• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.6
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• pp.560-565
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• 2005

This paper deals with the development of manually operated die used for the manufacture of octagonal boxes into two sets of automated die. In particular, theoctagonal boxes are used fur the switch boxes intended fur the cable conduit of buildings or f3r wiring connection. Manufacturing these boxes requires forming the materials using the primary press before they undergo 2nd through 6th processing by the press machine including the four sides of the octagonal outlet box and bending. Such complicated process hikes up labor cost, slows down production, and results in defect rate of $10\%$ or higher; hence the overall rise in manufacturing cost. Moreover, workers avoid this type of work due to the roar and vibration coming from the press and the risk of accident. To eliminate such phenomenon, a CAM die made by integrating five sets of die into one set of die and an automatic conveyor system were developed. As a result, unmanned work was realized with only two units of press and two sets of die; thus solving the problem of work being avoided and saving on manufacturing cost.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.5
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• pp.872-882
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• 2017

There are no specific guidelines on how to control the heat input for the heat generating smart base layer. This study investigated the mode of actuating heat pad attached to the base layer by performing a human wear test in a cold environment. Subjects participating in the test wore T-shirts, jumper and pants on the base layer with heating pads. Skin temperature, total time of heating and the number of switching for the heating mode were observed as the subject controlled the heating mode voluntarily. The comfortable range of skin temperature on the abdomen was larger than on the lower back. The subject felt hot and turned off the switch when the mean skin temperature of the abdomen was $48.8^{\circ}C$ and the lower back was $40.1^{\circ}C$. The total heating time and the number of actuating switching were larger for women than men. The voluntary action of heating for men with high cold sensitivity was significantly different from men with low cold sensitivity. Therefore, it is necessary (depending on gender and cold sensitivity) to set the heating mode differently for the automatic heat control of a future smart base layer.

• Journal of the Ergonomics Society of Korea
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• v.34 no.2
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• pp.85-101
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• 2015

Objective: The purpose of this study was to develop and evaluate smart secondary controls using iPad for the drivers with physical disabilities in the driving simulator. Background: The physically disabled drivers face problems in the operation of secondary control devices that accept a control input from a driver for the purpose of operating the subsystems of a motor vehicle. Many of conventional secondary controls consist of small knobs or switches that physically disabled drivers have difficulties in grasping, pulling or twisting. Therefore, their use while driving might increase distraction and workload because of longer operation time. Method: We examined the operation time of conventional and smart secondary controls, such as hazard warning, turn signal, window, windshield wiper, headlights, automatic transmission and horn. The hardware of smart secondary control system was composed of iPad, wireless router, digital input/output module and relay switch. We used the STISim Drive3 software for driving test, customized Labview and Xcode programs for interface control of smart secondary system. Nine subjects were involved in the study for measuring operation time of secondary controls. Results: When the driver was in the stationary condition, the average operation time of smart secondary devices decreased 32.5% in the normal subjects (p <0.01), 47.4% in the subjects with left hemiplegic disabilities (p <0.01) and 38.8% in the subjects with right hemiplegic disabilities (p <0.01) compared with conventional secondary devices. When the driver was driving for the test in the simulator, the average operation time of smart secondary devices decreased 36.1% in the normal subjects (p <0.01), 41.7% in the subjects with left hemiplegic disabilities (p <0.01) and 34.1% in the subjects with right hemiplegic disabilities (p <0.01) compared with conventional secondary devices. Conclusion: The smart secondary devices using iPad for people with hemiplegic disabilities showed significant reduction of operation time compared with conventional secondary controls. Application: This study can be used to design secondary controls for adaptive vehicles and to improve the quality of life of the people with disabilities.

• Journal of Biosystems Engineering
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• v.31 no.5 s.118
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• pp.436-442
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• 2006

This research was conducted to design and develop a wired monitoring system for judging if sick or dead layers (SDL) exist in multi-tier layers battery (MLB) by machine vision, and to analyze its performance. In this study, 20 Brown Leghorn (Hi-Brown) layers aged 37 weeks old, were used as the experimental animals. The intensity of concern paid by layers on feed was over 90% during 5 minutes and 30 seconds after providing feed, and normal layers (NL) had been standing to take feed for that period. Therefore, in this study, the optimal judging time was set by this test result. The wired monitoring system developed was consisted of a driving device for carrying machine vision systems, a control program, a RS232 to RS485 convertor, an automatic positioning system, and an image capture system. An image processing algorithm was developed to find SDL in MLB by the processes of binary processing, erosion, expansion, labeling, and reckoning central coordinate of the captured images. The optimal velocity for driving unit was set up as 0.13 m/s by the test results for wired monitoring system, and the proximity switch was controlled not to be operated for 1.0 second after first image captured. The wired monitoring system developed was tested to evaluate the remote monitoring performance at lab-scale laying hen house. Results showed that its judgement success.ate on normal cage (without SDL) was 87% and that on abnormal cage (with SDL) was 90%, respectively. Therefore, it would be concluded that the wired monitoring system developed in this study was well suited to the purpose of this study.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.423-431
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• 2022

