• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.19-28
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• 2016

This study was to design the optimal locations of the water level monitoring to quantify the agricultural water use in irrigation area supplied from an agricultural reservoir. In most of agricultural areas without TM/TC (Tele-Monitoring and Tele-Control) or monitoring network, irrigation water have been supplied on conventional experience and agricultural reservoir have been operated based on the operating simulation results by HOMWRS (Hydrological Operation Model for Water Resources System). Therefore, this study quantified the amount of agricultural water use in an irrigation area (Musu Reservoir, Jincheon-gun) by establishing water level monitoring network and analyzed the agricultural water saving effect. According to the evaluation of the economic values for water saving effect, the saving agricultural water of 1.7 million ton was analyzed to have economic values of 0.85 million won as water for living, and 1.78 million won as water for industrial use. It is identified to secure economic feasibility of the new water monitoring network by establishing one monitoring point in the entrance, irrigation area and endpoint through the economic analysis.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.133-142
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• 2007

The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection

• ETRI Journal
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• v.40 no.5
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• pp.664-676
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• 2018

Given the rapidly increasing market penetration of photovoltaic (PV) systems in many fields, including construction and housing, the effective maintenance of PV systems through remote monitoring at the panel level has attracted attention to quickly detect faults that cause reductions in yearly PV energy production, and which can reduce the whole-life cost. A key point of PV monitoring at the panel level is cost-effectiveness, as the installation of the massive PV panels that comprise PV systems is showing rapid growth in the market. This paper proposes an implementation method that involves the use of a panel-level wireless PV monitoring module (WPMM), and which assesses the cost-effectiveness of this approach. To maximize the cost-effectiveness, the designed WPMM uses a voltage-divider scheme for voltage metering and a shunt-resistor scheme for current metering. In addition, the proposed method offsets the effect of element errors by extracting calibration parameters. Furthermore, a design method is presented for portable and user-friendly PV monitoring, and demonstration results using a commercial 30-kW PV system are described.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.41-44
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• 2021

In this paper, we propose a monitoring system that can monitor gas leakage concentrations in real time and forecast the amount of gas leaked after one minute. When gas leaks happen, they typically lead to accidents such as poisoning, explosion, and fire, so a monitoring system is needed to reduce such occurrences. Previous research has mainly been focused on analyzing explosion characteristics based on gas types, or on warning systems that sound an alarm when a gas leak occurs in industrial areas. However, there are no studies on creating systems that utilize specific gas explosion characteristic analysis or empirical urban gas data. This research establishes a deep learning model that predicts the gas explosion risk level over time, based on the gas data collected in real time. In order to determine the relative risk level of a gas leak, the gas risk level was divided into five levels based on the lower explosion limit. The monitoring platform displays the current risk level, the predicted risk level, and the amount of gas leaked. It is expected that the development of this system will become a starting point for a monitoring system that can be deployed in urban areas.

• Journal of the Korean Society of Visualization
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• v.22 no.2
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• pp.55-62
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• 2024

Using an internal flow noise test bench, this study investigates the variation in internal flow noise at the inlet and outlet monitoring points of a DN100 T-junction pipe under different flow velocities. Results indicate that with increasing flow velocity, both the sound pressure level and total sound pressure level at the inlet and outlet monitoring points increase. The highest total sound pressure level is observed at the vertical outlet monitoring point B, followed by the horizontal inlet monitoring point A, with the lowest at the horizontal outlet monitoring point C. At a constant flow velocity, the sound pressure level at the inlet and outlet points initially increases and then decreases as frequency increases.

