Bearing fault identification method and system based on EEMD sparse decomposition

Abstract

The invention relates to a bearing fault identification method and system based on EEMD sparse decomposition. The method comprises the steps of firstly obtaining a bearing vibration signal and converting the bearing vibration signal into an electric signal; decomposing the electric signal by using an EMD method to obtain a plurality of IMF components and a remainder; performing sparse processing on the plurality of IMF components; and calculating the energy entropy of the bearing vibration signal by using the IMF component subjected to overall averaging by using the EEMD method, and identifying the fault type of the bearing in combination with the energy distribution condition. The method serves as an effective self-adaptive algorithm and is particularly used for decomposing non-stationary signal processing, and for each independent IMF component, the IMF components have the scale characteristics of the signals and have the characteristic changing along with the scale characteristics of the signals.

Description

technical field [0001] The invention relates to the field of signal and information processing, in particular, to a bearing fault identification method and system based on EEMD sparse decomposition. Background technique [0002] Large bearings that run for a long time in harsh working conditions are often under high load, strong high temperature, strong high pressure and high humidity, strong electromagnetic interference and strong coupling conditions, material aging during operation, high temperature and high pressure, sudden load effect, design Defects, especially abnormal vibration factors, can cause irreversible damage accumulation to the bearing. At the same time, because the normal operation of the entire bearing is seriously affected by the failure, and in most cases, it is caused by the abnormal operation of some key parts, which causes permanent damage to the bearing and also brings huge economic losses. How to ensure the stable, reliable and safe operation of the...

AI Technical Summary

Problems solved by technology

[0002] Large-scale bearings that operate for a long time under harsh working conditions are often under high load, strong high temperature, strong high pressure and high humidity, strong electromagnetic interference and strong coupling. Material aging, high temperature and high pressure, sudden load, and design during operation Defects, especially abnormal vibration factors, will cause irreversible damage accumulation to the bearing

At the same time, because the normal operation of the entire bearing is seriously affected by the fault, and in most cases it is caused by the abnormal operation of certain key parts, this will cause permanent damage to the bearing and also bring huge economic loss

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