• Nuclear Engineering and Technology
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• v.47 no.2
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• pp.165-175
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• 2015

The application of neutron noise analysis (NNA) to the ex-core neutron detector signal for monitoring the vibration characteristics of a reactor core support barrel (CSB) was investigated. Ex-core flux data were generated by using a nonanalog Monte Carlo neutron transport method in a simulated CSB model where the implicit capture and Russian roulette technique were utilized. First and third order beam and shell modes of CSB vibration were modeled based on parallel processing simulation. A NNA module was developed to analyze the ex-core flux data based on its time variation, normalized power spectral density, normalized cross-power spectral density, coherence, and phase differences. The data were then analyzed with a fuzzy logic module to determine the vibration characteristics. The ex-core neutron signal fluctuation was directly proportional to the CSB's vibration observed at 8Hz and15Hzin the beam mode vibration, and at 8Hz in the shell mode vibration. The coherence result between flux pairs was unity at the vibration peak frequencies. A distinct pattern of phase differences was observed for each of the vibration models. The developed fuzzy logic module demonstrated successful recognition of the vibration frequencies, modes, orders, directions, and phase differences within 0.4 ms for the beam and shell mode vibrations.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.179-184
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• 2002

In this study, we developed a portable device which can monitor and analyze vibration signals from machines. This system consists a PDA loading the program for vibration analysis and A/D board for vibration acquisition. A PDA is smaller than the palm of the hand, but it has a powerful computing ability as much as an IBM compatible PC with a Pentium 100MHz CPU. The A/D board developed in this study supports LAN interface using TCP/IP communication protocol. The application program for vibration analysis includes signal processing module, fault diagnosis module, data store module, and plot display module. MS visual embedded C＋＋ 3.0 was used to developed the program.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.261-263
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• 2006

Nowadays, technologies such as RFID, sensor network makes our life comfortable more and more. In this paper we propose a wearable computing system for blind and deaf person who can be easily out of sight from our technology. We are making a wearable computing system that is consisted of embedded board to processing data, ultrasonic sensors to get distance data and motors that make vibration as a signal to see the screen for a deaf person. This system offers environmental informations by text and voice. For example, distance data from a obstacle to a person are calculated by data compounding module using sensed ultrasonic reflection time. This data is converted to text or voice by main processing module, and are serviced to a handicapped person. Furthermore we will extend this system using a voice recognition module and text to voice convertor module to help communication among the blind and deaf persons.

• Plant Journal
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• v.17 no.4
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• pp.53-60
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• 2021

The purpose of this study was to develop a portable vibration analyzer that is effective for acquiring and analyzing vibration data of rotating equipment of a power plant and a domestic vibration monitoring system manufacturer Nada Co., Ltd. The hardware of the developed portable vibration analyzer minimizes measurement errors by calibrating the measured values obtained through measurement uncertainty for calibration of the measuring devices in the system, and is composed of a signal processing device with high resolution through high speed data processing. The software structure implements a variety of vibration plots to execute a detailed analysis program, and applies algorithms to measure and remove noise caused by disturbances while operating a rotating machine. The developed product contributed greatly to increase the user's mobility and performance, as well as to reduce the purchase cost due to localization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1478-1485
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• 2007

In this paper, a meteorological system including a wind speed & direction module and the DSP(Digital Signal Processor) sensor interface circuit board are proposed. This DSP system accepts and process the informations from a wind speed & direction module, the atmospheric pressure sensor, the ambient air temperature sensor and transfers it to the PC monitoring system. Especially, a wind speed & direction module and a DSP hardware are directly designed and applied. A wind speed & direction module have a construction that it have four film type RID(Resistive Temperature Detectors) resistive sensor adhered around the circular metal body heated constantly by heating coil for obtaining vector informations about wind. By this structure, the module is enabled precise measurement having a robustness about vibration, humidity, corrosion. A sensor signal processing circuit is using TMS320F2812 TI(Texas Instrument) Corporation high speed DSP. An economical meteorological system could be constructed through the data from wind speed & direction module and by the fast processing of DSP interface circuit board.

• Journal of KSNVE
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• v.6 no.2
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• pp.205-214
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• 1996

Active noise control(ANC) requires the full capability of a modern digital signal processing module. This paper describes the digital signal processing unit which is designed for ANC of noise fields in passenger car. System hardware is designed to allow software controlled versatility as well as fully qutomatic operation. The developed system is provided with the ability to be self-operated except the case of upload/download of data and program between the personal computer and the system memory. Experimental results are presented to demonstrate ANC performance of noise fields in lightly damped enclosure and passenger car.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.183-189
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• 2021

In recent years, active research has been devoted toward developing a monitoring system using ambient vibration data in order to quantitatively determine the deterioration occurring in a structure over a long period of time. This study developed a low-cost edge computing system that detects the abnormalities in structures by utilizing the dynamic characteristics acquired from the structure over the long term for ensemble learning. The system hardware consists of the Raspberry Pi, an accelerometer, an inclinometer, a GPS RTK module, and a LoRa communication module. The structural abnormality detection afforded by the ensemble learning using dynamic characteristics is verified using a laboratory-scale structure model vibration experiment. A real-time distributed processing algorithm with dynamic feature extraction based on the experiment is installed on the Raspberry Pi. Based on the stable operation of installed systems at the Community Service Center, Pohang-si, Korea, the validity of the developed system was verified on-site.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.10
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• pp.728-737
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• 2019

In this study, the minimized on-board computer (OBC) module for integrated navigation is developed, which provides satellites' relative position information in formation flying and cluster operation situations. The scalability is considered to apply the user-selected wireless communication module and Global Positioning System (GPS) receiver for navigation, while considering to meet the structural design standard of nano-satellites. As a result of the product development and production, the processing speed of integrated navigation and real-time data synchronization is satisfied for cluster operation nano-satellites by using micro controller unit (MCU). From a heat/vacuum, vibration and radiation test, the OBC was confirmed to be operated in space environments. From these results, a mass production system of OBC was made which is a key part of development on satellite formation flying and cluster/constellation missions that the community demands are increasing.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.1-8
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• 2023

If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.

• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.401-406
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• 2007

This study discusses the development of a u-Health care system that can detect quickly and cope actively with emergent situations of chronic disease patients who lead everyday life. If a patient's emergent situation is detected by personal health care host(PHCH), which is composed of acceleration and vibration sensors, GPS, and CDMA communication module, a text message on the patient's current location is transmitted to the hospital and the guardian's mobile terminal so that they can cope with the situation immediately. Especially, the system analyzes data from sensors by using neural network and determines emergent situations such as syncope and convulsion promptly. The exact location of patients can also be found in the electronic map by using GPS information. The experiments show that this system is very effective to find emergencies promptly for chronic disease patients who cannot take care of themselves and it is expected to save many lives.