• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.45-52
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• 2016

Blast furnaces are crucial equipment for steel production. A typical furnace risks unexpected accidents caused by contraction and expansion of the walls under an environment of high temperature and pressure. In this study, an acoustic emission (AE) monitoring system was tested for evaluating the large-scale structural health of a blast furnace. Based on the growth of shell cracks with the emission of high energy levels, severe damage can be detected by monitoring increases in the AE energy parameter. Using this monitoring system, steel mill operators can establish a maintenance period, in which actual shell cracks can be verified by cross-checking the UT. From this study, we expect that AE systems permit early fault detection for structural health monitoring by establishing evaluation criteria based on the severity of shell cracking.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.2
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• pp.81-88
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• 2023

SHM (Structural Health Monitoring) technique for monitoring aircraft structural health and damage, EHM (Engine Health Monitoring) for monitoring aircraft engine performance, and APM (Application Performance Management) is used for each function. APMS (Airplane Performance Monitoring System) is a program that comprehensively applies these techniques to identify the difference between the performance manual provided by the manufacturer and the actual fuel mileage of the aircraft and reflect it in the flight plan. The main purpose of using APMS is to understand the performance of each aircraft, to plan and execute flights in an optimal way, and consequently to reduce fuel consumption. First, it is to check the fuel efficiency trend of each aircraft, check the correlation between the maintenance work performed and the fuel mileage, find the cause of the fuel mileage increase/decrease, and take appropriate measures in response. Second, it is to find the cause of fuel mileage degradation in detail by checking the trends by engine performance and fuselage drag effect. Third, the APMS is to be used in making maintenance work decisions. Through APMS, aircraft with below average fuel mileage are identified, the cause of fuel mileage degradation is identified, and appropriate corrective actions are determined. Fourth, APMS data is used to analyze the economic analysis of equipment installation investment. The cost can be easily calculated as the equipment installation cost, but the benefit is fuel efficiency improvement, and the only way to check this is the manufacturer's theory. Therefore, verifying the effect after installation and verifying the economic analysis is to secure the appropriateness of the investment. Through this, proper investment in fuel efficiency improvement equipment will be made, and fuel efficiency will be improved.

• Smart Structures and Systems
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• v.20 no.1
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• pp.35-42
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• 2017

Recently, compressive sensing based data loss recovery techniques have become popular for Structural Health Monitoring (SHM) applications. These techniques involve an encoding process which is onerous to sensor node because of random sensing matrices used in compressive sensing. In this paper, we are presenting a model where the sampled raw acceleration data is directly transmitted to base station/receiver without performing any type of encoding at transmitter. The received incomplete acceleration data after data losses can be reconstructed faithfully using compressive sensing based reconstruction techniques. An in-depth simulated analysis is presented on how random losses and continuous losses affects the reconstruction of acceleration signals (obtained from a real bridge). Along with performance analysis for different simulated data losses (from 10 to 50%), advantages of performing interleaving before transmission are also presented.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.393-410
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• 2012

The 610 m high Canton Tower (formerly named Guangzhou New Television Tower) is currently considered as a benchmark problem for structural health monitoring (SHM) of high-rise slender structures. In the benchmark study task I, a set of 24-hour ambient vibration measurement data has been available for the output-only system identification study. In this paper, the vector autoregressive models (ARV) method is adopted in the operational modal analysis (OMA) for this TV tower. The identified natural frequencies, damping ratios and mode shapes are presented and compared with the available results from some other research groups which used different methods, e.g., the data-driven stochastic subspace identification (SSI-DATA) method, the enhanced frequency domain decomposition (EFDD) algorithm, and an improved modal identification method based on NExT-ERA technique. Furthermore, the environmental effects on the estimated modal parameters are also discussed.

• Structural Monitoring and Maintenance
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• v.2 no.4
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• pp.339-355
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• 2015

Corrosion of prestressed concrete structures is one of the main challenges that engineers face today. In response to this national need, this paper presents the results of a long-term project that aims at developing a structural health monitoring (SHM) technology for the nondestructive evaluation of prestressed structures. In this paper, the use of permanently installed low profile piezoelectric transducers (PZT) is proposed in order to record the acoustic emissions (AE) along the length of the strand. The results of an accelerated corrosion test are presented and k-means clustering is applied via principal component analysis (PCA) of AE features to provide an accurate diagnosis of the strand health. The proposed approach shows good correlation between acoustic emissions features and strand failure. Moreover, a clustering technique for the identification of false alarms is proposed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1551-1560
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• 2016

With the advancement of wearable devices and wireless body are networks, smart healthcare systems based on such technologies have been emerging to effectively monitor patient health and disease progression. In order to implement viable smart healthcare systems, the security and privacy of patient's personal health information must be considered. Yang et al. proposed a privacy-preserving authentication scheme using key-insulation technique for remote health monitoring system, however, key-insulation technique is not properly adapted to their scheme which in turn causes a security pitfall contrary to their assertions. Besides, Yang et al.'s scheme does not guarantee user anonymity against healthcare service provider. Therefore, in this paper, we discuss the security concerns for Yang et al.'s scheme and present an improved anonymous authentication scheme.

