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Method for predicting residual life of wind turbine gearbox bearing

A gearbox and bearing technology, which is applied in the field of predicting the remaining life of wind turbine gearbox bearings, can solve the problem of not considering factors such as sudden failure, and achieve good prediction effect and high accuracy

Active Publication Date: 2020-08-28
XINJIANG UNIVERSITY
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Problems solved by technology

[0006] The current research only describes the wind turbine bearings from the perspective of degradation failure, and does not consider the factors of sudden failure

Method used

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  • Method for predicting residual life of wind turbine gearbox bearing
  • Method for predicting residual life of wind turbine gearbox bearing
  • Method for predicting residual life of wind turbine gearbox bearing

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Embodiment Construction

[0068] Specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0069] A method for predicting the remaining life of a wind turbine gearbox bearing proposed by the present invention, the specific flow chart of the embodiment is as attached figure 1 shown, including the following steps:

[0070] S1. Selection of characteristic parameters of wind turbine gearbox bearings based on data

[0071] The SCADA system equipped in the wind farm can monitor the bearings of the gear box in real time, and the monitoring parameters of the bearings can be regarded as internal covariates that cause the performance degradation of the bearings. According to the wind field monitoring data, after the wind turbine gearbox bearing fails, it is mainly reflected in a sharp increase in temperature and an increase in vibration amplitude, and there is no major change in wind speed and lubricating oil parameters. Therefore, the prese...

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Abstract

The invention discloses a method for predicting the residual service life of a wind turbine gearbox bearing. The method is a method for predicting the residual service life of the gearbox bearing based on a competitive improved proportional failure model. The method comprises the following steps: carrying out principal component fusion on temperature and vibration data of a gearbox bearing in a whole life cycle from use to failure to obtain a one-dimensional characteristic quantity so as to reflect the degradation performance of the bearing; and considering the particularity of a wind turbinegenerator gearbox bearing, and establishing a competition failure reliability evaluation model of a Wiener degradation process and Weibull distribution sudden failure by adopting an improved proportional hazard model. Through example analysis, residual life analysis of the degradation failure and burst failure competition model, the irrelevant model and the independent degradation failure and burst failure model is compared, and reliability and optimality of the competition model are verified. The invention provides an effective, practical and high-precision prediction method for analyzing theresidual service life of the wind turbine gearbox bearing.

Description

technical field [0001] The invention relates to a method for predicting the remaining life of a wind turbine gearbox bearing. Background technique [0002] With the continuous increase of the installed capacity of megawatt wind turbines, the gearbox has become an indispensable component. Its advantages are that it can effectively increase the speed ratio of the transmission system, reduce the space occupation of the nacelle, and optimize the overall design of the nacelle. However, the damage rate of gearboxes of wind turbines in China is as high as 50%, and about 80% of mechanical failures of gearboxes are caused by bearing failures. [0003] The traditional wind turbine gearbox bearing research method is to use finite element technology to analyze the bearing life. With the development of sensing technology and signal processing technology, the research on bearings focuses on condition monitoring and evaluation and fault diagnosis and prediction. The fault diagnosis method ...

Claims

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Application Information

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IPC IPC(8): G06F30/20G01M13/04G01M13/045G06F111/10G06F119/02
CPCG06F30/20G01M13/04G01M13/045G06F2111/10G06F2119/02
Inventor 袁逸萍赵琴樊盼盼马占伟赵瑛
Owner XINJIANG UNIVERSITY
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