Abstract
The resonance demodulation is an important method in rolling bearing fault feature extraction and fault
diagnosis. But in the traditional resonance demodulation method, the resonant frequency of the accelerometer sensing
fault information is discrete to some degree due to processing, debugging and installing factors, and the parameters of the
band-pass filter are in need for defining beforehand. Meanwhile, as the message generated by bearing early minor failure
is often submerged in strong background noise, the SNR is low, the capacity to apply traditional resonance demodulation
method to improve the SNR is limited, and the diagnosis effects are not obvious enough. This paper makes use of the
equivalence between the electronic resonant system and the mechanical resonance system and conducts resonant gain for
sensor output signal using electronic resonators, overcoming the shortcomings of the traditional methods, realizing a
UNB high-resolution detection and improved fault feature signal SNR. Besides, the effectiveness of the proposed method
has been validated by simulations and experiments, which possess important guiding significance for the engineering
practice.
Publisher
Bentham Science Publishers Ltd.
Cited by
1 articles.
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1. Rolling bearing fault diagnosis based on HVD algorithm and sample entropy;Journal of Computational Methods in Sciences and Engineering;2019-08-14