• KEPCO Journal on Electric Power and Energy
• /
• v.6 no.4
• /
• pp.405-411
• /
• 2020

In this paper, we designed the COS MEMS system for sensing the falling detection and explosive noise of fuse link in COS (Cut Out Switch) installing on the power distribution. This system analyzed the failure characteristics and an instantaneous breakdown of power distribution. Therefore, our system strengths the industrial competence and guaranties the stable power supply. In this paper, we applied BLE (Bluetooth Low Energy) technology which is suitable protocol for low data rate, low power consumption and low-cost sensor applications. We experimented with LSM6DSOX which is system-in-module featuring 3 axis digital accelerometer and gyroscope boosting in high-performance mode and enabling always-on low-power features for an optimal motion for the COS fuse holder. Also, we used the MP34DT05-A for gathering an ultra-compact, low power, omnidirectional, digital MEMS microphone built with a capacitive sensing element and an IC interface. The proposed COS MEMS system is developed based on nRF52 SoC (System on Chip), and contained a 3-axis digital accelerometer, a digital microphone, and a SD card. In this paper of experiment steps, we analyzed the performance of COS MEMS system with gathering the accelerometer raw data and the PDM (Pulse Data Modulation) data of MEMS microphone for broadcasting the failure of COS status.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.3
• /
• pp.173-180
• /
• 2016

Fault detection and diagnosis is a task to monitor the occurrence of faults and pinpoint the exact location of faults in the system. Fault detection and diagnosis is gaining importance in development of efficient, advanced and safe industrial systems. Three phase inverter is one of the most common and excessively used power electronic system in industries. A fault diagnosis system is essential for safe and efficient usage of these inverters. This paper presents a fault detection technique and fault classification algorithm. A new feature extraction approach is proposed by using three-phase load current in three-dimensional space and neural network is used to diagnose the fault. Neural network is responsible of pinpointing the fault location. Proposed method and experiment results are presented in detail.

• Proceedings of the KIEE Conference
• /
• 1987.11a
• /
• pp.463-468
• /
• 1987

In this paper, a high impedance fault detection on 22.9kV multigrounded distribution system that has been very difficult by any existing conventional protective relaying systems is studied. Because the fault current is very low, it cannot be distinguished from neutral current caused by load unvalanced on multigrounded distribution system. We developed the new and best algorithms of high impedance ground fault detection. This algorithms are 'the even order power method, even order ratio method', 'and even order ratio varience method'. Using this algorithms, a detection device for high impedance faults is constructed and tested in the laboratory. And continually, it is installed and has been tested in KEPCO substations.

• Journal of Biomedical Engineering Research
• /
• v.29 no.1
• /
• pp.66-72
• /
• 2008

The major risk associated with the use of automated power injectors is the well known complication of contrast material extravasation at the injection site. Automated injection of computed tomography (CT) contrast media can produce the compartment syndrome. The purpose of this study was to assess the ability of this device during clinically important episodes of extravasation. The extravasation detection accessory (EDA) system was composed of a strain gage, an amplifier and a computer based system. A strain gage pliable adhesive patch was applied to the skin aver the intravenous catheter and the catheter was connected to the power injector with a cable to monitor the resolution data. If the programmed monitoring, which was developed with MS Visual C++, at the extravasation occurred, then the injection was interrupted the auto injector. CT was used to demonstrate the clinically important extravasation. This study was a prospective, observational study in which the EDA system was used to monitor the automated mechanical injection of contrast material in 7 dogs. There were two true-positive cases (range of extravasation volumes: $18{\sim}22ml$), twenty three true-negative cases, three false-positive cases and no false-negative cases. The EDA system had a sensitivity of 100% and a specificity of 88% for the detection of clinically important extravasation. The EDA system had good sensitivity for the detection of clinically important extravasation and the EDA system has the clinical potential for the early detection of extravasation of the contrast medium that is administered with power injectors. The EDA system is easy to use safe and accurate for the monitoring extravasation of the intravenous injections, and this system may prove especially useful in CT applications.

