基于WPT-SVD-KELM的大型风力机叶片表面裂纹识别方法研究

刘钦东; 罗勇水; 张军华; 艾真伟; 程启超; 杨世锡

doi:10.19912/j.0254-0096.tynxb.2021-1258

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太阳能学报 ›› 2023, Vol. 44 ›› Issue (3) : 155-161. DOI: 10.19912/j.0254-0096.tynxb.2021-1258

基于WPT-SVD-KELM的大型风力机叶片表面裂纹识别方法研究

刘钦东^1,2, 罗勇水^1~3, 张军华^1,2, 艾真伟^1,2, 程启超³, 杨世锡³

作者信息 +

RESEARCH ON SURFACE CRACK IDENTIFICATION METHOD OF LARGE WIND TURBINE BLADE BASED ON WPT-SVD-KELM

Liu Qindong^1,2, Luo Yongshui^1~3, Zhang Junhua^1,2, Ai Zhenwei^1,2, Cheng Qichao³, Yang Shixi³

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文章历史 +

摘要

为准确识别风力机叶片表面裂纹位置和长度,提出基于小波包-奇异值分解-核极限学习机（WPT-SVD-KELM）的裂纹识别方法。搭建风力机某典型叶片裂纹识别平台,开展正常叶片和含裂纹叶片的模态实验和变桨实验,获取不同工况下正常叶片和含裂纹叶片的振动信号。利用频响函数研究裂纹位置对振动信号幅频响应的影响,从而准确识别叶片表面裂纹位置,利用WPT-SVD提取风力机叶片表面裂纹振动信号的时频特征,定义参数k_r表征裂纹长度的变化,并将特征参数导入优化后的KELM,从而识别风力机叶片表面裂纹长度。

Abstract

In order to accurately identify the location and length of surface cracks on wind turbine blades, a crack identification method based on wavelet packet decomposition - singular value decomposition - nuclear limit learning machine (WPT-SVD-KELM) is proposed. The crack identification experiment platform of a typical blade was built, modal experiments and pitch experiments of normal blades and cracked blades were carried out, and vibration signals of normal blades and cracked blades under different working conditions were obtained. The frequency response function is used to study the influence of the crack position on the amplitude-frequency response of the vibration signal, so as to accurately identify the position of the crack on the blade surface. The WPT-SVD is used to extract the time-frequency characteristics of the wind turbine blade surface crack vibration signal, and the parameter k_r is defined to characterize the change of the crack length. The characteristic parameters are imported into the optimized KELM to identify the length of surface crack on the wind turbine blade. The research results have important guiding significance for the identification of surface cracks on large wind turbine blades.

导出引用

刘钦东, 罗勇水, 张军华, 艾真伟, 程启超, 杨世锡. 基于WPT-SVD-KELM的大型风力机叶片表面裂纹识别方法研究[J]. 太阳能学报. 2023, 44(3): 155-161 https://doi.org/10.19912/j.0254-0096.tynxb.2021-1258

Liu Qindong, Luo Yongshui, Zhang Junhua, Ai Zhenwei, Cheng Qichao, Yang Shixi. RESEARCH ON SURFACE CRACK IDENTIFICATION METHOD OF LARGE WIND TURBINE BLADE BASED ON WPT-SVD-KELM[J]. Acta Energiae Solaris Sinica. 2023, 44(3): 155-161 https://doi.org/10.19912/j.0254-0096.tynxb.2021-1258

中图分类号： TH165.3

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