Online identification method for multiple loads on blades of large wind power generation set

A technology for wind turbines and identification methods, which is applied in the fields of electrical digital data processing, special data processing applications, instruments, etc., and can solve problems such as difficult problems.

Active Publication Date: 2015-06-24
HUNAN UNIV OF SCI & TECH
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, since the blade root load is the result of multiple loads, how to extract gravity, centrifugal force, inertial

Method used

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  • Online identification method for multiple loads on blades of large wind power generation set
  • Online identification method for multiple loads on blades of large wind power generation set
  • Online identification method for multiple loads on blades of large wind power generation set

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Embodiment Construction

[0032] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0033] Such as figure 1 Shown is a schematic diagram of the overall structure of the large-scale wind turbine blade of the present invention.

[0034] 1. Define the coordinate system and the transformation relationship between coordinate systems

[0035] Such as figure 2 As shown, the wind turbine blade coordinate system is established, and the fixed coordinate system xyz of the nacelle is defined to be fixed on the nacelle (not rotating), and the hub rotating coordinate system x 0 the y 0 z 0 It is fixed on the rotating shaft and rotates synchronously, where y 0 It coincides with the y-axis of the fixed coordinate system of the cabin, and the direction is the same, and the xoz plane revolves around y 0 The axis rotates with angular velocity ω, x 0 with x-axis and z 0 The angle with the z-axis is ωt, from the coordinate system xyz to the coordinate s...

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Abstract

The invention discloses an online identification method for multiple loads on blades of a large wind power generation set. The method includes following steps that 1, the transformation relation between coordinate systems of the large wind power generation set is set; 2, the arrangement mode of blade root circumferential strain gages and blade axial strain gages is determined; 3, a data processing algorithm is adopted for decomposing the multiple loads on the blades; 4, an outline deformation correction algorithm is adopted for correcting the loads. By means of the method, the multiple loads such as gravitational loads, centrifugal force loads, inertial loads and complex aerodynamic loads can be effectively extracted and identified on line, the information of gravity, centrifugal force, inertia force, aerodynamic force and the like can be extracted from measured data, a computer is adopted for performing real-time computing on the computing algorithms, rapid and accurate online identification of the multiple loads on the large blades is performed, and it is guaranteed that the large wind power generation set operates safely and reliably in the service cycle.

Description

technical field [0001] The invention relates to the technical field of wind power, in particular to an online identification method with multiple loads on the blades of a large-scale wind turbine. Background technique [0002] In recent years, the world's wind power industry has developed rapidly. At the end of 2010, the annual power generation of wind turbines around the world exceeded the electricity demand of the United Kingdom, accounting for about 2.5% of the total global electricity demand. This figure increased to 3% at the end of 2011. In 2013 it was 3.5%. In some countries and regions, wind power has become one of the largest sources of electricity, such as Denmark, Portugal, Spain and Germany. As of 2013 statistics, China has rapidly developed into the country with the largest wind power installed capacity in the world, exceeding 27% of the world. [0003] At present, large-scale horizontal axis wind turbines are the mainstream models of wind farms, generally com...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 戴巨川张帆刘德顺沈意平龙辛杨书仪
Owner HUNAN UNIV OF SCI & TECH
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