• Steel and Composite Structures
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• v.19 no.1
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• pp.131-152
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• 2015

Easy detection and evaluation of defect in the tube structure is a continuous problem and remains a significant demand in tube inspection technologies. This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. The stress wave signals from vibrational impact excitation on several tube conditions were captured to identify the defect in ASTM A179 seamless steel tubes. The variation in stress wave propagation was captured by a high frequency sensor. Stress wave signals from four tubes with artificial defects of different depths and one reference tube were classified using the autoregressive (AR) algorithm. The results were demonstrated using a dendrogram. The preliminary research revealed the natural arrangement of stress wave signals were grouped into two clusters. The stress wave signals from the healthy tube were grouped together in one cluster and the signals from the defective tubes were classified in another cluster. This approach was effective in separating different stress wave signals and allowed quicker and easier defect identification and interpretation in steel tubes.

• Journal of the Ergonomics Society of Korea
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• v.18 no.1
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• pp.121-131
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• 1999

There have been many questionnaires, catecholeamins analysis and bio-signal analysis to analyze human stress condition through out the years, and especially researches in bio-signal analysis have been actively increasing. The purpose of our research is Quantitative analysis of stress with synthesis of bio-signals. The stress status was estimated using the bio-signals and fuzzy theory which combines these signals and physiological knowledge. Stress was estimated by a 'coin-stacking' experiment with two type-relax and stress status. To do the experiment EMG, respiration, periphery temperature, heart rate and skin conductances were used to evaluate human stress stages. The system was tested to 10 healthy persons and achieved a template of a stress progress and stress variations were classified to 4 steps by continuous or rising status of stress progress.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1131-1135
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• 2010

The development of modern civilization result from the abundance of material. Yet modern people live with chronic mild stress. Excessive chronic mild stress leads to various diseases. From the risk of the disease in order to protect our bodies need to manage chronic mild stress. The purpose of this study is to inspection the effectiveness of detecting in chronic mild stress using the Multi-sensor system. The Multi-sensor system is designed that can be measure three kinds of vital signals of chronic mild stress for the detection. First Photoplethysmogram(PPG), second Electro Dermal Activity(EDA), third Skin Temperature(SKT). The ages and occupations exposed to chronic mild stress, people often use out of this system was applied to dairy products(Pen). In addition, vital signals that occur when the variety of noise was used to remove the accelerometer. Chronic mild stress by the analysis of measured vital signals from Multi-sensor system to the measurement information to a PC to a wireless transmission(Bluetooth). In this study, using Multi-sensor system writing conditions and a variety of situations in the movement to measure vital signals and measurement results verified the accuracy and reliability. Through this measure chronic mild stress in everyday life and managing to maintain will help more healthy lifestyle.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.62-69
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• 2020

Most people suffer from stress during day life because modernized society is very complex and changes fast. Because stress can affect to many kind of physiological phenomena it is even considered as a disease. Therefore, it should be detected earlier, then must be released. When a person is being stressed several bio-signals such as heart rate, etc. are changed. So, those can be detected using medical electronics techniques. In this paper, stress assessment system is studied using random forest algorithm based on heart rate, RR interval and Galvanic skin response. The random forest model was trained and tested using the data set obtained from the bio-signals. It is found that the stress assessment procedure developed in this paper is very useful.

• Journal of the Korean Magnetics Society
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• v.13 no.2
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• pp.76-81
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• 2003

Non-linear anisotropic materials were used to simulate the effects of tensile stress in 3D finite element analysis (FEA). FEA was used to calculate the effects of far and near-side pit depth and tensile stress on magnetic flux leakage (MFL) signals. The axial and radial MFL signals were depended on far and near-side double circular pit depth and on the stress, but the circumferential MFL signal was not depended on them. The axial and radial MFL signals increased with greater pit depth and applied stress, but the circumferential MFL signal was scarcely changed.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.1-18
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• 2017

Recently, identification of the extremely stressed condition of children is an essential skill for real-time recognition of a dangerous situation because incidents of children have been dramatically increased. In this paper, therefore, we present a model based on machine learning techniques for stress status identification of a child by using bio-signals such as voice and heart rate that are major factors for presenting a child's emotion. In addition, a smart band for collecting such bio-signals and a mobile application for monitoring child's stress status are also suggested. Specifically, the proposed method utilizes stress patterns of children that are obtained in advance for the purpose of training stress status identification model. Then, the model is used to predict the current stress status for a child and is designed based on conventional machine learning algorithms. The experiment results conducted by using a real-world dataset showed that the possibility of automated detection of a child's stress status with a satisfactory level of accuracy. Furthermore, the research results are expected to be used for preventing child's dangerous situations.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.263-269
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• 2003

Magnetic flux leakage (MFL) signals were used for corrosion inspection of buried oil and gas pipeline. 3D finite element analysis was used to examine the effects of far and near-side pit depth and tensile stress on MFL signals. Anisotropci materials were used, and the effects of simulated tensile stress on MFL were investigated. The axial and radial MFL signals depended on far and near-side single pit depth and on the bulk stress, but the circumferential MFL signal did not depend on them. The axial and radial MFL signals increased with increasing pit depth and the bulk stress, but the circumferential MFL signal was scarcely changed.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.04a
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• pp.171-175
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• 1998

This work presents an estimation for stress status using biosignal and fuzzy theory. Stress is estimated by 'coin-build' experiment with two type, relax and stress status. The estimator uses five biosignals, fuzzy logic to combine these signals and physiological knowledge. The system was tested in 10 records of healthy indivisuals and acheived a template of a stress progress. This work presents an estimation for stress status using biosignal and fuzzy theory. Stress is estimated by 'coin-build' experiment with two type, relax and stress status. The estimator uses five biosignals, fuzzy logic to combine these signals and physiological knowledge. The system was tested in 10 records of healthy indivisuals and acheived a template of a stress progress.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.8 no.3
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• pp.7-12
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• 2012

Steam generator tubes are critical boundary of the primary and secondary side in nuclear power plants. Eddy current testing is commonly used as the method of non-destructive testing for the safety and integrity of steam generator tubes in the nuclear power plants. Changes in the geometric shape act as a stress concentration factor likely to cause a defect during the steam generator operation. The mixed-signals with the geometric shape are distorted and attributes that are difficult to detect signals. An example is bending stress due to compression process at a U-bend occurring in the intrados region which has a small radius of curvature. The resulting change in the geometric shape may lead to a dent like occurrences. The dent can cause stress concentration and generates stress corrosion cracks. In this study, the steam generator tubes of nuclear power plant were selected to study for analysis of mixed-signal containing dent and stress corrosion cracks.

• Journal of Ocean Engineering and Technology
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• v.17 no.1
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• pp.47-54
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• 2003

In this study, the residual stress and the acoustic emission Charactreistics from fatigue crack propagation were investigated, bused on the welded material of STS316L. The residual stress of welding locations could be evaluated by ultrasonic parameters, such as L$_{CR}$ wave velocity and L$_{CR}$ wave frequency； the residual stress between base metal and weld metal was evaluated. In the fatigue tests, three types of signals were observed, regardless of specimen condition, base metal, and weld metal. Based on NDE analysis of AE signals by the time-frequency analysis method, it should also be possible to evaluate, in real-time, the crack propagation and final fracture process, resulting from various damages and defects in welded structural members.