Application of wavelet transform for the impulse response of pile

2017 ◽  
Vol 19 (5) ◽  
pp. 513-521 ◽  
Author(s):  
Sheng-Huoo Ni ◽  
Yu-Zhang Yang ◽  
Chia-Rong Lyu
Author(s):  
ASHOKA JAYAWARDENA ◽  
PAUL KWAN

In this paper, we focus on the design of oversampled filter banks and the resulting framelets. The framelets obtained exhibit improved shift invariant properties over decimated wavelet transform. Shift invariance has applications in many areas, particularly denoising, coding and compression. Our contribution here is on filter bank completion. In addition, we propose novel factorization methods to design wavelet filters from given scaling filters.


2011 ◽  
Vol 204-210 ◽  
pp. 1378-1381
Author(s):  
Hui Li

A novel method for detection the gear wear fault according to impulse response wavelet transform is presented. The continuous wavelet transform is widely recognized as an effective technique for rotating machine fault detection using vibration signal since it can be used to detect both stationary and transitory signals. This advantage makes it very suitable for the detection of singularity generated by localized damage in gearbox. In this study, the impulse response wavelet time-frequency joint representation is used to diagnose the gear wear fault. The experimental result shows that impulse response wavelet time-frequency joint representation is a sensitive indicator of the existence of damage in the gearbox.


1998 ◽  
Vol 120 (1) ◽  
pp. 252-260 ◽  
Author(s):  
A. N. Robertson ◽  
K. C. Park ◽  
K. F. Alvin

This paper presents a wavelet transform-based method of extracting the impulse response characteristics from the measured disturbances and response histories of linear structural dynamic systems. The proposed method is found to be effective in determining the impulse response functions for systems subjected to harmonic (narrow frequency-band) input signals and signals with sharp discontinuities, thus alleviating the Gibbs phenomenon encountered in FFT methods. When the system is subjected to random burst input signals for which the FFT methods are known to perform well, the proposed wavelet method performs equally well with a fewer number of ensembles than FFT-based methods. For completely random input signals, both the wavelet and FFT methods experience difficulties, although the wavelet method appears to perform somewhat better in tracing the fundamental response modes.


2020 ◽  
Vol 43 (1) ◽  
pp. 46-56
Author(s):  
Nikita Rathi ◽  
Saugata Sinha ◽  
Bhargava Chinni ◽  
Vikram Dogra ◽  
Navalgund Rao

Photoacoustic signal recorded by photoacoustic imaging system can be modeled as convolution of initial photoacoustic response by the photoacoustic absorber with the system impulse response. Our goal was to compute the size of photoacoustic absorber using the initial photoacoustic response, deconvolved from the recorded photoacoustic data. For deconvolution, we proposed to use the impulse response of the photoacoustic system, estimated using discrete wavelet transform based homomorphic filtering. The proposed method was implemented on experimentally acquired photoacoustic data generated by different phantoms and also verified by a simulation study involving photoacoustic targets, identical to the phantoms in experimental study. The photoacoustic system impulse response, which was estimated using the acquired photoacoustic signal corresponding to a lead pencil, was used to extract initial photoacoustic response corresponding to a mustard seed of 0.65 mm radius. The recovered radius values of the mustard seed, corresponding to the experimental and simulation studies were 0.6 mm and 0.7 mm.


Author(s):  
Suchetha M. ◽  
Jagannath M.

The main aim of ECG signal enhancement is to separate the required signal components from the unwanted artifacts. Adaptive filter-based ECG enhancement helps in detecting time varying potentials and also helps to track the dynamic variations of the signals. LMS-based adaptive recurrent filter is used to obtain the impulse response of normal QRS complexes. It is also used for arrhythmia detection in ambulatory ECG recordings. Adaptive filters self-modify its frequency response to change the behavior in time. This property of adaptive filter allows it to adapt its response to change in the input signal characteristics. A major problem in adaptive filtering is the computational complexity of adaptive algorithm when the unknown system has a long impulse response and therefore requires a large number of taps. The wavelet transform is a time-scale representation method with a basis function called mother wavelet. In wavelet transform, the input signal is subsequently decomposed into subbands. Wavelet transform thresholding in the subband gives better performance of denoising.


Author(s):  
A. N. Robertson ◽  
K. C. Park ◽  
K. F. Alvin

Abstract This paper presents a wavelet transform-based method of extracting the impulse response characteristics from the measured disturbances and response histories of linear structural dynamic systems. The proposed method appears to have alleviated some of the most pronounced deleterious aspects of both the time-domain methods that suffer from the matrix ill-conditioning of the input signals and FFT-based methods that must cope with erraneous auto and cross-correlation functions, unless the input signals are rich enough in frequency content The method is found to be effective in capturing very low frequency response components and also far insensitive to output noises than existing methods. The present method has been applied to a variety of problems, which show significant improvements over existing impulse response function extraction methods, especially for limited harmonic excitations and input/output data contaminated with noises.


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