• Title/Summary/Keyword: Signal Pattern

검색결과 1,423건 처리시간 0.03초

Enhancement of Fall-Detection Rate using Frequency Spectrum Pattern Matching

  • 이수환;오동익;남윤영
    • 인터넷정보학회논문지
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    • 제18권3호
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    • pp.11-17
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    • 2017
  • To the elderly, sudden falls are one of the most frightening accidents. If an accident occurs, a prompt action has to be taken to deal with the situation. Recently, there have been a number of attempts to detect sudden falls using acceleration sensors embedded in the mobile devices, such as smart phones and wrist-bands. However, using the sensor readings only, the detection rate of the falls is around 65%. Ordinary daily activities such as running or jumping could not be well distinguished from the falls. In this paper, we describe our attempts on improving the fall-detection rate. We implemented a wrist-band fall detection module, using a three-axis acceleration sensor. With the pattern matching on the fall signal-strength frequency spectrum, in addition to the conventional signal strength measurement, we could improve the detection rate by 9% point. Furthermore, by applying two wrist-bands in the experiment, we could further improve the detection rate to 82%.

초음파의 형상인식법을 이용한 저널베어링의 마멸파손 검지 (The Early Detection of Journal Bearing Failures by a Pattern Recognition of Ultrasonic Wave)

  • 윤의성;손동구;안효석
    • 대한기계학회논문집
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    • 제17권8호
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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.

혼합형 신경회로망을 이용한 근전도 패턴 분류에 의한 가상 로봇팔 제어 방식 (The Virtual Robot Arm Control Method by EMG Pattern Recognition using the Hybrid Neural Network System)

  • 정경권;김주웅;엄기환
    • 한국정보통신학회논문지
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    • 제10권10호
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    • pp.1779-1785
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    • 2006
  • 본 논문은 근전도 패턴 인식에 의한 가상 로봇팔 제어 방식을 제안한다. 고차원의 근전도 신호를 정밀하게 분류하기 위하여 혼합형 신경 회로망 방식을 사용한다. 혼합형 신경회로망은 SOFM과 LVQ로 구성되고, 고차원의 EMG 신호를 2차원 데이터로 변환한다. 3개의 표면 전극을 이용하여 EMG 신호를 측정 한다. 제안한 혼합 시스템을 이용하여 한글 자음 6개의 수화 신호를 분류한다. 가상 로봇팔 실험을 통해서 제안한 혼합 시스템을 이용한 수신호의 EMG 패턴 인식의 유용성을 확인하였다.

Application of SA-SVM Incremental Algorithm in GIS PD Pattern Recognition

  • Tang, Ju;Zhuo, Ran;Wang, DiBo;Wu, JianRong;Zhang, XiaoXing
    • Journal of Electrical Engineering and Technology
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    • 제11권1호
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    • pp.192-199
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    • 2016
  • With changes in insulated defects, the environment, and so on, new partial discharge (PD) data are highly different from the original samples. It leads to a decrease in on-line recognition rate. The UHF signal and pulse current signal of four kinds of typical artificial defect models in gas insulated switchgear (GIS) are obtained simultaneously by experiment. The relationship map of ultra-high frequency (UHF) cumulative energy and its corresponding apparent discharge of four kinds of typical artificial defect models are plotted. UHF cumulative energy and its corresponding apparent discharge are used as inputs. The support vector machine (SVM) incremental method is constructed. Examples show that the PD SVM incremental method based on simulated annealing (SA) effectively speeds up the data update rate and improves the adaptability of the classifier compared with the original method, in that the total sample is constituted by the old and new data. The PD SVM incremental method is a better pattern recognition technology for PD on-line monitoring.

오스테나이트계 스테인리스강 304 용접부의 초음파 형상 인식 평가를 위한 카오스 시뮬레이터의 구축 (Construction fo chaos simulator for ultrasonic pattern recognition evaluation of weld zone in austenitic stainless steel 304)

  • 이원;윤인식;장영권
    • Journal of Welding and Joining
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    • 제16권5호
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    • pp.108-118
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    • 1998
  • This study proposes th analysis and evaluation method of time series ultrasonic signal using the chaos feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaos time series signal analyze quantitatively weld defects. For this purpose, analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaosity resulting from distance shifts such as 0.5 and 1.0 skip distance. Such differences in chaosity enables the evaluation of unique features of defects in the weld zone. In quantitative chaos feature extraction, feature values of 4.511 and 0.091 in the case of side hole and 4.539 and 0.115 in the case of vertical hole were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaos feature extraction in this study can enhances ultrasonic pattern recognition results from defect signals of weld zone such as side hole and vertical hole.

