Definitions of non-stationary vibration power for time–frequency analysis and computational algorithms based upon harmonic wavelet transform

2015 ◽  
Vol 336 ◽  
pp. 275-292 ◽  
Author(s):  
YongHwa Heo ◽  
Kwang-joon Kim
Keyword(s):  
Wavelet Transform ◽  
Frequency Analysis ◽  
Computational Algorithms ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Harmonic Wavelet ◽  
Stationary Vibration

Joint Time-Frequency Analysis of Small Scale Ocean Storms via the Harmonic Wavelet Transform

2017 ◽  
Author(s):  
Valentina Laface ◽  
Felice Arena ◽  
Ioannis A. Kougioumtzoglou ◽  
Ketson Roberto Maximiano dos Santos
Keyword(s):  
Wavelet Transform ◽  
Frequency Analysis ◽  
Sea Surface ◽  
Surface Elevation ◽  
Scale Model ◽  
Small Scale ◽  
Ocean Engineering ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Harmonic Wavelet

The paper focuses on utilizing the Harmonic Wavelet Transform (HWT) for estimating the evolutionary power spectrum (EPS) of sea storms. A sea storm is considered herein as a non-stationary stochastic process with a time duration of the order of days. The storm evolution can be represented in three stages: the growth, the peak and the decay. Specifically, during growth the intensity of the wave increases with time until reaching the apex, and then decreases. The analysis is carried out by processing the time series of the free surface elevation recorded at the Natural Ocean Engineering Laboratory of Reggio Calabria, Italy. A peculiarity of the NOEL lab is that a local wind from NNW often generates sea states consisting of pure wind waves that represent a small scale model, in Froude similarity, of ocean storms (www.noel.unirc.it). The main focus of the paper is, first, to acquire a joint time-frequency representation of the storm via estimating the associated EPS, and second, to explore the variability in time of the spectrum and of the dominant frequencies of the storm. The EPS is estimated by utilizing a non-stationary record of the sea surface elevation during a storm recorded at NOEL lab. Further, in this paper, the standard representation of sea storms is also considered. That is, the non-stationary process is represented as a sequence of stationary processes (sea states or buoy records), each of them characterized by an intensity defined by a significant wave height Hs and by a duration Δt. During the time interval Δt the sea surface elevation is considered stationary and the frequency spectrum may be computed via the Fast Fourier Transform (FFT). Results obtained following this procedure, which can be considered essentially as a brute-force application of the short-time FT, are compared with those obtained via a HWT based joint time-frequency analysis.

Time-Frequency Analysis of Partial Discharge Phenomena in SF6 gas using Wavelet Transform

1997 ◽  
Vol 117 (3) ◽  
pp. 338-345 ◽  
Author(s):  
Masatake Kawada ◽  
Masakazu Wada ◽  
Zen-Ichiro Kawasaki ◽  
Kenji Matsu-ura ◽  
Makoto Kawasaki
Keyword(s):  
Wavelet Transform ◽  
Frequency Analysis ◽  
Partial Discharge ◽  
Time Frequency Analysis ◽  
Time Frequency

Time Frequency Domain Analysis of the Dispersion of Guided Wave Modes

2004 ◽  
Author(s):  
Youn-Ho Cho ◽  
Yong-Kwon Kim ◽  
Ik-Keun Park
Keyword(s):  
Wavelet Transform ◽  
Group Velocity ◽  
Frequency Analysis ◽  
Time Domain ◽  
Excitation Frequency ◽  
Guided Wave ◽  
Time Frequency Analysis ◽  
Mode Identification ◽  
Time Frequency ◽  
Wave Modes

One of unique characteristics of guided waves is a dispersive behavior that guided wave velocity changes with an excitation frequency and mode. In practical applications of guided wave techniques, it is very important to identify propagating modes in a time-domain waveform for determination of defect location and size. Mode identification can be done by measurement of group velocity in a time-domain waveform. Thus, it is preferred to generate a single or less dispersive mode. But, in many cases, it is difficult to distinguish a mode clearly in a time-domain waveform because of superposition of multi modes and mode conversion phenomena. Time-frequency analysis is used as efficient methods to identify modes by presenting wave energy distribution in a time-frequency. In this study, experimental guided wave mode identification is carried out in a steel plate using time-frequency analysis methods such as wavelet transform. The results are compared with theoretically calculated group velocity dispersion curves. The results are in good agreement with analytical predictions and show the effectiveness of using the wavelet transform method to identify and measure the amplitudes of individual guided wave modes.

Seismic Time-Frequency Analysis Based on Entropy-Optimized Paul Wavelet Transform

2020 ◽  
Vol 17 (2) ◽  
pp. 342-346
Author(s):  
Yi Luan ◽  
Yucheng Huang ◽  
Xiaodong Zheng ◽  
Jixing Cheng
Keyword(s):  
Wavelet Transform ◽  
Frequency Analysis ◽  
Time Frequency Analysis ◽  
Time Frequency
Sign in / Sign up

Export Citation Format

Share Document