• 한국음향학회지
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• 제38권1호
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• pp.23-29
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• 2019

본 논문에서는 국내에서 발생한 지진 신호를 검출 및 식별하기 위한 방법을 다루었다. 국내에서 발생한 지진 신호들을 분석해 본 결과 서로 다른 주파수 대역 신호의 특징들이 각각 분류를 위한 특징으로 적절함을 확인할 수 있었다. 이러한 분석 결과를 바탕으로 지진 신호에서 추출한 다중 주파수 대역 특징을 기반으로 하는 CNN(Convolutional Neural Network) 기법에 대해서 제안하였다. 제안하는 다중 주파수 대역 CNN 기법은 지진 신호에서 추출한 멜 스펙트럼에 대해서 각각 필터를 적용하여 서로 다른 주파수 대역(저/중/고 주파수)의 신호를 추출하였다. 추출된 신호들을 바탕으로 각각 CNN 기반 분류를 수행하였고, 수행된 결과를 융합하여 최종적으로 지진 이벤트에 대해 식별하였다. 2018년 동안 대한민국에서 발생한 실제 지진데이터를 기반으로 하는 실험을 통해 제안하는 기법에 대한 효용성을 검증하였다.

• 산업경영시스템학회지
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• 제44권2호
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• pp.115-123
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• 2021

A lot of sensor and control signals is generated by an industrial controller and related internet-of-things in discrete manufacturing system. The acquired signals are such records indicating whether several process operations have been correctly conducted or not in the system, therefore they are usually composed of binary numbers. For example, once a certain sensor turns on, the corresponding value is changed from 0 to 1, and it means the process is finished the previous operation and ready to conduct next operation. If an actuator starts to move, the corresponding value is changed from 0 to 1 and it indicates the corresponding operation is been conducting. Because traditional fault detection approaches are generally conducted with analog sensor signals and the signals show stationary during normal operation states, it is not simple to identify whether the manufacturing process works properly via conventional fault detection methods. However, digital control signals collected from a programmable logic controller continuously vary during normal process operation in order to show inherent sequence information which indicates the conducting operation tasks. Therefore, in this research, it is proposed to a recurrent neural network-based fault detection approach for considering sequential patterns in normal states of the manufacturing process. Using the constructed long short-term memory based fault detection, it is possible to predict the next control signals and detect faulty states by compared the predicted and real control signals in real-time. We validated and verified the proposed fault detection methods using digital control signals which are collected from a laser marking process, and the method provide good detection performance only using binary values.

• 한국임상약학회지
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• 제31권4호
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• pp.324-331
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• 2021

To investigate signals of adverse drug reactions of finasteride by using the Korea Adverse Events Reporting System (KAERS) database. This pharmacovigilance was based on the database of the drug-related adverse reactions reported spontaneously to the KAERS from 2013 to 2017. This study was conducted by disproportionality analysis. Data mining analysis was performed to detect signals of finasteride. The signal was defined by three criteria as proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC). The signals of finasteride were compared with those of the other drugs; dutasteride (similar mechanism of action), minoxidil (different mechanism but similar indications for alopecia), silodosin (different mechanism but similar indications for BPH). It was examined whether the detected signals exist in drug labels in Korea. The total number of adverse event-drug pairs was reported 2,665,429 from 2013 to 2017, of which 1,426 were associated with finasteride. The number of investigated signals of finasteride was 42. The signals that did not include in the drug label were 29 signals, including mouth dry, hypotension, dysuria etc. The signal of finasteride was similar to that of dutasteride and silodosin but was different to that of minoxidil. Early detection of signals through pharmacovigilance is important to patient safety. We investigated 29 signals of finasteride that do not exist in drug labels in Korea. Further pharmacoepidemiological studies should be needed to evaluate the signal causality with finasteride.

• 한국음향학회지
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• 제24권7호
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• pp.387-394
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• 2005

본 논문에서는 다채널 오디오 시스템의 스피커들을 직렬로 연결하기 위한 새로운 오디오 신호 전송 기법을 제시한다. 다채널 오디오 본체로부터의 아날로그 신호는 디지털 신호로 변환되고 신호 처리 과정을 거쳐서 직렬로 연결된 각 스피커에 전달된다. 여기서 신호 처리 과정은 오디오 신호의 특성을 고려한 데이터 압축과 전송을 위한 패킷 생성을 포함한다. 각 스피커는 전달된 패킷으로부터 해당하는 디지털 신호만을 검출하여 아날로그 신호로 다시 변환하여 음향을 재생한다. 제시된 모든 기능은 VHDL을 사용하여 모델링되었으며 FPGA 칩으로 구현하였고 실제 다채널 오디오 시스템에서 테스트하였다.

