• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.106-109
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• 2002

In the integrated systems, that is integrated digital TV(DTV) internet and home automation, like home server, is needed integration of digital TV video signal and computer graphic signal. The graphic signal is operating at the high speed and has time-divide-stream. So the re-request of data is not easy at the time of error detection. therefore EDAC algorithm is efficient. This paper presents the efficiency error detection auto correction(EDAC) for conversion of graphics signal to DTV video signal. A presented EDAC algorithms use the modified Hamming code for enhancing video quality and reliability. A EDAC algorithm of this paper can detect single error, double error, triple error and more error for preventing from incorrect correction. And it is not necessary an additional memory. In this paper The comparison between digital TV video signal and graphic signal, a EBAC algorithm and a design of conversion graphic signal to DTV signal with EDAC function is described.

• 대한전자공학회논문지TC
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• 제42권10호
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• pp.25-30
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• 2005

본 논문에서는 신호공간 검출의 개념을 일반화하여 하나의 심볼 구간에서 하나 이상의 심볼들의 블록에 대한 검출을 수행하는 고정지연 트리 검색 신호검출기의 구성을 제안한다. 제안된 기법은 고속의 구현에 적합하다. 두 가지의 접근방법이 논의되며 이들은 모두 효율적인 신호공간 분할에 기반을 두고 있다. 첫 번째 방법에서는 심볼의 검출이 다중 클래스 분할에 기반을 둔다. 이 방법은 2개의 클래스에 기반을 둔 이진 심볼 검출방법을 일반화한 접근방법을 사용한다. 두 번째 방법에서는 이진 신호 검출이 look-ahead 기법과 결합된 고도의 병렬처리 신호검출 구조를 활용한다.

• 제어로봇시스템학회논문지
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• 제22권6호
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• pp.483-489
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• 2016

This paper proposes a repeat-back jamming signal detection scheme that utilizes a combined pseudo random noise signal that is effective for processing a global positioning system (GPS) repeat-back jamming signal with the early minus late phase scheme to alleviate any existing multipath signal detection. The proposed scheme uses the combined pseudo random noise signal to treat repeat-back jamming signals like similar multipath signals and can effectively detect a repeat-back jamming signal by applying the early minus late phase scheme to a combined pseudo random noise signal. Through a Monte-Carlo simulation, the detection probability of the proposed scheme is better than the one of the conventional scheme under low jamming to signal power ratio.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.415-418
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• 1996

Etching Process, one of the most important process in semiconductor fabrication, has input control part of which components are pressure, gas flow, RF power and etc., and plasma gas which is complex and not exactly understood is used to etch wafer in etching chamber. So this process has not real-time feedback controller based on input-output relation, then it uses EPD(End Point Detection) signal to determine when to start or when to stop etching. Various type EPD controller control etching process using EPD signal obtained from optical intensity of etching chamber. In development EPD controller we concentrate on compensation of this signal intensity and setting the relative signal magnitude at first of etching. We compensate signal intensity using neural network learning method and set the relative signal magnitude using fuzzy inference method. Potential of this method which improves EPD system capability is proved by experiences.

• 디지털산업정보학회논문지
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• 제17권4호
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• pp.85-94
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• 2021

The LPR system's trigger sensor makes problem occasionally due to the heave weight of vehicle or the obsolescence equipment. If we replace the hardware sensor to the deep-learning based software sensor in order to generate the trigger signal, LPR system maintenance would be a lot easier. In this paper we proposed the deep-learning sliding window based object detection and tracking algorithm for the LPR system's trigger signal generation. The gate passing vehicle's license plate recognition results are combined into the normal tracking algorithm to catch the position of the vehicle on the trigger line. The experimental results show that the deep learning sliding window based trigger signal generating performance was 100% for the gate passing vehicles including the 5.5% trigger signal position errors due to the minimum bounding box location errors in the vehicle detection process.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제50권9호
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• pp.445-452
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• 2001

Two switching signal patterns are proposed to prevent short circuit of PWM ac choppers. The voltage detection method and the current detection method are proposed to execute two switching signal patterns. In the voltage detection method, the dead-time has to be inserted to the switching signals after polarity of input voltage is checked by voltage transducer at input side. In the current detection method, the direction of load current is checked by current transducer at output side, and the dead-time delay is not considered. Controlling circuit built by current detection method is simple because the dead-time delay is considered. The experimental results are presented to prevent short circuit of ac chopper safely.

