• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.343-346
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• 2008

To improve the reliability and extend the life for a wind-turbine gearbox, the gearbox needs to be monitored and analysed exactly. This study was conducted to analyze and detect the gearbox conditions when lubricating oil contaminated by wear particles was used. Characteristics of the gearbox failure by wear particles were monitored simultaneously by the on-line measurement sensor of vibration, oil condition and temperature. For the detail vibration analyses, frequency analysis(FFT) was performed. The results of the study were summarized as follows: Vibrational signal was found sensitive to abnormal changes of the gearbox conditions when lubricant was contaminated by wear particles. Also, using frequency analysis for the harmonics of gear mesh frequency(GMF), it is found that the failure of gearbox was caused by the damages of meshing gears. However, temperature and oil condition measuring signals were found not so effective to detect any gearbox failure by oil contamination.

• Tribology and Lubricants
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• v.33 no.4
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• pp.141-147
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• 2017

The vibration data of bearings are very useful for monitoring and determining the condition of the bearings. The defect frequencies of ball bearings have been used for monitoring there condition. However, it is not easy to verify the defect frequencies as the wear progress. Therefore there is a need for an easy method to monitor the damages of bearings in real-time and to observe the variations in vibration characteristics as the wear progress. In this study, a bearing test equipment is constructed to diagnose the damage of bearings. The friction coefficient and vibration data are measured by using a torque sensor and an acceleration sensor, and the correlation between the measured data is analyzed to diagnose the condition of the bearing. We reached the following conclusions from the results. When the ball surface, inner and outer rings of a ball bearing are damaged, the friction coefficient increases to over 0.02 with an adhesion on the surface. Moreover this damage occurs more quickly with an increase in the number of revolutions. In the vibration characteristics, the amplitude of vibration wave appears high with an increase in the friction coefficient. In the high frequency range between 1000 and 2000 Hz, a wide range of frequency components with high amplitude occurs continuously irrespective of the number of revolutions.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.565-569
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• 2009

This paper proposed the safety helmet monitoring system based on USN(Ubiquitous Sensor Networks) to secure the wear of helmet for labor on the construction area. As one of the most significant gear to assure labor's safety, The safety helmet would have the extend of labor's injuries minimized whether one wears or not when an accident takes place. At this point, we have developed and demonstrated the system which is able to check who wear the safety helmet properly for labors, composed of safety helmets with sensor node, router nodes, sink node and management program. Moreover, we could show optimized parameters for the proposed USN system as doing experiment and demonstration, we expected that this system would make for labor wear the safety helmet properly on the construction area as well as prevent economic injury caused by an accident with not wearing for labors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.256-258
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• 2016

Domestic vehicle demand is growing steadily. In proportion to the increased interest generated by the automobile-related accidents are more frequent. One of the causes of these accidents are caused by vehicle accidents exists tire problems. Users check tire wear with their naked eyes or check the tread and the wear indicator by using a coin. However, such visual judgment cannot be precise and make it possible to identify the time for tire replacement. Therefore, by utilizing visual and objective data rather than incorrect decisions through objective data, we designed a system that accurately and can easily tell whether the tire condition and replacement of the driver.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.142-151
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• 1993

An intelligent mulitiple monitoring system to monitor tool/machining states synthetically was proposed and developed. It consists of 2 fundamental subsystems : the multiple sensor detection unit and the intellignet integrated diagnosis unit. Three signals, that is, spindle motor current, Z-axis motor current, and machining sound were adopted to detect tool/machining states more reliably. Based on the multiple sensor information, the diagnosis unit judges either tool breakage or degree of tool wear state using fuzzy reasoning. Tool breakage is diagnosed by the level of spindle/z-axis motor current. Tool wear is diagnosed by both the result of fuzzy pattern recognition for motor currents and the result of pattern matching for machining sound. Fuzzy c-means algorithm was used for fuzzy pattern recognition. Experiments carried out for drill operation in the machining center have shown that the developed system monitors abnormal drill/states drilling very reliably.

