Techno Press
Tp_Editing System.E (TES.E)
Login Search


sss
 
CONTENTS
Volume 18, Number 3, September 2016
 

Abstract
.

Key Words
.

Address
.

Abstract
The classical Kalman filter (KF) can provide effective state estimation for structural identification and vibration control, but it is applicable only when external inputs are measured. So far, some studies of Kalman filter with unknown inputs (KF-UI) have been proposed. However, previous KF-UI approaches based solely on acceleration measurements are inherently unstable which leads to poor tracking and fictitious drifts in the identified structural displacements and unknown inputs in the presence of measurement noises. Moreover, it is necessary to have the measurements of acceleration responses at the locations where unknown inputs applied, i.e., with collocated acceleration measurements in these approaches. In this paper, it aims to extend the classical KF approach to circumvent the above limitations for general real time estimation of structural state and unknown inputs without using collocated acceleration measurements. Based on the scheme of the classical KF, an improved Kalman filter with unknown excitations (KF-UI) and without collocated acceleration measurements is derived. Then, data fusion of acceleration and displacement or strain measurements is used to prevent the drifts in the identified structural state and unknown inputs in real time. Such algorithm is not available in the literature. Some numerical examples are used to demonstrate the effectiveness of the proposed approach.

Key Words
Kalman filter; unknown inputs; data fusion; structural identification; least-square estimation

Address
Ying Lei, Sujuan Luo and Ying Su: Department of Civil Engineering, Xiamen University, Xiamen 361005, China

Abstract
Structural deflection can be identified from measured strains from long gague sensors, but the sensor layout scheme greatly influences on the accuracy of identified resutls. To determine the optimal sensor layout scheme for accurate deflection identification of the tied arch bridge, the method of optimal layout of long-gauge fiber optic sensors is studied, in which the characteristic curve is first developed by using the bending macro-strain curve under multiple target load conditions, then optimal sensor layout scheme with different number of sensors are determined. A tied arch bridge is studied as an example to verify the effectiveness and robustness of the proposed method for static and dynamic deflection identification.

Key Words
optimal sensor layout; tied arch bridge; long-gauge fiber optic sensor; deflection identification

Address
Jian Zhang: Key Laboratory of Engineering Mechanics of Jiangsu province, Southeast University, Nanjing 210096, China;
International Institute for Urban Systems Engineering, Southeast University, Nanjing 210096, China
Qingqing Zhang, Qi Xia and Zhishen Wu: International Institute for Urban Systems Engineering, Southeast University, Nanjing 210096, China

Abstract
In this study, the feasibility of using telecommunication single-mode optical fiber (SMF) as a distributed fiber optic strain and crack sensor was evaluated in concrete pavement monitoring. Tensile tests on various sensors indicated that the SMF-28e+ fiber revealed linear elastic behavior to rupture at approximately 26 N load and 2.6% strain. Six full-scale concrete panels were prepared and tested under truck and three-point loads to quantify the performance of sensors with pulse pre-pump Brillouin optical time domain analysis (PPP-BOTDA). The sensors were protected by precast mortar from brutal action during concrete casting. Once air-cured for 2 hours after initial setting, half a mortar cylinder of 12 mm in diameter ensured that the protected sensors remained functional during and after concrete casting. The strains measured from PPP-BOTDA with a sensitivity coefficient of 5.43 10-5 GHz/ were validated locally by commercial fiber Bragg grating (FBG) sensors. Unlike the point FBG sensors, the distributed PPP-BOTDA sensors can be utilized to effectively locate multiple cracks. Depending on their layout, the distributed sensors can provide one- or two-dimensional strain fields in pavement panels. The width of both micro and major cracks can be linearly related to the peak strain directly measured with the distributed fiber optic sensor.