• 한국인터넷방송통신학회논문지
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• 제15권6호
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• pp.141-146
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• 2015

다양하게 복합된 소리 및 음성신호를 FPGA의 마이크로 입력받아서 신호를 분류하고 분석하여 이상 신호를 감지할 수 있는 많은 시스템이 있으나, 효율적이며 효과적으로 이상 신호를 감지하는 시스템을 구현하는데 있어서는 많은 문제점들을 가지고 있다. 따라서 이 문제를 해결하고 감지율을 높이기 위하여 본 연구에서 제안된 방법에서는 소리 신호가 입력되는 마이크 센서를 사용하여 FIFO(First-in First-out) 구조에 적용하고, 통계학적으로 분산과 변동계수를 적용한 알고리즘을 기반으로 이상 신호를 효과적으로 분류하고, 효율적으로 감지 여부를 출력하는 시스템을 제안하고 구현하였다. 제안된 알고리즘을 적용한 시스템을 통하여 100회 이상의 실험을 반복한 결과 96.3%의 감지율을 보였다.

• 제어로봇시스템학회논문지
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• 제4권2호
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• pp.246-255
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• 1998

This paper presents a novel method for real-time malfunction detection of plasma etching process using EPD signal traces. First, many reference EPD signal traces are collected using monochromator and data acquisition system in normal etching processes. Critical points are defined by applying differentiation and zero-crossing method to the collected reference signal traces. Critical parameters such as intensity, slope, time, peak, overshoot, etc., determined by critical points, and frame attributes transformed signal-to symbol of reference signal traces are saved. Also, UCL(Upper Control Limit) and LCL(Lower Control Limit) are obtained by mean and standard deviation of critical parameters. Then, test EPD signal traces are collected in the actual processes, and frame attributes and critical parameters are obtained using the above mentioned method. Process malfunctions are detected in real-time by applying SPC(Statistical Process Control) method to critical parameters. the Real-time malfunction detection method presented in this paper was applied to actual processes and the results indicated that it was proved to be able to supplement disadvantages of existing quality control check inspecting or testing random-selected devices and detect process malfunctions correctly in real-time.

• 한국안전학회지
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• 제37권3호
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• pp.16-23
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• 2022

This study aims to provide a fundamental material for identifying fire and no-fire signals using the detection signal characteristics of IoT-based fire-detection systems. Unlike analog automatic fire-detection equipment, IoT-based fire-detection systems employ wireless digital communication and are connected to a server. If a detection signal exceeds a threshold value, the measured values are saved to a server within seconds. This study was conducted with the detection data saved from seven fire accidents that took place in traditional markets from 2020 to 2021, in addition to 233 fire alarm data that have been saved in the K institute from 2016 to 2020. The saved values demonstrated variable and continuous VC-Signals. Additionally, we discovered that the detection signals of two fire accidents in the K institution had a VC-Signal. In the 233 fire alarms that took place over the span of 5 years, 31% of smoke alarms and 30% of temperature alarms demonstrated a VC-Signal. Therefore, if we selectively recognize VC-Signals as fire signals, we can reduce about 70% of false alarms.

• 한국멀티미디어학회논문지
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• 제19권5호
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• pp.818-825
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• 2016

The existing R-peak detection research suggests improving the distortion of the signal such as baseline variations in ECG signals by using preprocessing techniques such as a bandpass filtering. However, preprocessing can introduce another distortion, as it can generate a false detection in the R-wave detection. In this paper, we propose an R-peak detection algorithm in ECG signal, based on primitive signal in order to detect reliably an R-peak in baseline variation. First, the proposed algorithm decides the primitive signal to represent the QRS complex in ECG signal, and by scaling the time axis and voltage axis, extracts multiple primitive signals. Second, the algorithm detects the candidates of the R-peak using the value of the voltage. Third, the algorithm measures the similarity between multiple primitive signals and the R-peak candidates. Finally, the algorithm detects the R-peak using the mean and the standard deviation of similarity. Throughout the experiment, we confirmed that the algorithm detected reliably a QRS group similar to multiple primitive signals. Specifically, the algorithm can achieve an R-peak detection rate greater than an average rate of 99.9%, based on eight records of MIT-BIH ADB used in this experiment.