• Korean Journal of Ecology and Environment
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• v.56 no.3
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• pp.196-206
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• 2023

Benthic attached diatoms (BADs), a major primary producer in lotic stream and river ecosystems are micro-sized organisms and require a highly magnified microscopic technique in the observation work. Thus, it is often not easy to ensure accuracy and precision in both qualitative and quantitative analyses. This study proposed a new technique applicable to improve quality control of aquatic ecosystem monitoring and assessment using BADs. In order to meet the purpose of quality control, we developed a permanent mounting slide technique which can be used for both qualitative and quantitative analyses simultaneously. We designed specimens with the combination of grid on both cover and slide glasses and compared their efficiency. As a result of observation and counting of BADs, the slide glass designed with the color-lined grid showed the highest efficiency compared to other test conditions. We expect that the method developed in this study could be effectively used to analyze BADs and contributed to improve the quality control in aquatic ecosystem health monitoring and assessment.

• Smart Structures and Systems
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• v.16 no.5
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• pp.835-851
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• 2015

This paper presents theoretical and experimental evaluation of the structural health monitoring (SHM) capability of piezoelectric wafer active sensors (PWAS) at elevated temperatures. This is important because the technologies for structural sensing and monitoring need to account for the thermal effect and compensate for it. Permanently installed PWAS transducers have been One of the extensively employed sensor technologies for in-situ continuous SHM. In this paper, the electro-mechanical impedance spectroscopy (EMIS) method has been utilized as a dynamic descriptor of PWAS behavior and as a high frequency standing wave local modal technique. Another SHM technology utilizes PWAS as far-field transient transducers to excite and detect guided waves propagating through the structure. This paper first presents how the EMIS method is used to qualify and quantify circular PWAS resonators in an increasing temperature environment up to 230 deg C. The piezoelectric material degradation with temperature was investigated and trends of variation with temperature were deduced from experimental measurements. These effects were introduced in a wave propagation simulation software called Wave Form Revealer (WFR). The thermal effects on the substrate material were also considered. Thus, the changes in the propagating guided wave signal at various temperatures could be simulated. The paper ends with summary and conclusions followed by suggestions for further work.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.3
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• pp.268-279
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• 2007

The reliability of cold-bonding repair technique of carbon-fiber reinforced plastics (CFRP) laminates, often used as a temporary repair for the airplane maintenance, has been evaluated during cyclic loading and localized heating by nondestructive methods. Major concern was given to the evolution of damage after repair in the form of delaminations due to localized heating and cyclic loading combined. An area of interest both on the specimen repaired by cold-bonding and the specimen without repair where delaminations were induced by localized heating and cyclic loading was monitored by acoustic emission (AE) testing and further examined by pitch-catch low-frequency bond testing, and pulse-echo high-frequency ultrasonic testing. The results showed that the reliability of cold-bonding repair would be significantly reduced by the localized heating and cyclic loading combined rather than by the cyclic loading only. AE monitoring appeared to be an effective and reliable tool to monitor the integrity of temporarily repaired CFRP laminates in terms of the structural health monitoring (SHM) philosophy.

• Structural Monitoring and Maintenance
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• v.7 no.3
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• pp.261-281
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• 2020

Civil structures may experience progressive deterioration and damage under environmental and operational conditions over their service life. Finite element (FE) model updating method is one of the most important approaches for damage identification in structures due to its capabilities in structural health monitoring. Although various damage detection approaches have been investigated on structures, there are limited studies on large-sized space structures. Thus, this paper aims to investigate the applicability and efficiency of sensitivity-based FE model updating framework for damage identification in large space structures from a distinct point of view. This framework facilitates modeling and model updating in large and geometric complicated space structures. Considering sensitivity-based FE model updating and vibration measurements, the discrepancy between acceleration response data in real damaged structure and hypothetical damaged structure have been minimized through adjusting the updating parameters. The feasibility and efficiency of the above-mentioned approach for damage identification has finally been demonstrated with two numerical examples: a flat double layer grid and a double layer diamatic dome. According to the results, this method can detect, localize, and quantify damages in large-scaled space structures very accurately which is robust to noisy data. Also, requiring a remarkably small number of iterations to converge, typically less than four, demonstrates the computational efficiency of this method.