• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.987-990
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• 2000

In modern manufacturing industry such as aerospace, vehicle and die/mold industry, the high hardness malarial which is remarkable in aspects of durability is effectively used. The high-speed and precision machining technology has been applied in these fields. In this study, efficient sensors in high-speed machining by observing similar tendency through comparing cutting force with AE signal, gap sensor signal and accelerometer signal are selected, and machinability of high-speed machining is experimentally evaluated. We performed a basic research for sensing system construction to monitor a machine tool and machining condition.

• Journal of the Society of Disaster Information
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• v.16 no.2
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• pp.374-382
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• 2020

Purpose: Recently, structural defects in old safety management facilities have led to the collapse of buildings and facilities. The purpose of this study is to develop guidelines for the installation of regular monitoring systems that determine the optimal sensor location for monitoring exhibition space building sensors equipped with visual elements in order to analyze the risk signs of exhibition space buildings and develop measurement technology. Method: The components, installation locations, alarm criteria, and management measures of the instrument are presented. Result: A measure was proposed to determine the location of sensors, secure signal processing technology for analysis by having unified visual perception, and configure optimal 'risk sign detection' based on sensor monitoring through test-bed operation. Conclusion: The results of this study can be prepared against the disasters that may arise from the collapse of exhibition buildings, and contribute to strengthening safety management capabilities.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.106-113
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• 2009

Recently, due to many industrial accidents at construction sites, a variety of researches for structural health monitoring (SHM) of buildings are progressing. For real site application of SHM, one of the advanced technologies has blown as wireless sensor networks (WSN). In this paper, we proposed WIVA(WSN Monitoring framework based on 3D Visualization and Augmented Reality in Mobile Devices) system that applies 3D visualization and AR technology to mobile devices with camera based on WSN in order to expand the extent of information can observe. Moreover, we performed experiments to validate effectiveness in 3D and AR mode that utilize WSN data based on IEEE 802.15.4. In real implementation scenario, we demonstrated a fire occurrence test in 3-story building miniature.

• Journal of Korean Tunnelling and Underground Space Association
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• v.15 no.5
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• pp.469-481
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• 2013

The monitoring of a free surface generated by waterjet cutting technology is very important for an efficient construction process. In this study, experiments using a laser sensor were performed to provide a data processing method and to determine optimized parameters. The experimental parameters here are the angular resolution, measurement distance, and free surface cutting shape. The results show that the monitoring resolution increases with a decrease in the angular resolution and the horizontal measurement distance and with an increase in the cutting (free surface) width. This laser monitoring method can be applied during the measurement of free surface shapes and depths in situ.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.359-366
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• 2018

Social infrastructure facilities that have been under construction since the country's high-growth period are undergoing rapid aging, and safety assessments of large structures such as bridge tunnels, which can be directly linked to large-scale casualties in the event of an accident, are necessary. Wireless smart sensor networks that improve SHM(Structural Health Monitoring) based on existing wire sensors are difficult to construct economical and efficient system due to short signal reach. The LPWAN, Low Power Wide Area Network, is becoming popular with the Internet of Things and it is possible to construct economical and efficient SHM by applying it to structural health monitoring. This study examines the applicability of LoRa LPWAN to structural health monitoring and proposes a channel usage pre-planning based LoRa network operation method that can efficiently utilize bandwidth while resolving conflicts between channels caused by using license - exempt communication band.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.87-95
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• 2020

Generally, occupational safety and particularly construction safety is an intricate phenomenon. Industry professionals have devoted vital attention to enforcing Occupational Safety and Health (OHS) from the last three decades to enhance safety management in construction. Despite the efforts of the safety professionals and government agencies, current safety management still relies on manual inspections which are infrequent, time-consuming and prone to error. Extensive research has been carried out to deal with high fatality rates confronting by the construction industry. Sensor systems, visualization-based technologies, and tracking techniques have been deployed by researchers in the last decade. Recently in the construction industry, computer vision has attracted significant attention worldwide. However, the literature revealed the narrow scope of the computer vision technology for safety management, hence, broad scope research for safety monitoring is desired to attain a complete automatic job site monitoring. With this regard, the development of a broader scope computer vision-based risk recognition system for correlation detection between the construction entities is inevitable. For this purpose, a detailed analysis has been conducted and related rules which depict the correlations (positive and negative) between the construction entities were extracted. Deep learning supported Mask R-CNN algorithm is applied to train the model. As proof of concept, a prototype is developed based on real scenarios. The proposed approach is expected to enhance the effectiveness of safety inspection and reduce the encountered burden on safety managers. It is anticipated that this approach may enable a reduction in injuries and fatalities by implementing the exact relevant safety rules and will contribute to enhance the overall safety management and monitoring performance.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.766-777
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• 2008

Currently in increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method (NATM). Successful design, construction and maintenance of NATM tunnel demands prediction, control and monitoring of ground displacement and support stress high accuracy. A magnetic anisotropy sensor is used for nondestructive measurement of stress on surfaces of a ferromagnetic material, such as steel. The sensor is built on the principle of the magneto-strictive effect in which changes in magnetic permeability due to deformation of a ferromagnetic material is measured in a nondestructive manner, which then can be translated into the absolute values of stresses existing on the surface of the material. This technique was applied to measure stresses of H-beams, used as tunnel support structures, to confirm expected measurement accuracy with reading error of about 10 to 20 MPa, which was confirmed by monitoring strains released during cutting tests The results show that this method could be one of the promising technologies for non-destructive stress measurement for safe construction and maintenance of underground rock structures encountered in civil and mining engineering.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.1392-1397
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• 2010

Currently in increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method(NATM). Successful design, construction and maintenance of NATM tunnel demands prediction, control and monitoring of ground displacement and support stress high accuracy. A magnetic anisotropy sensor is used for non-destructive measurement of stress on surfaces of a ferromagnetic material, such as steel. The sensor is built on the principle of the magneto-strictive effect in which changes in magnetic permeability due to deformation of a ferromagnetic material is measured in a non-destructive manner, which then can be translated into the absolute values of stresses existing on the surface of the material. This technique was applied to measure stresses of H-beams, used as tunnel support structures, to confirm expected measurement accuracy with reading error of about 10 to 20MPa, which was confirmed by monitoring strains released during cutting tests The results show that this method could be one of the promising technologies for non-destructive stress measurement for safe construction and maintenance of underground rock structures encountered in civil and mining engineering.

• Smart Structures and Systems
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• v.14 no.5
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• pp.917-942
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• 2014

Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.129-155
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• 2022

In this study, parametric analyses on a hoop-type PZT (lead-zirconate-titanate) interface are performed to estimate the effects of the PZT interface's materials and geometries on sensitivities of impedance responses under strand breakage. The paper provides a guideline for installing the PZT interface suitable in tendon anchorages for damage-sensitive impedance signatures. Firstly, the concept of the PZT interface-based impedance monitoring technique in prestressed tendon anchorage is briefly described. A FE (finite element) analysis is conducted on a multi-strands anchorage equipped with a hoop-type PZT interface for analyzing materials and geometric effects. Various material properties, geometric sizes of the interface, and PZT sensor are simulated under two states of prestressing force for acquiring impedance responses. Changes in impedance signals are statistically quantified to analyze the effect of these factors on damage-sensitive impedance monitoring in the tendon anchorage. Finally, experimental analyses are performed to demonstrate the effects of materials and geometrical properties of the PZT interface on damage-sensitive impedance monitoring.