文件名称:Recent-timefrequency-analysis
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Nonstationary signal analysis one of the main topics in the field of machinery fault diagnosis.Time-frequency analysis can identify the signal frequency components,
reveals their time variant features,and is an effective tool to extract machinery health information contained innonstationary signals.Various time-frequency analysis methods have been proposed and applied to machinery fault diagnosis.These include linear and bilineartime–frequency representations(e.g.,wavelet transform,Cohen and affine class distributions),adaptive parametric time-frequency an alysis(basedonatomic decomposition and time-frequency auto regressive moving average models),adaptive
non-parametric time–frequencyanalysis-Nonstationary signal analysis is one of the main topics in the field of machinery fault diagnosis.Time-frequency analysis can identify the signal frequency components,
reveals their time variant features,and is an effective tool to extract machinery health information contained innonstationary signals.Various time-frequency analysis methods have been proposed and applied to machinery fault diagnosis.These include linear and bilineartime–frequency representations(e.g.,wavelet transform,Cohen and affine class distributions),adaptive parametric time-frequency an alysis(basedonatomic decomposition and time-frequency auto regressive moving average models),adaptive
non-parametric time–frequencyanalysis
reveals their time variant features,and is an effective tool to extract machinery health information contained innonstationary signals.Various time-frequency analysis methods have been proposed and applied to machinery fault diagnosis.These include linear and bilineartime–frequency representations(e.g.,wavelet transform,Cohen and affine class distributions),adaptive parametric time-frequency an alysis(basedonatomic decomposition and time-frequency auto regressive moving average models),adaptive
non-parametric time–frequencyanalysis-Nonstationary signal analysis is one of the main topics in the field of machinery fault diagnosis.Time-frequency analysis can identify the signal frequency components,
reveals their time variant features,and is an effective tool to extract machinery health information contained innonstationary signals.Various time-frequency analysis methods have been proposed and applied to machinery fault diagnosis.These include linear and bilineartime–frequency representations(e.g.,wavelet transform,Cohen and affine class distributions),adaptive parametric time-frequency an alysis(basedonatomic decomposition and time-frequency auto regressive moving average models),adaptive
non-parametric time–frequencyanalysis
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Print_print_print_2013_Recent advances in time–frequency analysis methods.pdf
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