• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.11
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• pp.1174-1185
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• 2012

This study develops tight-fitting upper clothing to measure electrocardiography (ECG) data. Taking into consideration the elasticity of the clothing, we made 4 experimental clothes by applying to each a weft reduction rate of 40%, 50%, 60%, and 70%. The 4 experimental clothes were used to measure resting ECG, exercise ECG, and post-exercise ECG for 4 men in their 20s. We compared clothing pressures using sensors on the human body and on a dressform. Subjective wear sensations of the 4 experimental clothes were evaluated using a subjective 7-point scale (with 7 being most excellent). We measured clothing pressures by using the air type pressure (AMI 3037-2) for upper and lower chest sensors in the developed tight-fitting upper clothing. The lower chest sensor showed that the clothing pressure on a human body and dressform changed consistently as the weft reduction rate decreased. The upper chest sensor showed inconsistent changes in clothing pressure as the weft reduction rate decreased. The wearing-test result for preliminary subjects showed that the lower chest sensor was more stable than the upper chest sensor; therefore, we inserted the sensor at the lower chest position before performing ECG. Except for Subject 4, the resting ECGs were stably measured for 3 subjects (Subject 1, Subject 2, and Subject 3) in all the developed clothes (A clothing, B clothing, C clothing, and D clothing). However, D clothing showed stable ECG values after exercise. The results of the experiment showed that we could measure ECG without difficulty using clothes with a weft reduction rate of 40% when the movement was not intense; however, tight-fitting upper clothing with a weft reduction rate of 70% was necessary to measure exercise ECG and post-exercise ECG values.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.579-593
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• 2010

Low-power radio frequency (RF) chip transceiver technology and the associated structural health monitoring platforms have matured recently to enable high-rate, lossless transmission of measurement data across large-scale sensor networks. The intrinsic value of these advanced capabilities is the allowance for high-quality, rapid operational modal analysis of in-service structures using distributed accelerometers to experimentally characterize the dynamic response. From the analysis afforded through these dynamic data sets, structural identification techniques can then be utilized to develop a well calibrated finite element (FE) model of the structure for baseline development, extended analytical structural evaluation, and load response assessment. This paper presents a case study in which operational modal analysis is performed on a three-span prestressed reinforced concrete bridge using a wireless sensor network. The low-power wireless platform deployed supported a high-rate, lossless transmission protocol enabling real-time remote acquisition of the vibration response as recorded by twenty-nine accelerometers at a 256 Sps sampling rate. Several instrumentation layouts were utilized to assess the global multi-span response using a stationary sensor array as well as the spatially refined response of a single span using roving sensors and reference-based techniques. Subsequent structural identification using FE modeling and iterative updating through comparison with the experimental analysis is then documented to demonstrate the inherent value in dynamic response measurement across structural systems using high-rate wireless sensor networks.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.433-438
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• 2010

Reactor vessel internals comprehensive vibration assessment program(RVI CVAP) is one of the necessary tests to ensure the safety of nuclear power plants. RVI CVAP of U.S. Nuclear Regulatory Commission Regulatory Guide 1.20(U.S. NRC R.G. 1.20) consists of the analysis, measurement, and inspection. One of the core technologies of the measurement program for RVI CVAP is to select suitable sensors. We analyzed RVI design data of Palo Verde nuclear generating station(U.S.) and Yonggwang nuclear generating station(Korea) and investigated measuring sensors used in both of them; moreover, we investigated sensors used for measurement of RVI CVAP for the last 20 years throughout the world. Based on these results, we selected the most suitable sensors for RVI CVAP in Advanced Power Reactor 1400(APR1400).

• Proceedings of the Korea Concrete Institute Conference
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• 2002.10a
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• pp.717-723
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• 2002

Recently, the interest in safety assessment of civil infrastructures is increasing in Korea. Especially, as bridge structures become large-scale, it is necessary to monitor and maintain the safety state of bridges, which requires the monitoring system that can make a long-term measurement during the service time of bridge. In this paper, advanced fiber optic sensors for long-term measurement, setup techniques of bridge monitoring system and the assessment of measured data are introduced. Attached or embedded optical fiber sensors to structural members of small and big structures including Sung San Bridge are surveyed. For the Sung San Bridge, the responses of the fiber optic sensors by 30 ton weigh truck loads with various speeds ate measured. Monitoring system is also applied to the mock-up of bridges. The monitoring capability of the advanced fiber optic sensor system was confirmed.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.10a
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• pp.92-104
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• 2005

Over the past decade, major advances have occurred in both understanding and practice with regard to assessment and mitigation of hazard area associated with seismically induced soil liquefaction. In this paper, assessment of liquefaction resistance of soil are reviewed from the recent researches. In addition site characteristics investigation methods and tests for seismic design and liquefaction analysis are reviewed. Finally, introduction and characteristics of remedial measures against soil liquefaction are reviewed briefly.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.2
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• pp.29-36
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• 2005

In oder to generate various shock signals in a field study, a passenger car was driven at several speeds over road profiles that included a number of half sine shaped bumps of various heights. A triaxial SAE pad sensor was mounted on the front passenger seat to measure the acceleration signals which might produce subjective discomfort. The measured accelerations were correlated with the subjective assessments of 14 subjects. The magnitude of subjective discomfort was found to be proportional to the VDV and also the peak to peak of the frequency weighted acceleration signal.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.194-195
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• 2015

Methods for measuring the physical workload of construction workers are classified into posture assessment techniques (i.e., OWAS, RULA, etc.) and physiological measurement techniques (i.e., EMG, heart rate, etc.). The one does not quantify the workload on a specific body part of a worker by considering the weight of the hand tools or materials on hand and time for holding a particular posture. This paper presents a procedure for evaluating a physical demand using the electromyography (EMG) sensor. This study compares the EMG measurement and the posture assessment. The case study is carried out on a masonry operation.

• Journal of Environmental Impact Assessment
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• v.22 no.4
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• pp.389-395
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• 2013

Geostationary Ocean Color Imager(GOCI), the World's first spaceborne ocean color observation satellite operated in geostationary orbit, was successfully launched on May 2010. The main missions of GOCI is the coastal environment monitoring of GOCI in order to meet the necessity of long-term climate change monitoring and research. The GOCI have higher spatial resolution than MODIS, $500m{\times}500m$, and 8 spectral ocean color channels. GOCI have a capability for observation on the coastal environment change, GOCI perform the observation with 8 times a day. In this paper, we presented the more improved results for observation on the coastal environment change than MODIS ocean color sensor and detected the spatial difference of CDOM for monitoring coastal environment change.

• Journal of Navigation and Port Research
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• v.42 no.5
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• pp.323-330
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• 2018

The Korean e-Navigation system is a Korean approach to correspond with implementation of IMO e-Navigation. It provides five services, among them SV20 service, a ship remote monitoring system that collects and processes sensor information related to fire, navigation, and seakeeping performance safety. The system also detects abnormal conditions such as fires, capsizing, sinking, navigation equipment failure during navigation, and calculates the safety index and determines the emergency level. According to emergency level, it provides appropriate emergency response guidance for the onboard operator. The fire safety module is composed of three sub-modules; each module is the safety index sub-module, the emergency level determination sub-module and emergency response guidance sub-module. In this study, operational concept of the fire safety module in SV20 service is explained, and fire safety assessment factors are estimated, to calculate the fire safety index. Fire assessment factors included 'Fire detector position factor,' 'Smoke diffusion rate factor,' and 'Fire-fighting facilities factor.'