Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale structures. According to the mathematical background and implicit assumptions made in the triaxial effective independence (EfI) method, this paper presents a novel multi-dimensional OSP method for the Canton Tower focusing on application demands. In contrast to existing methods, the presented method renders the corresponding target mode shape partitions as linearly independent as possible and, at the same time, maintains the stability of the modal matrix in the iteration process. The modal assurance criterion (MAC), determinant of the Fisher Information Matrix (FIM) and condition number of the FIM have been taken as the optimal criteria, respectively, to demonstrate the feasibility and effectiveness of the proposed method. Numerical investigations suggest that the proposed method outperforms the original EfI method in all instances as expected, which is looked forward to be even more pronounced should it be used for other multi-dimensional optimization problems.

Measurement of deflections of certain bridges is usually hampered by corruption of the GPS signal by multipath associated with passing vehicles, resulting to unrealistically large apparent displacements. Field data from the Gorgopotamos train bridge in Greece and systematic experiments revealed that such bias is due to superimposition of two major effects, (i) changes in the geometry of satellites because of partial masking of certain satellites by the passing vehicles (this effect can be faced with solutions excluding satellites that get temporarily blocked by passing vehicles) and (ii) dynamic multipath caused from reflection of satellite signals on the passing trains, a high frequency multipath effect, different from the static multipath. Dynamic multipath seems to have rather irregular amplitude, depending on the geometry of measured satellites, but a typical pattern, mainly consisting of a baseline offset, wide base peaks correlating with the sequence of main reflective surfaces of the vehicles passing next to the antenna. In cases of limited corruption of GPS signal by dynamic multipath, corresponding to scale distortion of the short-period component of the GPS waveforms, we propose an algorithm which permits to reconstruct the waveform of bridge deflections using a weak fusion of GPS and RTS data, based on the complementary characteristics of the two instruments. By application of the proposed algorithm we managed to extract semi-static and dynamic displacements and oscillation frequencies of a historical railway bridge under train loading by using noisy GPS and RTS recordings. The combination of GPS and RTS is possible because these two sensors can be fully collocated and have complementary characteristics, with RTS and GPS focusing on the long- and short-period characteristics of the displacement, respectively.

The acceleration information is significant for the structural health monitoring, which is the basic measurement to identify structural dynamic characteristics and structural vibration. The efficiency of the accelerometer is subsequently important for the structural health monitoring. In this paper, the distance measure matrix and the support level matrix are constructed firstly and the synthesized support level and the fusion method are given subsequently. Furthermore, the synthesized support level can be served as the determination for diagnosis on accelerometers, while the consensus data fusion method can be used to recover the acceleration information in frequency domain. The acceleration acquisition measurements from the accelerometers located on the real structure National Aquatics Center are used to be the basic simulation data here. By calculating two groups of accelerometers, the validation and stability of diagnosis and recovering on acceleration based on the data fusion are proofed in the paper.

A novel concept of transmissibility based on a wavelet transform for structural damage detection is presented in this paper. The main objective of the research was the development of a method for detecting slight damage at the incipient stage. As a vibration-based approach, the concept of transmissibility has attracted considerable interest because of its advantages and effectiveness in damage detection. However, like other vibration-based methods, transmissibility-based approaches suffer from insensitivity to slight local damage because of the regularity of the traditional Fourier transform. Therefore, the powerful signal processing techniques must be found to solve this problem. Wavelet transform that is able to capture subtle information in measured signals has received extensive attention in the field of damage detection in recent decades. In this paper, we first propose a novel transmissibility concept based on the wavelet transform. Outlier analysis was adopted to construct a damage detection algorithm with wavelet-based transmissibility. The feasibility of the proposed method was numerically investigated with a typical six-degrees-of-freedom spring-mass system, and comparative investigations were performed with a conventional transmissibility approach. The results demonstrate that the proposed transmissibility is more sensitive than conventional transmissibility, and the former is a promising tool for structural damage detection at the incipient stage.

Environmental and operational variables are inevitable concerns by researchers and engineers when implementing the damage detection algorithm in practical projects, because the change of structural behavior could be masked by the conditions in a large extent. Thus, reliable damage detection methods should have a virtue of immunity from environmental and operational variables. In this paper, the pair cointegration method was presented as a novel way to remove the effect of environmental variables. At the beginning, the concept and procedure of this approach were introduced, and then the theoretical formulation and numerical simulations were put forward to illustrate the feasibility. The jump exceeding the control limit in the residual indicates the occurrence of damage, while the direction and magnitude imply the most potential damage location. In addition, the simulation results show that the proposed method has strong ability to resist the noise.

