• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1531-1539
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• 2014

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. In other words, the design of algorithm that exactly detects abnormal signal and classifies PVC by analyzing the persons's physical condition and/or environment and variable QRS pattern is needed. Thus, PVC classification by personalized abnormal signal detection and QRS pattern variability is presented in this paper. For this purpose, we detected R wave through the preprocessing method and subtractive operation method and selected abnormal signal sets. Also, we classified PVC in realtime through QS interval and R wave amplitude. The performance of abnormal beat detection and PVC classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 98.33% in abnormal beat classification error and 94.46% in PVC classification.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.6
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• pp.637-644
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• 2015

In order to estimate harbor tranquility, it is needed to simulate wave propagation in a harbor by using both methods under abnormal wave condition and normal wave condition. The problem is the latter case was not simulated in the statement for the Sea Area Utilization Conference. As harbor calmness about normal wave condition has the same meaning as harbor serviceability, in order to assess harbor tranquility, it is needed to survey wave data for long periods but the survey was not done by reason of a lack of budget and shortage of time for plan. It is more important to make a plan for minimizing environmental impact and to assess an improvement of fisherman's living environmental as the assessment of the harbor serviceability is related with the propriety of the plan. In order to assess it, it is needed to understand it clearly, survey for long period of wave data, and clarify the procedure for computation of it. And also providing wave data like tide and tidal current data from KHOA (Korea Hydro graphic and Oceanographic Agency) and making a guideline for assessing it are needed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.6
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• pp.508-517
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• 2009

The real time movement of the caisson was measured when it was open to the waves during breakwater construction. As a result of measurement, no more settlement after the preloading in condition of designed loading was expected but sudden abnormal settlement took place through whole area of the breakwater when waves occurred by typhoon effect. To clarify the reason of this case, wave of the site has been reproduced and the equivalent wave pressure on the caisson was calculated. The numerical analysis of the effect of wave to the ground had been done. Site measurement data is in accordance with the result of numerical analysis.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.597-599
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• 1996

This paper describes the bending traveling-wave type ultrasonic motor which generates the traveling wave by combining two standing waves with phase difference time and space. In $+20^{\circ}C{\sim}30^{\circ}C$, the USM motor operation character has represented normal condition. But the other temperature, (that is say, when long time operating condition) USM operation characteristic has abnormal condition, that is driving frequency, drive current and r.p.m is down. The recent USM has controller without temperature compensation. This study aimed at fuzzy controller which must follow the frequency at operation temperature and then r.p.m and torque increase.

• Proceedings of the KIPE Conference
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• 1996.06a
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• pp.52-55
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• 1996

This paper describes the bending traveling-wave type ultrasonic motor which generates the traveling wave by combining two standing waves with phase difference time and space. In $+20^{\circ}C$~$30^{\circ}C$, the USM motor operation character has represented normal condition. But the other temperature, (that is say, when long time operating condition) USM operation characteristic has abnormal condition, that is driving frequency, drive current and r.p.m is down. The recent USM has controller without temperature compensation. This study aimed at fuzzy controller which must follow the phase angle difference 90$^{\circ}$at operation temperature and them r.p.m and torque increase.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.441-444
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• 1997

This paper describes the bending traveling-wave type ultrasonic motor which generates the traveling wave by combining two standing waves with phase difference time and space. In +2$0^{\circ}C$~3$0^{\circ}C$, the operation characteristic of USM has represented normal condition. But in the other temperature, the operation characteristic of USM has abnormal condition, that is driving frequency, drive current and r.p.m are down. The recent USM has controller without temperature compensation. This study aimed at fuzzy controller which must follow the frequency at operation temperature and then r.p.m and torque increased.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1382-1385
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• 2007

In this paper, we study about the measuring algorithm that can implement Structural Health Monitoring (SHM) more efficiently by two measurement methods using smart sensor. Through the impedance measurement method, the damage condition of structures on wide area is monitored first, and then it changes the mode to guided wave measurement mode by mode switching algorithm when impedance measurement mode detects abnormal signals. Efficient handling of the real-time data would be available by analyzing location and shape of damage through guided wave measurement.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.2061-2068
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• 1993

Condition monitoring technology is of great importance for the maintenance of complex machinery in view of its early monitoring of the abnormal condition and the protection against failure. Several methods have been used for the detection of failure of journal bearings, one of the main elements of mechanical system. The methods most frequently used are vibration and temperature monitoring, but these are unable to monitor the wear conditions exactly. In this study, an ultrasonic measument method, one of the non-destructive testing methods, was introduced as the monitoring technology. Furtermore a pattem recognition method was applied to analyze the ultrasonic signal. The monitoring system using the pattern recognition method is composed of digital signal processing units and uses Hamming net algorithm for the recognition of ultrasonic waves. From the journal bearing wear test, the occurrence of adhesive wear of the white metal in rubbing contact with the shaft was exactly detected by this system, and the wear status of the journal bearing was monitored by measuring the wear thickness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.2021-2030
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• 2012

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Particularly, in the healthcare system that must continuously monitor patient's situation, it is necessary to process ECG (Electrocardiography) signal in realtime. In other words, the design of algorithm that exactly detects R wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, the patient adaptive pattern matching algorithm for the classification of PVC is presented in this paper. For this purpose, we detected R wave through the preprocessing method, adaptive threshold and window. Also, we applied pattern matching method to classify each patient's normal cardiac behavior through the Hash function. The performance of R wave detection and abnormal beat classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.33% in R wave detection and the rate of 0.32% in abnormal beat classification error.

• Journal of IKEEE
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• v.25 no.1
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• pp.212-217
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• 2021

Premature contraction arrhythmia is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Most of arrhythmia clasification methods have been developed with the primary objective of the high detection performance without taking into account the computational complexity. Also, personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Therefore it is necessary to design efficient method that classifies arrhythmia by analyzing the persons's physical condition and decreases computational cost by accurately detecting minimal feature point based on only QRS features. We propose method for personalized specific classification of premature contraction arrhythmia based on QRS features in smart healthcare environments. For this purpose, we detected R wave through the preprocessing method and SOM and selected abnormal signal sets.. Also, we developed algorithm to classify premature contraction arrhythmia using QRS pattern, RR interval, threshold for amplitude of R wave. The performance of R wave detection, Premature ventricular contraction classification is evaluated by using of MIT-BIH arrhythmia database that included over 30 PVC(Premature Ventricular Contraction) and PAC(Premature Atrial Contraction). The achieved scores indicate the average of 98.24% in R wave detection and the rate of 97.31% in Premature ventricular contraction classification.