KEYWORDS: Ferroelectric materials, Sensors, Microsoft Foundation Class Library, Structural health monitoring, Resistance, Head, Databases, Numerical simulations, Neodymium, Smart materials
For a nuclear containment structure, the structural health monitoring is essential because of its high potential risk and
grave social impact. In particular, the tendon and anchorage zone are to be monitored because they are under high tensile
or compressive stress. In this paper, a method to monitor the tendon force and the condition of the anchorage zone is
presented by using the impedance-based health diagnosis system. First, numerical simulations were conducted for cases
with various loose tensile forces on the tendon as well as damages on the bearing plate and concrete structure. Then,
experimental studies were carried out on a scaled model of the anchorage system. The relationship between the loose
tensile force and the impedance-based damage index was analyzed by a regression analysis. When a structure gets
damaged, the damage index increases so that the status of damage can be identified. The results of the numerical and
experimental studies indicate a big potential of the proposed impedance-based method for monitoring the tendon and
anchorage system.
KEYWORDS: Sensors, Structural health monitoring, Bridges, Fiber Bragg gratings, Safety, Signal processing, System integration, Temperature metrology, Environmental sensing, Data acquisition
Recently a challenging project has been carried out for construction of a national network for safety management and
monitoring of civil infrastructures in Korea. As a part of the project, structural health monitoring (SHM) systems have
been established on railroad bridges employing various types of sensors such as accelerometers, optical fiber sensors,
and piezoelectric sensors. This paper presents the current status of railroad bridge health monitoring testbeds. Emerging
sensors and monitoring technologies are under investigation. They are local damage detection using PZT-based electro-mechanical
impedances; vibration-based global monitoring using accelerations, FBG-based dynamic strains; and
wireless sensor data acquisition systems. The monitoring systems provide real-time measurements under train-transit and
environmental loadings, and can be remotely accessible and controllable via the web. Long-term behaviors of the
railroad bridge testbeds are investigated, and guidelines for safety management are to be established by combining
numerical analysis and signal processing of the measured data.
KEYWORDS: Sensors, Structural health monitoring, Ferroelectric materials, Signal processing, Microcontrollers, Damage detection, Solar cells, Bridges, Solar energy, Clouds
This study presents the development of a multi-functional wireless sensor node for the impedance-based SHM. The
bottom line is to provide multifunctional wireless sensor nodes for low cost and low power excitation/sensing, structural
damage detection/sensor self-diagnosis using embedded algorithms, temperature/power monitoring, and energy
scavenging. A miniaturized impedance measuring chip is utilized for low cost and low power structural excitation/selfsensing.
Then, structural damage detection/sensor self-diagnosis are executed on the on-board microcontroller.
Moreover, it can use the harvested power from solar energy to measure and analyze the impedance data. Simultaneously
it can monitor temperature and power consumption. In order to validate the feasibility of this multi-functional wireless
impedance sensor node, a series of experimental studies have been carried out for detecting loose bolts and crack
damages on a lab-scale steel structure as well as on real steel bridge/building structures. As a result, it has been found
that the proposed wireless impedance sensor nodes can be effectively used for local health monitoring of structural
components and for constructing a low-cost and low-power but multifunctional SHM system as "place and forget"
sensors.
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.
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