• 제목/요약/키워드: wavelet technique

검색결과 607건 처리시간 0.022초

Acoustic emission source location and noise cancellation for crack detection in rail head

  • Kuanga, K.S.C.;Li, D.;Koh, C.G.
    • Smart Structures and Systems
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    • 제18권5호
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    • pp.1063-1085
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    • 2016
  • Taking advantage of the high sensitivity and long-distance detection capability of acoustic emission (AE) technique, this paper focuses on the crack detection in rail head, which is one of the most vulnerable parts of rail track. The AE source location and noise cancellation were studied on the basis of practical rail profile, material and operational noise. In order to simulate the actual AE events of rail head cracks, field tests were carried out to acquire the AE waves induced by pencil lead break (PLB) and operational noise of the railway system. Wavelet transform (WT) was first utilized to investigate the time-frequency characteristics and dispersion phenomena of AE waves. Here, the optimal mother wavelet was selected by minimizing the Shannon entropy of wavelet coefficients. Regarding the obvious dispersion of AE waves propagating along the rail head and the high operational noise, the wavelet transform-based modal analysis location (WTMAL) method was then proposed to locate the AE sources (i.e. simulated cracks) respectively for the PLB-induced AE signals with and without operational noise. For those AE signals inundated with operational noise, the Hilbert transform (HT)-based noise cancellation method was employed to improve the signal-to-noise ratio (SNR). Finally, the experimental results demonstrated that the proposed crack detection strategy could locate PLB-simulated AE sources effectively in the rail head even at high operational noise level, highlighting its potential for field application.

이산웨이블렛 변환기법을 이용한 부분방전종류의 신호특징추출에 관한연구 (A Study on Signal Feature Extraction of Partial Discharge Types Using Discrete Wavelet Transform Technique)

  • 박재준;전병훈;김진승;전현구;백관현
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2002년도 춘계학술대회 논문집 유기절연재료 전자세라믹 방전플라즈마 일렉트렛트 및 응용기술
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    • pp.170-176
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    • 2002
  • In this papers, we proposed the feature extraction method due to partial discharge type of transformers. For wavelet transform, Daubechie's filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion, skewness, kurtosis) about acoustic emission signal generated from each partial discharge type. The defects which could occur in a transformer were simulated by using needle-plane electrode, IEC electrode and Void electrode. Also, these coefficients are used to identify signal of partial discharge type electrode fault in transformer. As a result, from compare of acoustic emission amplitude and acoustic average value, we are obtained results of IEC electrode> Void electrode> Needle-Plane electrode. otherwise, In case of skewness and kurtosis, we are obtained results of Needle-Plane electrode electrode> Void electrode> IEC electrode.

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스프레드 스펙트럼 워터마킹 기법의 연구 (A Study on the Spread Spectrum Watermarking Method)

  • 강환일;김갑일;한승수
    • 한국지능시스템학회논문지
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    • 제11권8호
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    • pp.731-735
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    • 2001
  • 본 논문은 새로운 워터마킹기법을 제안하고 이 기법은 실시간 처리에 이용될 수 있다. 웨이브릿변환 대신에 계산량을 줄이기 위해 정수 웨이브릿변환을 이용한다. 본 논문에서 정수 웨이브릿 공간에서 카이자승분포와 관련한 워터마크를 삽입한다. 워터마크를 추출할 때 확산스펙트럼 기법을 이용하고 유사도는 공분산 수열에서 결정하낟. 실험을 통하여 카이 자승분포를 이용한 워터마크를 이용하는 것이 소음에 강인함을 보인다. 이 워터마킹 기법은 동시에 은닉된 정보에 제어되고 오디오 신호에 따라 움직일 수 있는 전기 기기의 제작에 쓰일 수 있다.

