Decomposition of wave forces into linear and non-linear components

Bendat, Julius S.; Piersol, Allan G.

doi:10.1016/0022-460x(86)90186-0

Cited by 38 publications

(34 citation statements)

References 2 publications

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“…It is shown that 1 x and 2 x are largely correlated with the output, whereas 3 x is poorly correlated with the output. This agrees with the results of correlation coefficients.…”

Section: Resultsmentioning

confidence: 97%

“…8. It can be seen that 1 x , 2 x and y are the time varying signals, and 3 x is different from the other signals. A maximum phase plane (MPP) is introduced as the maximum values of the wavelet packet coefficients for each time.…”

Section: Coherence Analysismentioning

confidence: 95%

“…But the slope of 3 x is 1.67095, which indicates distinctive frequency variations correspond with other signals. Thus, it can be concluded that the signals, except 3 x , are about 5~6.2 frequency increment for 1 second, and so these signals can be considered as nonstationary signals.…”

Section: Degree Of Non-stationaritymentioning

confidence: 95%

“…For linear systems, Fourier-based analysis gives a good estimate of input-output relationships [1][2][3][4]. However, these methods are not well applicable to non-stationary systems, since the frequency content of a response varies with time, and 'averaging' over a large number of data windows smears the response characteristics.…”

Section: Introductionmentioning

confidence: 99%

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Application of non-stationary signal characteristics using wavelet packet transformation

et al. 2008

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Although Fourier-based methods have been standard methods for frequency analysis, they are not well suited for the analysis of nonlinear or non-stationary systems due to their time-varying natures. Thus, in this paper, a wavelet packetbased technique, which calculates time-varying coherence functions for input/output relationships, is developed. The developed method uses the Coiflet wavelet that has been widely used in signal processing. It is applied to obtain the time-varying coherence function, and to detect the impulse signal from the impulse-embedded signal such as an automobile sound/vibration signal with an external impact caused by a collision or passing over rough terrain. Some characteristics of non-stationary behavior such as the wavelet packet coefficients, maximum phase plane (MPP) analysis and fault detection are also demonstrated. The method gives promising results of non-stationary input-output systems, and so may be used as an effective tool for condition monitoring or fault detection area.

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“…It is shown that 1 x and 2 x are largely correlated with the output, whereas 3 x is poorly correlated with the output. This agrees with the results of correlation coefficients.…”

Section: Resultsmentioning

confidence: 97%

Section: Coherence Analysismentioning

confidence: 95%

Section: Degree Of Non-stationaritymentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Application of non-stationary signal characteristics using wavelet packet transformation

et al. 2008

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“…Mottershed and Stanway [10] have developed procedure for estimation on nth power non-linear damping. Bendat and Peirsol [11] estimated quadratic sti!ness of wave forces in terms of a stochastically equivalent polynomial form. Studies have been carried out by Tiwary and Vyas [12], and Khan and Vyas [13] for rotor-bearing systems modelled as Du$ng oscillator.…”

Section: Introductionmentioning

confidence: 99%