Key Words
concrete pavement; crack detection; distributed fiber optic sensor; strain distribution; PPP-BOTDA

Address
Yi Bao, Fujian Tang, Yizheng Chen, Weina Meng and Genda Chen: 1Department of Civil, Architectural, and Environmental Engineering, Missouri University of Science and Technology, 1401 N. Pine Street, Rolla, MO 65409, USA
Ying Huang: Department of Civil and Environmental Engineering, North Dakota State University, 1410 N. 14th Avenue, Fargo, ND 58105, USA


Abstract
In this paper, a new Pigeon Colony Algorithm (PCA) based on the features of a pigeon colony flying is proposed for solving global numerical optimization problems. The algorithm mainly consists of the take-off process, flying process and homing process, in which the take-off process is employed to homogenize the initial values and look for the direction of the optimal solution; the flying process is designed to search for the local and global optimum and improve the global worst solution; and the homing process aims to avoid having the algorithm fall into a local optimum. The impact of parameters on the PCA solution quality is investigated in detail. There are low-dimensional functions, high-dimensional functions and systems of nonlinear equations that are used to test the global optimization ability of the PCA. Finally, comparative experiments between the PCA, standard genetic algorithm and particle swarm optimization were performed. The results showed that PCA has the best global convergence, smallest cycle indexes, and strongest stability when solving high-dimensional, multi-peak and complicated problems.

Key Words
optimization algorithm; Pigeon Colony Algorithm; low-dimensional function; high-dimensional function; nonlinear equation

Address
Ting-Hua Yi and Kai-Fang Wen:School of Civil Engineering, Dalian University of Technology, Dalian 116023, China
Hong-Nan Li: School of Civil Engineering, Dalian University of Technology, Dalian 116023, China;
School of Civil Engineering, Shenyang Jianzhu University, Shenyang 110168, China


Abstract
Energy harvesting is an emerging technique that extracts energy from surrounding environments to power low-power devices. For example, it can potentially provide sustainable energy for wireless sensing networks (WSNs) or structural control systems in civil engineering applications. This paper presents a comprehensive study on harvesting energy from earthquake-induced structural vibrations, which is typically of low frequency, to power WSNs. A macroscale pendulum-type electromagnetic harvester (MPEH) is proposed, analyzed and experimentally validated. The presented predictive model describes output power dependence with mass, efficiency and the power spectral density of base acceleration, providing a simple tool to estimate harvested energy. A series of shaking table tests in which a single-storey steel frame model equipped with a MPEH has been carried out under earthquake excitations. Three types of energy harvesting circuits, namely, a resistor circuit, a standard energy harvesting circuit (SEHC) and a voltage-mode controlled buck-boost converter were used for comparative study. In ideal cases, i.e., resistor circuit cases, the maximum electric energy of 8.72 J was harvested with the efficiency of 35.3%. In practical cases, the maximum electric energy of 4.67 J was extracted via the buck-boost converter under the same conditions. The predictive model on output power and harvested energy has been validated by the test data.

Key Words
vibration energy harvesting; earthquake; circuit; predictive model; low frequency; shaking table test

Address
Wenai Shen and Hongping Zhu: School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan 430074, China
Songye Zhu and You-lin Xu: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong


Abstract
Optical fiber sensors have been proven that they have the potential to detect high-frequency ultrasonic signals, in structural health monitoring field which generally refers to acoustic emission signals from active structural damages and guided waves excited by ultrasonic actuators and propagating in waveguide. In this work, the sensing properties of optical fiber sensors based on Mach-Zehnder interferometer were investigated in the metal plate. Analytical formulas were conducted first to explore the parameters affecting its sensing performances. Due to the simple and definable frequency component, the Lamb wave excited by the piezoelectric wafer was employed to study the sensitivity of the proposed optical fiber sensors with respect to the frequency, rather than the acoustic emission signals. In the experiments, according to above investigations, spiral shape optical fiber sensors with different size were selected to increase their sensitivity. Lamb waves were excited by a circular piezoelectric wafer, while another piezoelectric wafer was used to compare their voltage responses. Furthermore, by changing the excitation frequency, the tuning frequency characteristic of the proposed optical fiber sensor was also investigated experimentally.

