稳态工况下在役风力机叶片的载荷测试和识别

周勃; 张丽新; 包洪兵; 俞志强

doi:doi:10.19912/j.0254-0096.tynxb.2024-0243

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稳态工况下在役风力机叶片的载荷测试和识别

更新时间：2025-12-02

- 稳态工况下在役风力机叶片的载荷测试和识别
- Vol. 46, Issue 6, Pages: 597-606(2025)
- 作者机构：
- 作者简介：
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- DOI：doi:10.19912/j.0254-0096.tynxb.2024-0243
  CLC： TK83
- Published Online：07 July 2025，
  
  Published：2025
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周勃, 张丽新, 包洪兵, et al. 稳态工况下在役风力机叶片的载荷测试和识别[J]. 2025, 46(6): 597-606.
DOI：

周勃, 张丽新, 包洪兵, et al. 稳态工况下在役风力机叶片的载荷测试和识别[J]. 2025, 46(6): 597-606. DOI： doi:10.19912/j.0254-0096.tynxb.2024-0243.

摘要

针对稳态工况下运行的陆上风力机叶片载荷测试和识别问题

首先基于等效疲劳载荷理论

结合应变载荷测量技术设计载荷测试方案

根据载荷测量要求进行数据采集、传感器布置和标定

搭建叶片载荷监测系统;其次

在叶片监测系统中通过应变片获得稳态工况下的测试载荷

同步采集测风塔、雷达等风特性信息以及数据采集与监视控制（SCADA）系统获得风力机控制状态信息

并根据风速俘获矩阵模拟得到仿真载荷;由于测试载荷数据时长与设计载荷时长不同

为便于比较

将设计载荷、测试载荷、仿真载荷都转换为1 Hz下的等效疲劳载荷进行对比。结果表明：同一截面测试载荷与设计载荷比值在104.0%~130.2%区间

符合叶片载荷设计安全裕量

同一截面测试载荷与仿真载荷比值差异较大

说明稳态工况下载荷监测的动态变化与湍流强度强相关

有必要监测风剪切和湍流参数以反映实际载荷有效防止过载运行。

Abstract

The problem of blade load testing and identification are discussed for onshore wind turbines operating under steady state conditions. Firstly

the load test scheme is designed based on the equivalent fatigue load theory and strain load measurement technology. According to the load measurement requirements

data acquisition

sensor layout and calibration are carried out to build the blade monitoring system. Secondly

the strain gauges are used in the blade monitoring system to obtain the test load under steady state conditions. In the blade monitoring system

the wind characteristic information from wind tower and radar is collected synchronously. At the same time

the wind turbine control state information is obtained by the SCADA system. The simulation load is obtained according to the wind speed capture matrix. Since the test load data duration is different from that of the design load

the design load

test load and simulation load are converted to equivalent fatigue load at 1Hz for comparison. The results show that the ratio of test load and design load of the same section is in the range of 104.0%-130.2%

which meets the safety margin of blade load design. The test load and simulation load of the same section are quite different

indicating that the dynamic change of load monitoring under steady state condition is strongly related to turbulence intensity. Therefore

it is necessary to monitor wind shear and turbulence parameters to reflect the actual load

which can prevent overload operation effectively.

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Keywords

references

REN Z R, VERMA A S, LI Y, et al.Offshore wind turbine operations and maintenance: a state-of-the-art review[J]. Renewable and sustainable energy reviews, 2021, 144: 110886.

DAI J C, LI M M, CHEN H G, et al.Progress and challenges on blade load research of large-scale wind turbines[J]. Renewable energy, 2022, 196: 482-496.

NIELSEN J S, TCHERNIAK D, ULRIKSEN M D.A case study on risk-based maintenance of wind turbine blades with structural health monitoring[J]. Structure and infrastructure engineering, 2021, 17(3): 302-318.

DU Y, ZHOU S X, JING X J, et al.Damage detection techniques for wind turbine blades: a review[J]. Mechanical systems and signal processing, 2020, 141: 106445.

GARCÍA MÁRQUEZ F P, PECO CHACÓN A M. A review of non-destructive testing on wind turbines blades[J]. Renewable energy, 2020, 161: 998-1010.

高峰, 张鸿, 许琳, 等. 风电机组叶片故障仿真与状态判别研究[J]. 太阳能学报, 2023, 44(4): 52-59.

LIU P F, XU D, LI J G, et al.Damage mode identification of composite wind turbine blade under accelerated fatigue loads using acoustic emission and machine learning[J]. Structural health monitoring, 2020, 19(4): 1092-1103.

CHANDRASEKHAR K, STEVANOVIC N, CROSS E J, et al.Damage detection in operational wind turbine blades using a new approach based on machine learning[J]. Renewable energy, 2021, 168: 1249-1264.

DAO C D, KAZEMTABRIZI B, CRABTREE C J, et al.Integrated condition-based maintenance modelling and optimisation for offshore wind turbines[J]. Wind energy, 2021, 24(11): 1180-1198.

陈雪峰, 郭艳婕, 许才彬, 等. 风电装备故障诊断与健康监测研究综述[J]. 中国机械工程, 2020, 31(2): 175-189.

陈雪峰, 杨志勃, 田绍华, 等. 复合材料结构损伤识别与健康监测展望[J]. 振动测试与诊断, 2018, 38(1): 1-10, 202.

SIERRA-PÉREZ J, TORRES-ARREDONDO M A, GÜEMES A. Damage and nonlinearities detection in wind turbine blades based on strain field pattern recognition FBGs, OBR and strain gauges comparison[J]. Composite structures, 2016, 135: 156-166.

MOYNIHAN B, MOAVENI B, LIBERATORE S, et al.Estimation of blade forces in wind turbines using blade root strain measurements with OpenFAST verification[J]. Renewable energy, 2022, 184: 662-676.

MYLONAS C, ABDALLAH I, CHATZI E.Conditional variational autoencoders for probabilistic wind turbine blade fatigue estimation using Supervisory, Control, and Data Acquisition data[J]. Wind energy, 2021, 24(10): 1122-1139.

ZHU P Y, FENG X B, LIU Z, et al.Reliable packaging of optical fiber Bragg grating sensors for carbon fiber composite wind turbine blades[J]. Composites science and technology, 2021, 213: 108933.

王超, 戴巨川, 杨鑫, 等. 基于“应变-载荷” 模型的大型风电机组叶片载荷识别研究[J]. 太阳能学报, 2019, 40(5): 1423-1432.

李德顺, 胡渊, 李仁年, 等. 强湍流相干结构对偏航风力机叶根载荷的影响[J]. 农业工程学报, 2020, 36(20): 102-109.

KAEWNIAM P, CAO M S, ALKAYEM N F, et al.Recent advances in damage detection of wind turbine blades: a state-of-the-art review[J]. Renewable and sustainable energy reviews, 2022, 167: 112723.

IEC/TS 61400-13,Wind turbine generator systems-part 13: measurement of mechanical loads[S].

JB/T 25383—2010, 风力发电机组-风轮叶片[S].

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