• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1021-1022
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• 2010

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.2
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• pp.105-111
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• 2010

The purpose of this study was to detect early children with hyperactivity which is one of the symptoms of Attention Deficit-Hyperactivity Disorder (ADHD). This study used two methods: K-CBCL and observation of children's behavior. K-CBCL was done online by parents at home. For observation of children's behavior, the school asked children to wear a 3-axis accelerometer on their wrists. The data from K-CBCL and 3-axis accelerometer were analyzed and clustered to separate hypersensitive children from ordinary children. This experiment confirmed that 3-axis accelerometer which is one of Ubiquitous techniques and the K-CBCL questionnaire were helpful for detection of hypersensitive children.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.271-290
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• 2013

The acceleration information is significant for the structural health monitoring, which is the basic measurement to identify structural dynamic characteristics and structural vibration. The efficiency of the accelerometer is subsequently important for the structural health monitoring. In this paper, the distance measure matrix and the support level matrix are constructed firstly and the synthesized support level and the fusion method are given subsequently. Furthermore, the synthesized support level can be served as the determination for diagnosis on accelerometers, while the consensus data fusion method can be used to recover the acceleration information in frequency domain. The acceleration acquisition measurements from the accelerometers located on the real structure National Aquatics Center are used to be the basic simulation data here. By calculating two groups of accelerometers, the validation and stability of diagnosis and recovering on acceleration based on the data fusion are proofed in the paper.

• 한국IT서비스학회:학술대회논문집
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• 2009.11a
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• pp.453-458
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• 2009

The purpose of this study was to detect early children with hyperactivity which is one of the symptoms of Attention Deficit - Hyperactivity Disorder (:ADHD). For this Purpose, This study used two methods; K-CBCL and observation of children`s behavior. K-CBCL was done online by parents at home. For observation of children's behavior, the school asked children to wear a 3 - axis accelerometer on their wrists. The data from K - CBCL and 3 - axis accelerometer were analyzed and clustered to separate hypersensitive children from ordinary children.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.10
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• pp.699-703
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• 1999

An experimental study to identify the energized status of the 22.9kV underground power cable by the detection of vibration has been performed. We have derived that there exists vibration at double the line frequency in live cables by electromagnetic force. The relative amplitudes of the cable vibration according to the energized status of the cable were calculated by computer simulation. The cable vibration can also be picked up by accelerometer. A prototype was tested on the underground distribution system in Chonan substation, KEPCO. Comparison between simulation results and field test results was performed. The results showed that the energized status of the calble can be identified by measuring the vibration of the cable using accelerometer.

• Journal of Oriental Neuropsychiatry
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• v.31 no.4
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• pp.225-233
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• 2020

Objectives: This study aimed to reveal the gait characteristics of each Sasang constitution by examining the differences in gait analysis indicators using a 3-axis accelerometer. Methods: Ninety-one participants were classified through the TS-QSCD (Two-Step Questionnaire for Sasang Constitution Diagnosis) method and gait analysis was performed using a 3-Axis Accelerometer (G-WALK. BTS Bioengineering, Italy). Gait analysis in returning to the 6-meter turnaround point and 6-minute walking test were performed. The differences in the gait analysis index values were analyzed between each constitution. Results: The gait analysis of 91 subjects (37 Taeumin, 37 Soyangin, and 17 Soeumin), showed that the percent stride length/height in the Soyangin subjects was significantly higher than that of the Taeeumin and Soeuminin subjects in the spatiotemporal walking variables (p<0.05). Stride length also showed the widest tendency in the Soyangin subjects (p=0.05). In the kinesiological analysis, the range of pelvic obliquity angles in the Soeumin subjects was significantly wider than that of the Taeumin and Soyangin subjects (p<0.05). In the six-minute walking test, the Soyangin subjects walked the farthest at 309.41±35.23 m (p=0.064). Conclusions: In a comparison of the gait characteristics for each Sasang constitution using a three-dimensional accelerometer, the stride width of the Soyangin subjects was the widest compared to the Taeeumin, and Soeumin subjects, and Soyangin's walking speed showed a faster tendency than that of the Taeeumin and Soeumin subjects.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.223-233
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• 2017

The railway turnout system is one of the most important systems that set train routes. Turnout system integrity should be guaranteed for robust train operation. To diagnose the turnout system status, LVDT and accelerometers are installed on a turnout system in a high speed line. The LVDT and accelerometers produce signals containing physical meaning of the turnout systems. The LVDT produces the displacement of the rail gauge and vibration when point moving or a train passes on turnout systems and the accelerometer produces impact forces induced by wheel sets. We performed data extraction from the measured signals and parameterized the extracted signals into meaningful quantities. The parameters are used for classifying whether the turnout status is normal. We proposed two methods for the classification, one uses probabilistic distribution and the other artificial neuron networks. The probabilistic distribution is used for the parameter being classified by the quantities and the artificial neuron networks for the form classification. Finally, we show how to learn the normal status of a turnout system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.394-399
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• 2012

In recent years, MEMS sensors show huge attraction in machine condition monitoring, which have advantages in power, size, cost, mobility and flexibility. They can integrate with smart sensors and MEMS sensors are batch product. So the prices are cheap. And the suitability of it for condition monitoring is researched by experimental study. This paper presents a comparative study and performance test of classification of MEMS sensors in target machine fault classification by 3 intelligent classifiers. We attempt to signal validation of MEMS sensor accuracy and reliability and performance comparisons of classifiers are conducted. MEMS accelerometer and MEMS current sensors are employed for experiment test. In addition, a simple feature extraction and cross validation methods were applied to make sure MEMS sensors availabilities. The result of application is good for using fault classification.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.236-241
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• 2010

This paper presents a wear diagnosis method for centrifugal impellers by using an accelerometer. The features are calculated from raw and wavelet transformed signals with several statistical methods applied in time or frequency domains. From the effectiveness coefficient test, it is shown that 7th level of wavelet transformed signal is suitable for wear classification problems. A neural network with 5 feature sets is applied to diagnose the wear magnitude of pump impellers. The verification result reveals that high accuracy for the wear diagnosis of impellers can be obtained by using wavelet features transformed from acceleration signals.

• International Journal of High-Rise Buildings
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• v.6 no.3
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• pp.207-216
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• 2017

Installing accelerometers in a building is an effective way to know how the building shakes when an earthquake happens. In this paper, we will introduce an example of an analysis that captures the acceleration reduction effect of the vibration damping device using data observed by the accelerometer at Roppongi Hills Mori Tower in Minato-ku, Tokyo, during the Great East Japan Earthquake on March 11, 2011. Moreover, as the latest effort, from the standpoint of a developer who builds and operates a number of high-rise buildings in Japan, where frequent earthquakes are experienced, a system for real-time processing of accelerometer data was developed to instantly diagnose the degree of damage to high-rise buildings, and the actual system of earthquake damage health monitoring is discussed. This system is currently in operation in twelve high-rise buildings including Roppongi Hills Mori Tower.