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Fault feature extraction method of gear root crack based on stochastic resonance and graph fourier transform theory
2022, 42(2):
108-113.
Abstract:. The working environment of locomotive gearbox is very bad, and the gear is easy to be damaged. Gear box root crack damage detection is an effective way to ensure the safe operation of the train. In this paper, a fault extraction method based on stochastic resonance and spectrum theory is proposed. Firstly, the complex Morlet wavelet comb filter is used to demodulate the original signal; Then, the spectrum theory is used to process the simulation signal and extract the impact signal components contained in the signal; Finally, the stochastic resonance method is used to process the extracted impulse signal to eliminate the noise interference and enhance the impulse component in the signal. The simulation data are processed by using the proposed method, which proves the effectiveness of the proposed method.
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