• Title/Summary/Keyword: wavelet packet transform

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Statistical damage classification method based on wavelet packet analysis

  • Law, S.S.;Zhu, X.Q.;Tian, Y.J.;Li, X.Y.;Wu, S.Q.
    • Structural Engineering and Mechanics
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    • v.46 no.4
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    • pp.459-486
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    • 2013
  • A novel damage classification method based on wavelet packet transform and statistical analysis is developed in this study for structural health monitoring. The response signal of a structure under an impact load is normalized and then decomposed into wavelet packet components. Energies of these wavelet packet components are then calculated to obtain the energy distribution. Statistical similarity comparison based on an F-test is used to classify the structure from changes in the wavelet packet energy distribution. A statistical indicator is developed to describe the damage extent of the structure. This approach is applied to the test results from simply supported reinforced concrete beams in the laboratory. Cases with single and two damages are created from static loading, and accelerations of the structure from under impact loads are analyzed. Results show that the method can be used with no reference baseline measurement and model for the damage monitoring and assessment of the structure with alarms at a specified significance level.

Improvement of Strain Detection Accuracy of Aircraft FBG Sensors Using Stationary Wavelet Transform (정상 웨이블릿 변환을 이용한 항공기 FBG 센서의 변형률 탐지 정확도 향상)

  • Son, Yeong-Jun;Shin, Hyun-Sung;Hong, Gyo-Young
    • Journal of Advanced Navigation Technology
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    • v.23 no.4
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    • pp.273-280
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    • 2019
  • There are many studies that use structure health monitoring to reduce maintenance costs for aircraft and to increase aircraft utilization. Many studies on FBG sensors are also being conducted. However, if the FBG sensor is installed inside the composite, voids will occur between the layers of the composite, resulting in signal split problem. In addition, the FBG sensor is not affected by electromagnetic waves, but will produce electromagnetic noise caused by electronic equipment during post-processing. In this paper, to reduce the error caused by these noises, the stationary wavelet transform, which has the characteristics of movement immutability and is efficient in nonlinear signal analysis, is presented. And in the above situation, we found that noise rejection performance of stationary wavelet transform was better compared with the wavelet packet transform.

Wavelet Packet-Based Progressive Image Transmission (Wavelet Packet 기반 점진적 영상 전송)

  • Song, Joon-Ho;Lee, Gi-Hun;Park, Rae-Hong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.8
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    • pp.77-85
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    • 1998
  • This paper proposes progressive image transmission(PIT) methods based on the wavelet packet transform, in which quantizers are optimized at each stage for the given bit rate. Scalar and vector quantizers are used and the performance of each quantizer is compared. After quantization, selected subbands are ordered by their priority for transmission. Subjective quality of the reconsetructed image is improved by human visual system (HVS) weighting.

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Image Denosing Based on Wavelet Packet with Absolute Average Threshold (절대평균임계값을 적용한 웨이블릿 패킷 기반의 영상 노이즈 제거)

  • Ryu, Kwang-Ryol;Sclabassi, Robert J.
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.605-608
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    • 2007
  • The denoising for image restoration based on the Wavelet Packet with absolute average threshold is presented. The Existing method is used standard deviation estimated results in increasing the noise and threshold, and damaging an image quality. In addition that is decreased image restoration PSNR by using the same threshold in spite of changing image because of installing a threshold in proportion of noise size. In contrast, the absolute average threshold with wavelet packet is adapted by changing image to set up threshold by statistic quantity of resolved image and is avoided an extreme impart. The results on the experiment has improved 10% and 5% over than the denoising based on simple wavelet transform and wavelet packet respectively.

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Development of Non-destructive Evaluation Method for Composite Structures using Tapping Sound (타격음을 이용한 복합재료 구조물의 비파괴 검사법 개발)

  • 황준석;김승조
    • Composites Research
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    • v.17 no.1
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    • pp.1-9
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    • 2004
  • A new non-destructive evaluation method using tapping sound is proposed. This method, named Tapping Sound Analysis, is using the difference between tapping sound data of healthy structure and defective structure as the criteria of determination of internal defect of composite structure. For the characterization of tapping sound, a feature extraction method based on wavelet packet transform is proposed. And a feature index is defined for the decision of existence of internal defects. To prove the possibility of proposed method as a non-destructive evaluation method, experimental study is performed. The tapping sound data of healthy structure and defective structure are measured and compared based on the proposed decision method. The experimental results showed that the feature index is a good indicator for the determination of internal defects.

