• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.163-171
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• 2009

Precaution is important in cardiac disease above all things. However, current developed tele-monitoring devices limit their communication distance by 100 m and have disadvantage that the device must be activated by the patients themselves. To overcome these shortcomings, we design and implement a cardiac disease management system by sending abnormal ECG signals automatically to the PC in hospital using mobile networks. Experiments show that ECG signals of the patients are transmitted to the database server in hospital without any distortion. Moreover, the amount of SMS data decreased by more than 30% using base64 method than hexadecimal one.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.813-822
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• 2012

Abnormal operating sounds radiated from a moving transfer robot in LCD (liquid crystal display) product lines have been used for the fault detection line of a robot instead of other source signals such as vibrations, acoustic emissions, and electrical signals. Its advantage as a source signal makes it possible to monitor the status of multiple faults by using only a microphone, despite a relatively low sensitivity. The wavelet packet transform for feature extraction and the artificial neural network for fault classification are employed. It can be observed that the abnormal operating sound is sufficiently useful as a source signal for the fault diagnosis of mechanical components as well as other source signals.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.1-8
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• 2016

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring(SHM) technique is ever-increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and are influenced by various external loads. Generally, the visual inspection and non-destructive test for an accessible point of structures are performed by experts. But nowadays, the system is required which is online measurement and detect risk elements automatically without blind spots on structures. In this study, in order to consider the response of non-linear structures, proposed a signal feature extraction and the adaptive threshold setting algorithm utilized to determine the abnormal behavior by using statistical methods such as control chart, root mean square deviation, generalized extremely distribution. And the performance of that was validated by using the acceleration response of structures during earthquakes measuring system of forced vibration tests and actual operation.

• Journal of Yeungnam Medical Science
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• v.18 no.1
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• pp.39-50
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• 2001

Background: Power spectrum analysis method is a powerful noninvasive tool for quantifying autonomic nervous system activity. In this paper, we developed a data acquistion system for estimating the activity of the autonomic nervous system by the analysis of heart rate and respiratory rate variability using power spectrum analysis. Materials and methods: For the detection of QRS peak and measurement of respiratory rate from patient's ECG, we used low-pass filter and impedence method respectively. This system adopt an isolated power for patient's safety. In this system, two output signals can be obtained: R-R interval heart rate) and respiration rate time series. Experimental ranges are 30-240 BPM for ECG and 15-80 BPM for respiration. Results: The system can acquire two signals accurately both in the experimental test using simulator and in real clinical setting. Conclusion: The system developed in this paper is efficient for the acquisition of heart rate and respiration signals. This system will play a role in research area for improving our understanding of the pathophysiologic involvement of the autonomic nervous system in various disease states.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2480-2487
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• 2011

As sensor technology grows up in fields such as environmental hazards detecting system, ubiquitous sensor network, intelligent robot, the sensing and detecting system for sensor is increasing. The sensor data is measured by change of chemical and physical status. Because of decrepit sensor or various sensing environment, it is problem that sensor data is inaccurate result. So the reliability of sensor data is essential. In this paper, we proposes a reliable sensor signal processing platform for various sensor. To improve reliability, we use same sensors in multiple array structure. As sensor data is corrected by spatial and temporal relation signal processing algorithm for measured sensor data, reliability of sensor data can be improved. The exclusive protocol between platform components is designed in order to verify sensor data and sensor state in various environment.

• 한국항공운항학회:학술대회논문집
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• 2016.05a
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• pp.233-239
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• 2016

NASA(미국 항공우주청)를 중심으로 무인항공기교통관리(UTM) 체계를 이용한 드론 항공교통통제 모의시험을 진행하고 있다. 국내에서도 2017년부터 안전한 무인항공기교통관리(UTM) 체계 구축을 위한 '저고도 무인기 감시관리 기술 개발 및 시스템 시범 운용사업'을 진행할 예정이다. 본 논문은 지상도로망을 버드뷰(Birdview)처럼 내려다보며 비행할 수 있는 저고도 드론이 안전하고 효율적인 운항을 보장하기 위해서는, 상공에 장애물이 없는 지상도로망의 상공에 가상도로망과 가상신호체계를 확장시킨 한국형 가상 'SKYWAY' 항법 및 관제 체계(${\mu}$ATM)에 관한 기획 연구에 관한 것이다.

