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GEAR FAULT DIAGNOSIS BASED ON THE FREQUENCY SLICE WAVELET TRANSFORM TIME-FREQUENCY ANALYSIS METHOD
In order to extract the gear fault characteristics under the strong noise condition,a fault feature separation and extraction method was proposed based on a new time-frequency decomposition method,the frequency slice wavelet transform（ FSWT）. Firstly,the signal was processed with the FSWT to get its time-frequency distribution. Then the time and frequency intervals,which contain the fault feature, were chosen to do threshold de-noising in time-frequency domain. Through reconstructing signals from the characteristic frequency slices,separation and extraction of time-frequency features were realized.The proposed method was shown to be efficient by simulations and engineering applications. It has the ability to isolate the desired components from noisy signals. It achieves an ideal effect on feature extraction for gear fault diagnosis.
GEAR FAULT DIAGNOSIS BASED ON THE FREQUENCY SLICE WAVELET TRANSFORM TIME-FREQUENCY ANALYSIS METHOD
In order to extract the gear fault characteristics under the strong noise condition,a fault feature separation and extraction method was proposed based on a new time-frequency decomposition method,the frequency slice wavelet transform（ FSWT）. Firstly,the signal was processed with the FSWT to get its time-frequency distribution. Then the time and frequency intervals,which contain the fault feature, were chosen to do threshold de-noising in time-frequency domain. Through reconstructing signals from the characteristic frequency slices,separation and extraction of time-frequency features were realized.The proposed method was shown to be efficient by simulations and engineering applications. It has the ability to isolate the desired components from noisy signals. It achieves an ideal effect on feature extraction for gear fault diagnosis.
GEAR FAULT DIAGNOSIS BASED ON THE FREQUENCY SLICE WAVELET TRANSFORM TIME-FREQUENCY ANALYSIS METHOD
CAI JianHua (author) / HUANG GuoYu (author) / LI XiaoQin (author)
2017
Article (Journal)
Electronic Resource
Unknown
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