• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.451-464
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• 2022

The high-level nuclear waste repository is a deep geological disposal system exposed to complex environmental conditions such as high temperature, radiation, and ground-water due to handling spent nuclear fuel. Continuous exposure can lead to cracking and deterioration of the structure over time. On the other hand, the high-level nuclear waste repository requires an ultra-long life expectancy. Thus long-term structural health monitoring is essential. Various sensors such as an accelerometer, earth pressure gauge, and displacement meter can be used to monitor the health of a structure, and a piezoelectric sensor is generally used. Therefore, it is necessary to develop a highly durable sensor based on the durability assessment of the piezoelectric sensor. This study designed an accelerated life test for durability assessment and life prediction of the piezoelectric sensor. Based on the literature review, the number of accelerated stress levels for a single stress factor, and the number of samples for each level were selected. The failure mode and mechanism of the piezoelectric sensor that can occur in the environmental conditions of the high-level waste repository were analyzed. In addition, two methods were proposed to investigate the maximum harsh condition for the temperature stress factor. The reliable operating limit of the piezoelectric sensor was derived, and a reasonable accelerated stress level was set for the accelerated life test. The suggested methods contain economical and practical ideas and can be widely used in designing accelerated life tests of piezoelectric sensors.

• Journal of Korean Society of Steel Construction
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• v.17 no.1 s.74
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• pp.1-11
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• 2005

A bi-level damage detection algorithm that utilizes the dynamic responses of the structure as input and neural network (NN) as pattern classifier is presented. Signal anomaly index (SAI) is proposed to express the amount of changes in the shape of frequency response functions (FRF) or strain frequency response function (SFRF). SAI is calculated using the acceleration and dynamic strain responses acquired from intact and damaged states of the structure. In a bi-level damage identification algorithm, the presence of damage is first identified from the magnitude of the SAI value, then the location of the damage is identified using the pattern recognition capability of NN. The proposed algorithm is applied to an experimental model bridge to demonstrate the feasibility of the algorithm. Numerically simulated signals are used for training the NN, and experimentally-acquired signals are used to test the NN. The results of this example application suggest that the SAI-based pattern recognition approach may be applied to the structural health monitoring system for a real bridge.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.8-16
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• 2016

This study presents the visualization of shape information based on Octree using 3D laser scanning. The process of visualization was established to construct the Octree structure from the 3D scan data. The scan data was converted to a 2D surface through the mesh technique and the surface was then converted to a 3D object through the Raster/Vector transformation. The 3D object was transmitted to the Octree Root Node and The shape information was constructed by the recursive partitioning of the Octree Root Node. The test-bed was selected as the steel bridge structure in Sungkyunkwan University. The shape information based on Octree was condensed into 89.3%. In addition, the Octree compressibility was confirmed to compare the shape information of the office building, a computer science campus in Germany and a New College in USA. The basis is created by the visualization of shape information for double-deck tunnel and it will be expected to improve the efficiency of structural health monitoring and maintenance.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.239-240
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• 2012

With advancements in semiconductor device technologies, manufacturing processes are getting more complex and it became more difficult to maintain tighter process control. As the number of processing step increased for fabricating complex chip structure, potential fault inducing factors are prevail and their allowable margins are continuously reduced. Therefore, one of the key to success in semiconductor manufacturing is highly accurate and fast fault detection and classification at each stage to reduce any undesired variation and identify the cause of the fault. Sensors in the equipment are used to monitor the state of the process. The idea is that whenever there is a fault in the process, it appears as some variation in the output from any of the sensors monitoring the process. These sensors may refer to information about pressure, RF power or gas flow and etc. in the equipment. By relating the data from these sensors to the process condition, any abnormality in the process can be identified, but it still holds some degree of certainty. Our hypothesis in this research is to capture the features of equipment condition data from healthy process library. We can use the health data as a reference for upcoming processes and this is made possible by mathematically modeling of the acquired data. In this work we demonstrate the use of recurrent neural network (RNN) has been used. RNN is a dynamic neural network that makes the output as a function of previous inputs. In our case we have etch equipment tool set data, consisting of 22 parameters and 9 runs. This data was first synchronized using the Dynamic Time Warping (DTW) algorithm. The synchronized data from the sensors in the form of time series is then provided to RNN which trains and restructures itself according to the input and then predicts a value, one step ahead in time, which depends on the past values of data. Eight runs of process data were used to train the network, while in order to check the performance of the network, one run was used as a test input. Next, a mean squared error based probability generating function was used to assign probability of fault in each parameter by comparing the predicted and actual values of the data. In the future we will make use of the Bayesian Networks to classify the detected faults. Bayesian Networks use directed acyclic graphs that relate different parameters through their conditional dependencies in order to find inference among them. The relationships between parameters from the data will be used to generate the structure of Bayesian Network and then posterior probability of different faults will be calculated using inference algorithms.

