• Journal of Engineering Education Research
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• v.13 no.5
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• pp.36-40
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• 2010

The vehicle oriented block box system based on the u-healthcare and the human-free guard functions is developed in this paper. We also suggested the design philosophies, ideas, and analyzed the performance of the suggested system. The developed vehicle oriented black box system has some characteristics such as; 1) detects the dangerous situation by ultrasonic sensor in advance, and stores the situation information of the neighborhood of the vehicle to the imbedded SD memory card if the dangerous situation may be occurred in the parked vehicle; 2) detects the present location and speed information of the vehicle by GPS receiver and 3-axes acceleration sensor, and stores the information to the SD memory card periodically if the vehicle is running; 3) measures the dioxide carbon in the vehicle inside using $CO_2$ sensor, and forces the ventilation motor of the vehicle to operate and maintains the driver's health if the measured level is more than standard health requirements; 4) provides the stored vehicle's operating information to the driver by GUI (Graphical User Interface) based touch LCD monitor.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2195-2196
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• 2006

This study is for implementation of PC based Motor fault diagnosis system. By using harmonics and current signals of the motor, this system diagnoses the motor condition by accumulated harmonic contribution rate. In this proposed system that was composed of 5 parts. A sensor, connection box, evaluation board, device server, and main computer are those. There were two types of sensor, one was harmonic sensor the other was current sensors. The signal was acquired by sensor, and transferred to evaluation board. Second one is connection box. Because the output type of sensor and input type of evaluation board is different, connection box was necessary. Third one was evaluation board. The signal from the sensor was converted to digital signal in evaluation board. And this signal was transferred to device server. Fourth one was device server. Device server transferred the data from evaluation board to main computer. And the last one was other parts controlled by main computer. In main computer, there were communication and diagnosis algorithms. The result was derived by main computer. In the result, there were 12 categories and 5 levels of motor conditions. The proposed system had some advantages comparing with stand alone type commercial motor fault diagnosis system. The first, by using remote access it was easier to get the conditions of motor. The second, there was no need to handle the sensors when users measured the motor signals. By this property, no one was necessary at motor location site. The third, this system was less restricted by times and places than commercial stand alone type diagnosis system. Therefore users can operate this system only using the main computer. Once the sensors are installed at the motor, users doesn't need to move to check up the condition of motors. Moreover, if there is ethernet hub, many motors can be not only diagnosed at once but also decreased its cost.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.563-564
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• 2006

This study is for implementation of PC based Motor fault diagnosis system. By using harmonics and current signals of the motor, this system diagnoses the motor condition by accumulated harmonic contribution rate. In this proposed system that was composed of 5 parts. A sensor, connection box, evaluation board, device server, and main computer are those. There were two types of sensor, one was harmonic sensor the other was current sensors. The signal was acquired by sensor, and transferred to evaluation board. Second one is connection box. Because the output type of sensor and input type of evaluation board is different, connection box was necessary. Third one was evaluation board. The signal from the sensor was converted to digital signal in evaluation board. And this signal was transferred to device server Fourth one was device solver. Device server transferred the data from evaluation board to main computer. And the last one was other parts controlled by main computer. In main computer, there were communication and diagnosis algorithms. The result was derived by main computer. In the result, there were 12 categories and 5 levels of motor conditions. The proposed system had some advantages comparing with stand alone type commercial motor fault diagnosis system. The first, by using remote access it was easier to get the conditions of motor. The second, there was no need to handle the sensors when users measured the motor signals. By this Property, no one was necessary at motor location site. The third, this system was less restricted by times and places than commercial stand alone type diagnosis system. Therefore users can operate this system only using the main computer. Once the sensors are installed at the motor, users doesn't need to move to check up the condition of motors. Moreover, if there is ethernet hub, many motors can be not only diagnosed at once but also decreased its cost.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1229-1230
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• 2006

This study is for implementation of PC based Motor fault diagnosis system. By using harmonics and current signals of the motor, this system diagnoses the motor condition by accumulated harmonic contribution rate. In this proposed system that was composed of 5 parts. A sensor, connection box, evaluation board, device server, and main computer are those. There were two types of sensor, one was harmonic sensor the other was current sensors. The signal was acquired by sensor, and transferred to evaluation board. Second one is connection box. Because the output type of sensor and input type of evaluation board is different, connection box was necessary. Third one was evaluation board. The signal from the sensor was converted to digital signal in evaluation board. And this signal was transferred to device server. Fourth one was device server. Device server transferred the data from evaluation board to main computer. And the last one was other parts controlled by main computer in main computer, there were communication and diagnosis algorithms. The result was derived by main computer. In the result, there were 12 categories and 5 levels of motor conditions. The proposed system had some advantages comparing with stand alone type commercial motor fault diagnosis system. The first, by using remote access it was easier to get the conditions of motor. The second, there was no need to handle the sensors when users measured the motor signals. By this property, no one was necessary at motor location site. The third, this system was less restricted by times and places than commercial stand alone type diagnosis system. Therefore users can operate this system only using the main computer. Once the sensors are installed at the motor, users doesn't need to move to check up the condition of motors. Moreover, if there is ethernet hub, many motors can be not only diagnosed at once but also decreased its cost.

• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1689-1690
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• 2006

This study is for implementation of PC based Motor fault diagnosis system. By using harmonics and current signals of the motor, this system diagnoses the motor condition by accumulated harmonic contribution rate. In this proposed system that was composed of 5 parts. A sensor, connection box, evaluation board, device server, and main computer are those. There were two types of sensor, one was harmonic sensor the other was current sensors. The signal was acquired by sensor, and transferred to evaluation board. Second one is connection box. Because the output type of sensor and input type of evaluation board is different, connection box was necessary. Third one was evaluation board. The signal from the sensor was converted to digital signal in evaluation board. And this signal was transferred to device server. Fourth one was device server Device server transferred the data from evaluation board to main computer. And the last one was other parts controlled by main computer. In main computer, there were communication and diagnosis algorithms. The result was derived by main computer. In the result, there were 12 categories and 5 levels of motor conditions. The proposed system had some advantages comparing with stand alone type commercial motor fault diagnosis system. The first, by using remote access it was easier to get the conditions of motor. The second, there was no need to handle the sensors when users measured the motor signals. By this property, no one was necessary at motor location site. The third, this system was less restricted by times and places than commercial stand alone type diagnosis system. Therefore users can operate this system only using the main computer. Once the sensors are installed at the motor, users doesn't need to move to check up the condition of motors. Moreover, if there is ethernet hub, many motors can be not only diagnosed at once but also decreased its cost.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.171-182
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• 2019

Bicycles are a pollution-free means of transportation. In addition to leisure, the use of bicycles is increasing as alternative eco-friendly transportation. Accordingly, bicycle accidents are also increasing. The purpose of this study is to implement bicycle black box technology to identify situation when a bicycle accident occurs. Currently, bicycle black box products are mainly based on video cameras, and are commercially available by adding various functions mainly on high resolution cameras and are sold at high prices. If a bicycle accident occurs, quantitative data on the accident location at the time of the accident and the state of the bicycle at the time of the accident is required. In this study, IMU sensor used to obtain acceleration and slope, and time and coordinates are obtained. In addition, real-time acceleration and tilt data while is stored in memory card and by using Bluetooth transmit to the smart phone owned by the in real time to prevent accidents and to monitor status.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.671-677
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• 2012

A black-box program was implemented in order to monitor abnormal symptoms of human body irregularly occurring during sleep. The system consists of sensor probing body signals, auxiliary devices such as the alarm, lamp, network camera, and signal monitoring computer. Various types of sensors, PPG, ECG, EEG, temperature, respiration sensor, G-sensor, and microphone were used to more exactly identify the causes of abnormal symptoms. If a symptom occurs, the system records the patient's condition to provide information being utilized in the treatment. The sensors are attached on some locations of body being proper to check a specific type of abnormal reaction. Based on the normal range and type of measurement data, criteria of signal levels were set to distinguish abnormal reaction. An abnormal signal being probed, the program starts to operate the lamp, alarm, and network camera at the same time and stores the signal and video data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6214-6220
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• 2015

A track circuit has used stably more than 100 years for detecting train position, but solution of track circuit sort circuit incapacity due to a rust is necessary for side line in station yard, coast line and level crossing for conventional line in rural line. Domestically, Axle Counter System(ACS) has partially used for Hot Box System for high speed line and turnout for CBTC system. In contrast, most of countries has used ACS not only trunk line but also rural line and its application has increased for metro, electric car and industrial railway. In this paper, we has verified the operating status of ACS which installed with existing track circuit through log analsis to implement pilot application in mail track and turnout in station yard. And interface test with interlocking system has conducted at Obong shunting yard, as well as Cheongju station and has analyzed test result. Based on a test result, we made fail safe design, manufacturing skill and established system requirement specification for the smooth operation and maintenance.

• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.283-292
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• 2020

Current sensors that use a Hall element and Hall IC to measure the magnetic fields generated in steel silicon core gaps do not distinguish between direct and alternating currents. Thus, they are primarily used to measure direct current (DC) in industrial equipment. Although such sensors can measure the DC when installed in expensive equipment, ascertaining problems becomes difficult if the equipment is set up in an unexposed space. The control box is only opened during scheduled maintenance or when anomalies occur. Therefore, in this paper, a method is proposed for facilitating the safety management and maintenance of equipment when necessary, instead of waiting for anomalies or scheduled maintenance. A Bluetooth 4.0 low-energy current-sensor system based on near-field communication is used, which compensates for the nonlinearity of the current-sensor output signal using a piecewise linear model. The sensor is controlled using its generic attribute profile. Sensor nodes and cell phones used to check the signals obtained from the sensor at 50-A input currents showed an accuracy of ±1%, exhibiting linearity in all communications within the range of 0 to 50 A, with a stable output voltage for each communication segment.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.85-94
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• 2021

The LPR system's trigger sensor makes problem occasionally due to the heave weight of vehicle or the obsolescence equipment. If we replace the hardware sensor to the deep-learning based software sensor in order to generate the trigger signal, LPR system maintenance would be a lot easier. In this paper we proposed the deep-learning sliding window based object detection and tracking algorithm for the LPR system's trigger signal generation. The gate passing vehicle's license plate recognition results are combined into the normal tracking algorithm to catch the position of the vehicle on the trigger line. The experimental results show that the deep learning sliding window based trigger signal generating performance was 100% for the gate passing vehicles including the 5.5% trigger signal position errors due to the minimum bounding box location errors in the vehicle detection process.