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Fault diagnostic system for rotating machine based on Wavelet packet transform and Elman neural network

  • Youk, Yui-su;Zhang, Cong-Yi;Kim, Sung-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제9권3호
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    • pp.178-184
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    • 2009
  • An efficient fault diagnosis system is needed for industry because it can optimize the resources management and improve the performance of the system. In this study, a fault diagnostic system is proposed for rotating machine using wavelet packet transform (WPT) and elman neural network (ENN) techniques. In most fault diagnosis for mechanical systems, WPT is a well-known signal processing technique for fault detection and identification. In previous work, WPT can improve the continuous wavelet transform (CWT) used over a longer computing time and huge operand. It can also solve the frequency-band disagreement by discrete wavelet transform (DWT) only breaking up the approximation version. In the experimental work, the extracted features from the WPT are used as inputs in an Elman neural network. The results show that the scheme can reliably diagnose four different conditions and can be considered as an improvement of previous works in this field.

초저속 전송 네트웍을 위한 웨이브릿 변환을 이용한 비디오 코딩 (Video Coding Using Wavelet Decomposition for Very Low Bit - rate Networks)

  • 오황석;이흥규
    • 한국정보처리학회논문지
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    • 제4권10호
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    • pp.2629-2639
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    • 1997
  • 최근 초저속 전송 매체용 비디오 코딩 기법에 대한 관심이 높아지고 있다. 그러나 기존의 블럭을 기반으로 하는 변환 코딩기법들은 비트율 제한으로 인해 블럭화 현상 등으로 화질 열화가 심하다. 본 논문에서는 초저속 전송 매체를 위하여 웨이브릿 변환과 다중해상도 움직임 추정 및 보상 기법을 이용하는 비디오 코딩 시스템을 제안한다. 제안된 시스템은 non-stationary 신호를 적응적으로 표현하며, 인간 시각 특성을 잘 반영하는 웨이브릿 변환을 사용한다. 웨이브릿 변환된 계수들은 움직임 추정 및 보상 후 예측 오차의 크기에 따라서 다양한 모드로 코딩된다. 이와 함께 일정한 화질을 유지하기 위하여 간단한 버퍼 제어 기법을 사용한다. 실험을 통하여 제안된 기법은 블럭화 현상이 줄어들며, 기존의 블럭을 기반으로 하는 변환 코딩 기법보다 복원 영상의 화질이 좋음을 보였다.

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A Study on Classification and Localization of Structural Damage through Wavelet Analysis

  • 고봉환;정욱
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2007년도 추계학술대회논문집
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    • pp.754-759
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    • 2007
  • This study exploits the data discriminating capability of silhouette statistics, which combines wavelet-based vertical energy threshold technique for the purpose of extracting damage-sensitive features and clustering signals of the same class. This threshold technique allows to first obtain a suitable subset of the extracted or modified features of our data, i.e., good predictor sets should contain features that are strongly correlated to the characteristics of the data without considering the classification method used, although each of these features should be as uncorrelated with each other as possible. The silhouette statistics have been used to assess the quality of clustering by measuring how well an object is assigned to its corresponding cluster. We use this concept for the discriminant power function used in this paper. The simulation results of damage detection in a truss structure show that the approach proposed in this study can be successfully applied for locating both open- and breathing-type damage even in the presence of a considerable amount of process and measurement noise.

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Jammer Identification: Spectral Correlation Function and Wavelet Coherence

  • Jin, Mi Hyun;Choi, Yun Sub;Choi, Heon Ho;Lee, Sang Jeong
    • Journal of Positioning, Navigation, and Timing
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    • 제7권3호
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    • pp.147-153
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    • 2018
  • Jamming countermeasures are used to decrease or prevent the impact of intentional jamming applied to degrade the quality of information provided by a global navigation satellite system (GNSS) receiver. The maximum performance of jamming countermeasure can be obtained only when a proper technique is applied according to the type of jammer. This paper suggests a jamming identification technique for providing information regarding the type of jamming. The center frequency and bandwidth of jammer signal are inconsistent and may change according to time, and thus a spectral correlation function and wavelet coherence were considered in order to analyze the signal in the time and frequency space. Because the two characteristics derive different analysis results, two different identification techniques were suggested and the performances thereof were analyzed. Numerical results show that the two identification techniques have relative advantages and disadvantages as to time consumed and performance. The suggested methods can sufficiently identify the jammer before the GNSS receiver becomes inoperable because of jamming.

