In this study, wireless structural health monitoring (SHM) system of cable-stayed bridge is developed using Imote2-
platformed smart sensors. In order to achieve the objective, the following approaches are proposed. Firstly, vibrationand
impedance-based SHM methods suitable for the pylon-cable-deck system in cable-stayed bridge are briefly
described. Secondly, the multi-scale vibration-impedance sensor node on Imote2-platform is presented on the design of
hardware components and embedded software for vibration- and impedance-based SHM. In this approach, a solarpowered
energy harvesting is implemented for autonomous operation of the smart sensor node. Finally, the feasibility
and practicality of the multi-scale sensor system is experimentally evaluated on a real cable-stayed bridge, Hwamyung
Bridge in Korea. Successful level of wireless communication and solar-power supply for smart sensor nodes are verified.
Also, vibration and impedance responses measured from the target bridge which experiences various weather conditions
are examined for the robust long-term monitoring capability of the smart sensor system.
The amount and magnitude of absorption and scattering of stress waves in concrete, mainly due to internal friction and
aggregate inclusions, may be different when the concrete mix proportion varies. In this study, the surface wave spectral
energy transmission method is proposed for the estimation of crack depth in concrete structures, in which the effect of
the concrete mix proportion on measurements of self-compensated surface wave transmission functions (TRFs) and
surface wave spectral energy transmission ratios (SETRs) is investigated and a relationship between the crack depth and
the SETR has been determined from experimental data on various concrete specimens with different mix proportions and
different crack depths using a regression analysis. In the results, it is found that the self-compensated surface wave TRFs
are very sensitive to both concrete mix proportions and crack depths. However, SETR is not much affected by the
concrete mix proportion but very sensitive to the crack depth. Therefore, the spectral energy transmission method can be
effectively used for crack depth estimation in concrete structures regardless of their material mix proportions.
Determination of crack depth in field using the self-calibrating surface wave transmission measurement and the cutting
frequency in the transmission function (TRF) is very difficult due to variations of the measurement conditions. In this
study, it is proposed to use the measured full TRF as a feature for crack depth assessment. A principal component
analysis (PCA) is employed to generate a basis of the measured TRFs for various crack cases. The measured TRFs are
represented by their projections onto the most significant principal components. Then artificial neural network (ANN)
using the PCA-compressed TRFs is applied to assess the crack in concrete. Experimental study is carried out for five
different crack cases to investigate the effectiveness of the proposed method. Results reveal that the proposed method
can be effectively used for the crack depth assessment of concrete structures.
A modified one-sided measurement technique is proposed for Rayleigh wave (R-wave) velocity measurement in concrete. The scattering from heterogeneity may affect the waveforms of R-waves in concrete, which may make the R-waves dispersive. Conventional one-sided techniques do not consider the scattering dispersion of R-waves in concrete. In this study, the maximum energy arrival concept is adopted to determine the wave velocity by employing its continuous wavelet transform. Experimental study was performed to show the effectiveness of the proposed method. The present method is applied to monitor the strength development of early-age concrete. A series of experiments were performed on early-age concrete specimens with various curing conditions. Results reveal that the proposed method can be effectively used to measure the R-wave velocity in concrete structures and to monitor the strength development of early-age concrete.
One of the most promising NDT technologies is the guided ultrasonic wave technology. The most useful guided ultrasonic wave is Lamb waves. Damage detection and (or) nondestructive evaluation of structures using Lamb waves may be completed by the comparison between the analytic and the experimental dispersion diagram of Lamb waves. In order to construct the experimental dispersion diagram, the estimation of group velocities of each Lamb modes is necessary. Time of arrival information is needed to calculate the group velocity of each Lamb mode, and frequency information is needed to tell the Lamb modes from receiving signals because at least two modes are present at same frequency. Current research for detection of the time of arrival and the frequency is either in time domain or in frequency domain. However, these methods were not designed to give simultaneous information of the time and the frequency. Furthermore the scattering of waves and the background noise often mask the signal, leading difficulties in its estimation of the time of arrival and the frequency of the reflected and transmitted of dispersive Lamb waves. In this study, the authors introduce a detection method to estimate the time of arrival and the frequency simultaneously via time-frequency representation and to resolve the noise problem based on statistical signal detection theory. Numerical experiments were conducted to verify and validate the capability of the proposed method. The results of experiments demonstrate the utility of the proposed method.