Jin-Hak Yi

Performance monitoring of the Geumdang Bridge using a dense network of high-resolution wireless sensors

As researchers continue to explore wireless sensors for use in structural monitoring systems, validation of field performance must be done using actual civil structures. In this study, a network of low-cost wireless sensors was installed in the Geumdang Bridge, Korea to monitor the bridge response to truck loading. Such installations allow researchers to quantify the accuracy and robustness of wireless monitoring systems within the complex environment encountered in the field. In total, 14 wireless sensors were installed in the concrete box girder span of the Geumdang Bridge to record acceleration responses to forced vibrations introduced by a calibrated truck. In order to enhance the resolution of the capacitive accelerometers interfaced to the wireless sensors, a signal conditioning circuit that amplifies and filters low-level accelerometer outputs is proposed. The performance of the complete wireless monitoring system is compared to a commercial tethered monitoring system that was installed in parallel. The performance of the wireless monitoring system is shown to be comparable to that of the tethered counterpart. Computational resources (e.g. microcontrollers) coupled with each wireless sensor allow the sensor to estimate modal parameters of the bridge such as modal frequencies and operational displacement shapes. This form of distributed processing of measurement data by a network of wireless sensors represents a new data management paradigm associated with wireless structural monitoring. (Some figures in this article are in colour only in the electronic version)

Joint damage assessment of framed structures using a neural networks technique

Abstract A method is proposed to estimate the joint damages of a steel structure from modal data using a neural networks technique. The beam-to-column connection in a steel frame structure is represented by a zero-length rotational spring at the end of the beam element, and the joint fixity factor is defined from the rotational stiffness so that the factor may be in the range of 0–1.0. The severity of joint damage is then defined as the reduction ratio of the connection fixity factor. Several advanced techniques are employed to develop the robust damage identification technique using neural networks. The concept of substructural identification is used for the localized damage assessment in a large structure. The noise-injection learning algorithm is used to reduce the effects of the noise in the modal data. The data perturbation scheme is also employed to assess the confidence in the estimated damages based on a few sets of actual measurement data. The feasibility of the proposed method is examined through a numerical simulation study on a 2-bay 10-story structure and an experimental study on a 2-story structure. It is found that joint damages can be reasonably estimated even for the case where the measured modal vectors are limited to a localized substructure and the data are severely corrupted with noise.

Temperature effects on frequency-based damage detection in plate-girder bridges

In this paper the variability of modal properties caused by temperature effects is assessed in order to adjust modal data used for nondestructive damage detection in structures. First, an experiment to estimate temperature effects on modal properties is performed. Pre-damage and post-damage dynamic modal data from a model plate-girder bridge are described. The relationship between temperature and natural frequencies is analyzed and a set of empirical frequency-correction formulas are obtained for the test structure. Next, a frequency-based damage-detection method is utilized to locate and estimate severity of damage in the test structure for which a set of pre-damage and post-damage frequencies were measured at different temperature conditions. A theory of the frequency-based damage-detection algorithm that related to beam-type structures is outlined. The measured frequencies are adjusted by the frequency-correction formulas and fed into the damage-detection scheme that locates damage and estimates severity of damage in the test structure. Results of the analysis indicates that the temperature correction scheme works for the accurate damage localization and severity estimation in the test structure.

Impedance-based Damage Detection for Civil Infrastructures

The objective of this study is to investigate the feasibility of an impedance-based damage detection technique using piezoelectric (PZT) transducers for civil infrastructures such as steel bridges. The basic concept of the technique is to monitor the changes in the electrical impedance to detect structural damages. Those changes in the electrical impedance are due to the electro-mechanical coupling property of piezoelectric materials and the host structure. In this study, at first, a numerical analysis was performed to understand the basics of this technique through a simple 1-D electro-mechanical system. The experimental studies on three kinds of structural members were carried out to detect the locations of cracks and loosened bolts. It was that cracks or loosened bolts near the PZT sensors could be effectively detected by monitoring the shifts of the resonant frequencies of the impedance functions.

On the natural frequency of tidal current power systems—A discussion of sea testing

To study the wet natural frequency (in water) and dry natural frequency (in air) of a tidal current turbine, we conducted a two-year measurement campaign by deploying a full-scale prototype of the system. In this article, a theoretical model is developed and validated with the frequency measurements. It reveals the measured wet natural frequency of the system could approach half that of the dry one. The measurements also show that inflow turbulence is very important in the excitation of system resonances that can lead to system failure. We also briefly discuss how the wet frequency varies over a long period.

Application of Structural Health Monitoring System for Reliable Seismic Performance Evaluation of Infrastructures

In this study, the useful application of an instrumented structural health monitoring (SHM) system is proposed for the reliable seismic performance evaluation based on measured response data. A seismic fragility is chosen as a key index for probabilistic seismic performance assessment on an infrastructure. The seismic performance evaluation procedure consists of the following five main steps; (1) measuring ambient vibration of a bridge under general traveling vehicles; (2) identifying modal parameters including natural frequencies and mode shapes from the measured acceleration data by output-only modal identification method; (3) updating linear structural parameters in a preliminary finite element (FE) model using the identified modal parameters; (4) analyzing nonlinear response time histories of the structure using nonlinear seismic analysis program; and finally (5) evaluating the probabilistic seismic performance in terms of seismic fragility. In the present study, the seismic fragility curves are represented by a log-normal distribution function. An instrumented highway bridge is utilized to demonstrate the proposed evaluation procedure and it is found that the seismic fragility of a highway bridge can be reliably evaluated by combining the modal information obtained from the instrumented SHM system and FE model updating by using the information.

