• 제목/요약/키워드: signal pattern recognition

검색결과 281건 처리시간 0.024초

용접결함의 패턴분류를 위한 특징변수 유효성 검증 (Availability Verification of Feature Variables for Pattern Classification on Weld Flaws)

  • 김창현;김재열;유홍연;홍성훈
    • 한국공작기계학회논문집
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    • 제16권6호
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    • pp.62-70
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    • 2007
  • In this study, the natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. Feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

MFCC-HMM-GMM을 이용한 근전도(EMG)신호 패턴인식의 성능 개선 (Performance Improvement of EMG-Pattern Recognition Using MFCC-HMM-GMM)

  • 최흥호;김정호;권장우
    • 대한의용생체공학회:의공학회지
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    • 제27권5호
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    • pp.237-244
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    • 2006
  • This study proposes an approach to the performance improvement of EMG(Electromyogram) pattern recognition. MFCC(Mel-Frequency Cepstral Coefficients)'s approach is molded after the characteristics of the human hearing organ. While it supplies the most typical feature in frequency domain, it should be reorganized to detect the features in EMG signal. And the dynamic aspects of EMG are important for a task, such as a continuous prosthetic control or various time length EMG signal recognition, which have not been successfully mastered by the most approaches. Thus, this paper proposes reorganized MFCC and HMM-GMM, which is adaptable for the dynamic features of the signal. Moreover, it requires an analysis on the most suitable system setting fur EMG pattern recognition. To meet the requirement, this study balanced the recognition-rate against the error-rates produced by the various settings when loaming based on the EMG data for each motion.

Pattern Recognition Methods for Emotion Recognition with speech signal

  • Park Chang-Hyun;Sim Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제6권2호
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    • pp.150-154
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    • 2006
  • In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition are determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section.

초음파신호의 특징 파라메터 및 증거축적 방법을 이용한 콘크리트 강도 분류 (Pattern Classification of the Strength of Concrete by Feature Parameters and Evidence Accumulation of Ultrasonic Signal)

  • 김세동;신동환;이영석;김성환
    • 대한전기학회논문지:전력기술부문A
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    • 제48권10호
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    • pp.1335-1343
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    • 1999
  • This paper presents concrete pattern recognition method to identify the strength of concrete by evidence accumulation with multiple parameters based on artificial intelligence techniques. At first, zero-crossing(ZCR), mean frequency(MEANF), median frequency(MEDF) and autoregressive model coefficient(ARC) are extracted as feature parameters from ultrasonic signal of concrete. Pattern recognition is carried out through the evidence accumulation procedure using distance measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. Results are presented to support the feasibility of the suggested approach for concrete pattern recognition.

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UT 신호형상 인식을 위한 Intelligence Package 개발과 Austenitic Stainless Steel Welding부 결함 분류에 관한 적용 연구 (Intelligence Package Development for UT Signal Pattern Recognition and Application to Classification of Defects in Austenitic Stainless Steel Weld)

  • 이강용;김준섭
    • 비파괴검사학회지
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    • 제15권4호
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    • pp.531-539
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    • 1996
  • 본 연구에서는 초음파 신호형상인식법을 이용하여 용접부의 인공 결함을 분류하기 위한 연구를 실시하였다. 이를 위해 신호처리 및 특징 변수를 추출할 때에 많은 사용자 정의 변수를 가지는 신호 형상 인식 패키지를 개발하였으며 디지탈 신호처리, 특징 변수 추출, 특징 변수의 선택, 분류기 선정 등의 과정을 일괄적으로 처리하였다. 특히, 선형 분류기, 경험적 Bayesian 분류기 등의 통계적 분류기와 신경회로망 분류기를 함께 사용하여 비교, 검토하였다. 이에 관한 적용 연구로 노치와 구멍으로 이루어진 인공 결함을 분류하였다. 그 결과 인공결함 분류에서 높은 인식률을 얻었으며, 특히 적절히 학습 시켰을 경우 신경회로망 분류기가 통계적 분류기에 비하여 인식률 면에서 유리하였다.