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음성 신호를 사용한 GMM기반의 감정 인식 (GMM-based Emotion Recognition Using Speech Signal)

  • 서정태;김원구;강면구
    • 한국음향학회지
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    • 제23권3호
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    • pp.235-241
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    • 2004
  • 본 논문은 화자 및 문장 독립적 감정 인식을 위한 특징 파라메터와 패턴인식 알고리즘에 관하여 연구하였다. 본 논문에서는 기존 감정 인식 방법과의 비교를 위하여 KNN을 이용한 알고리즘을 사용하였고, 화자 및 문장 독립적 감정 인식을 위하여 VQ와 GMM을 이용한 알고리즘을 사용하였다. 그리고 특징으로 사용한 음성 파라메터로 피치, 에너지, MFCC, 그리고 그것들의 1, 2차 미분을 사용하였다. 실험을 통해 피치와 에너지 파라메터를 사용하였을 때보다 MFCC와 그 미분들을 특징 파라메터로 사용하였을 때 더 좋은 감정 인식 성능을 보였으며, KNN과 VQ보다 GMM을 기반으로 한 인식 알고리즘이 화자 및 문장 독립적 감정 인식 시스템에서 보다 적합하였다.

LOC 형광검출 소자를 위한 광 다이오드의 제작 및 특성 평가 (Development of Photo-diode for LOC fluorescence detector)

  • 김주환;신경식;김용국;김상식;주병권
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2003년도 춘계학술대회 논문집 디스플레이 광소자분야
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    • pp.100-103
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    • 2003
  • Signal detection technologies such as fluorescence, charge and electrochemical detection used in the monolithic capillary electrophoresis system to convert the biochemical reaction into the electrical signal. The fluorescence detection using photodiodes that measure fluorescence emitted from eluting molecules is widely used for the monolithic capillary electrophoresis system. In this paper, in order to fabricate a photosensor has the increased sensitivity, we investigated on the sensitivity of general type and p-i-n type diode. The p-i-n diode has higher sensitivity than photodiode. Considering these results, we fabricated p-i-n diodes on the high resistive$(4k{\Omega}{\cdot}cm)$ wafer into rectangle and finger pattern and compared internal resistance of each pattern. The internal resistance of p-i-n diode can be decreased by the application of finger pattern has parallel resistance structure from $571{\Omega}$ to $393{\Omega}$.

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전기부하 패턴분류를 위한 신호처리 기법에 관한 연구 (A Study on the Signal Processing Techiques for Pattern Classification of Electrical Loads)

  • 임용배;김동우;진상민;조성원
    • 한국지능시스템학회논문지
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    • 제26권5호
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    • pp.409-415
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    • 2016
  • 최근 사물인터넷 기반의 재해예방 기술이 개발되고 있다. 본 논문에서는 사물인터넷기반의 공동주택용 자율전기안전관리 기술 개발을 위하여 부하 전류 파형을 FFT와 MFCC를 이용하여 신호변환 후 신경회로망 모델에 적용하여 정확도가 개선된 전기 부하 패턴분류 시스템을 제안한다. 오실로스코프와 CT를 이용하여 측정한 전기 부하의 전류 파형을 FFT 알고리즘을 적용한 후 신경회로망을 이용하여 단일부하패턴 분류 실험을 하였다. 본 연구를 통하여 부하의 특성을 파악함으로서 고장에 대해 보다 신속하고 정확하게 대처할 수 있을 것으로 예측된다.

레이저 파면 획득용 Lenslet Array 점 패턴 검출 알고리즘 (Detection Algorithm of Lenslet Array Spot Pattern for Acquisition of Laser Wavefront)

  • 이재일;이영철;허준
    • 한국군사과학기술학회지
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    • 제8권4호
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    • pp.110-119
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    • 2005
  • In this paper, a new detection algorithm was proposed for finding the position of lenslet array spot pattern used to acquire laser wavefront. Based on the analysis of the required signal processing characteristics, we categorized into and designed four main signal processing functions. The proposed was designed in order to have robust feature against a variation of geometrical form of the spot and also implemented to have semi-automatic thresholding capability based on CCD noise analysis. For performance evaluation, we made qualitative and quantitative comparisons with Carvalho's algorithm which has been published in recent. In the given experimental spot images, the proposed could detect the spots which has 1/3 times lower than the least S/N of which Carvalho's can detect and could reach to a detection precision of 0.1 pixel at the S/N. In functional aspect, the proposed could separate all valid spots locally. From these results, the proposed could have a superior precision of location detection of spot pattern in wider S/N range.

PVA를 이용한 산업용 모터 고장진단 모니터링 시스템의 가시성을 높이는 방법 (Method for High-visibility of Online Monitoring and Fault Diagnosis System for Industrial Motor using PVA)

  • 고영진;강인원
    • 대한안전경영과학회지
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    • 제22권1호
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    • pp.15-21
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    • 2020
  • Industrial Motors diagnostic equipment is highly dependent on the automation system, so if there are defects in the automation equipment, it can only rely on the operator's intuitive judgment.To help with intuitive judgment, Park's Vactor Approach(PVA) represents the current signal as a pattern of circles, so it can tell if a fault occurs when the circle is distorted. However, the failure to judge the degree of distortion of the circle pattern is the basis of the fault, so it will face difficulties. In this paper, in order to compare the faults of PVA, the period of d-axis current of PVA pulsation was mastered, so that two phase differences occurred in the same signal source. Through experiments, it is confirmed that this is a 90 degree cross formation of PVA, which is convenient for judging from the vision that there is no fault, thus helping the operator to make intuitive judgment.