Bearing early fault diagnosis method for multiple noise reduction processing
A technology for noise reduction and early failure. It is used in the testing of mechanical components, testing of machine/structural components, and measuring devices. It can solve the difficulty of increasing the difficulty of diagnosing early bearing failures, difficult to identify early bearing failures, and the surrounding environment. It can improve the efficiency of fault diagnosis, improve the speed and accuracy of diagnosis, and achieve good anti-noise effect.
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[0074] Such as figure 1 As shown, the bearing early fault diagnosis method with multiple noise reduction treatment includes the following steps:
[0075] Step 1: Collect the vibration signal of the bearing;
[0076] Step 2: Perform short-time Fourier transform on the vibration signal of the bearing to preliminarily judge whether the bearing is faulty;
[0077] Given a window function γ(t) with a very short time width, let the window slide, then the calculation formula of the short-time Fourier transform of the signal z(t) is as follows
[0078]
[0079] In the formula, * represents complex conjugate, t and f represent time and frequency respectively, STFT z (t,f) represents the short-time Fourier transform result of the signal z(t).
[0080] Step 3: Use wavelet packet transform to decompose and reconstruct the bearing vibration signal for preliminary denoising;
[0081] The calculation formula of binary wavelet packet decomposition is as follows:
[0082]
[0083] w...
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