주파수 영역에서 웨이브릿 변환을 이용한 디지털 이미지의 효과적인 보호 (The Effective Protection Mechanism for Digital Images using Transform of the Wavelet in Frequency Domain)

  • 최우진;오무송
    • 한국정보통신학회논문지
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    • 제6권6호
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    • pp.937-942
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    • 2002
  • 지난 몇 년 동안 인터넷 기반의 디지털 컨텐츠의 신장으로 인하여 디지털 이미지의 기술과 사용이 대폭 늘어나면서 디지털 이미지의 보호에 대한 필요성이 대두되었다 이러한 디지털 이미지에 대한 저작권 보호를 위해서는 이미지의 내용 인증과 소유권 인증, 불법 복제 등을 확인할 수 있는 인증 기술이 요구된다. 눈에 띄지 않는 암호인 디지털 워터마크를 이미지에 삽입하는 기술인 디지털 워터마킹은 이미지의 투명성과 견고성을 제공해야 하며, 이를 위하여 정교한 인지 정보가 워터마킹 처리에 사용되어야 한다. 또 논문에서는 인간 중심의 시각 시스템의 관점에서 주파수 기반의 워터마크인 웨이브릿 변환을 통한 저작권 보호와 인증과 위조 방지에 대한 알고리즘을 구현하고자 한다.

이진트리 비 균일 필터뱅크를 이용한 잡음감소기법 및 구현 (A Noise De-Noising Technique using Binary-Tree Non-Uniform Filter Banks and Its Realization)

  • 손상욱;최훈;배현덕
    • 대한전자공학회논문지SP
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    • 제44권5호
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    • pp.94-102
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    • 2007
  • 잠음감소에 있어서 웨이브렛 임계처리 알고리즘은 미니맥스 관점에서 거의 최적의 성능을 보이는 것으로 알려져 있다. 그러나 웨이브렛 임계처리 알고리즘은 웨이브렛 함수의 복잡성으로 인해 FPGA와 같은 하드웨어 상에 구현이 어렵다. 본 논문에서는 이진트리 구조 필터뱅크에서 전체 신호전력에 대한 각 부밴드 신호 전력비에 기반한 새로운 잡음감소 기법을 제안한다. 그리고 이 기법을 FPGA 상에 구현한다. 간단한 구현을 위해 필터뱅크는 하다마드 변환 계수로 설계된다. 시뮬레이션과 하드웨어 실험결과 제안방법이 간단하지만 웨이브렛에 기반한 소프트 임계처리 잡음감소 알고리즘과 성능이 유사함을 보인다.

Detection of Microcalcification Using the Wavelet Based Adaptive Sigmoid Function and Neural Network

  • Kumar, Sanjeev;Chandra, Mahesh
    • Journal of Information Processing Systems
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    • 제13권4호
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    • pp.703-715
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    • 2017
  • Mammogram images are sensitive in nature and even a minor change in the environment affects the quality of the images. Due to the lack of expert radiologists, it is difficult to interpret the mammogram images. In this paper an algorithm is proposed for a computer-aided diagnosis system, which is based on the wavelet based adaptive sigmoid function. The cascade feed-forward back propagation technique has been used for training and testing purposes. Due to the poor contrast in digital mammogram images it is difficult to process the images directly. Thus, the images were first processed using the wavelet based adaptive sigmoid function and then the suspicious regions were selected to extract the features. A combination of texture features and gray-level co-occurrence matrix features were extracted and used for training and testing purposes. The system was trained with 150 images, while a total 100 mammogram images were used for testing. A classification accuracy of more than 95% was obtained with our proposed method.