滤波算法在风电塔筒长期姿态监测 数据处理中的应用
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作者单位:

北京科技大学土木与资源工程学院

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中图分类号:

TK83

基金项目:

国家重点研发计划(2019YFC1509600)


Filtering algorithm for long-term attitude monitoring of wind power tower Application of data processing
Author:
Affiliation:

School of civil and resource engineering, university of science and technology beijing

Fund Project:

National Key R&D Program of China (2019YFC1509600)

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    摘要:

    风电塔筒的姿态监测是风电塔安全监测的重要组成部分,为解决姿态监测过程中产生数据噪声,难以判断塔筒运行姿态的问题,融合基于SVD的PCA算法与EMD算法对含噪数据进行提纯。姿态监测过程中产生的噪声由周期性分量与随机高频噪声组成,首先使用SVD-PCA算法提取数据主要本征频率,根据特征频率重构数据得到周期干扰数据的本征频率,然后使用EMD算法对数据进行分解与重构,消除数据的周期性特征,并通过模拟信号验证了算法的有效性。以盐城某风电塔为研究对象,将算法应用于塔顶倾角传感器长期监测数据的滤波,取得了较好的效果。经过判断,该风电塔仍处于安全服役状态。

    Abstract:

    The attitude monitoring of the wind turbine tower is an important part of the safety monitoring of the wind turbine tower. In order to solve the problem that the data noise is generated in the process of attitude monitoring and it is difficult to determine the operation attitude of the tower, the PCA algorithm based on SVD and the EMD algorithm are integrated to purify the noisy data. The noise generated in the process of attitude monitoring is composed of periodic component and random high frequency noise. Firstly, SVD-PCA algorithm is used to extract the main intrinsic frequency of the data, and the intrinsic frequency of the periodic interference data is reconstructed according to the characteristic frequency. Then EMD algorithm is used to decompose and reconstruct the data to eliminate the periodic characteristics of the data. The validity of the algorithm is verified by simulation signals. Taking a wind power tower in Yancheng as the research object, the algorithm is applied to the filtering of long-term monitoring data of tower top inclination sensor, and good results are achieved. After judgment, the wind tower is still in safe service condition.

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张金戈,谢谟文,张磊,等. 滤波算法在风电塔筒长期姿态监测 数据处理中的应用[J]. 科学技术与工程, , ():

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  • 收稿日期:2021-06-02
  • 最后修改日期:2022-03-02
  • 录用日期:2022-03-15
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