Bearing fault early warning method based on high-frequency signal characteristic amplitude

Abstract

The invention discloses a bearing fault early warning method based on high-frequency signal characteristic amplitude, which belongs to the field of rolling bearing fault early warning. The bearing fault early warning method comprises the steps of: collecting vibration signals of a trained bearing at equal intervals; carrying out discrete wavelet transform on the vibration signals and extracting high-frequency components; sorting absolute values of the high-frequency components to obtain an enhanced impact amplitude LR and a carpet impact amplitude HR; taking an LR-HR value corresponding to thesame moment as an early warning feature of the moment; carrying out normal stage and fault stage division on the trained bearing according to the LR-HR value of the whole life cycle of the trained bearing; performing Weibull distribution fitting on the early warning feature of each stage to obtain probability distribution; acquiring an LR-HR value of a test bearing in operation; and calculating the probability that the test bearing is in a normal stage and a fault stage based on the probability distribution. According to the bearing fault early warning method, the high-frequency noise signalsare used for fault early warning, the complex denoising and signal enhancement processes are avoided, the fault early warning characteristics can be increased along with the degradation severity, theearly warning speed is high, and the method is suitable for practical application.

Description

technical field [0001] The invention belongs to the field of rolling bearing operating state monitoring and fault early warning, and more specifically relates to a bearing fault early warning method based on the characteristic amplitude of high-frequency signals. Background technique [0002] Rolling bearings are widely used in the industrial field and are called the joints of industry. The normal operation of rolling bearings is related to the production quality and the safety of personnel and property in the entire industrial production process. During the operation process, the rolling bearings will degrade with the operation time due to environmental factors, wear factors and human factors, and the faults of the inner ring, outer ring and rotor will occur after accumulating for a certain period of time. In order to avoid economic and safety problems caused by major bearing failures, online monitoring and early warning of rolling bearings are very necessary, which is the...

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Problems solved by technology

[0005] In view of the above defects or improvement needs of the prior art, the present invention provides a bearing fault early warning method based on the characteristic amplitude of high-frequency signals, and its purpose is to solve the problem that the existing rolling bearing fault detection method cannot detect the fault feature when the bearing is seriously degraded The frequency, the extracted degraded features fluctuate greatly, and the technical problems of high false alarm rate

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