• Journal of Welding and Joining
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• 제21권6호
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• pp.33-39
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• 2003

Wavelet transform analysis results show a spectrum energy distribution of CWT along scale factors distinguish the partial, full and over penetration in a electron beam welding by analyzing the curve of spectrum energy at small scale, middle and large scale range, respectively. Two types of signals collected by Ion collector and x-ray sensors and analyzed. The acquired signals from sensors are very complicated since these signals are very closely related the dynamics of keyhole which interact the very high density energy with materials during welding. The results show the wavelet transform is more effective to diagnosis than Fourier Transform, further for the general welding defects which are not a periodic based, but a transient, non-stationary and time-varying phenomena.

• Journal of Mechanical Science and Technology
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• 제15권5호
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• pp.535-543
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• 2001

This paper presents the ride comfort analysis of a vehicle based on wavelet transform. Traditionally, the objective evaluation of impact harshness is based on the vibration dose value (VDV) and frequency weighting method. These methods do not consider the damping effect of the suspension system of a vehicle. In this paper, the damping is estimated using wavelet transform based on Morlet mother wavelet and its effect is considered for the subjective evaluation of impact harshness of a car.

• 한국기계가공학회지
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• 제3권2호
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• pp.32-38
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• 2004

The chatter behaviour in endmilling is a complex and nonlinear phenomenon, so it is very difficult to detect and diagnose this chatter phenomenon, This paper presents new method for the detection of chatter in endmilling operation based on the wavelet transform. In this paper, the fundamental property of the wavelet transform is reviewed by comparing the spectrum of other algorithm such as FFT. This result using wavelet transform shows the possibiling of the chatter detection in endmilling operation.

• Earthquakes and Structures
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• 제6권4호
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• pp.393-408
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• 2014

In this paper, a direct identification of modal parameters using the continuous wavelet transform is proposed. The purpose of this method is to transform the differential equations of motion into a system of algebraic linear equations whose unknown coefficients are modal parameters. The efficiency of the present method is confirmed by numerical data, without and with noise contamination, simulated from a discrete forced system with four degrees-of-freedom (4DOF) proportionally damped.

• 한국지구과학회지
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• 제28권7호
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• pp.903-913
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• 2007

천부지반에서 레일리파의 군속도와 위상속도 분산곡선을 역산하여 S파 속도구조를 구하는 방법을 비교하였다. 위상속도를 구하기 위해서 ${\tau}-p$ stacking 방법을 이용하였고, 군속도를 구하기 위해서 두 가지 방법, multiple filtering technique(MFT) continuous wavelet transform(CWT) 방법을 사용하였다. 고차모드가 존재하는 경우, 위상속도에서 기본모드와 고차모드를 분리하기가 용이하지 않았고, 군속도에서는 continuous wavelet transform 방법이 multiple filtering technique보다 효과적이었다. S파 속도 역산 결과, 위상속도와 군속도의 기본 모드만 역산할 경우, 신뢰구간의 깊이가 아주 얕았다. Continuous wavelet transform으로 구한 기본 모드와 1차 모드를 동시 역산할 경우, 신뢰구간의 깊이가 2배 이상 증가함을 알 수 있었다. 이는 1차 모드의 에너지가 더 깊은 층을 통과함으로 깊은 층에 대한 5파 속도 정보를 지니고 있기 때문으로 보인다. 위의 방법을 서해안 동호항의 조간대에 적용하여, continuous wavelet transform으로 구한 군속도의 기본 모드와 1차 모드를 동시 역산하여 S파 속도구조를 구하고, 해당 지역의 시추조사 결과와 비교하였다.

• 한국구조물진단유지관리공학회 논문집
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• 제12권6호
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• pp.140-146
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• 2008

본 논문에서는 연속웨이블렛 변환(Continuous Wavelet Transform; CWT)을 이용하여 구조물의 손상도를 평가 하였다. 지진하중을 받은 프레임 구조물의 응답 가속도를 CWT를 이용하여 분해한 후 각각의 스케일에 관해서 손상전과 손상후의 정규화된 에너지 곡률(Normalized Energy Curvature; NEC)을 계산하였다. 손상전과 손상후의 NEC 값은 손상된 부재에서 크게 변화 하여 손상된 부재를 쉽게 나타내었고 또한 손상도가 심할 수 록 그 값의 차이가 컸다. 이 논문에서는 CWT로부터 계산된 NEC값이 구조물의 손상위치와 손상도를 평가하는 효과적인 지표임을 나타내었다.

• 한국생산제조학회지
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• 제18권4호
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• pp.381-387
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• 2009

The end-milling force behaviour is very complex and it is related to a de-noising phenomenon, so it is very difficult to detect and diagnose this static cutting force phenomenon. This paper presents a new method of filtering of end-milling force in end-milling operation using filter bank technique, based on the wavelet transform. In this paper by comparing the history of end-milling force using wavelet filtering the fundamental end-milling property of the wavelet transform is well reviewed and analyzed. This result of wavelet transform using filter bank shows the possible static prediction of end-milling force with severe dynamic properties such as chatter in end-milling operation.

• Smart Structures and Systems
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• 제1권2호
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• pp.185-215
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• 2005

Advanced signal processing techniques have been long introduced and widely used in structural health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform (DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis. Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from the original signal the component with the excitation signal's frequency. Third, cross correlation method and Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory experiments have been conducted and have verified that, with the advanced signal processing approaches, the EUSR has enhanced damage detection ability.

• 한국음향학회지
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• 제20권8호
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• pp.81-87
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• 2001

The human auditory system is appropriate for the "constant Q"system. The STFT (Short Time Fourier Transform) is not suitable for the auditory perception model since it has constant bandwidth. In this paper, the CWT (continuous wavelet transform) is employed for the auditory filter model. In the CWT, the frequency resolution can be adjusted for auditory sensation models. The proposed CWT is applied to the modeling of the JNVF. In addition, other signal processing methods such as STFT, VER-FFT and VFR-STFT are discussed. Among these methods, the model of JNVF (Just Noticeable Variation in Frequency) by using the CWT fits in with the JNVF of auditory model although it requires quite a long time.

• 디지털산업정보학회논문지
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• 제10권3호
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• pp.237-247
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• 2014

This paper describes a 2D discrete-time wavelet transform for which the Q-factor is easily specified. Hence, the transform can be tuned according to the oscillatory behavior of the image signal to which it is applied. The tunable Q-factor wavelet transform (TQWT) is a fully-discrete wavelet transform for which the Q-factor, Q, of the underlying wavelet and the asymptotic redundancy (over-sampling rate), r, of the transform are easily and independently specified. In particular, the specified parameters Q and r can be real-valued. Therefore, by tuning Q, the oscillatory behavior of the wavelet can be chosen to match the oscillatory behavior of the signal of interest, so as to enhance the sparsity of a sparse signal representation. The TQWT is well suited to fast algorithms for sparsity-based inverse problems because it is a Parseval frame, easily invertible, and can be efficiently implemented. The TQWT can also be used as an easily-invertible discrete approximation of the continuous wavelet transform. The transform is based on a real valued scaling factor (dilation-factor) and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. The transform is parameterized by its Q-factor and its oversampling rate (redundancy), with modest oversampling rates (e. g. 3-4 times overcomplete) being sufficient for the analysis/synthesis functions to be well localized. Therefore, This method services good performance in image processing fields.