Beam string structure (BSS) is introduced as a new type of hybrid prestressed string structures. The composition and mechanics features of BSS are discussed. The main principles of wavelet packet transform (WPT), principal component analysis (PCA) and support vector machine (SVM) have been reviewed. WPT is applied to the structural response signals, and feature vectors are obtained by feature extraction and PCA. The feature vectors are used for training and classification as the inputs of the support vector machine. The method is used to a single one-way arched beam string structure for damage detection. The cable prestress loss and web members damage experiment for a beam string structure is carried through. Different prestressing forces are applied on the cable to simulate cable prestress loss, the prestressing forces are calculated by the frequencies which are solved by Fourier transform or wavelet transform under impulse excitation. Test results verify this method is accurate and convenient. The damage cases of web members on the beam are tested to validate the efficiency of the method presented in this study. Wavelet packet decomposition is applied to the structural response signals under ambient vibration, feature vectors are obtained by feature extraction method. The feature vectors are used for training and classification as the inputs of the support vector machine. The structural damage position and degree can be identified and classified, and the test result is highly accurate especially combined with principle component analysis.

Locating and assessing the severity of damage in large or complex structures is one of the most challenging problems in the field of civil engineering. Considering that the wavelet packet transform (WPT) has the ability to clearly reflect the damage characteristics of structural response signals and the artificial neural network (ANN) is capable of learning in an unsupervised manner and of forming new classes when the structural exhibits change, this paper investigates a multi-stage structural damage diagnosis method by using the WPT and ANN based on "energy-damage" theory, in which, the wavelet packet component energies are first extracted to be damage sensitive feature and then adopted as input into an improved back propagation (BP) neural network model for damage diagnosis in a step by step mode. To validate the efficacy of the presented approach of the damage diagnosis, the benchmark structure of the American Society of Civil Engineers (ASCE) is employed in the case study. The results of damage diagnosis indicate that the method herein is computationally efficient and is able to detect the existence of different damage patterns in the simulated experiment where minor, moderate and severe damages corresponds to involving in the loss of stiffness on braces or the removal bracing in various combinations.

Dynamic displacement of structures is an important index for in-service structural condition and behavior assessment, but accurate measurement of structural displacement for large-scale civil structures such as long-span bridges still remains as a challenging task. In this paper, a vision-based dynamic displacement measurement system with the use of digital image processing technology is developed, which is featured by its distinctive characteristics in non-contact, long-distance, and high-precision structural displacement measurement. The hardware of this system is mainly composed of a high-resolution industrial CCD (charge-coupled-device) digital camera and an extended-range zoom lens. Through continuously tracing and identifying a target on the structure, the structural displacement is derived through cross-correlation analysis between the predefined pattern and the captured digital images with the aid of a pattern matching algorithm. To validate the developed system, MTS tests of sinusoidal motions under different vibration frequencies and amplitudes and shaking table tests with different excitations (the El-Centro earthquake wave and a sinusoidal motion) are carried out. Additionally, in-situ verification experiments are performed to measure the mid-span vertical displacement of the suspension Tsing Ma Bridge in the operational condition and the cable-stayed Stonecutters Bridge during loading tests. The obtained results show that the developed system exhibits an excellent capability in real-time measurement of structural displacement and can serve as a good complement to the traditional sensors.

In this paper, wireless health monitoring of stay cables using piezoelectric strain sensors and a smart skin technique is presented. For the cables, tension forces are estimated to examine their health status from vibration features with consideration of temperature effects. The following approaches are implemented to achieve the objective. Firstly, the tension force estimation utilizing the piezoelectric sensor-embedded smart skin is presented. A temperature correlation model to recalculate the tension force at a temperature of interest is designed by correlating the change in cable's dynamic features and temperature variation. Secondly, the wireless health monitoring system for stay cables is described. A piezoelectric strain sensor node and a tension force monitoring software which is embedded in the sensor are designed. Finally, the feasibility of the proposed monitoring technique is evaluated on stay cables of the Hwamyung Grand Bridge in Busan, Korea.