Efficient Noise Estimation for Speech Enhancement in Wavelet Packet Transform

  • Jung, Sung-Il;Yang, Sung-Il
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.4E
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    • pp.154-158
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    • 2006
  • In this paper, we suggest a noise estimation method for speech enhancement in nonstationary noisy environments. The proposed method consists of the following two main processes. First, in order to receive fewer affect of variable signals, a best fitting regression line is used, which is obtained by applying a least squares method to coefficient magnitudes in a node with a uniform wavelet packet transform. Next, in order to update the noise estimation efficiently, a differential forgetting factor and a correlation coefficient per subband are used, where subband is employed for applying the weighted value according to the change of signals. In particular, this method has the ability to update the noise estimation by using the estimated noise at the previous frame only, without utilizing the statistical information of long past frames and explicit nonspeech frames by voice activity detector. In objective assessments, it was observed that the performance of the proposed method was better than that of the compared (minima controlled recursive averaging, weighted average) methods. Furthermore, the method showed a reliable result even at low SNR.

Condition Monitoring of an LCD Glass Transfer Robot Based on Wavelet Packet Transform and Artificial Neural Network for Abnormal Sound (LCD 라인의 음향 특성신호에 웨이브렛 변환과 인경신경망회로를 적용한 공정로봇의 건정성 감시 연구)

  • Kim, Eui-Youl;Lee, Sang-Kwon;Jang, Ji-Uk
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.7
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    • pp.813-822
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    • 2012
  • Abnormal operating sounds radiated from a moving transfer robot in LCD (liquid crystal display) product lines have been used for the fault detection line of a robot instead of other source signals such as vibrations, acoustic emissions, and electrical signals. Its advantage as a source signal makes it possible to monitor the status of multiple faults by using only a microphone, despite a relatively low sensitivity. The wavelet packet transform for feature extraction and the artificial neural network for fault classification are employed. It can be observed that the abnormal operating sound is sufficiently useful as a source signal for the fault diagnosis of mechanical components as well as other source signals.

Band Estimation using Third-order Statistics and Wavelet Packet Transform (3차 통계기법과 웨이블릿 패킷 변환을 이용한 대역 추정 알고리즘)

  • 박현석;이종희;남상원
    • Proceedings of the IEEK Conference
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    • 2000.09a
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    • pp.923-926
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    • 2000
  • In this paper we address the problem of detecting and estimating an unknown narrow band signal in a noise interference environment A new practical band estimation method, yielding good performance even in case of finite-length data, is presented. More specifically, wavelet packet transform is utilized to detect the more accurate time-variant band, then we estimate the power from wavelet filter-coefficients of the respective band. Also, third-order cumulants, and projection cross-correlation (PCC) criterion are utilized to achieve an effective SNR improvement for the time-variant band estimation. In case of time variant band estimation, the PCC method yields better performance than the correlation method.

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Noise suppressor Using Psychoacoustic Model and Wavelet Packet Transform (심리음향 모델과 웨이블릿 패킷 변환을 이용한 잡음제거기)

  • Kim, Mi-Seon;Kim, Young-Ju;Lee, In-Sung
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.345-346
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    • 2006
  • In this paper, we propose the noise suppressor with the psychoacoustic model and wavelet packet transform. The objective of the scheme is to enhance speech corrupted by colored or non-stationary noise. If corrupted noise is colored, subband approach would be more efficient than whole band one. To avoid serious residual noise and speech distortion, we must adjust the Wavelet Coefficient threshold. In this paper, the subband is designed matching with the critical band. And WCT is adapted by noise masking threshold(NMT) and segmental signal to noise ratio(seg_SNR). Consequently this work improve the PESQ-MOS about 0.23 in the case of coded speech.

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