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Bearing Fault Diagnosis Based on Wavelet Analysis
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The de-noising principle using wavelet was discussed and the de-noising property was compared with that of using general threshold strategy. The steps of the per-level de-noising method were then given and the experimental study with a vibration model was carried out. The results prove that the method is advantageous to de-noising, which is more suitable to recover the interest mutations signal buried in intensive background noise. The application of the method in the bearing vibration was presented and the results show that it can inhibit the background noise effectively and recover the interest information satisfactorily.
Title: Bearing Fault Diagnosis Based on Wavelet Analysis
Description:
The de-noising principle using wavelet was discussed and the de-noising property was compared with that of using general threshold strategy.
The steps of the per-level de-noising method were then given and the experimental study with a vibration model was carried out.
The results prove that the method is advantageous to de-noising, which is more suitable to recover the interest mutations signal buried in intensive background noise.
The application of the method in the bearing vibration was presented and the results show that it can inhibit the background noise effectively and recover the interest information satisfactorily.
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