Key Words
optical fiber sensor; guided wave; Mach-Zehnder interferometer; sensing property

Address
Wensong Zhou,Hui Li and Anbang Wang: Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education, Harbin Institute of Technology, 73 Huanghe Road, Harbin 150090, China;
School of Civil Engineering, Harbin Institute of Technology, 73 Huanghe Road, Harbin 150090, China
Yongkang Dong: National Key Laboratory of Science and Technology on Tunable Laser, Harbin Institute of Technology, 2 Yikuang Street, Harbin 150001, China



Abstract
Stay cables in some cable-stayed bridges suffer large amplitude vibrations under the simultaneous occurrence of rain and wind. This phenomenon is called rain–wind-induced vibration (RWIV). The upper rivulet oscillating circumferentially on the inclined cable surface plays an important role in this phenomenon. However, its small size and high sensitivity to wind flow make measuring rivulet size and its movement challenging. Moreover, the distribution of the rivulet along the entire cable has not been measured. This paper applies the videogrammetric technique to measure the movement and geometry dimension of the upper rivulet along the entire cable during RWIV. A cable model is tested in an open-jet wind tunnel with artificial rain. RWIV is successfully reproduced. Only one digital video camera is employed and installed on the cable during the experiment. The camera records video clips of the upper rivulet and cable movements. The video clips are then transferred into a series of images, from which the positions of the cable and the upper rivulet at each time instant are identified by image processing. The thickness of the upper rivulet is also estimated. The oscillation amplitude, equilibrium position, and dominant frequency of the rivulet are presented. The relationship between cable and rivulet variations is also investigated. Results demonstrate that this non-contact, non-intrusive measurement method has good resolution and is cost effective.

Key Words
cable vibration; rain–wind-induced vibration; rivulet movement; rivulet thickness; image processing

Address
Haiquan Jing, Yong Xia and Youlin Xu: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong
Yongle Li: Department of Bridge Engineering, Southwest Jiaotong University, Chengdu, China

Abstract
Electromechanical impedance (EMI) based structural health monitoring is performed by measuring the variation in the impedance due to the structural local damage. The impedance signals are acquired from the piezoelectric patches that are bonded on the structural surface. The impedance variation, which is directly related to the mechanical properties of the structure, indicates the presence of local structural damage. Two traditional EMI-based damage detection methods are based on calculating the difference between the measured impedance signals in the frequency domain from the baseline and the current structures. In this paper, a new structural damage detection approach by analyzing the time domain impedance responses is proposed. The measured time domain responses from the piezoelectric transducers will be used for analysis. With the use of the Time Frequency Autoregressive Moving Average (TFARMA) model, a damage index based on Singular Value Decomposition (SVD) is defined to identify the existence of the structural local damage. Experimental studies on a space steel truss bridge model in the laboratory are conducted to verify the proposed approach. Four piezoelectric transducers are attached at different locations and excited by a sweep-frequency signal. The impedance responses at different locations are analyzed with TFARMA model to investigate the effectiveness and performance of the proposed approach. The results demonstrate that the proposed approach is very sensitive and robust in detecting the bolt damage in the gusset plates of steel truss bridges.

Key Words
structural damage detection; piezoelectric impedance; time-frequency ARMA; steel bridge; gusset; joint condition

Address
Xingyu Fan, Jun Li and Hong Hao: Centre for Infrastructural Monitoring and Protection, School of Civil and Mechanical Engineering, Curtin University, Kent Street, Bentley, WA6102, Australia


Abstract
The CFRP-confined circular concrete-filled steel tubular column is composed of concrete, steel, and CFRP. Its failure mechanics are complex. The most important difficulties are lack of an available method to establish a relationship between a specific damage mechanism and its acoustic emission (AE) characteristic parameter. In this study, AE technique was used to monitor the evolution of damage in CFRP-confined circular concrete-filled steel tubular columns. A fuzzy c-means method was developed to determine the relationship between the AE signal and failure mechanisms. Cluster analysis results indicate that the main AE sources include five types: matrix cracking, debonding, fiber fracture, steel buckling, and concrete crushing. This technology can not only totally separate five types of damage sources, but also make it easier to judge the damage evolution process. Furthermore, typical damage waveforms were analyzed through wavelet analysis based on the cluster results, and the damage modes were determined according to the frequency distribution of AE signals.