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Fuzzy Syntactic Pattern Recognition Approach for Extracting and Classifying Flaw Patterns from and Eddy-Current Signal Waveform

  • Kang, Soon-Ju
    • Journal of Electrical Engineering and information Science
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    • 제2권4호
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    • pp.59-65
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    • 1997
  • In this paper, a general fuzzy syntactic method for recognition of flaw patterns and for the measurement of flaw characteristic parameters for a non-destructive inspections signal, called eddy-current, is presented. Solutions are given to the subtasks of primitive pattern selection, signal to symbol transformation, pattern grammar formulation, and event-synchronous flaw pattern extraction based on the grammars. Fuzzy attribute grammars are used as the model for the pattern grammar because of their descriptive power in the face of uncertain constraints caused by nose or distortion in the signal waveform, due to their ability to handle syntactic as well as semantic information. This approach has been implemented and the performance of eh resultant system has been evaluated using a library of law patterns obtained from steam generator tubes in nuclear power plants by an eddy current-based non-destructive inspection method.

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카메라 Back Cover의 형상인식 및 납땜 검사용 Vision 기술 개발 (Development of Vision Technology for the Test of Soldering and Pattern Recognition of Camera Back Cover)

  • 장영희
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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    • pp.119-124
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    • 1999
  • This paper presents new approach to technology pattern recognition of camera back cover and test of soldering. In real-time implementing of pattern recognition camera back cover and test of soldering, the MVB-03 vision board has been used. Image can be captured from standard CCD monochrome camera in resolutions up to 640$\times$480 pixels. Various options re available for color cameras, a synchronous camera reset, and linescan cameras. Image processing os performed using Texas Instruments TMS320C31 digital signal processors. Image display is via a standard composite video monitor and supports non-destructive color overlay. System processing is possible using c30 machine code. Application software can be written in Borland C++ or Visual C++

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영상 신호에서 패턴인식을 이용한 다중 포인트 변위측정 (Displacement Measurement of Multi-point Using a Pattern Recognition from Video Signal)

  • 전형섭;최영철;박종원
    • 한국소음진동공학회논문집
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    • 제18권12호
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    • pp.1256-1261
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    • 2008
  • This paper proposes a way to measure the displacement of a multi-point by using a pattern recognition from video signal. Generally in measuring displacement, gab sensor, which is a displacement sensor, is used. However, it is difficult to measure displacement by using a common sensor in places where it is unsuitable to attach a sensor, such as high-temperature areas or radioactive places. In this kind of places, non-contact methods should be used to measure displacement and in this study, images of CCD camera were used. When multi-point is measure by using a pattern recognition, it is possible to measure displacement with a non-contact method. It is simple to install and multi-point displacement measuring device so that it is advantageous to solve problems of spatial constraints.

심전도 신호의 신택틱 패턴인식 (Syntatic Pattern recognition of the ECG)

  • 남승우;이병채;신건수;이재준;이명호
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1991년도 추계학술대회
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    • pp.129-132
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    • 1991
  • This paper describes the ECG pattern recognition using the syntatic pattern recognition algorithm. The algorithm uses the BNF rule wi th the semantic evaluation which has the structural Information of the ECG. This algorithm is constructed with (1) removing the baseline drift by the Cubic spline function and exract the significant point by the line-approximation algorithm, (2) syntatic peak recognition algorithm with the extracted significant point, (3) produce the token which is used pattern recognition, (4) pattern recognition of the ECG by the syntatic pattern recognition algorithm, (5) extract the parameter with the pattern recognized ECG signal.

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은닉 마르코프 모형을 이용한 회전체 결함신호의 패턴 인식 (Pattern Recognition of Rotor Fault Signal Using Bidden Markov Model)

  • 이종민;김승종;황요하;송창섭
    • 대한기계학회논문집A
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    • 제27권11호
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    • pp.1864-1872
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    • 2003
  • Hidden Markov Model(HMM) has been widely used in speech recognition, however, its use in machine condition monitoring has been very limited despite its good potential. In this paper, HMM is used to recognize rotor fault pattern. First, we set up rotor kit under unbalance and oil whirl conditions. Time signals of two failure conditions were sampled and translated to auto power spectrums. Using filter bank, feature vectors were calculated from these auto power spectrums. Next, continuous HMM and discrete HMM were trained with scaled forward/backward variables and diagonal covariance matrix. Finally, each HMM was applied to all sampled data to prove fault recognition ability. It was found that HMM has good recognition ability despite of small number of training data set in rotor fault pattern recognition.