• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.4
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• pp.75-82
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• 2014

A pin-type load-cell which uses shear-type strain gauges was developed to measure the tension of a wire in a winch. A finite element analysis was performed to determine the locations of the strain gauges. All of the shear-type strain gauges were attached onto parts that undergo regularly shear stress distributions. A Wheatstone bridge circuit was used to connect each of the gauges and to measure the strains. Linearity within the 5% error range was noted when testing the pin-type load-cell.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.79-86
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• 2009

With the substantial increase of the size of structure, the management of excavation becomes more difficult. Therefore, massive collapses which are related to retaining wall recently increase. However, since the study on measuring and monitoring the pre-stressing force of anchor is insufficient, behavior of anchor may not be predicted and monitored appropriately by the existing strain gauge and load cell type monitoring system. FBG Sensor, which is smaller than strain gauge and has better durability and does not have a noise from electromagnetic waves, is adapted to measure the strain and pre-stressing force of 7-wire strand, so called smart tendon. A series of pullout tests were performed to verify the feasibility of smart tendon and find out the load transfer mechanism around the steel wire tendon fixed to rock with grout. Distribution of measured strains and estimated shear stresses are compared with those predicted by theoretical solutions. It was found that developed smart tendon can be used effectively for measuring strain of 7-wire strand anchor and theoretical solutions underestimate the magnitude of shear stress and load transfer depth.

• Journal of the Korea Concrete Institute
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• v.21 no.2
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• pp.121-127
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• 2009

The failure behavior of RC structure was exceedingly affected by the size and the local strain distribution of the failure zone due to the strain localization behavior on the tension softening materials. However, it is very difficult to quantify and assess the local strain occurring in the failure zone by the conventional test method. In this study, image processing technology, which is available to measure the strain up to the complete failure of RC structures, was used to estimate the local strain distribution and the size of failure zone. In order to verify the reliability and validity for the image processing technology, the strain transition acquired by the image processing technology was compared with strain values measured by the concrete gauge on the uniaxial compressive specimens. Based on the verification of image processing technology for the uniaxial compressive specimens, the size and the local strain distribution of the failure zone of deep beam was measured using the image processing technology. With the results of test, the principal tensile/compressive strain contours were drawn. Using the strain contours, the size of the failure zone and the local strain distribution on the failure of the deep beam was evaluated. The results of strain contour showed that image processing technology is available to assess the failure behavior of deep beam and obtain the local strain values on the domain of the post-peak failure comparatively.