Method for predicting bearing fault based on Gaussian process regression

Abstract

The invention discloses a method for predicting a bearing fault based on Gaussian process regression. The method comprises the following five steps of: step 1, setting prediction system parameters, initializing a Gaussian process regression model; step 2, collecting a bearing vibration signal regularly, extracting characteristics of a vibration signal to obtain time domain characteristic parameters of the bearing vibration signal, and carrying out fault symptom judgment; step 3, judging whether a fault symptom exists; step 4, calculating and storing the characteristic parameters, and carrying out dynamic updating of the Gaussian process regression model; and step 5, predicting the fault of a bearing. According to an actual use condition of a product, small amount of data is collected, time that the product possibly has the fault is given quantificationally, a calculation speed and prediction accuracy are improved by using the Gaussian process regression, a whole life cycle of the bearing is divided into three time ranges, such as a health time range, a sub-health time range and a fault time range by use of an idea of health management, fault prediction is carried out in the sub-health state, usage management capacity of the bearing is improved.

Description

Technical field: [0001] The invention relates to a bearing fault prediction method based on Gaussian process regression, and belongs to the technical field of bearing fault prediction. Background technique: [0002] Bearing is an indispensable part of rotating machinery, and it is also a core component to ensure the accuracy, performance, life and reliability of important equipment and facilities such as precision machine tools, high-speed railways, and wind turbines. At the same time, bearings are vulnerable parts, so their condition monitoring , fault diagnosis, and fault prediction have always been research hotspots. In recent years, the condition-based maintenance of the system has gradually attracted people's attention. As the core technology of condition-based maintenance, fault prediction technology has great significance for improving production safety, reducing production costs and prolonging the service life of equipment. [0003] At present, in the fault predicti...

Images