Rolling bearing fault diagnosis method based on double-tree complex wavelet packet manifold domain noise reduction
A technology for rolling bearings and fault diagnosis, which is applied in complex mathematical operations, testing of mechanical components, testing of machine/structural components, etc. It can solve frequency aliasing of wavelets and wavelet packets, difficulty in selecting wavelet bases, and lack of translation invariance, etc. problems, to achieve the effect of less noise components, obvious frequency characteristics, and accurate acquisition of fault characteristic frequencies
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[0022] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:
[0023] A kind of rolling bearing fault diagnosis method based on dual-tree complex wavelet packet manifold domain noise reduction of the present invention is characterized in that it comprises the following steps:
[0024] Step 1: Use the acceleration sensor to collect the vibration signal of the rolling bearing;
[0025] The vibration signal of the rolling bearing is measured by the acceleration sensor installed on the bearing seat. The geometric parameters of the bearing are: pitch diameter 39.04mm, rolling element diameter 7.94mm, number of rolling elements 9, contact angle 0°. Use electric discharge machining technology to manufacture a crack fault with a diameter of 0.7112mm in the inner ring of the rolling bearing. During the experiment, the rotational speed of the shaft is set to 1797r / min, the sampling frequency is 12kHz, and the sampli...
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