforcement corrosion during their lifecycle.

Key Words
reinforcement corrosion; concrete cracking; bond strength; performance deterioration; gamma process; reliability analysis

Address
Hua-Peng Chen and Jaya Nepal: School of Engineering, University of Greenwich, Chatham Maritime, Kent, ME4 4TB, UK

Abstract
This paper presents a feasibility study on structural damage alarming and localization of longspan cable-supported bridges using multi-novelty indices formulated by monitoring-derived modal parameters. The proposed method which requires neither structural model nor damage model is applicable to structures of arbitrary complexity. With the intention to enhance the tolerance to measurement noise/uncertainty and the sensitivity to structural damage, an improved novelty index is formulated in terms of auto-associative neural networks (ANNs) where the output vector is designated to differ from the input vector while the training of the ANNs needs only the measured modal properties of the intact structure under in-service conditions. After validating the enhanced capability of the improved novelty index for structural damage alarming over the commonly configured novelty index, the performance of the improved novelty index for damage occurrence detection of large-scale bridges is examined through numerical simulation studies of the suspension Tsing Ma Bridge (TMB) and the cable-stayed Ting Kau Bridge (TKB) incurred with different types of structural damage. Then the improved novelty index is extended to formulate multinovelty indices in terms of the measured modal frequencies and incomplete modeshape components for damage region identification. The capability of the formulated multi-novelty indices for damage region identification is also examined through numerical simulations of the TMB and TKB.

Key Words
structural health monitoring; damage alarming and localization; multi-novelty indices; auto- associative neural networks; cable-supported bridges

Address
Yi-Qing Ni, Junfang Wang: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Tommy H.T. Chan: School of Civil Engineering and Built Environment, Queensland University of Technology, Brisbane, Australia

Abstract
Estimation of geotechnical properties is an essential but challenging task since they are major components governing the safety and reliability of the entire structural system. However, due to time and budget constraints, reliable geotechnical properties estimation using traditional site characterization approach is difficult. In view of this, an alternative efficient and cost effective approach to address the overall uncertainty is necessary to facilitate an economical, safe and reliable geotechnical design. In this paper a probabilistic approach is proposed for real-time updating by incorporating new geotechnical information from the underlying project site. The updated model obtained from the proposed method is advantageous because it incorporates information from both existing database and the site of concern. An application using real data from a site in Hong Kong will be presented to demonstrate the proposed method.

Key Words
bayesian inference; empirical correlation; model selection; nonparametric; normally consolidated clays; undrained shear strength

Address
Iok-Tong Ng, Ka-Veng Yuen and Le Dong: Department of Civil and Environmental Engineering. Faculty of Science and Technology, University of Macau, Macao, China

Abstract
A number of acceleration-based damage detection methods have been developed but they have not been widely applied in engineering practices because the acceleration response is insensitive to minor damage of civil structures. In this article, a damage detection approach using the long-gauge strain sensing technology and the principle component analysis technology is proposed. The Long gauge FBG sensor has its special merit for damage detection by measuring the averaged strain over a long-gauge length, and it can be connected each other to make a distributed sensor network for monitoring the large-scale civil infrastructure. A new damage index is defined by performing the principle component analyses of the long-gauge strains measured from the intact and damaged structures respectively. Advantages of the long gauge sensing and the principle component analysis technologies guarantee the effectiveness for structural damage localization. Examples of a simple supported beam and a steel stringer bridge have been investigated to illustrate the successful applications of the proposed method for structural damage detection.

Key Words
principal component analysis; impact testing; long-gauge fiber optic sensor; Euclidean norm; damage detection

Address
Q. Xia, Y.D. Tian, X.W. Zhu, D.W. Xu and J. Zhang: Key Laboratory of C&PC Structures of the Ministry of Education, Southeast University, Nanjing 210096, China


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