• Journal of the Korean Society for Precision Engineering
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• v.7 no.2
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• pp.47-57
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• 1990

In-process recognition of the cutting states is one of the very important technologies to increase the reliability of mordern machining process. In this study, practical methods which use the dynamic component of the cutting force are proposed to recognize cutting states (i.e. chip formation, tool wear, surface roughness) in turning process. The signal processing method developed in this study is efficient to measure the maximum amplitude of the dynamic component of cutting force which is closely related to the chip breaking (cut-off frequency : 80-500 Hz) and the approximately natural frequency of cutting tool (5, 000-8, 000 Hz). It can be clarified that the monitoring of the maximum apmlitude in the dynamic component of the cutting force enables the state of chip formation which chips can be easily hancled and the inferiority state of the machined surface to be recognized. The microcomputer in-process tool wear monitor- ing system introduced in this paper can detect the determination of the time to change cutting tool.

• Journal of Sensor Science and Technology
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• v.25 no.4
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• pp.257-263
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• 2016

Among several technologies related to human brain, Brain Computer Interface (BCI) system is one of the most notable technologies recently. Conventional BCI for direct communication between human brain and machine are discomfort because normally electroencephalograghy(EEG) signal is measured by using multichannel EEG sensor. In this study, we propose 2-channel EEG sensor-based application control system which is more convenience and low complexity to wear to get EEG signal. EEG sensor module and system algorithm used in this study are developed and designed and one of the BCI methods, Motor Imagery (MI) is implemented in the system. Experiments are consisted of accuracy measurement of MI classification and driving control test. The results show that our simple wearable system has comparable performance with studies using multi-channel EEG sensor-based system, even better performance than other studies.

• International Journal of Human Ecology
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• v.13 no.2
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• pp.87-100
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• 2012

Smart wear integrates computing technology into fabric or a garment for additional functionality. This research explored the attitudes and opinions of the use of smart wear from the viewpoint of caregivers. Thirty two individuals including care providers of children and adult family members with health problems participated in focus group interviews. Participants reported being interested in smart wear because of the potential to detect the location (GPS) of a dependent (e.g., child, elderly) and to monitor vital signs. Participants indicated perceived advantages of smart wear such as identifying geographical location and effectiveness. Perceived concerns mentioned were privacy/security issues and accuracy of data. Participants taking care of dependents without a specific disease were hesitant to adopt and pay for smart wear. However, caregivers of elderly individuals expressed positive adoption intentions and willingness to reasonably pay for smart wear. They indicated expectations that potential insurance would provide coverage for cost savings. Caregivers expressed the need of specific requirements for future adoption such as customizability, and comfort/safety. Specific to smart wear clothing, most respondents preferred it be an undershirt or a jacket with a sensor located in the shoulder area. The findings from this study can be used in product development, promotion and marketing of smart wear.

• Fashion & Textile Research Journal
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• v.23 no.1
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• pp.98-105
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• 2021

This study investigates and analyzes user preferences for golf wear with a sense of wear and smart function for the development of smart golf wear based on user convenience. A survey was conducted on 124 males in the age range of 40-60s that consisted of professional golfers, amateur golfers and the public with golf experience (such as major golf consumers) from August 1 to August 30, 2019 (IRB NO. 1040198-190617-HR-057-03); consequently, a 117 copies were accepted for analysis. The findings are as follows. The elbow (4.3%) of golf wear is unsatisfactory. The important part of the golf swing motion is the shoulder (39.3)>, elbow (30.8%)>, and wrist (6.8%). In addition, the unsatisfactory wearing of golf wear due to golf swing movements indicated that the shoulder or elbow area was pulled or the bottom of the top was raised during the back swing movements. The survey results on the expected discomfort when wearing smart wear are 'discomfort of obstruction when wearing' (53.8%), 'discomfort of washing' (17.1%), and 'weight of attached machine' (13.7%). Opinions such as 'Will not feel good when the sensor is attached' were investigated. The examination of the preference for golf wear equipped with smart functions indicated that a posture correction function to correct the golf swing posture is the most desired quality that is also considered important when correcting posture.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.101-104
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• 1995

A acoustic emission (AE) sensor has been used to monitor tool were during milling process. The relation between tool wear and AE RMS (Root mean Square) signal was investigated experimentally. A avaliable monitoring index for monitoring toolwear was newly extracted form AE RMS. And on-line monitoring program was developed. The proposed monitoring system has verified experimentally by roughing end milling titanium alloy with TIN coated HSS tool.