• Journal of environmental and Sanitary engineering
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• v.7 no.2
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• pp.1-10
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• 1992

Since 1960's along with industrialization and urbanization, economic growth has been . achieved, however, at the same time, environmental condition has been seriously deteriorated. . Currently, volume of wastewater has been increasing at annual rate of 7% in sewage and 20% in industrial wastewater. However, the nation's sewage treatment serves only 33% of the municipal wastewater as of 1991. Major portion of air pollutants comes from combustion of oil and coal which comprise 81% of total energy use and emission gases from motor vehicles increasing at an accelerated rate. It is known that Korea generates the highest amount of waste per capta. Nevertheless, it is not sufficient to reduce the volume of waste by means of resources recovery and recycling. Recognizing the importance of global environmental problems such as ozone layer depletion, global warming and acid rain, international society has been making various efforts since the 1972 Stockholm conference. In particular, it is expected that the Rio conference which has adopted the Rio declaration and Agenda 21 will form a crucial turning point of the emerging new world order after the Cold War confrontation. To cope with such issues as domestic pollution and global environmental problems, the fundamental national policy aims at harmonizing "environmental protection and sustainable development". The Ministry of Environment has recently set up a mid-term comprehensive plan which includes annual targets for environmental protection. According to the government plan, gradual improvement of various environmental conditions and specific measures to achieve them is planned in time frame. Additional sewage treatment plants will be constructed in urban areas with the target to treat 65% of the nation's municipal sewage by 1996. Supply of clean fuels such as LNG will also be expanded starting from large cities as a cleaner substitute energy for coal and oil. In parallel with expansion of LNG, emphasis will be placed on installation of stack monitoring system. Due to the relatively limited land, government's basic policy for solid waste treatment is to develop large scale landfill facilities rather than small sized ones. Thirty three regional areas have been designated for the purpose of waste management. For each of these regions, big scale landfill site is going to be developed. To increase the rate of waste recycling the government is planning to reinforce separate collection system and to provide industries with economic incentives. As a part of meeting the changing situation on global environmental problems after UNCED, and accommodation regulatory measures stipulated in the global environmental conventions and protocols, national policy will try to alter industrial and economic structure so as to mitigate the increasing trends of energy consumption, by encouraging energy conservation and efficiency. In this regard, more attention will be given to the policy on the development of the cleaner technology. Ultimately, these policies and programs will contribute greatly to improving the current state of national public health.

• Ecology and Resilient Infrastructure
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• v.6 no.4
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• pp.227-235
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• 2019

This study monitored Daecheong 1-bo, Daecheong-stream, which carried out the project in 2014, from 2015 to 2016. The technology applied to the stream was evaluated using Periphytic Algae to check contamination indicators and ecological health of the area with an integral river-bed protection using non-toxic materials. The water quality of the monitoring section was confirmed to be above the river environment standard (II), and it was confirmed that the Saproxenic taxa of the river bed protection were higher than the upper and downstream sections. The TDI, which is an index of attachment algae, was shown in the average 51.03 and 52.15 for the pilot project sections in 2015 and 2016, confirming that the index is of the "normal" grade. This is the other sections in the upstream and downstream sections showed higher than "bad", which is thought to have a positive effect on the habitat of the river ecosystem components, especially the microbial population in river bed protection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.323-335
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• 2015

Mobile healthcare is a fusion of information technology and biotechnology and is a new type of health management service to keep people's health at anytime and anywhere without regard to time and space. The WBAN(Wireless Body Area Network) technology that collects bio signals and the data analysis and monitoring technology using mobile devices are essential for serving mobile healthcare. WBAN consisting of users with mobile devices meet another WBAN during movement, WBANs transmit data to the other media. Because of WBAN conflict, several nodes transmit data in same time slot so a collision will occur, resulting in the data transmission being failed and need more energy for re-transmission. In this thesis, we proposed a MAC protocol for WBAN with mobility to solve these problems. First, we proposed a superframe structure for WBAN. The proposed superframe consists of a TDMA(Time Division Muliple Access) based contention access phase with which a node can transmit data in its own time slot and a contention phase using CSMA/CA algorithm. Second, we proposed a network merging algorithm for conflicting WBAN based on the proposed MAC protocol. When a WBAN with mobility conflicts with other WBAN, data frame collision is reduced through network reestablishment. Simulations are performed using a Castalia based on the OMNeT++ network simulation framework to estimate the performance of the proposed superframe and algorithms. We estimated the performance of WBAN based on the proposed MAC protocol by comparing the performance of the WBAN based on IEEE 802.15.6. Performance evaluation results show that the packet transmission success rate and energy efficiency are improved by reducing the probability of collision using the proposed MAC protocol.

