• 한국컴퓨터정보학회논문지
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• 제23권11호
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• pp.1-7
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• 2018

In this paper, we propose soft dead pixels detection method by analysing different response at hot and cold images. Abnormal pixels are able to effect detecting a small target. It also makes confusing real target or not cause of changing target size. Almost exist abnormal pixels after image signal processing even if dead pixels are removed by dead pixel compensation are called soft dead pixels. They are showed defect in final image. So removing or compensating dead pixels are very important for detecting object. The key idea of this proposed method, detecting dead pixels, is that most of soft deads have different response characteristics between hot image and cold image. General infrared cameras do NUC to remove FPN. Working 2-reference NUC must be needed getting data, hot & cold images. The way which is proposed dead pixel detection is that we compare response, NUC gain, at each pixel about two different temperature images and find out dead pixels if the pixels exceed threshold about average gain of around pixels.

• 센서학회지
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• 제29권4호
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• pp.249-254
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• 2020

It is difficult to control children who exhibit negative behavior in dental clinics. Various methods are used for preventing pediatric dental patients from being afraid and for eliminating the factors that cause psychological anxiety. However, when it is difficult to apply this routine behavioral control technique, sedation therapy is used to provide quality treatment. When the sleep anesthesia treatment is performed at the dentist's clinic, it is challenging to identify emergencies using the current breath detection method. When a dentist treats a patient that is under the influence of an anesthetic, the patient is unconscious and cannot immediately respond, even if the airway is blocked, which can cause unstable breathing or even death in severe cases. During emergencies, respiratory instability is not easily detected with first aid using conventional methods owing to time lag or noise from medical devices. Therefore, abnormal breathing needs to be evaluated in real-time using an intuitive method. In this paper, we propose a method for identifying abnormal breathing in real-time using an intuitive method. Respiration signals were measured using a 3M Littman electronic stethoscope when the patient's posture was supine. The characteristics of the signals were analyzed by applying the signal processing theory to distinguish abnormal breathing from normal breathing. By applying a short-time Fourier transform to the respiratory signals, the frequency range for each patient was found to be different, and the frequency of abnormal breathing was distributed across a broader range than that of normal breathing. From the wavelet transform, time-frequency information could be identified simultaneously, and the change in the amplitude with the time could also be determined. When the difference between the amplitude of normal breathing and abnormal breathing in the time domain was very large, abnormal breathing could be identified.

• 제어로봇시스템학회논문지
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• 제4권4호
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• pp.506-516
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• 1998

In this paper, an algorithm is proposed to detect the malfunction of plasma-etching characteristics using EPD signal trajectories. EPD signal trajectories offer many information on plasma-etching process state, so they must be considered as the most important data sets to predict the wafer states in plasma-etching process. A recent work has shown that EPD signal trajectories were successfully incorporated into process modeling through critical parameter extraction, but this method consumes much effort and time. So Principal component analysis(PCA) can be applied. PCA is the linear transformation algorithm which converts correlated high-dimensional data sets to uncorrelated low-dimensional data sets. Based on this reason neural network model can improve its performance and convergence speed when it uses the features which are extracted from raw EPD signals by PCA. Wafer-state variables, Critical Dimension(CD) and uniformity can be estimated by simulation using neural network model into which EPD signals are incorporated. After CD and uniformity values are predicted, proposed algorithm determines whether malfunction values are produced or not. If malfunction values arise, the etching process is stopped immediately. As a result, through simulation, we can keep the abnormal state of etching process from propagating into the next run. All the procedures of this algorithm can be performed on-line, i.e. wafer to wafer.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1989년도 춘계학술대회
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• pp.19-22
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• 1989

This paper represents a syntactic peak detection algorithm which detects peaks in the ECG signal. In the algorithm, the input waveform is linearly approximated by "split-and-merge" method, and then each line segment is symbolized with primitive set. The peeks in the symbolized input waveform are recognized by the finite-state automata, which the deterministic finite-state language is parsed by. This proposed algorithm correctly detects peaks in a normal ECG signal as well as in the abnormal ECG signal such as tachycardia and the contaminated signal with noise.

