• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.177-184
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• 2018

In case that limited resources can be mobilized, non-structural countermeasures such as 'monitoring using Information and Communication Technology might be one of solutions to mitigate disaster risks. Having established the monitoring system, operational and maintenance costs to maximize the effectiveness might trouble the authority concerned or duty attendant who is in charge. In this respect, "Guerrilla Sensor" would be very cost effective because of the inherent mobility characteristic. The sensor device with the IRIS camera and GPS (Global Positioning System) equipped, is basically battery-operated and communicates with WCDMA (Wideband Code Division Multiple Access). It has a strong advantage of capabilities for 'Disaster Response' with immediate and prompt action on the spot, making the best use of IoT (Internet of Things), especially with the mobile web. This paper will explain how the sensor system works in real-time GIS (Geographic Information System) pinpointing the exact location of the abnormal movement/ground displacement and notifying the registered users via SMS (Short Message Service). Real time monitoring with early warning and evaluation of current situations with LBS (Location Based Service), live image and data information can help to reduce the disaster impact. Installation of Guerrilla sensor for a real site application at Gimcheon, South Korea is also reported.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2488-2511
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• 2015

Data redundancy has high impact on Wireless Sensor Network's (WSN) performance and reliability. Spatial and temporal similarity is an inherent property of sensory data. By reducing this spatio-temporal data redundancy, substantial amount of nodal energy and bandwidth can be conserved. Most of the data gathering approaches use either temporal correlation or spatial correlation to minimize data redundancy. In Collective Prediction exploiting Spatio Temporal correlation (CoPeST), we exploit both the spatial and temporal correlation between sensory data. In the proposed work, the spatial redundancy of sensor data is reduced by similarity based sub clustering, where closely correlated sensor nodes are represented by a single representative node. The temporal redundancy is reduced by model based prediction approach, where only a subset of sensor data is transmitted and the rest is predicted. The proposed work reduces substantial amount of energy expensive communication, while maintaining the data within user define error threshold. Being a distributed approach, the proposed work is highly scalable. The work achieves up to 65% data reduction in a periodical data gathering system with an error tolerance of 0.6℃ on collected data.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.4
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• pp.321-325
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• 2020

Atmospheric environmental problems have a major impact on human health and lifestyle. In humans, inhalation of nitrogen oxides causes respiratory diseases, such as bronchitis. In this paper, thermal analysis of a gas sensor was carried out to design and fabricate a wearable nylon-yarn gas sensor for the detection of NO_x gas. In the thermal analysis method, the thermal diffusion process was analyzed while operating the sensors at 40 and 60℃ to secure a temperature range that does not cause thermal runaway due to temperature in the operating environment. Thermal diffusion analysis was performed using the COMSOL software. The thermal analysis results could be useful for analyzing gas adsorption and desorption, as well as the design of gas sensors. The thermal energy diffusion rate increased slightly from 10.05 to 10.1 K/mm as the sensor temperature increased from 40 to 60℃. It was concluded that the sensor could be operated in this temperature range without thermal breakdown.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.6
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• pp.427-439
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• 2006

Accurate estimates of in place thickness of early age (3 to 28 days after casting) concrete pavements are needed, where a thickness accuracy of ${\pm}6mm$ is desired. The impact-echo method is a standardized non-destructive technique that has been applied for this task. However, the ability of impact-echo to achieve this precision goal is affected by Vp (measured) and ${\beta}$ (assumed) values that are applied in the computation. A deeper understanding of the effects of these parameters on the accuracy of impact-echo should allow the technique to be improved to meet the desired accuracy goal. In this paper, the results of experimental tests carried out on a range of concrete slabs are reported. Impact-echo thickness estimation errors caused by material property gradients and sensor type are identified. Correction factors to the standard analysis method are proposed to correct the identified errors and to increase the accuracy of the standard method. Results show that improved accuracy can be obtained in the field by applying these recommendations with the standard impact-echo method.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.232-237
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• 2007

The deformation of polymers under high loading-rate conditions will be a governing factor to be considered in their impact-resistant applications such as protective shields and transparent armor. In this paper, the deformation and fracture behaviors of polymeric materials such as PE, PC and PEEK have been investigated by Taylor Impact tests. Taylor cylinder impact tests and high speed photography are introduced to examine the deformation behavior under dynamic loading condition. 20 mm air gun was used to perform the impact experiments. Cylindrical projectiles have been impacted onto a hardened steel anvil at a velocity ranging from 100 to $350\;ms^{-1}.$ Along the barrel line, a photo-sensor which measures the speed of the projectile, four digital cameras which has shutter speed of 1/917,000sec and a rigid anvil were set up. After impact experiments, the shapes of projectiles and images taken using high speed cameras were analysed. Depending on materials adopted, they showed a variety in deformation and fracture behaviors.