Key Words
acoustic emission; CFRP–CCFT column; clustering analysis; damage pattern recognition; health monitoring

Address
Dongsheng Li, Fangzhu Du, Zhi Chen and Yanlei Wang: School of Civil Engineering, Dalian University of Technology, Dalian 116024, China

Abstract
The goal of this study is to investigate the effect of non-synchronous sensing when using wireless sensors on structural identification and to attempt correcting such errors in order to obtain a better identification result. The sources causing non-synchronous sensing are discussed first and the magnitudes of such synchronization errors are estimated based on time stamps of data samples collected from Imote2 sensors; next the impact of synchronization errors on power spectral densities (PSDs) and correlation functions of output responses are derived analytically; finally a new method is proposed to correct such errors. In this correction method, the corrected PSDs of output responses are estimated using non-synchronous samples based on a modified FFT. The effect of synchronization errors in the measured output responses on structural identification and the application of this correction method are demonstrated using simulation examples. The simulation results show that even small synchronization errors in the output responses can distort the identified modal and stiffness parameters remarkably while the parameters identified using the proposed correction method can achieve high accuracy.

Key Words
wireless sensor; non-synchronous sensing; structural identification

Address
Zhouquan Feng and Lambros Katafygiotis: Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

Abstract
This paper presents a method for stochastic modelling of fatigue crack growth and optimising inspection and maintenance strategy for the structural members of steel bridges. The fatigue crack evolution is considered as a stochastic process with uncertainties, and the Gamma process is adopted to simulate the propagation of fatigue crack in steel bridge members. From the stochastic modelling for fatigue crack growth, the probability of failure caused by fatigue is predicted over the service life of steel bridge members. The remaining fatigue life of steel bridge members is determined by comparing the fatigue crack length with its predetermined threshold. Furthermore, the probability of detection is adopted to consider the uncertainties in detecting fatigue crack by using existing damage detection techniques. A multi-objective optimisation problem is proposed and solved by a genetic algorithm to determine the optimised inspection and maintenance strategy for the fatigue affected steel bridge members. The optimised strategy is achieved by minimizing the life-cycle cost, including the inspection, maintenance and failure costs, and maximizing the service life after necessary intervention. The number of intervention during the service life is also taken into account to investigate the relationship between the service life and the cost for maintenance. The results from numerical examples show that the proposed method can provide a useful approach for cost-effective inspection and maintenance strategy for fatigue affected steel bridges.

Key Words
steel bridge; fatigue crack; maintenance strategy; Gamma process; life-cycle cost analysis; genetic algorithm

Address
Tian-Li Huang and Hua-Peng Chen: School of Civil Engineering, Central South University, Changsha, Hunan Province, 410075, China;
Department of Engineering Science, University of Greenwich, Chatham Maritime, Kent, ME4 4TB, UK
Hao Zhou and Wei-Xin Ren: School of Civil Engineering, Central South University, Changsha, Hunan Province, 410075, China


Abstract
Steel cables serve as the key structural components in long-span bridges, and the force state of the steel cable is deemed to be one of the most important determinant factors representing the safety condition of bridge structures. The disadvantages of traditional cable force measurement methods have been envisaged and development of an effective alternative is still desired. In the last decade, the vision-based sensing technology has been rapidly developed and broadly applied in the field of structural health monitoring (SHM). With the aid of vision-based multi-point structural displacement measurement method, monitoring of the tensile force of the steel cable can be realized. In this paper, a novel cable force monitoring system integrated with a multi-point pattern matching algorithm is developed. The feasibility and accuracy of the developed vision-based force monitoring system has been validated by conducting the uniaxial tensile tests of steel bars, steel wire ropes, and parallel strand cables on a universal testing machine (UTM) as well as a series of moving loading experiments on a scale arch bridge model. The comparative study of the experimental outcomes indicates that the results obtained by the vision-based system are consistent with those measured by the traditional method for cable force measurement.

