Wind driven generator part fault early warning method

A technology for wind turbines and fault early warning, applied in instruments, data processing applications, calculations, etc., can solve problems such as restricting wind power, poor targeting of thresholds, and major accidents of wind turbines, avoiding deep damage, improving accuracy and reliability. performance, guaranteeing accuracy and reliability

Active Publication Date: 2014-12-10
YANSHAN UNIV
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Problems solved by technology

However, due to the different operating environments of wind turbines, the set thresholds are not targeted, and there is a lack of judgment on early failures of wind turbines, which can easily cause major accidents of wind turbines; wind turbines are co

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  • Wind driven generator part fault early warning method
  • Wind driven generator part fault early warning method
  • Wind driven generator part fault early warning method

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[0036] The present invention provides a wind turbine component failure warning method. The core of the method is a new threshold determination method with predictive function. In order to improve the accuracy and reliability of the early warning result, information fusion technology is applied, and the difference The parameter prediction results are fused to give the health status of the wind turbine components, and the weights of the characteristic parameters in the information fusion are adaptively adjusted according to the warning results.

[0037] In order to enable those skilled in the art to better understand the solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0038] figure 1 It is a schematic structural diagram of a wind turbine component failure warning method provided by a specific embodiment of the present invention. The method includes three parts: a...

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Abstract

The invention discloses a wind driven generator part fault early warning method, which comprises the steps of: performing model training on a parallel echo state network group by calling data in a historical database, testing the accuracy of each echo state network model, and performing process statistical analysis on models satisfying the requirements so as to obtain a standard threshold of each characteristic parameter; after processing acquired different signals of all the parts of the wind driven generator, comparing each characteristic parameter in an information fusion module with a corresponding standard threshold, combining the comparison result with a corresponding weight value to give out early warning information, and adjusting the weight value of each characteristic parameter based on the practical condition of the on-site maintenance, wherein the monitored real-time data are based on the early-warning information and the on-site maintenance condition. According to the invention, health parameters of the parts of the wind driven generator are given after the monitoring results of the characteristic parameters are subjected to the fusion analysis, so that the accuracy and reliability of the early warning result are ensured.

Description

technical field [0001] The invention belongs to the field of wind power generator state monitoring, and relates to a method for early warning of wind power generator component failures. Background technique [0002] In recent years, with the uncertainty of fossil energy supply and the increasingly severe situation of energy conservation and emission reduction in various countries in the world, green renewable energy and an environmentally friendly low-carbon economy have received more and more attention. Especially in the past five years, China's wind power installed capacity has grown extremely rapidly, and it surpassed the United States at the end of 2010 to become the world's largest country in terms of wind power installed capacity. [0003] Under the premise of the rapid development of the wind power industry, a series of serious problems have also been triggered. Among them, there are even reports that dozens of wind turbines in a certain wind farm have been installed...

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Application Information

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IPC IPC(8): G06Q50/06
Inventor 谢平张欣欣江国乾何群杜义浩王一凡
Owner YANSHAN UNIV
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