We devised the system to automatically shutdown the boiler and to fundamentally block the harmful gases, including carbon monoxide, into the indoor when the exhaust system swerves: (1) The discharge pressure of the exhaust gas decreases when the exhaust pipe is disconnected. The monitoring system of the exhaust pipe is implemented by measuring the output voltage of APS(Air Pressure Sensor) installed to control the amount of combustion air. (2) The operating software was modified so that when the system recognizes the fault condition of a flue pipe, the boiler control unit displays the fault status on the indoor regulator while shutting down the boiler. In accordance with the ventilation facility standards in the "Rules for Building Equipment Standards" by the Ministry of Land, Infrastructure and Transport, experiments were conducted to ventilate indoor air. When carbon monoxide leaked in worst-case scenario, it was possible to prevent poisoning accidents. However, since 2013, the number of indoor air exchange times has been mitigated from 0.7 to 0.5 times per hour. We observed the concentration exceeding TWA 30 ppm occasionally and thus recommend to reinforce this criterion. In conclusion, if the flue pipe fault detection and the indoor air ventilation system are introduced, carbon monoxide poisoning accidents are expected to decrease significantly. Also when the manufacturing and inspection steps, the correct installation and repair are supplemented with the user's attention in missing flue, it will be served to prevent human casualties from carbon monoxide poisoning.
Kim, Jong-Hyun;Shin, Pyeong-Su;Kwon, Dong-Jun;Park, Joung-Man
Composites Research
/
v.33
no.6
/
pp.365-370
/
2020
The icing formation at aircraft occur problems such as increasing weight of the body, fuel efficiency reduction, drag reduction, the error of sensor, and etc. The viscosity of polyurethane (PU) topcoat was measured at 60℃ in real time to set the pre-curing time. SiO2 nanoparticles were dispersed in ethanol using ultra-sonication method. The SiO2/ethanol solution was sprayed on PU topcoat that was not cured fully with different pre-curing conditions. Surface roughness of SiO2/PU nanocomposites were measured using surface roughness tester and the surface roughness data was visualized using 3D mapping. The adhesion property between SiO2 and PU topcoat was evaluated using adhesion pull-off test. The static contact angle was measured using distilled water to evaluate the hydrophobicity. Finally, the pre-curing time of PU topcoat was optimized to exhibit the hydrophobicity of SiO2/PU topcoat.
In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.
Kim, Kye-Ryung;Kim, Wan;Lee, Yong-Hyun;Kang, Hee-Dong
Journal of Sensor Science and Technology
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v.7
no.3
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pp.179-187
/
1998
A neutral particle energy analyzer, which has the carbon stripping foil and the $90^{\circ}$ cylindrical electrostatic deflection plate, was designed and constructed for measuring of ion temperature in plasma. The energy calibration and energy resolution were studied in detail for a hydrogen ion at the $0.5{\sim}3.0\;keV$ energy using a duoplasmatron ion source. An energy of hydrogen ion to the deflection plate voltage at the peak ion count rate could be fitted by the expression $E_{o}(keV)$=3.83V(kV). The measured energy resolution, which was about 2 % at the energy of 3.0 keV and 9 % at the energy of 0.5keV, was better for the increased hydrogen ion energy. For the charge exchanged hydrogen atom due to the carbon stripping foil, the energy calibration, energy loss and resolution were measured to the $0.5{\sim}2.0{\mu}g/cm^{2}$ thickness of the carbon stripping foil. An energy of the charge exchanged hydrogen atom as a function of the deflection plate voltage and carbon foil thickness could be fitted by the expression $E_{o}(keV)=(0.53d+4.4){\cdot}V(kV)$. The energy loss was $0.23{\sim}0.89\;keV $ to the $0.5{\sim}2.0{\mu}g/cm^{2}$ carbon foil thickness and the $0.5{\sim}3.0\;keV$ energy of the incident neutral hydrogen atom, it could be fitted by the expression ${\Delta}E=(0.12d+0.27){\cdot}{E_{o}}^{1/2}(keV)$. The measured energy resolution for the neutral hydrogen atom, which was between 7 % and 35 % in this experiment region, was increased for the increasing neutral hydrogen atom energy and the decreasing carbon stripping foil thickness.
The lattice parameters of stoichiometric $UO_2$ and $U_{1-y}Er_{y}O_2$ in the range of y=0.01 to y =0.33 were determined with use of X-ray diffraction data. Oxygen potentials have been measured by means of a thermogravimetric method in the range of 1200~$1500^{\circ}C$ and $10^{-14}$$\leq$$Po_2$$\leq$$10^{-3}$ for pure $UO_2$ and $U_{1-y}Er_{y}O_{2{\pm}x}$ solid solutions with y=0.02, y=0.06 and y=0.20, respectively. Their oxygen partial pressures were maintained by controlling $CO_2$/CO mixture atmosphere, and the $Po_2$ values corresponding to x of $U_{1-y}Er_{y}O_{2{\pm}x}$ solid solutions were measured with an electrolyte oxygen sensor. The lattice parameter decreases linearly with an increase in the erbium content. The change of the lattice parameter can be expressed in a linear equation of y as a($\AA$) =5.4695-0.220y for 0 $\leq$y$\leq$0.33. The experimental coefficient of y -0.220 in $U_{1-y}Er_{y}O_2$ was an intermediate value between the calculated values -0.273 and -0.156 in the case of $U^{5+}$ and $U^{6+}$, respectively. The (equation omitted) has been found to undergo abrupt increase in the range of -360 to -270 kJ/mole for y=0.06 and -320 to -220 H/mole for y=0.20, respectively, in the temperature range of 1200-$1500^{\circ}C$. (equation omitted) increases with erbium content, but the effect of the dopant for x =0.01 is less significant than that for stoichiometry. The oxygen potentials for $UO_2$ and $U_{0.98}Er_{0.02}O_{2+x}$ can be approximately represented by the $U^{5+}$/$U^{4+}$ model but those for y$\geq$ 0.06 in $U_{1-y}Er_{y}O_{2{\pm}x}$ solid solutions cannot be interpreted by the mean uranium valence model.