The smart sensor technology has opened new horizons for assessing and monitoring structural health of civil infrastructure. Smart sensor's unique features such as onboard computation, wireless communication, and cost effectiveness can enable a dense network of sensors that is essential for accurate assessment of structural health in large-scale civil structures. While most research efforts to date have been focused on realizing wireless smart sensor networks (WSSN) on bridge structures, relatively less attention is paid to applying this technology to buildings. This paper presents a decentralized damage detection using the WSSN for building structures. An existing flexibility-based damage detection method is extended to be used in the decentralized computing environment offered by the WSSN and implemented on MEMSIC's Imote2 smart sensor platform. Numerical simulation and laboratory experiment are conducted to validate the WSSN for decentralized damage detection of building structures.

Condition assessment and monitoring of bridges is critical for safe passenger travel, public transportation, and efficient freight. In monitoring, displacement measurement capability is important to keep track of performance of bridge, in part or as whole. One of the most important parts of a bridge is the expansion joint, which accommodates continuous cyclic thermal expansion of the whole bridge. Though expansion joint is critical for bridge performance, its inspection and monitoring has not been considered significantly because the monitoring requires long-term data using cost intensive equipment. Recently, a wireless smart sensor network (WSSN) has drawn significant attention for transportation infrastructure monitoring because of its merits in low cost, easy installation, and versatile on-board computation capability. In this paper, a rapid wireless displacement monitoring system, wireless hybrid sensor (WHS), has been developed to monitor displacement of expansion joints of bridges. The WHS has been calibrated for both static and dynamic displacement measurement in laboratory environment, and deployed on an in-service highway bridge to demonstrate rapid expansion joint monitoring. The test-bed is a continuous steel girder bridge, the Founders Bridge, in East Hartford, Connecticut. Using the WHS system, the static and dynamic displacement of the expansion joint has been measured. The short-term displacement trend in terms of temperature is calculated. With the WHS system, approximately 6% of the time has been spent for installation, and 94% of time for the measurement showing strong potential of the developed system for rapid displacement monitoring.

A growing need has developed in the United States to obtain more specific knowledge on the structural integrity of infrastructure due to aging service lives, heavier and more frequent loading conditions, and durability issues. This need has spurred extensive research in the area of structural health monitoring over the past few decades. Several structural health monitoring techniques have been developed that are capable of locating damage in structures using modal strain energy of mode shapes. Typically in the past, bending strain energy has been used in these methods since it is a dominant vibrational mode in many structures and is easily measured. Additionally, there may be cases, such as pipes, shafts, or certain bridges, where structures exhibit significant torsional behavior as well. In this research, torsional strain energy is used to locate damage. The damage index method is used on two numerical models; a cantilevered steel pipe and a simply-supported steel plate girder bridge. Torsion damage indices are compared to bending damage indices to assess their effectiveness at locating damage. The torsion strain energy method is capable of accurately locating damage and providing additional valuable information to both of the structures' behaviors.

In this paper, a simplified planar model is developed for damage estimation of interlocked caisson systems. Firstly, a conceptual dynamic model of the interlocked caisson system is designed on the basis of the characteristics of existing harbor caisson structures. A mass-spring-dashpot model allowing only the sway motion is formulated. To represent the condition of interlocking mechanisms, each caisson unit is connected to adjacent ones via springs and dashpots. Secondly, the accuracy of the planar model's vibration analysis is numerically evaluated on a 3-D FE model of the interlocked caisson system. Finally, the simplified planar model is employed for damage estimation in the interlocked caisson system. For localizing damaged caissons, a damage detection method based on modal strain energy is formulated for the caisson system.

Recently, a novel stress sensor, which utilizes the elasto-magnetic (EM) effect of ferromagnetic materials, has been developed to measure stress in steel cables and wires. In this study, the effectiveness of this EM based stress sensors for monitoring of the cable tension force of a real scale cable-stayed bridge was investigated. Two EM stress sensors were installed on two selected multi-strand cables in Hwa-Myung Bridge, Busan, South Korea. Conventional lift-off test was conducted to obtain reference cable tension forces of two test cables. The reference forces were used to calibrate and validate cable tension force measurements from the EM sensors. Tension force variations of two test cables during the second tensioning work on Hwa-Myung Bridge were monitored using the EM sensors. Numerical simulations were conducted to compare and verify the monitoring results. Based on the results, the effectiveness of EM sensors for accurate field monitoring of the cable tension force of cable-stayed bridge is discussed.