• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.1
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• pp.33-39
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• 2012

The tool wear and failure in automatic production system directly influences the quality and productivity of a product, thus it is essential to monitor the tool state in real time. For such purpose, an ART2-based remote monitoring system has been developed to predict the appropriate tool change time in accordance with the tool wear, and this study aims to experimently find the relationship between the tool wear and the monitoring signals in cutting processes. Also, the roughness of workpiece according to the wool wear is examined. Here, the tool wear is indirectly monitored by signals from a vibration senor attached to a machining center. and the wear dimension is measured by a microscope at the start, midways and the end of a cutting process. A series of experiments are carried out with various feedrates and spindle speeds, and the results show that the sensor signal properly represents the degree of wear of a tool being used, and the roughnesses measured has direct relation with the tool wear dimension. Thus, it is concluded that the monitoring signals from the vibration sensor can be used as a useful measure for the tool wear monitoring.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.767-774
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• 2011

In recent years, wind turbine system has been considered as the most efficient renewable energy source. Wind turbine system is a complex system which is composed of blade, generator and inverter systems. Recently, lots of researches on fault detection and diagnosis of wind turbine system have been done. Most of them are related with the fault diagnosis of mechanical elements using bivration signal. In this work, a new type of inverter fault detection and diagnstic algorithm is proposed. Furthermore, extensive simulation studies and practical experiments are carried out to verify the proposed algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.5
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• pp.13-18
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• 2015

In this paper, we implemented a polarimetric vibration sensor using a Sagnac birefringence interferometer composed of polarization-maintaining photonic crystal fiber(PM-PCF). By changing the amplitude and frequency of vibration applied to PM-PCF employed as the sensor head of the proposed sensor, sensor responses to various types of vibration were investigated. First, the vibration characteristic of the sensor was explored for a single frequency in a frequency range from 1 to 3000Hz with a cylindrical piezoelectric transducer, and then the sensor response to naturally damped vibration was examined by utilizing a metal cantilever. It was experimentally observed that the sensor output signal was deteriorated by more than 3dB at ~1900Hz in the single frequency vibration measurement with a minimum detectable strain perturbation of ${\sim}1.34n{\varepsilon}/Hz^{1/2}$ at 1500Hz and the peak value of the sensor output signal was proportional to the strength of initially applied stress in the naturally damped vibration measurement.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.57-62
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• 2019

In this paper, oneM2M based data monitoring and acquisition system is designed and implemented to measure and transmit the voltage, current, temperature, acceleration and vibration of the motor. The proposed system can detect electrical faults (overcurrent, reverse phase, phase loss, ground fault) and mechanical faults (MC counter, motor operation time, bearing and winding temperature, motor speed, insulation resistance). The system consists of sensor data collection, web server, php, database, wired/wireless communication system. The insulation resistance and the motor speed were measured, and the experimental results were similar for both the test resistance value and the reference input value.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.6 no.1
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• pp.46-55
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• 1995

Authors devised an objective test for nasal resonatory disorders using a vibratory sensor(Piezoelectric receiver) which is relatively cheap. The vibratory sensor was covered with duralumin to eliminate contamination of acoustic sound except a small hole which is attached on ala nasi during the test. Electrical signals front the vibratory sensor and the microphone while the subject is phonating vowel/a/ and nasal consonant /ng/ and phonating 8 syllable sentence /papa/ passage and /mama/ passage were digitized with n 12 bit A/D converter. For the evaluation of the hypernasality, the ratio of /ng/ to /a/ and /mama/ passage to /papa/ passage were used instead of individual values to reduce the observational error. For the evaluation of the hyponasality, the cul-de-sac resonation was induced by obstructing the nasal aperture of the ipsilateral side with the finger. In the normal control group, the ratio of /ng/ to /a/ and /mama/ passage to /papa/ passage was larger than 8. In the hypernasality with nasal emission group. the ratio was decreased markedly(p＜0.01). When the nasal aperture was obstructed with the finger, the vibratory signals of /a/ and /ng/ were increased markedly in the control group and hypernasality group(p＜0.01). However, in the hyponasality group(severe), the increment was minimal. So this system can be used to detect the nasal resonatory disorders objectively and differentiate the hypernasality front hyponasality easily.

• Elastomers and Composites
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• v.45 no.4
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• pp.291-297
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• 2010

Strut insulator in a vehicle is an important part to prevent noise and vibration which is created for driving on the road. Most of the viscoelastic-mounts are made of rubber and natural rubber is the key ingredient. These rubber products show well performance for the initial time, but they will degrade after they are exposed to a high temperature circumstance and a cyclic load. NVH performance and comfort in a vehicle were decreased by these degradation of the rubber. In this study, spring displacement in a vehicle was measured to make a profile in the simulation test performed with an acceleration sensor. In addition, acceleration level, rubber permanent deformation and hardness of the rubber were measured according to drive distance and vehicle model.

• Journal of Korean Association for Spatial Structures
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• v.18 no.4
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• pp.49-59
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• 2018

Wireless sensors are more favorable in measuring structural response compared to conventional sensors. This is because they are easier to use with no issues with cables and are considerably cheaper. There are several applications that can be used in recording and analyzing data from MEMS sensor installed on an iPhone. The Vibration App is one of the applications used and there has not been adequate research conducted in analyzing the performance of this App. This paper analyzed the performance of the Vibration App by comparing it with the performance of an ICP sensor. Results show that natural frequency results are more accurate (error less than 5%) in comparison to the amplitude results. This means that built- in MEMS sensor in smartphones are good at estimating natural frequency of structures. In addition, it was seen that the results became more accurate at higher frequencies (5.0Hz and 10.0Hz).

• Membrane Journal
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• v.33 no.2
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• pp.53-60
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• 2023

Mechanical energy can be harvested by triboelectric nanogenerators (TENG) from biological and environmental systems. In wearable electronics, TENG has a lot of significance as biomechanical energy can be harvested from the motion of humans, which is applied in vibrational sensors. Wearable TENG is prone to moisture and polytetrafluoroethylene (PTFE) is an excellent hydrophobic material used in these applications. The presence of highly electronegative fluorine atoms leads to very low surface energy. At the same time, the performance of the device increases due to the efficient capture of the electrons on the microporous membrane surface. This similar behavior occurs with polyvinylidene fluoride (PVDF) due to the presence of fluoride atoms, which is relatively less as compared to PTFE.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.82-84
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• 2021

Through the smart factory construction project, sensor data such as power, vibration, pressure, and temperature are collected from production facilities, and services such as predictive maintenance, defect prediction, and abnormality detection are developed through data analysis. In general, in the case of manufacturing data, because the imbalance between normal and abnormal data is extreme, an anomaly detection service is preferred. In this paper, FFT method is used to extract feature data of manufacturing data as a pre-stage of the anomaly detection service development. Using this method, we classified the produced products and confirmed results. In other words, after FFT of the representative pattern for each product, we verified whether product classification was possible or not, by calculating correlation coefficient.

• Journal of IKEEE
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• v.28 no.2
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• pp.180-186
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• 2024

This paper proposes an efficient fault diagnosis method for ITSC(Inter-Turn Short Circuit) in three-phase induction motors using CNN. By utilizing only the D-axis component of the D-Q synchronous coordinate system, it compares SWM(Slide Window Method) and GAF(Gramian Angular Field) methods for image encoding. Results show GAF achieving ~74% accuracy, while SWM achieves ~65%, indicating GAF's superiority by 9%. Learning time (~14.74s) remains consistent, particularly with epochs ≤ 100, showcasing faster learning.