• Journal of Advanced Marine Engineering and Technology
• /
• v.36 no.5
• /
• pp.662-673
• /
• 2012

This study introduces a condition diagnosis technique for a turbine governor system. The governor system is an important control system to handle turbine speed in a nuclear power plant. The turbine governor system includes turbine valves and stop valves which have their own functions in the system. Because a turbine governor system is operated by high oil pressure, it is very difficult to maintain under stable operating conditions. Turbine valves supply oil pressure to the governor system for proper operation. Using the pressure variation of turbine and governor valves, operating conditions of the turbine governor control system are detected and identified. To achieve automatic detection of valve status, time-based and frequency-based analysis is employed. In this study, a new approach, wavelet decomposition, was used to extract specific features from the pressure signals of the governor and stop valves. The extracted features, which represent the operating conditions of the turbine governor system, include important information to control and diagnose the valves. After extracting the specific features, decision rules were used to classify the valve conditions. The rules were generated by a decision tree algorithm (a typical simple method for data-based rule generation). The results given by the wavelet-based analysis were compared to detection results using time- and frequency-based approaches. Compared with the several related studies, the wavelet transform-based analysis, the proposed in this study has the advantage of easier application without auxiliary features.

• Journal of the Optical Society of Korea
• /
• v.20 no.5
• /
• pp.557-562
• /
• 2016

In this paper, for the first time, the transmission performances of long-haul 100-Gb/s direct detection optical OFDM (DDO-OFDM) and coherent optical OFDM (CO-OFDM) wavelength division multiplexing (WDM) systems are compared by simulation. It provides specific guides for system parameter selection to get a high-performance and cost-effective OFDM WDM system. Specifically, the comparison involves three aspects: launched power is investigated to achieve better system performance; laser linewidth is numerically investigated to choose cost-effective laser; system dispersion tolerances with different laser linewidths are analyzed to further reveal the advantages and disadvantages of these two detecting methods, direct detection and coherent detection, in long-haul OFDM WDM system.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.4
• /
• pp.197-203
• /
• 2015

Nuclear power plant has increased continuously for power production in all over the world and the interest about nuclear accident and the dismantling of aging nuclear power plant has been a growing. The leaked radioactive source that is generated by radiation accidents must detect and remove to minimized the damage as soon as possible. Gamma-ray detection system that have been developed until now cannot provide the precise position of radioactive sources because they detect and imaging the position of radiation sources in just two dimensions. In this paper, stereo gamma ray detection system has developed and the algorithm for calculation of the distance has implemented to be able to measure the distribution of the leakage gamma ray source for the system. Stereo camera calibration for distance detection was conducted with the correction pattern and LED light and we carried out performance test of the system for the LED light source and a gamma ray source. In both experiments the results of the performance test, it was confirmed to have a 5% error. The results of this paper is used as a material for the development of gamma-ray imaging device.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.12
• /
• pp.4489-4501
• /
• 2014

We propose a novel lane detection method based on classification in image sequences. Both structural and statistical features of the extracted bright shape are applied to the neural network for finding correct lane marks. The features used in this paper are shown to have strong discriminating power to locate correct traffic lanes. The traffic lanes detected in the current frame is also used to estimate the traffic lane if the lane detection fails in the next frame. The proposed method is fast enough to apply for real-time systems; the average processing time is less than 2msec. Also the scheme of the local illumination compensation allows robust lane detection at nighttime. Therefore, this method can be widely used in intelligence transportation systems such as driver assistance, lane change assistance, lane departure warning and autonomous vehicles.

• Journal of Korea Multimedia Society
• /
• v.24 no.7
• /
• pp.860-867
• /
• 2021

Lane detection is important technology for implementing ADAS or autonomous driving. Although edge detection has been typically used for the lane detection however, false detections occur frequently. To improve this problem, a deep learning based lane detection algorithm is proposed in this paper. This algorithm is mounted on an ARM-based embedded system to implement a LDW(lane departure warning). Since the embedded environment lacks computing power, the VGG-11, a lightweight model based on VGG-13, has been proposed. In order to evaluate the performance of the LDW, the test was conducted according to the test scenario of NHTSA.

• Journal of Korea Society of Industrial Information Systems
• /
• v.18 no.5
• /
• pp.45-50
• /
• 2013

Recently, as the market for SMART TV expands, the camera is embedded for providing various user experience. However, this leads to occurrence of camera failure due to TV power up sequence problem, which are usually not detectable in conventional test equipments. Although the failure-detection can be possible by re-generating control signals for audio interface with new equipment, it is expensive and also requires much time to test. In this paper, for SMART TV, FPGA(Field Programmable Gate Array)-based failure-detection system is proposed which can lead to reduction of both cost and time for test.