• Smart Structures and Systems
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• v.18 no.5
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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.

• Earthquakes and Structures
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• v.11 no.6
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• pp.1143-1164
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• 2016

Time Delay of Arrival (TDOA) estimation methods based on correlation function analysis play an important role in the micro-seismic event monitoring. It makes full use of the similarity in the recorded signals that are from the same source. However, those methods are subjected to the noise effect, particularly when the global similarity of the signals is low. This paper proposes a new approach for micro-seismic monitoring based on cross wavelet transform. The cross wavelet transform is utilized to analyse the measured signals under micro-seismic events, and the cross wavelet power spectrum is used to measure the similarity of two signals in a multi-scale dimension and subsequently identify TDOA. The offset time instant associated with the maximum cross wavelet transform spectrum power is identified as TDOA, and then the location of micro-seismic event can be identified. Individual and statistical identification tests are performed with measurement data from an in-field mine. Experimental studies demonstrate that the proposed approach significantly improves the robustness and accuracy of micro-seismic source locating in mines compared to several existing methods, such as the cross-correlation, multi-correlation, STA/LTA and Kurtosis methods.

• The Journal of the Acoustical Society of Korea
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• v.32 no.6
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• pp.525-531
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• 2013

In this paper, we propose to apply low delay algorithm using power complementary window to Integer Modified Discrete Cosine Transform (IntMDCT). Conventional transform, the Modified Discrete Cosine Transform (MDCT) usually produces floating point values for integer input values. This causes the expansion of the data. To refine on this, IntMDCT that produces integer values even for integer input values have emerged. However, IntMDCT has a problem of the algorithm delay, such as MDCT. Delay has became a key issue in environments for the purpose of real-time communications. In order to reduce the delay, the proposed algorithm was applied and the results of the performance evaluation show that delay of IntMDCT has reduced by halfexisting delay.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.291-295
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• 2008

In this paper, we propose an input image reduction method to solve the problems of Radon transform which is a line structure analysis tool to correct a rotated object through a vision system. First we extract an object image removed background from the input image. Then we also select a reduced object image as a final input mage of Radon transform from the object image by considering slope. Finally we extract a rotated angle by using Radon transform with the final input image and correct the rotated object with the angle. In experimental results, we could improve the process time of about 64%, reduce the memory space of about 18% and make progress the line detection rate of about 18%.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.26-31
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• 2012

The highest frequency band of wavelet decomposition band is divided into 4 equal subbands and by the minimum power of the subbands and by the monotonic transform, the level adapted threshold is obtained. The adapted threshold is applied to the soft threshold technique to denoise high and middle frequency band noise of image signals. And the results of PSNRs are compared with the results obtained by the VisuShrink technique and by the technique using the monotonic transform and the weight value. The results showed the validity of this technique.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.583-586
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• 1997

In this study, we proposed an application of wavelet transform or analysis of ultrasound echo signals to improve troubles of convenianced methods such as SDM, SSM. We examined method using wavelet transform to prove again our proposal which we have proposed prior time. At first, we made phantoms by adding 0.01, 0.015, 0.02, 0.025, 0.03, 0.035, 0.04, 0.045, 0.05($g/cm^3$) on constant quantity of distilled water and agar, and collected echo signals. We used SDM(spectral difference method) and WTM(wavelet transform method) as signal processing method. To compare with WTM, SDM was used. In WTM, we selected detail signals of level 3 of Daubechies 16, and got derivative, calculated area of it. Next, we calculated slopes. In SDM, it was 0.0308 and in WTM, it was 0.5248. As a result, we knew that we could know that the values using WTM showed more detailed than those using SDM. So we could concluded wavelet transform is very useful and powerful in ultrasound tissue characterization.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.952-957
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• 2006

The present study applied wavelet transform and artificial neural networks (ANNs) for the prediction of daily TOC data. TOC data were transformed into denoised data by the wavelet transform and the noise-reduced data were used for the prediction model by artificial neural networks. For the application of wavelet transform, Daubechies wavelet of order 10 ('db10') was used as a basis function and decomposed the TOC data up to fifth level with five detail components and one approximation component. ANNs were calibrated with the input data of the segregated TOC data corresponding to the details from second to fifth level and the approximation. Consequently, the ANNs model for the prediction of daily TOC data showed the best result when it had seventeen hidden nodes in its layer.

• Transactions of Materials Processing
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• v.12 no.4
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• pp.277-283
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• 2003

In a closed-die forging process, blocker has been used to fill and distribute metal well in finisher die. Generally, the blocker shape was determined by an expert with many experiences. However, the manual blocker design process takes much time and efforts, so various automatic methods for the blocker design process have been suggested for the last three decades. The method with filtering in FFT (Fast Fourier Transform) for the blocker design provides general solution than other methods. But. due to the properties of FFT in time-frequency domain, this method has some drawbacks such as long calculation time, difficulty of local control and additional boundary process after filtering. In this study. DWT (Discrete Wavelet Transform), which is more flexible and is more wildly used than FFT, is applied to the blocker design. The method with filtering in DWT is very proper to design blocker in both 2-D and 3-D shapes. To verify the efficiency of this method, blockers of some models are designed and the results show that blocker design with DWT is effective for the blocker designs.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.119-131
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• 2011

In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. DDWT main property is a more computationally efficient approach to shift invariance. Also, the DDWT gives much better directional selectivity when filtering multidimensional signals. The dual-tree DWT of a signal is implemented using two critically-sampled DWTs in parallel on the same data. The transform is 2-times expansive because for an N-point signal it gives 2N DWT coefficients. If the filters are designed is a specific way, then the sub-band signals of the upper DWT can be interpreted as the real part of a complex wavelet transform, and sub-band signals of the lower DWT can be interpreted as the imaginary part. The quincunx lattice is a sampling method in image processing. It treats the different directions more homogeneously than the separable two dimensional schemes. Quincunx lattice yields a non separable 2D-wavelet transform, which is also symmetric in both horizontal and vertical direction. And non-separable wavelet transformation can generate sub-images of multiple degrees rotated versions. Therefore, non-separable image processing using DDWT services good performance.

• Journal of Biomedical Engineering Research
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• v.20 no.3
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• pp.265-274
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• 1999

In this paper, we propose a novel interframe coding algorithm especially appropriate for 3-D medical images. The proposed algorithm is based on a video coding algorithm using motion estimation/ compensation and transform coding. In the algorithm, warping is adopted lor motion compensation (MC). Then, by using adaptive mode selection, a motion compensated residual image and original image are mixed up in the wavelet transform domain for improvement in coding performance. The mixed image is then compressed by the zerotree coding method. We prove that the adaptive mode selection technique in the wavelet transform domain is very useful lor 3-D medical image coding. Simulation results show that the proposed scheme provides good performance regardless of inter-slice distance and is prospective for 3-D medical image compression.