• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1991.04a
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• pp.95-98
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• 1991

회전 기기의 이상으로 인하여 발생하는 진동은 축 회전속도의 고주파 성분 (super-harmonic)이나 또는 분수조파 성분(sub-harmonic)으로 나타나는 경 우가 대부분이기 때문에 회전기기의 진동을 주파수 영역에서 해석함에 있어 파워 스펙트럼의 주파수 축을 Hz로 나타내기보다는 축 회전속도의 order로 써 나타내는 것이 매우 유용하다. 스펙트럼을 order로써 나타내기 위해서는 샘플링 시간을 축 회전속도와 동기(synchronization)시켜야 하는데 이 방법으 로는 회전축에 엔코더(encorder)를 부착하여 엔코더에서 발생하는 펄스 신호 를 이용하여 샘플링하는 방법과 order tracking 필터를 이용하는 방법이 있 다. 그러나 전자의 방법은 원하는 회전축마다 엔코더를 부착하여야 하며 경 우에 따라서는 엔코더를 부착하기가 어려운 경우도 있으며, 회전기기의 운전 개시나 종료시처럼 회전속도가 급격히 변화하는 경우에는 낮은 주파수에서 중첩(aliasig)에 의한 오차가 수반될 수도 있다. 후자의 방법은 order tracking 필터 이외에도 여러 부수장비가 필요하며 기준 주파수(즉 회전속 도)가 급격히 변화하는 경우 PLL(phase locked loop)에서 tracking 오차가 발생된다. 최근에 발표된 논문에서 일정한 시간간격으로 샘플링한 데이터들 로부터 신호를 재합성하여 회전축의 속도와 동기가 되도록 재 샘플링함으로 서 스펙트럼의 주파수를 회전속도의 order로써 나타내는 방법을 제시하였다. 그러나 위 논문에서는 신호의 재합성에 필요한 재합성 필터(reconstruction filter)의 설계 방법에 대하여 구체적인 언급이 없이 다만 결과만을 논하였다. 따라서 본 논문에서는 재합성 필터의 설계 방법에 대하여 구체적인 방법을 제시하고 또한 동기화 샘플링의 장점 및 고려 사항에 대하여 고찰하였다. 고려한 능동 소음제어 에 대해 연구하였다. 경량화 추세에 따라 지반이나 케이싱이 경량이거나 유연하여 회전축과 동적으로 연성된 경우 회전축-베어링-지반으로 이루어진 2중구조의 회전축 계 동특성을 해석할 수 있는 프로그램을 개발하므로서 회전 기계류의 진동 전반에 걸친 문제점에 대한 그 원인과 현상을 명확히 분석하여 국내의 전기 계류의 보다 신뢰성있는 설계 및 제작자료를 확보하는데 기여할 수 있게 하 였다.존의 small molecular Gd-chelate에 비해 매우 큼을 알 수 있었다. MnPC는 간세포에 흡수된 후 담도계로 배출되는 간특이성 조영제임을 확인하였다. 장비 내에서 반복 시행한 평균값의 차이는 대체적으로 유의한 차이가 없었으나, 다른 장비에서 반복 시행한 장비간의 사이에는 유의한 차이가 있는 경우가 더 많았다. 따라서 , MRS 검사를 소뇌나 뇌교의 어떤 절환에 적용하기 전에 각 장비 마다 정상 기준치를 반드시 얻은 후에 이상여부를 판 정하는 것이 필수적이라고 생각된다.EX> 이상이 적절한 진단기준으로 생각되었다. $0.4{\;}\textrm{cm}^3$ 이상의 좌우 부피차를 보이는 모든 증례에서 육안적으로도 해마위축이 뚜렷이 나타났다. 결론 : MR영상을 이용한 해마의 부피측정은 해마경화증 환자의 진단에 있어 육안적인 MR 진단이 어려운 제한된 경우에만 실제적 도움을 줄 수 있는 보조적인 방법으로 생각된다.ofile whereas relaxivity at high field is not affected by τS. On the other hand, the change in τV does not affect low field profile but strongly in fluences on both inflection fie이 and the maximum relaxivity value. The re

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.425-428
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• 2008

To overcome the limitation of tracking speed on signal-shaded area and the discontinuity of GPS, we present a system which estimates the speed of moving object using GPS and accelerometer. This system is designed to correct accelerometer's noises which are caused by vibration and impact to the object and errors of itself, from the navigation information of GPS receiver and accelerometer which are installed to moving object. And using this information, it estimates the speed of moving object on GPS signal-shaded area to complement discontinuity of GPS navigation information. We designed Kalman Filter structure using GPS and accelerometer to apply this system, and verify that the system can estimate object's speed on GPS signal-shaded area. Finally, we present the possibilities applying to telematics systems like automatic navigation system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.1
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• pp.121-130
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• 2002

Clean stockers are being used by semiconductor and TFT-LCD manufacturers to store and buffer work in process. Since an important function of a stocker is to keep the contained material clean. The only way to keep the stored product clean is to provide constant clean airflow the product and through stocker, The airflow across the product prevent contamination from settling on the product. Up to now, stocker typically have been configured to receive their laminar airflow from fan filter units that are located on the side of the stocker This type of stocker may have such problems as complexity of structure, increment of temperature, mechanical vibration, initial investment and running cost. In this study, In order to solve the above mentioned problems, new air control system in stocker is proposed, which is to control open ratios of exits that are located on the side of the stocker without fan filter units. Open ratios of exits need to be optimized for the same quantities of airflow in each exit. In this study, static pressure regain was used for the analysis of the open ratios of exits theoretically and Blue Ridge Numerics FEM software, CFDesign, was used fur simulating airflow in stocker. As a result, Open ratios of exits important to provide constant clean airflow can be obtained by the analysis of static pressure regain and was verified by simulation results. Therefore, new air control system in stocker can be used by the semiconductor and TFT-LCD manufacturers.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.1
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• pp.160-165
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• 2014