• 한국정보통신학회논문지
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• 제26권1호
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• pp.30-40
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• 2022

심전도 신호는 개인에 따라 형태와 특징이 다양하므로, 하나의 신경망으로는 분류하기가 어렵다. 주어진 데이터를 직접적으로 분류하는 것은 어려우나, 대응되는 정상 데이터가 있을 경우, 이를 비교하여 정상 및 비정상을 분류하는 것은 상대적으로 쉽고 정확하다. 본 논문에서는 템플릿 군을 이용하여 대표정상심박 정보를 획득하고, 이를 입력 심박에 결합함으로써 심박을 분류한다. 결합된 심박을 영상화한 후, 학습 및 분류를 진행하여, 하나의 신경망으로도 다양한 레코드의 비정상심박을 검출이 가능하였다. 특히, GoogLeNet, ResNet, DarkNet 등 다양한 신경망에 대해서도 비교학습 기법을 적용한 결과, 모두 우수한 검출성능을 가졌으며, GoogLeNet의 경우 99.72%의 민감도로, 실험에 사용된 신경망 중 가장 우수한 성능을 가졌음을 확인하였다.

• 한국자동차공학회논문집
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• 제5권1호
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• pp.27-37
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• 1997

Internal combustion engine is the main source of environmental pollutants and therefore better technology is required to reduce harmful elements from the exhaust gases all over the world. Especially, harmful elements from the exhaust gases are caused by incomplete combustion of mixture inside the engine cylinder and this abnormal combustion like misfire or partial burning is the direct cause of the air pollution and engine performance degradation. the object of this research is to detect abnormal combustion like misfire and to keep the engine performance in the optimal operating state. Development of a new system therefore could be applied to a real car. To realize this, the spark-plug in a conventional ignition system is used as a misfire detection sensor and breakdown voltage is analyzed. In this research, bias voltage(about 3kV) was applied to the electrodes of spark-plug and breakdown voltage signal is obtained. This breakdown voltage signal is analyzed and found that a combustion phenomena in engine cylinder has close relationship with harmonic coefficient K which was introduced in this research. Newly developed combustion diagnostic method( breakdown voltage signal analysis) from this research can be used for the combustion diagnostic and combustion control system in an real car.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.821-826
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• 2001

Out of all metal-cutting processes, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. Accordingly, this paper deals with Basic system and Online system. Basic system comprised of spindle rotational speed, feed rates, thrust, torque and flank wear measured tool microscope. Online system comprised of spindle rotational speed, feed rates, AE signal, flank wear area measured computer vision. On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

• 한국멀티미디어학회논문지
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• 제19권11호
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• pp.1862-1870
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• 2016

A respiration is one of the most useful techniques for vital checking and an abnormal respiration is often the earliest sign of critical illness. Detection of respiration is based on the photo-plethysmography (PPG) with photodiode technique. Because PPG sensor using photodiode can be easily miniaturized, it is suitable for wearable devices. A system to measure respiration rate based on PPG signal is implemented and for a reliable measurement an improved algorithm in accuracy using PPG signal pattern is proposed in this paper. As results regarding to three types of respirations (regular interval, free interval, and weak respiration) the proposed algorithm showed error rate of 0.047, 0.067, and 0.122 respectively.

• 대한의용생체공학회:의공학회지
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• 제25권2호
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• pp.129-135
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• 2004

재택건강관리 시스템은 주로 정상인들로부터 빈번하게 측정한 생체신호의 실시간 처리과정을 필요로 한다. 본 논문에서는 이러한 환경에서 측정되는 심전도 신호에서 DRS를 검출하기 위한 단순화된 알고리즘과 검출된 QRS의 정상과 비정상 여부만을 분류하는 알고리즘에 대하여 기술한다. 기존에 사용되고 있는 실시간 QRS 검출 알고리즘을 세분화하여 단순화된 QRS 검출 알고리즘을 제안함으로서 저가형 소형 단말기에서도 사용이 가능하도록 하였다. 또한 검출된 QRS들로부터 QRS 폭, R-R 간격, DRS 형태변수를 추출하여 QRS의 정상과 비정상을 판단하는 알고리즘을 개발하였다. 단순화된 QRS 검출기의 성능과 정상과 비정상의 분류성능은 각각 약 99%와 96%로 나타났다. 본 논문에서 제안된 QRS 검출과 분류를 위한 알고리즘들은 복잡한 신호처리 과정이 필요치 않으므로 재택건강관리 시스템에서의 실시간 심전도처리에 사용될 수 있을 것이다

• 한국공작기계학회논문집
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• 제12권3호
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• pp.8-16
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• 2003

Monitoring of the drill wear :md hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work-piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process and provide a relatively easy way to monitor a machining process for industrial application. for this advantage, AE signal is used to estimate the abnormal fate. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so of but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality. As the results of this experiment AE RMS signal and measurements by vision system are shorn the similar tendency as abnormal state of drilling.