Bearing fault detection method based on manner of controlling stochastic resonance by external periodic signal

A stochastic resonance and fault detection technology, applied in the direction of mechanical bearing testing, etc., can solve problems such as the reduction of signal-to-noise ratio of on-site measurement signals, affecting the normal operation of rotating machines, and the inability to detect early characteristics of bearing faults, etc., achieving good application prospects and broadening Application, the effect of improving the signal-to-noise ratio

Inactive Publication Date: 2011-10-26
CHINA JILIANG UNIV
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Problems solved by technology

A large amount of background noise will cause the signal-to-noise ratio of the field measurement signal to decrease. When the interference is serious, it is even impossible to detect the early characteristics of the bearing fault, which affects the normal operation of the rotating machine

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  • Bearing fault detection method based on manner of controlling stochastic resonance by external periodic signal
  • Bearing fault detection method based on manner of controlling stochastic resonance by external periodic signal
  • Bearing fault detection method based on manner of controlling stochastic resonance by external periodic signal

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Embodiment Construction

[0019] The present invention is based on an external periodic signal to control the bearing fault detection method of stochastic resonance, and the specific steps are as follows:

[0020] 1. Use the acquisition system to collect vibration acceleration signals;

[0021] Fix the acceleration sensor on the vibration table, and use the acquisition system to collect the vibration acceleration signal of the bearing, that is, the bearing fault signal.

[0022] 2. Transform the bearing fault signal into a small frequency signal by the scaling method;

[0023] According to the frequency compression scale ratio Define Compressed Sampling Frequency ,in, is the actual sampling frequency of the fault signal, is the frequency compression scale ratio. The numerical calculation step size obtained by compressing the sampling frequency is , so that each frequency component of the bearing fault signal (the characteristic frequency of the fault signal is ) by frequency compression sc...

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Abstract

The invention discloses a bearing fault detection method based on a manner of controlling stochastic resonance by an external periodic signal. According to the method provided in the invention, after a bearing fault signal is converted by a variable metric method, the converted signal is input in a bistable system; meanwhile, an external single frequency periodic signal is taken as a control signal to act directly on the system; contact barrier height of the bistable system and an escape rate of Kramers are changed by continuously adjusting an amplitude of the control signal. Therefore, stochastic resonance can be generated or increased artificially; a spectral value of an output power spectrum at the position of an input signal frequency can be effectively improved; and thus a characteristic signal of a bearing fault can be detected accurately at last. The detection method provided in the invention enables the effective control of the stochastic resonance to be realized, thereby providing a novel method for early detection of equipment faults.

Description

technical field [0001] The invention relates to a fault signal detection method, in particular to a fault signal detection method used in bearing fault diagnosis. Background technique [0002] Bearings are the most frequently used parts of machines but subject to wear. According to incomplete statistics, about 30% of the failures of rotating machines are caused by bearing failures. The causes of bearing failure are fatigue spalling, wear, plastic deformation, corrosion, fracture, gluing, cage damage, etc. If the early failure of the bearing cannot be diagnosed in time, it will cause serious failure of the machinery and equipment, resulting in huge economic losses. Therefore, diagnosing the early fault characteristics of bearings has great practical significance to avoid serious faults and ensure the normal operation of machinery and equipment. In the field of bearing fault diagnosis, using modern signal processing methods to process bearing faults and accurately extractin...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/04
Inventor 林敏张美丽
Owner CHINA JILIANG UNIV
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