Key Words
structural health monitoring; cable-supported bridge; cable force; vision-based system; digital image processing; pattern matching algorithm

Address
X.W. Ye, C.Z. Dong and T. Liu: Department of Civil Engineering, Zhejiang University, Hangzhou 310058, China

Abstract
Precast concrete elements are widely used in the construction of buildings and civil infrastructures as they provide higher construction quality and requires less construction time. However, any abnormalities in precast concrete surfaces such as non-flatness or distortion, can influence the erection of the elements as well as the functional performance of the connections between elements. Thus, it is important to undertake surface flatness and distortion inspection (SFDI) on precast concrete elements before their delivery to the construction sites. The traditional methods of SFDI which are conducted manually or by contact-type devices are, however, time-consuming, labor-intensive and error-prone. To tackle these problems, this study proposes techniques for SFDI of precast concrete elements using laser scanning technology. The proposed techniques estimate the FF number to evaluate the surface flatness, and estimate three different measurements, warping, bowing, and differential elevation between adjacent elements, to evaluate the surface distortion. The proposed techniques were validated by experiments on four small scale test specimens manufactured by a 3D printer. The measured surface flatness and distortion from the laser scanned data were compared to the actual ones, which were obtained from the designed surface geometries of the specimens. The validation experiments show that the proposed techniques can evaluate the surface flatness and distortion effectively and accurately. Furthermore, scanning experiments on two actual precast concrete bridge deck panels were conducted and the proposed techniques were successfully applied to the scanned data of the panels.

Key Words
flatness inspection; distortion inspection; precast concrete elements; laser scanning; bridge deck panels

Address
Qian Wang: Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;
Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
Min-Koo Kim: Department of Engineering, University of Cambridge, Cambridge, England, United Kingdom
Hoon Sohn: Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
ack C.P. Cheng: Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong


Abstract
The rapid technology developments in smartphones have created a significant opportunity for their use in structural live load measurements. This paper presents extensive experiments conducted in two stages to investigate this opportunity. Shaking table tests were carried out in the first stage using selected popular smartphones to measure the sinusoidal waves of various frequencies, the sinusoidal sweeping, and earthquake waves. Comparison between smartphone measurements and real inputs showed that the smartphones used in this study gave reliable measurements for harmonic waves in both time and frequency domains. For complex waves, smartphone measurements should be used with caution. In the second stage, three-dimensional motion capture technology was employed to explore the capacity of smartphones for measuring the movement of individuals in walking, bouncing and jumping activities. In these tests, reflective markers were attached to the test subject. The markers\' trajectories were recorded by the motion capture system and were taken as references. The smartphone measurements agreed well with the references when the phone was properly fixed. Encouraged by these experimental validation results, smartphones were attached to moving participants of this study. The phones measured the acceleration near the center-of-mass of his or her body. The human-induced loads were then reconstructed by the acceleration measurements in conjunction with a biomechanical model. Satisfactory agreement between the reconstructed forces and that measured by a force plate was observed in several instances, clearly demonstrating the capability of smartphones to accurately assist in obtaining human-induced load measurements.

Key Words
human-induced load; smartphone; shaking table; motion capture technology; measurement

Address
Jun Chen, Huan Tan and Ziye Pan: Department of Structural Engineering, Tongji University, No.1239 Siping Road,
Yangpu District, Shanghai, China



Techno-Press: Publishers of international journals and conference proceedings.       Copyright © 2017 Techno-Press
P.O. Box 33, Yuseong, Daejeon 34186 Korea, Tel: +82-42-828-7996, Fax : +82-42-828-7997, Email: info@techno-press.com