• Journal of the Microelectronics and Packaging Society
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• v.24 no.4
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• pp.23-29
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• 2017

The packaged optical fiber Bragg grating sensors which were networked by multiplexing the Bragg grating sensors with WDM technology were investigated in application for the structural health monitoring of the marine trestle structure transporting the ship. The optical fiber Bragg grating sensor was packaged in a cylindrical shape made of aluminum tubes. Furthermore, after the packaged optical fiber sensor was inserted in polymeric tube, the epoxy was filled inside the tube so that the sensor has resistance and durability against sea water. The packaged optical fiber sensor component was investigated under 0.2 MPa of hydraulic pressure and was found to be robust. The number and location of Bragg gratings attached at the trestle were determined where the trestle was subject to high displacement obtained by the finite element simulation. Strain of the part in the trestle being subjected to the maximum load was analyzed to be ${\sim}1000{\mu}{\varepsilon}$ and thus shift in Bragg wavelength of the sensor caused by the maximum load of the trestle was found to be ~1,200 pm. According to results of the finite element analysis, the Bragg wavelength spacings of the sensors were determined to have 3~5 nm without overlapping of grating wavelengths between sensors when the trestle was under loads and thus 50 of the grating sensors with each module consisting of 5 sensors could be networked within 150 nm optical window at 1550 nm wavelength of the Bragg wavelength interrogator. Shifts in Bragg wavelength of the 5 packaged optical fiber sensors attached at the mock trestle unit were well interrogated by the grating interrogator which used the optical fiber loop mirror, and the maximum strain rate was measured to be about $235.650{\mu}{\varepsilon}$. The modelling result of the sensor packaging and networking was in good agreements with experimental result each other.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.1
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• pp.1-8
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• 2015

Wind power systems have gained much attention due to the relatively high reliability, good infrastructures and cost competitiveness to the fossil fuels. Advances have been made to increase the power efficiency of wind turbines while less attention has been focused on structural integrity assessment of structural sub-systems such as towers and foundations. Among many parameters for integrity assessment, the most perceptive parameter may be the induced horizontal displacement at the hub height although it is very difficult to measure particularly in large-scale and high-rise wind turbine structures. This study proposes an indirect displacement estimation scheme based on the combined use of inclinometers and accelerometers for more convenient and cost-effective measurements. To this end, (1) the formulation for data fusion of inclination and acceleration responses was presented and (2) the proposed method was numerically validated on an NREL 5 MW wind turbine model. The numerical analysis was carried out to investigate the performance of the propose method according to the number of sensors, the resolution and the available sampling rate of the inclinometers to be used.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.858-863
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• 2014

Through this study, we found out whether to measure objectively by using Transactional Analysis(TA) evaluating their own growth and benefit of health through the change of Ego-state, the personality structure and brain waves monitoring electric signals occurring in the brain of the human biological signals. According to the results of brain-wave test, M-type is brain-waves of healthy adults and a, ${\beta}$ were dominantly observed in the occipital while not sleeping. In particular, ${\beta}$ appears widely throughout the brain during nervous or concentrating metal activities and unlike N-type experimenters, ${\beta}$ was found to be dominant in M-type experimenters even in stable condition. N-type is brain waves of healthy adults and a, ${\beta}$ were dominantly observed in the occipital while not sleeping. In particular, unlike nervous or concentrating M-type, there was no noise such as tension and blink while resting. In addition, it turned out that subjects with high levels of A ego do not return quickly to the stable state and show a lot of Blinking and swallowing saliva, noise regardless of the pattern of Egogram. And brain waves of 11 people that the difference in data of OK-gram and Ego-state is the same in all items or less than -5 showed a low amplitude of $20{\mu}V$ in general. In conclusion, this study identified that the theory of personality pattern of Transactional Analysis Theory and brain-wave findings are consistent and also found out that brain waves are also associated according to each Ego-state of Egogram.