• Journal of Power System Engineering
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• v.11 no.1
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• pp.39-44
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• 2007

The purpose of this study is to verify availability of the acoustic emission in-situ monitoring method to the internal leak and operating conditions of the major valves at nuclear power plants. In this study, acoustic emission tests are performed when the pressurized temperature water and steam flowed through glove valve(main steam dump valve) and check valve(main steam outlet pump check valve) on the normal size of 12 and 18". The valve internal leak monitoring system for practical field was designed. The acoustic emission method was applied to the valves at the site, and the background noise was measured for the abnormal plant condition. To improve the reliability, a judgment of leak on the system was used various factors which are AE parameters, trend analysis, frequency analysis, voltage analysis and amplitude analysis of acoustic signal emitted from the valve operating condition internal leak.

• Proceedings of the KIEE Conference
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• summer
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• pp.280-282
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• 2004

본 논문에서는 고조파 저감을 위해 사용하는 수동필터를 부하의 운전조건에 따라 자동으로 $개\cdot폐$할 수 있는 DSP 기반의 제어시스템을 개발하였다. 수동필터 제어시스템은 부하에서 발생하는 전압, 전류, 고조파, 무효전력, 역률 등을 측정 및 감시하여 수동필터 $개\cdot폐$ 장치에 신호를 보내어 부하의 운전조건에 따라 필터의 각 분로를 자동으로 $개\cdot폐$하게된다. 이러한 제어시스템은 100마력 직류전동기 구동장치를 사용하는 계통에 수동필터와 함께 설치하고 고조파 및 무효전력등을 측정함으로써 성능을 입증하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.505-510
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• 2013

In order to detect and identify the GPS clock anomaly in the Differential GPS real environment, this paper addresses a method for minimizing the measurement noise of reference receivers. It estimates the real measurement noise that removed the uncommon error source from pseudorange measurement to minimize the measurement noise. Based on the output of two reference receivers, it first removes the uncommon errors, then optimizes the measurement noise by applying the correction data. Finally, it detects and identifies the satellite clock anomaly using the minimized measurement noise. The method will increase the availability of current DGPS reference system.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.429-438
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• 1997

Mechanical valve is one of the most widely used implantable artificial organs of which the reliability is so important that its failure means the death of patient. Therefore early noninvasive detection is essentially required, though mechanical valve failure with thrombosis is the most common. The objective of this paper is to detect the thrombosis formation by spectral analysis and neural network. Using microphone and amplifier, we measured the sound from the mechanical valve which is attached to the pneumatic ventricular assist device. The sound was sampled by A/D converter(DaqBook 100) and the periodogram is the main algorithm for obtaining spectrum. We made the thrombosis models using pellethane and silicon and they are thrombosis model on the valvular disk, around the sewing ring and fibrous tissue growth across the orifice of valve. The performance of the measurment system was tested firstly using 1 KHz sinusoidal wave. The measurement system detected well 1KHz spectrum as expected. The spectrum of normal and 5 kinds of thrombotic valve were obtained and primary and secondary peak appeared in each spectrum waveform. We find that the secondary peak changes according to the thrombosis model. So to distinguish the secondary peak of normal and thrombotic valve quantatively, 3 layer back propagation neural network, which contains 7, 000 input node, 20 hidden layer and 1 output was employed The trained neural network can distinguish normal and valve with more than 90% probability. As a conclusion, the noninvasive monitoring of implanted mechanical valve is possible by analysing the acoustical spectrum using neural network algorithm and this method will be applied to the performance evaluation of other implantable artificial organs.