• Steel and Composite Structures
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• 제19권1호
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• pp.131-152
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• 2015

Easy detection and evaluation of defect in the tube structure is a continuous problem and remains a significant demand in tube inspection technologies. This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. The stress wave signals from vibrational impact excitation on several tube conditions were captured to identify the defect in ASTM A179 seamless steel tubes. The variation in stress wave propagation was captured by a high frequency sensor. Stress wave signals from four tubes with artificial defects of different depths and one reference tube were classified using the autoregressive (AR) algorithm. The results were demonstrated using a dendrogram. The preliminary research revealed the natural arrangement of stress wave signals were grouped into two clusters. The stress wave signals from the healthy tube were grouped together in one cluster and the signals from the defective tubes were classified in another cluster. This approach was effective in separating different stress wave signals and allowed quicker and easier defect identification and interpretation in steel tubes.

• 전자공학회논문지
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• 제54권4호
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• pp.75-80
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• 2017

전자전지원 시스템(Electronic Warfare Support System)은 레이더 신호의 식별을 위해 수집한 신호의 주파수, 펄스폭, 펄스반복주기(PRI, Pulse Repetition Interval)등의 정보를 분석한 후 기존의 알려진 레이더 정보와 비교한다. 기존의 연구는 두 가지 단점이 있다. 첫 번째 단점은 기존의 알려진 레이더 정보를 마지막 비교단계에서만 비교한다는 점이다. 두 번째 단점은 PRI를 계산하기 위해 많은 연산이 필요하다는 점이다. 본 논문에서는 사전에 알려진 레이더 정보를 초기단계에서 활용하여 PRI를 계산하지 않고 수집된 신호에 미리 알고 있는 레이더 신호의 존재 여부를 식별하는 방법을 제안한다.

• 비파괴검사학회지
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• 제26권6호
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• pp.403-410
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• 2006

Eddy current testing (ECT) signals produced by a differential bobbin coil probe vary according to probe design parameters such as the number of turns, geometry and coil gap size. In the present study, the characteristics of a differential bobbin coil probe signals are investigated by numerical simulation in order to determine the optimum coil gap. For verification of numerical simulation accuracy, a specially designed bobbin probe of which the coil gap can be adjusted is fabricated and a series of experiments to acquire signals from two kinds of standard tubes with the variation in coil gap is performed. Then, the experimental signals are compared to the simulation results. Based on this investigation, a decision on the optimum range of coil gap is made. The theoretically predicted signals agree very well to the experimental signals. In fact, this excellent agreement demonstrates a high potential of the simulation as a design optimization tool for ECT bobbin probes.

• 한국멀티미디어학회논문지
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• 제19권1호
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• pp.68-79
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• 2016

Electromyographic (EMG) signals have been widely used as motion commands of prosthetic arms. Although EMG signals contain meaningful information including the movement intentions of human body, it is difficult to predict the subject's motion by analyzing EMG signals in real-time due to the difficulties in extracting motion information from the signals including a lot of noises inherently. In this paper, four Ag/AgCl electrodes are placed on the surface of the subject's major muscles which are in charge of four upper arm movements (wrist flexion, wrist extension, ulnar deviation, finger flexion) to measure EMG signals corresponding to the movements. The measured signals are sampled using DAQ module and clustered sequentially. The Fuzzy C-Means (FCMs) method calculates the center values of the clustered data group. The fuzzy system designed to detect the upper arm movement intention utilizing the center values as input signals shows about 90% success in classifying the movement intentions.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1997년도 영남지회 학술발표회 논문집 Acoustic Society of Korean Youngnam Chapter Symposium Proceedings
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• pp.27-34
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• 1997

In this study , we tried to test the classification performance of a neural netow and thereby to examine its applicability to the signals distorted by a shallow water einvironment . We conducted an acoustic experiment iin a shallow sea near Pohang, Korea in which water depth is about 60m. The signals, on which the network has been tested, is ilinear frequency modulated ones centered on one of the frequencies, 200, 400, 600 and 800 Hz, each being swept up or down with bandwidth 100Hz. we considered two transforms, STFT(short-time Fourier transform) and PWVD (pseudo Wigner-Ville distribution), form which power spectra were derived. The training signals were simulated using an acoutic model based on the Fourier synthesis scheme. When the network has been trained on the measured signals of center frequency 600Hz,it gave a little better results than that trained onthe simulated . With the center frequencies varied, the overall performance reached over 90% except one case of center frequency 800Hz. With the feature extraction techniques(STFT and PWVD) varied,the network showed performance comparable to each other . In conclusion , the signals which have been simulated with water depth were successully applied to training a neural network, and the trained network performed well in classifying the signals distorted by a surrounding environment and corrupted by noise.

• 한국통신학회논문지
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• 제32권11A호
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• pp.1213-1218
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• 2007

본 연구에서는 일본 TV 방송 신호의 월경실태를 파악하기 위하여 부산에 측정 시스템을 구성하고, 그 신호들을 APD 곡선으로 분석하였다. 부산에서 2006년 2월부터 10월까지 약 9개월 일본 방송신호에 대해서 측정하였다. 측정된 영상의 질은 최고영상이 2.5 레벨이고, 음질은 최대음질이 3 레벨이다. 일본 방송신호에 대한 분석결과 부산에서 일본 방송을 관찰할 수 있었으며, 특히 36과 38번 채널에 대해서는 계절에 따른 APD 곡선을 그려 분석하였다.