• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.119-124
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• 1994

Morden industrial society pursues unmanned system and automation of manufacturing rocess. Abreast with this tendensy, prodution of goods which requires advaned accuracy is increasing as well. According to this, the work sensing time of dressing by monitoring and diagnosis the condition of grinding, which is the representative way in accurate manufacturing, is a important work to prevent serios damages which affect grinding process or products by wearing wheel. Computer vision system is composed, so that grind wheel wurface was acquired by CCD camera and the change of cutting is composed. Then we used autometic threshoding technique from histogram as a way of deviding cutting edge which is used in manufacturing from the other parts. As a result, we are trying to approach unmanned system and sutomation by deciding more accurate time of dressing and by visualizing behavior of grinding wheel by marking use of computer vision.

• 대한의용생체공학회:의공학회지
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• 제24권5호
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• pp.381-389
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• 2003

상완혈압과 두부혈압의 상승은 혈액순환장애와 함께 각종 성인병과 난치성질환인 뇌졸중과 치매, 중풍의 원인이 되고 있다. 뇌졸중이나 중풍의 조기진단에 있어서, MRI 같은 의료장비는 발병전 진단보다는 발병후의 치료를 위한 목적으로 이용되고 있으며 의료비 부담이 큰 단점이 있다. 또한, 상완혈압이 정상인 사람에서도 중풍이 발생하고 있어서, 상완혈압에 의한 진단보다는 뇌혈류상태를 반영하는 두부혈압을 진단하는 것이 더 정확한 임상진단을 할 수 있다. 그러나 기존 혈압계로는 두부혈압을 측정할 수 없다. 본 논문에서는 상완혈압과 두부혈압을 쉽고 간편하게 측정하고, 상완혈압에 대한 두부 혈압의 상관성을 추출하여 뇌혈류 상태 및 건강상태를 조기 진단/예방할 수 있는 시스템 및 알고리즘을 개발하였다. 시스템의 임상실험 결과, 두부혈압의 최고압은 상완 최고압의 62%, 최저혈압은 상완 최저혈압의 46%에 해당하는 것을 확인하여 상관성을 추출하였다, 상완혈압이 정상, 고혈압 및 뇌졸중 환자를 대상으로 측정한 결과, 두 혈압간 상관성에 큰 차이가 있음을 확인하였다. 이는 상완혈압 측정에 의존한 진단보다 두부혈압 측정에 의해 더 중요한 진단요소를 추출할 수 있어서 더 정확한 진단을 할 수 있음을 의미한다. 따라서, 뇌혈류에 이상이 있을 때 달라지는 두부혈압을 측정하여 상완혈압과의 상관성을 추출하고, 환자를 대상으로 분석하여 뇌혈류 상태를 진단/개선함으로써 새로운 진단체계를 구축할 수 있는 시스템을 개발하였다.

• 한국멀티미디어학회논문지
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• 제21권8호
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• pp.837-848
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• 2018

Monitoring technology of machining has a long history since unmanned machining was introduced. Despite the long history, many researchers have presented new approaches continuously in this area. Sound based machine fault diagnosis is the process consisting of detecting automatically the damages that affect the machines by analyzing the sounds they produce during their operating time. The collected sound is corrupted by the surrounding work environment. Therefore, the most important part of the diagnosis is to find hidden elements inside the data that can represent the error pattern. This paper presents a feature extraction methodology that combines various digital signal processing and pattern recognition methods for the analysis of the sounds produced by tools. The magnitude spectrum of the sound is extracted using the Fourier analysis and the band-pass filter is applied to further characterize the data. Statistical functions are also used as input to the nonlinear classifier for the final response. The results prove that the proposed feature extraction method accurately captures the hidden patterns of the sound generated by the tool, unlike the conventional features. Therefore, it is shown that the proposed method can be applied to a sound based automatic diagnosis system.

• 대한의용생체공학회:의공학회지
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• 제28권2호
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• pp.294-299
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• 2007

For efficient and accurate diagnosis of ultrasound images, appropriate time gain compensation(TGC) and dynamic range(DR) control of ultrasound echo signals are important. TGC is used for compensating the attenuation of ultrasound echo signals along the depth, and DR controls the image contrast. In recent ultrasound systems, these two factors are automatically set by a system and/or manually adjusted by an operator to obtain the desired image quality on the screen. In this paper, we propose an algorithm to find the optimized parameter values far TGC and DR automatically. In TGC optimization, we determine the degree of attenuation compensation along the depth by dividing an image into vertical strips and reliably estimating the attenuation characteristic of ultrasound signals. For DR optimization, we define a novel cost function by properly using the characteristics of ultrasound images. We obtain experimental results by applying the proposed algorithm to a real ultrasound(US) imaging system. The results verify that the proposed algorithm automatically sets values of TGC and DR in real-time such that the subjective quality of the enhanced ultrasound images may be sufficiently high for efficient and accurate diagnosis.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.603-608
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• 2001