The UPS(Uninterruptible Power Supply) system operates in the battery charging mode when the grid is normal, and in the UPS mode, which is the battery discharge mode when a grid error occurs. Since the UPS must supply the same voltage as the grid to the load within 4 [ms] in case of a grid error, the switching time and power recovery time should be short when controlling the output voltage and current of the UPS, and the power failure detection time is also important. The power outage detection algorithm using DFT(Discrete Fourier Transform) proposed in this paper compares the grid voltage waveform with the voltage waveform including the 9th harmonic generated through DFT using Schmitt trigger to detect power outage faster than the existing power outage monitoring algorithm. There are advantages. Therefore, it is possible to supply instant and stable power when switching modes in the UPS system. The multi-power-applied UPS system proposed in this paper uses DFT, which is faster than the conventional blackout monitoring algorithm in detecting power failure, to provide stable power to the load in a shorter time than the existing power outage monitoring algorithm when a system error occurs. The detection method was applied. The changeover time of mode switching was set to less than 4 [ms], which is 1/4 of the system cycle, in accordance with KSC 4310 regulation, which was established by the Industrial Standards Council on the regulation of uninterruptible power supply. A 10 [kW] UPS system in which commercial voltage, vehicle generator, and auxiliary diesel generator can be connected to each of the proposed transfer devices was constructed and the feasibility was verified by conducting an experiment.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.191-201
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• 2011

Soybean has widely grown for its edible bean which has numerous uses. Microwave remote sensing has a great potential over the conventional remote sensing with the visible and infrared spectra due to its all-weather day-and-night imaging capabilities. In this investigation, a ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the crop conditions of a soybean field. Polarimetric backscatter data at L, C, and X-bands were acquired every 10 minutes on the microwave observations at various soybean stages. The polarimetric scatterometer consists of a vector network analyzer, a microwave switch, radio frequency cables, power unit and a personal computer. The polarimetric scatterometer components were installed inside an air-conditioned shelter to maintain constant temperature and humidity during the data acquisition period. The backscattering coefficients were calculated from the measured data at incidence angle $40^{\circ}$ and full polarization (HH, VV, HV, VH) by applying the radar equation. The soybean growth data such as leaf area index (LAI), plant height, fresh and dry weight, vegetation water content and pod weight were measured periodically throughout the growth season. We measured the temporal variations of backscattering coefficients of the soybean crop at L, C, and X-bands during a soybean growth period. In the three bands, VV-polarized backscattering coefficients were higher than HH-polarized backscattering coefficients until mid-June, and thereafter HH-polarized backscattering coefficients were higher than VV-, HV-polarized back scattering coefficients. However, the cross-over stage (HH > VV) was different for each frequency: DOY 200 for L-band and DOY 210 for both C and X-bands. The temporal trend of the backscattering coefficients for all bands agreed with the soybean growth data such as LAI, dry weight and plant height; i.e., increased until about DOY 271 and decreased afterward. We plotted the relationship between the backscattering coefficients with three bands and soybean growth parameters. The growth parameters were highly correlated with HH-polarization at L-band (over r=0.92).

• Journal of the Korean Institute of Gas
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• v.21 no.5
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• pp.83-88
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• 2017

The purpose of this paper is to study for a failure examples producing in electronic control air conditioner in vehicle. The first example, it looked for the repetitive fuse cutting phenomenon that the diode using for a surge voltage prevention of inner A/C relay damaged because of no absorbing the surge voltage by short of diode when the A/C is off. The second example, it knew the icing phenomenon of evaporator that the A/C ECU didn't control the A/C because of inner cutting of fin thermo sensor. The third example, it verified the operation trouble phenomenon because of the A/C switch and for sensor burned in flames by short phenom enon when the sheath of the cable has peeled off. Therefore, the driver have to manage the optimism system of a car by thoroughgoing inspection and improvement the failure phenomenon.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.1
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• pp.25-32
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• 2019

K-BEMS System was introduced to reduce peak load and to save total energy of the 200 buildings that KEPCO headquarter and branch offices use. And K-BEMS system is composed of PV, battery, and hybrid PCS. KEPCO research institute has carried out this K-BEMS research project for 3 years since January 2016. In this paper, the results of the project are shown. 9 modes of test results of K-BEMS system and are operational problems were analyzed. And measures to cure the trouble are also suggested. Batteries are operated more than 20% of SOC, and less than 20% of SOC battery protection switches are automatically shutting down the system and the system no longer respond to EMS, ending the supply of PV, and so therefore to continue the PV power supply it was turn out to be necessary that the EMS should automatically change its policy to change PV only supply mode automatically when the Battery Switch automatically operated. To operate the system continuously and automatically, it is necessary to modify the minimum operational SOC value, and in addition to that the EMS computer must remember the last shut-down SOC and Voltage which interrupted the system and add some margin to reflect the measurement error in the system.