• 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.

• Structural Engineering and Mechanics
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• v.53 no.3
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• pp.607-623
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• 2015

The wind-induced dynamic response of large-span flexible structures includes two important components-background response and resonant response. However, it is difficult to separate the two components in time-domain. To solve the problem, a relational expression of wavelet packet coefficients and power spectrum is derived based on the principles of digital signal processing and the theories of wavelet packet analysis. Further, a new approach is proposed for separation of the background response from the resonant response. Then a numerical example of frequency detection is provided to test the accuracy and the spectral resolution of the proposed approach. In the engineering example, the approach is applied to compute the power spectra of the wind-induced response of a large-span roof structure, and the accuracy of spectral estimation for stochastic signals is verified. The numerical results indicate that the proposed approach is efficient and accurate with high spectral resolution, so it is applicable for power spectral computation of various response signals of structures induced by the wind. Moreover, the background and the resonant response time histories are separated successfully using the proposed approach, which is sufficiently proved by detailed verifications. Therefore, the proposed approach is a powerful tool for the verification of the existing frequency-domain formulations.

• 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.

• 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.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.345-361
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• 2013

Locating and assessing the severity of damage in large or complex structures is one of the most challenging problems in the field of civil engineering. Considering that the wavelet packet transform (WPT) has the ability to clearly reflect the damage characteristics of structural response signals and the artificial neural network (ANN) is capable of learning in an unsupervised manner and of forming new classes when the structural exhibits change, this paper investigates a multi-stage structural damage diagnosis method by using the WPT and ANN based on "energy-damage" theory, in which, the wavelet packet component energies are first extracted to be damage sensitive feature and then adopted as input into an improved back propagation (BP) neural network model for damage diagnosis in a step by step mode. To validate the efficacy of the presented approach of the damage diagnosis, the benchmark structure of the American Society of Civil Engineers (ASCE) is employed in the case study. The results of damage diagnosis indicate that the method herein is computationally efficient and is able to detect the existence of different damage patterns in the simulated experiment where minor, moderate and severe damages corresponds to involving in the loss of stiffness on braces or the removal bracing in various combinations.

• Smart Structures and Systems
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• v.33 no.1
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• pp.41-53
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• 2024

Grouting sleeves are an essential connecting component of prefabricated components, and the quality of grouting has a significant influence on structural integrity and seismic performance. The embedded grouting sleeve (EGS)'s grouting defects are highly undetectable and random, and no effective monitoring method exists. This paper proposes an ultrasonic guided wave method and provides a set of guidelines for selecting the optimal frequency and suitable period for the EGS. The optimal frequency was determined by considering the group velocity, wave structure, and wave attenuation of the selected mode. Guided waves are prone to multi-modality, modal conversion, energy leakage, and dispersion in the EGS, which is a multi-layer structure. Therefore, a time-reversal (TR)-based multi-mode focusing and dispersion automatic compensation technology is introduced to eliminate the multi-mode phase difference in the EGS. First, the influence of defects on guided waves is analyzed according to the TR coefficient. Second, two major types of damage indicators, namely, the time domain and the wavelet packet energy, are constructed according to the influence method. The constructed wavelet packet energy indicator is more sensitive to the changes of defecting than the conventional time-domain similarity indicator. Both numerical and experimental results show that the proposed method is feasible and beneficial for the detection and quantitative estimation of the grouting defects of the EGS.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.89-92
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• 1999

인식기 훈련과정에서 발생하지 않았던 잡음이 인식과정에서 신호를 손상할 경우 인식률의 저하가 발생한다. 본 논문에서는 음성의 질을 떨어뜨리는 이러한 잡음을 Wavelet Packets을 이용하여 전처리함으로서 인식률을 향상시키는 방법을 제안한다. 인식기로는 Hidden Markov Model을 사용하였고, 시스템에 사용된 특징 파라미터로는 15차 Cepstrum을 사용하였다. 11 kHz로 샘플링된 숫자음에 Additive White Gaussian Noise를 첨가한 손상된 음성신호를 인식실험에 사용하였다. 화자독립으로 진행된 실험에서 잡음에 의해 손상된 SNR 20dB의 음성신호에 대하여 Wavelet Packets로 잡음을 제거한 후 복원된 음성신호 의 인식률은 약 $10\%$ 향상됨을 확인하였다.

• 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.

• 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.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.2
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• pp.35-38
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• 1998

We need the packet transmission of voice, data and video according to the development of ATM technology and packet network. In ATM, packet is parted to the constant length data, we called cell, the method is needed to minimize data loss. Because over ATM, we discard error cell without correction in transmission. So, about video, there is layered coding method. We simulated the coding using wavelet transform, which is structurally layed coded, so need not the additional coder.