In order to distinguish fault electric motors automatically in real time. an intelligent diagnosis technique may be required. This paper presents an automatic fault detection system for electric motors by using their acoustic noises. Time signals of each candidate motor were measured in an anechoic chamber for further analysis. Spectral analysis was first carried out and they showed that two typical types of fault motors could be successfully distinguished in the frequency domain; bearing faults and scratches. Unlike the trend of normal motors that shows only a single dominant peak at around 2000 ㎐, several peaks are bunched together in bearing fault motors. On the other hand, large frequency noises at around 6500 ㎐ are newly arisen in scratchy fault motors. However, the processing time for spectral analysis was rather long for a real time application in production lines. Thus, a number of band-pass filters were used in the time domain instead for a real time application. Before applying filters, the bands of filters were set from the information of spectral analysis. By applying a set of band-pass filters, the RMS values of each filtered signal were calculated, and thus the normal and damaged motors could be successfully distinguished.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1991년도 춘계학술대회
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• pp.94-97
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• 1991

It is well known that multipoint and computerized intraoperative mapping systems improve the results of surgery for Wolff-Parkinson-White syndrome and show tremendous potential for opening an entirely new era of surgical intervention for the more common and lethal types of supraventricular tachyarrhythmias such as atrial flutter and atrial fibrillation. In addition, the ability to map and ablate the sometimes fleeting automatic atrial tachycardia is greatly enhanced by computerized mapping systems. In this study, we have developed 16 channel computerized data analysis system using microcomputer for basic research of electrophysiology and electrical propagation. This system is expected to enable us to study pathophysiology of cardiac arrhythmia and to improve the results of diagnosis and surgical treatment for cardiac arrhythmia.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1994년도 추계학술대회
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• pp.81-84
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• 1994

A clinically oriented EEG and EP mapping system was developed with user-friendly interface and easy interactive operations. The system was based on the graphical user interface developed with C/C++ and Software Development Kit (SDK) operated under Microsoft Windows 3.1. Continuous acquisition for the EEG signal and burst mode acquisition for EEG signal syncronized to the external stimuli arc implemented with real time display. A neural network based automatic artifact discrimation is developed and implemented with which examination time can be reduced by a factor of 3 or more. Several bands of spectral maps and spectrums arc displayed for EEG diagnosis. Amplitude maps of EP signal at specified times by operator are displayed together with cine mode of EP maps for dynamic study. Source localization and other statistical signal processing are also included.

• 말소리와 음성과학
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• 제1권3호
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• pp.155-163
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• 2009

This paper introduces an automatic voice classification system for the diagnosis of individual constitution based on Sasang Constitutional Medicine (SCM) in Traditional Korean Medicine (TKM). For the developing of this algorithm, we used the voices of 473 speakers and extracted a total of 144 speech features from the speech data consisting of five sustained vowels and one sentence. The classification system, based on a rule-based algorithm that is derived from a non parametric statistical method, presents binary negative decisions. In conclusion, 55.7% of the speech data were diagnosed by this system, of which 72.8% were correct negative decisions.

• 전기학회논문지
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• 제67권12호
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• pp.1678-1684
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• 2018

Dental caries is one of the most popular oral disease. The aim of automatic dental cavity detection system is helping dentist to make accurate diagnosis. It is very important to separate cavity from the teeth in the detection system. In this paper, We compared two active contour algorithms, Snake and DRLSE(Distance Regularized Level Set Evolution). To improve performance, image is selected ROI(region of interest), then applied bilateral filter, Canny edge. In order to evaluate the algorithms, we applied to 7 tooth phantoms from incisor to molar. Each teeth contains two cavities of different shape. As a result, Snake is faster than DRLSE, but Snake has limitation to compute topology of objects. DRLSE is slower but those of performance is better.

• 한국IT서비스학회지
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• 제11권4호
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• pp.153-170
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• 2012

When companies or institutes manage data, in order to utilize it as useful resources for decision-making, it is essential to offer precise and reliable data. While most small and medium-sized enterprises and public institutes have been investing a great amount of money in management and maintenance of their data systems, the investment in data management has been inadequate. When public institutions establish their data systems, inspection has been constantly carried out on the data systems in order to improve safety and effectiveness. However, their capabilities in improving the quality of data have been insufficient. This study develops an automatic tool to diagnose the quality of data in a way to diagnose the data quality condition of the inspected institute quantitatively at the stage of design and closure by inspecting the data system and proves its practicality by applying the automatic tool to inspection. As a means to diagnose the quality, this study categorizes, in the aspect of quality characteristics, the items that may be improved through diagnosis at the stage of design, the early stage of establishing the data system and the measurement items by the quality index regarding measurable data values at the stage of establishment and operation. The study presents a way of quantitative measurement regarding the data structures and data values by concretizing the measurement items by quality index in a function of the automatic tool program. Also, the practicality of the tool is proved by applying the tool in the inspection field. As a result, the areas which the institute should improve are reported objectively through a complete enumeration survey on the diagnosed items and the indicators for quality improvement are presented quantitatively by presenting the quality condition quantitatively.