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.17-22
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• 2009

This study presents an investigation of the characteristics of piezoelectric sensors whose main utilization is to measure impact pressure. The piezoelectric sensors were tested from several points of view. Their characteristics were investigated for repeatability, the effect of the diameter, temperature effect, water purity, flush mounting, and AC and DC coupling. Out of these, it was revealed that the temperature effect is very significant. The characteristics of the AC and DC coupling are also very important in understanding the time history of the impact pressure.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.4
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• pp.299-304
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• 2007

There are to be some cracks on the material degradation part or the stress concentration parts of the main members, which carry on over-loads, of structures. Because these cracks can be used to evaluate the structural health status, it is important to monitor the crack growth for maintaining the structural safety. In this study, the fiber Bragg grating sensor with a drop ball was developed as a sensor for crack growth detection of an existing crack. The crack growth detection sensor was constructed with three parts: a probe part, a wavelength controling light source and receiver part, and an impact part. The probe part was just formed with a fiber Bragg grating optical fiber The wavelength controling light source part was composed of a current supplying circuit, a DFB laser diode, and a TEC controling circuit for wavelength control. Also, the impact part was just implemented by dropping a steel ball. The performance of this sensor was confirmed by the experiments of the crack detection with an aluminum plate having one existing crack. According to these experiments, the difference of the sensor signal outputs was correlated with the crack length. So, it was confirmed that this sensor could be applied to monitor the crack growth.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.785-796
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• 2023

In this study, a methodology for real-time classification and prediction of defects that may appear in PVDF(Polyvinylidene fluoride) sensors, which are widely used for structural integrity monitoring, is proposed. The types of sensor defects appearing according to the sensor attachment environment were classified, and an impact test using an impact hammer was performed to obtain an output signal according to the defect type. In order to cleary identify the difference between the output signal according to the defect types, the time domain statistical features were extracted and a data set was constructed. Among the machine learning based classification algorithms, the learning of the acquired data set and the result were analyzed to select the most suitable algorithm for detecting sensor defect types, and among them, it was confirmed that the highest optimization was performed to show SVM(Support Vector Machine). As a result, sensor defect types were classified with an accuracy of 92.5%, which was up to 13.95% higher than other classification algorithms. It is believed that the sensor defect prediction technique proposed in this study can be used as a base technology to secure the reliability of not only PVDF sensors but also various sensors for real time structural health monitoring.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.12
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• pp.1237-1244
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• 2016

Vehicle classification system in domestic tollgates is usually to use treadle sensor for calculating wheel width and tread of the vehicle. Due to the impact that occurs when the wheels of the vehicle contact, treadle sensor requires high durability. Recently, KHC(Korea Highway Corporation) began operating high-speed lane for cargo truck. High-speed cargo truck generate more impact the design criteria of previous treadle. Therefore, an increase in the maintenance and management costs of the treadle damage is concerned. In this paper, we propose an algorithm to classify vehicles using non-contact treadle sensors for improving durability from physical impacts. This was based on the KHC's classification criteria and showed a classification accuracy of 99.5 % in one experiment with 1892 vehicles through Changwon tollgate in 1020 local road. Therefore, it shows that vehicle classification system using non-contact treadle sensor could be applied to domestic toll tollgates, effectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.6
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• pp.627-634
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• 2016

Vehicle classification system in domestic tollgates is usually to use treadle sensor for calculating wheel width and tread of the vehicle. due to the impact that occurs when the wheels of the vehicle contact, treadle sensor requires high durability. recently, KHC(Korea Highway Corporation) began operating high-speed lane for cargo truck. high-speed cargo truck generate more impact the design criteria of previous treadle. therefore, an increase in the maintenance and management costs of the treadle damage is concerned. In this paper, we propose an algorithm for obtaining optimal wheel width and tread using non-contact treadle sensor that been improved durability from physical impacts. for the verification of the proposed algorithm, a field test was performed using 1/2/3/6 class vehicles based on the KHC's classification criteria. through this experiments, maximum error of the width and the tread is each ${\pm}2cm$ and ${\pm}8cm$, also the accuracy was measured as 98%, 97% or more, and proved that the proposed algorithm valid on to apply to the vehicle classification system.