• KCID journal
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• v.12 no.1
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• pp.60-68
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• 2005

The purpose of this study is to develop the reservoir water monitoring system with automatic level meter. Until now, installation of water level meter for reservoir stage monitoring were not widely spread in agricultural area. This has several reason : to

• Nuclear Engineering and Technology
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• v.48 no.1
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• pp.98-113
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• 2016

A reactor vessel level monitoring system measures the water level in a reactor during normal operation and abnormal conditions. A drop in the water level can expose nuclear fuel, which may lead to fuel meltdown and radiation spread in accident conditions. A level monitoring system mainly consists of a sensing line and pressure transmitter. Over a period of time boron sediments or other impurities can clog the line which may degrade the accuracy of the monitoring system. The aim of this study is to determine blockage in a sensing line using the energy of the composite signal. An equivalent Pi circuit model is used to simulate blockages in the sensing line and the system's response is examined under different blockage levels. Composite signals obtained from the model and plant's unblocked and blocked channels are decomposed into six levels of details and approximations using a wavelet filter bank. The percentage of energy is calculated at each level for approximations. It is observed that the percentage of energy reduces as the blockage level in the sensing line increases. The results of the model and operational data are well correlated. Thus, in our opinion variation in the energy levels of approximations can be used as an index to determine the presence and degree of blockage in a sensing line.

• Journal of Industrial Convergence
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• v.13 no.3
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• pp.57-76
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• 2015

The purpose of this paper is to examine the moderate effects of self monitoring and the ways of thinking on the relationships and the moderate effects of brand credibility and brand attachment on the relationships between the negative information about a brand and the customer attitude holistic and analytic on the relationships between the negative information about a brand and customer attitude. To accomplish these purposes, this research divided negative information about a brand into corporate ability and corporate social responsibility. In addition, research also divided product type into functional product and symbolic product. participants are classified as having Low or High self monitoring. and the ways of thinking divided into holistic and analytic on the relationships between the negative information about a brand and customer attitude. The following are the summary of hypothesis test: (1)the consumers with low(high) level of self monitering are more likely to reveal high level of preference for negative information of corporate ability. (2)the consumers with analytic(holistic) ways of thinking are more likely to reveal high level of preference for negative information of corporate ability. (3)the consumers with low(high) level of self monitering are more likely to reveal high level of preference for functional product. (4)the consumers with analytic(holistic) ways of thinking aren't more likely to reveal high level of preference for functional(symbolic) product.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.569-575
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• 2022

This is a research thesis on the development of a monitoring and diagnosis device that prevents the risk of an accident through monitoring and diagnosis of a modular Main Circuit Breaker (MCB) using Vacuum Interrupter (VI) for Korean high-speed rolling stock. In this paper, a comprehensive MCB monitoring and diagnosis was performed by converging vacuum level diagnosis of interrupter, operating coil monitoring of MCB and environmental temperature/humidity monitoring of modular box. In addition, to develop an algorithm that is expected to have a similar data processing before the actual field test of the MCB monitoring and diagnosis device in 2023, the cluster analysis and factor analysis were performed using the WEKA data mining technique on the big data of Korean railroad transformer, which was previously researched by Tae Hee Evolution with KORAIL.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.7
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• pp.1205-1214
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• 1997

The purpose of this study is to positively investigate if the theory of self-monitoring among various individual trait theories would be a theoretical concept which can explain about the differences of clothing behavior under given social situations among Female university students in Korea. For this purpose, the following research problem were set up; 1. Self-monitoring levels and changing differences of self-image as per situation would be reviewed. 2. Self-monitoring levels and changing differences of clothing selection factors as per situation would be reviewed. The results of this study can be summarized as follows; First, as a result of analyzing the differences of situational self-image pursuits within per situation depending on individuals self-monitoring levels, the differences were found significant by. Namely, the adjectives for situational self-image which corresponded to those who had high self-monitoring than low self.monitoring were "womanly", "refined", "sensual", "lively" and "elegant". Second, as a result of analyzing the differences of priority of clothing selection factors within per situation depending on individuals self-monitoring levels, the differences were found significant by. Those who had high self-monitoring level put a higher priority on fashionability, aesthetics and status.symbol of clothing within per situation, while those who had low self-monitoring thought important for economy or utility within per situation.rtant for economy or utility within per situation.