In this study, an efficiency test was performed by fabricating MEMS (Micro Electro Mechanical Systems) based 3-axis acceleration sensor modules and an earthquake monitoring system was composed. Data acquisition device (NI-9239) with a 24bit ADC (Analog to Digital Converter) was used for improving the performance of 3-axis acceleration sensor modules and filtered data (100Hz Low Pass Filter) was used for reducing noises. Also this paper focused on detecting meaningful vibration in the building by developing the earthquake monitoring software. If vector sum of 3-axis acceleration is greater than the preset value, the value will be recorded and saved to the file.

• Smart Structures and Systems
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• v.20 no.5
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• pp.619-636
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• 2017

Magnetorheological (MR) damper is a type of controllable device widely used in vibration mitigation. This device is highly nonlinear, and exhibits strongly hysteretic behavior that is dependent on both the motion imposed on the device and the strength of the surrounding electromagnetic field. An accurate model for understanding and predicting the nonlinear damping force of the MR damper is crucial for its control applications. The MR damper models are often identified off-line by conducting regression analysis using data collected under constant voltage. In this study, a MR damper model is integrated with a model for the power supply unit (PSU) to consider the dynamic behavior of the PSU, and then a real-time nonlinear model updating technique is proposed to accurately identify this integrated MR damper model with the efficiency that cannot be offered by off-line methods. The unscented Kalman filter is implemented as the updating algorithm on a cyber-physical model updating platform. Using this platform, the experimental study is conducted to identify MR damper models in real-time, under in-service conditions with time-varying current levels. For comparison purposes, both off-line and real-time updating methods are applied in the experimental study. The results demonstrate that all the updated models can provide good identification accuracy, but the error comparison shows the real-time updated models yield smaller relative errors than the off-line updated model. In addition, the real-time state estimates obtained during the model updating can be used as feedback for potential nonlinear control design for MR dampers.

• Geophysics and Geophysical Exploration
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• v.19 no.2
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• pp.84-90
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• 2016

The validation of performance test for newly developed or old-used sensor is very important in the earthquake monitoring and seismology using earthquake data. Especially the frequency response of the sensor is mainly used to correct the earthquake data. The technique of the calculation of phase and amplitude with Hilbert transformation for earthquake data that is filtered with band limited frequency in time domain is applied to calculate the frequency response of the sensor. This technique was tested for the acceleration sensors, CMG-5T of 1g and 2g installed on the vibration table at the laboratory and we could obtain satisfactory result. Tohoku large earthquake in 2011 observed at the station SNU that has accelerometer, ES-T and seismometer, STS-2 operated by KIGAM was also used to test the field data applicability. We could successfully get the low frequency response of broad band sensor, STS-2. The technique by using band limited frequency filter and Hilbert transformation showed the superior frequency response to the frequency spectrum ratio method for noisy part in data.

• Journal of Auto-vehicle Safety Association
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• v.13 no.2
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• pp.35-41
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• 2021

In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.3
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• pp.262-272
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• 2023

A polymer-based mechanical low-pass filter(m-LPF) for high-g accelerometers makes it possible to remove high-frequency transient noises from acceleration signals, thus ensuring repeatable and reliable measurement on high-g acceleration. We establish a prediction model for performance of m-LPF by combining a fundamental vibration model with the fractional derivative standard linear solid(FD SLS) model describing the storage modulus and loss modulus of polymers. Here, the FD SLS model is modified to consider the effect of m-LPF shape factor (i.e., thickness) on storage modulus and loss modulus. The prediction accuracy is verified by comparing the displacement transmissibility(or cut-off frequency) estimated using our model with that measured from 3 kinds of polymers(polysulfide rubber(PSR), silicone rubber(SR), and polydimethylsiloxane(PDMS)). Our findings will contribute a significant growth of m-LPF for high-g accelerometers.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.5
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• pp.422-426
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• 2011

Piezoelectric materials can be used to convert mechanical energy into electrical energy. In this study, we investigated the possibility of harvesting from mechanical vibration force using a high efficient piezoelectric material-polyvinylidene fluoride (PVDF). A piezoelectric energy harvesting system consists of rectifier, filter capacitor, resistance. The experiments were carried out with impacting force to PVDF film with the thickness of 1 ${\mu}m$. The output power was measured with change in the load resistance value from 100 ${\Omega}$ to 2.2 $M{\Omega}$. The highest power was obtained under optimization by selection of suitable resistive load and capacitance. A power of 0.3082 ${\mu}W/mm^2$ was generated at the external vibration force of 5 N (10 Hz) across a 1 $M{\Omega}$ optimal resistor. Also, the maximum power of 0.345 ${\mu}W/mm^2$ was generated at 22 ${\mu}F$ and 1 $M{\Omega}$. The developed system was expected at a solution to overcome the critical problem of making up small size energy harvester.