Journal of the Korea institute for structural maintenance and inspection
/
v.27
no.3
/
pp.21-29
/
2023
In this study, the stress characteristics of temporary fixed steel rods were analyzed in the "temporary fixing system using internal prestressing tension", which is mainly applied to the construction of superstructures by FCM. It was difficult to confirm the changes in initial tensile force in this system because the steel rod was internally connected to the pier and the PSC BOX. Therefore, measurement was performed before and after the completion of each segment using an FBG sensor to measure the change in the micro length of the steel rod. The results of the analysis showed that 75% to 90% of the maximum vertical contraction of the steel rod that occurred until the completion of the cantilever segment occurred in the fixing ~ 1segment, and the maximum loss of initial prestressing force was 39%. Such excessive loss of tension force to 1 segment means that tension is needed to improve the precision of construction during the fixation, and re-tension is needed to secure stability for conduction of cantilever segments after the completion of 1segment. In the 2 ~ last segment, the stress of the steel rod decreased gradually, and in the summer, the decrease in stress tended to partially recover due to the increase in the length of the steel rod corresponding to the increase in the vertical volume of PSC BOX. The dominant factor in the stress change in 2~ last segment in this phenomenon is judged to be the change in the length of the steel rod according to the temperature. Unlike the change in length, the relaxation was 1.2-2.7%, which was mostly offset by the opposite stress corresponding to the temperature stress. Therefore, a plan was proposed to improve the internal stress, such as adjusting the fixation time.
Korean Journal of Agricultural and Forest Meteorology
/
v.23
no.4
/
pp.329-339
/
2021
Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R2=0.74, RMSE=246 g/m2, RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m2 and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m2 and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m2) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.
Park, Gyou-Tae;Kim, Eun-Jung;Kim, In-Chan;Kim, Hie-Sik
Journal of the Korean Institute of Gas
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v.16
no.6
/
pp.128-135
/
2012
In this paper, we proposed a system and a scenario to raise efficiency of gas safety management by developing wireless ZigBee communication modules, smart-home gas safety appliances and the system suitable for gas safety. Our designed system consists of a micom gas meter, an automatic extinguisher, sensors, and a wall-pad. A micom-gas-meter monitors gas flow, gas pressure, and earthquake. An automatic fire extinguisher checks combustible gas leaks and temperature of $100^{\circ}C$(cut off) and $130^{\circ}C$(fire). Sensors measure smoke and CO gas. In our novel system, a micom-gas meter cut off inner valve with warnings, an automatic fire extinguisher cut off middle valve and spray extinguishing materials, and sensors generate signals when detecting smoke and CO and then take a next action. Gas safety appliances and sensors automatically takes measures, and transmit those information to a wall-pad. The wall-pad again transmits real time information to server. Users can check and manage gas safety situations by connecting BcN server through web or mobile application. We hereby devised scenarios for gas safety and risk management based on the smart, and demonstrated their efficiency through test applied to filed.
Park, Yong-Hyun;Lee, Kyung-Hoon;Choi, Hee-Cheol;Lee, Seung-Hoon
Journal of the Institute of Electronics Engineers of Korea SD
/
v.43
no.12
s.354
/
pp.65-73
/
2006
This work presents a 14b 200KS/s $0.87mm^2$ 1.2mW 0.18um CMOS algorithmic A/D converter (ADC) for intelligent sensors control systems, battery-powered system applications simultaneously requiring high resolution, low power, and small area. The proposed algorithmic ADC not using a conventional sample-and-hold amplifier employs efficient switched-bias power-reduction techniques in analog circuits, a clock selective sampling-capacitor switching in the multiplying D/A converter, and ultra low-power on-chip current and voltage references to optimize sampling rate, resolution, power consumption, and chip area. The prototype ADC implemented in a 0.18um 1P6M CMOS process shows a measured DNL and INL of maximum 0.98LSB and 15.72LSB, respectively. The ADC demonstrates a maximum SNDR and SFDR of 54dB and 69dB, respectively, and a power consumption of 1.2mW at 200KS/s and 1.8V. The occupied active die area is $0.87mm^2$.
In membrane bio-reactor (MBR), the aeration control is one of the important independent variables to decrease fouling and to save energy with shear stress change on the membrane surface. The paper was carried out for numerical simulation of 3-dimensional fluid flow phenomena of the cylindrical bioreactor with submerged flat membranes equipped in the center and supplied the air from the bottom by using the COMSOL program. The viscosity and temperature of solution were assumed to be constant, and the specific air demand based on permeate volume ($SAD_p$) defined as scouring air per permeate rates was used as a variable. The calculated CFD velocities were compared with those of the velocity meter measurement and video image analysis, respectively. The results were good agreement each other within 11% error. For fluid flow in the reactor the liquid velocity increased rapidly between the air diffuser and membrane module, but the velocity decreased during flowing of the membrane module. Also, the velocity increased as it was near from the reactor wall to the central axis. The calculated shear stress on the membrane surface showed the highest value at the center part of the module bottom side and increased as aeration rate increased. Especially, the wall shear stress increased dramatically as the aeration rate increased from 0.15 to 0.25 L/min.
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