Field Implementation of Wireless Vibration Sensing System for Monitoring of Harbor Caisson Breakwaters

A wireless sensing system for structural health monitoring (SHM) of harbor caisson structures is presented. To achieve the objective, the following approaches were implemented. First, a wave-induced vibration sensing system was designed for global structural health monitoring. Second, global SHM methods which are suitable for damage monitoring of caisson structures were selected to alarm the occurrence of unwanted behaviors. Third, an SHM scheme was designed for the target structure by implementing the selected SHM methods. Operation logics of the SHM methods were programmed based on the concept of the wireless sensor network. Finally, the performance of the proposed system was globally evaluated for a field harbor caisson structure for which a series of tasks were experimentally performed by the wireless sensing system.

Health Monitoring Method Using Committee of Neural Networks

Preventive maintenance and structural safety of large structures such as bridges and buildings may be guaranteed by application of structural health monitoring systems. Damage assessment using structural identification technique is essential for the structural health monitoring. In this study, the committee technique for neural networks is applied to damage estimation of structures for the purpose of the health monitoring. The input to the neural networks consists of the modal parameters, and the output is composed of the element-level damage indices. In the committee technique, multiple neural networks are constructed and each individual networks is trained independently. Then, the estimated damage indices from different neural networks are averaged. Various committee techniques are possible. The architecture, the training patterns, and the input of each individual networks can be taken to be the same and/or different. In this study, the validity of the several committee methods for damage estimation was examined through numerical simulation study. Then, experiments were carried out to verify the effectiveness of the committee technique. It has been found that the estimated damage indices improve significantly by employing the committee of neural networks. Introduction Recently, the neural networks technique has been well utilized in the field of structural identification for complex structures. The neural networks technique is adequate to the on-line health monitoring since the damage estimation takes very short time. Another advantage of neural networks technique for damage estimation is that it is useful for the cases with a various types of input. The committee technique for neural networks [1] has been widely used for pattern recognitions in speech and vision studies. It was observed that the committee provided good estimates by means of averaging the results of individual networks in the committee, when the individual errors are uncorrelated [1]. Marwala and Heyns’ [2] showed that this approach is effective for identification of damages in structures using vibration data. In this study, the committee technique for neural networks was applied to the damage estimation of a building structure through numerical simulation. Several committee methods were investigated and used to estimate the damage locations and severities for various damage cases. The validity of the committee technique for damage estimation was also examined on a bridge model with a composite cross section subjected to vehicle loadings. The committee technique has been found to be very effective to improve the accuracy of the damage estimation. Theoretical Background Neural Networks Technique. A popular neural networks model called a multi-layer perception neural networks [3] was used for identification of the element-level stiffness parameters. The input layer contains the measured modal properties, and the output layer consists of the element stiffness indices to be identified. The input/output relationship of the neural networks can be nonlinear as well as linear, and its characteristics are determined by the synaptic weights assigned to the connections between the neurons in two adjacent layers. Systematic way of updating the weights to achieve a Key Engineering Materials Online: 2004-08-15 ISSN: 1662-9795, Vols. 270-273, pp 1983-1988 doi:10.4028/www.scientific.net/KEM.270-273.1983

Flow-Turbine Interaction CFD Analysis for Performance Evaluation of Vertical Axis Tidal Current Turbines (II)

CFD (computational fluid dynamics) analyses that considered the dynamic interaction effects between the flow and a turbine were performed to evaluate the power output characteristics of two representative vertical-axis tidal-current turbines: an H-type Darrieus turbine and Gorlov helical turbine (GHT). For this purpose, a commercial CFD code, Star- CCM+, was utilized, and the power output characteristic were investigated in relation to the scale ratio using the relation between the Reynolds number and the lift-to-drag ratio. It was found that the power coefficients were significantly reduced when the scaled model t urbine was used, especially when the Reynolds number was lower than 10 5 . The power output characteristics of GHT in relation to the twisting angle were also investigated using a three-dimensional CFD analysis, and it was found that the power coefficient was maximized for the case of a Darrieus turbine, i.e., a twisting angle of 0°, and the torque pulsation ratio was minimized when the blade covered 360° for the case of a turbine with a twisting angle of 120°.

Seismic Risk Assessment of Bridges Using Fragility Analysis

Seismic risk assessment of bridge is presented using fragility curves which represent the probability of damage of a structure virsus the peak ground acceleration. In theseismic fragility analysis, the structural damage is defined using the rotational ductility at the base of the bridge pier, which is obtained through nonlinear dynamic analysis for various input earthquakes. For the assessment of seismic risk of bridge, peak ground accelerations are obatined for various return periods from the seismic hazard map of Korea, which enables to calculate the probability density function of peak ground acceleration. Combining the probability density function of peak ground acceleration and the seismic fragility analysis, seismic risk assessment is performed. In this study, seismic fragility analysis is developed as a function of not the surface motion which the bridge actually suffers, but the rock outcrop motion which the aseismic design code is defined on, so that further analysis for the seismic hazard assessment may become available. Besides, the effects of the friction pot bearings and the friction pendulum bearings on the seismic fragility and risk analysis are examined. Lastly, three regions in Korea are considered and compared in the seismic risk assessment.