基于振动响应的风力机塔筒法兰螺栓损伤识别方法研究

庞河清; 张万福; 张世东; 薛聪聪; 刘兵; 李春

doi:doi:10.19912/j.0254-0096.tynxb.2024-1276

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基于振动响应的风力机塔筒法兰螺栓损伤识别方法研究

更新时间：2025-12-10

- 基于振动响应的风力机塔筒法兰螺栓损伤识别方法研究
- Issue 11, Pages: 704-712(2025)
- 作者机构：
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- DOI：doi:10.19912/j.0254-0096.tynxb.2024-1276
  CLC： K131
- Published Online：04 December 2025，
  
  Published：04 December 2025
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庞河清, 张万福, 张世东, et al. 基于振动响应的风力机塔筒法兰螺栓损伤识别方法研究[J]. 2025, (11): 704-712.
DOI：

庞河清, 张万福, 张世东, et al. 基于振动响应的风力机塔筒法兰螺栓损伤识别方法研究[J]. 2025, (11): 704-712. DOI： doi:10.19912/j.0254-0096.tynxb.2024-1276.

摘要

摘要：针对风力机塔筒法兰螺栓断裂损伤识别问题

提出一种利用振动信号响应进行螺栓断裂损伤识别的检测方法

基于频率响应函数损伤识别理论

建立关于振动响应能量绝对变化率的损伤识别指标。以某1.5 MW风力机为研究对象

通过数值模拟对比分析应变、位移与加速度信号并得到不同损伤工况下该指标的识别效果。结果表明：相较于位移与加速度响应信号

基于应变响应的振动能量绝对变化率在识别螺栓断裂损伤方面表现出更高的灵敏度与准确性; 基于应变响应的能量损伤指标在螺栓断裂损伤部位会发生显著突变

可精准识别风力机塔筒段法兰螺栓断裂损伤位置。

Abstract

To address the problem of damage identification of wind turbine tower flange bolts

this paper proposes a detection method of bolt fracture damage identification using vibration signal response

and establishes a damage identification index based on the absolute rate of change of vibration response energy based on the damage identification theory of frequency response function. Taking a 1.5 MW wind turbine as the research object

the strain

displacement and acceleration signals are compared and analyzed by numerical simulation

and the identification effect of the index under different damage conditions is obtained. The results show that the absolute rate of change of vibration energy based on strain response shows higher sensitivity and accuracy in identifying the bolt fracture damage compared with the displacement and acceleration response signals

and the energy damage indicator based on strain response shows a significant change at the bolt fracture damage site

which can accurately identify the bolt fracture damage location of the tower section flange of the wind turbine.

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Keywords

references

焦巍峰. 光伏技术在建筑行业中的应用[J]. 太阳能学报, 2024, 45(7): 751.

李杨, 兰涌森, 李强, 等. 风力机塔架结构振动控制研究及方法综述[J]. 船舶工程, 2020, 42(S2): 248-253.

Global wind energy council. Global wind report 2025[R]. Brussels: Global wind energy council, 2025.

张洪达, 李怀刚, 郭家沛. 预紧力对风力发电机组偏航轴承螺栓的影响[J]. 山东电力技术, 2022, 49(4): 63-69, 80.

樊昂, 李录平, 张世海, 等. 大型风电机组塔筒动力学特性与寿命损耗研究进展[J]. 发电技术, 2022, 43(3): 421-430.

周舟, 杨理诚, 梁勇, 等. 大型风力机基础法兰高强度螺栓断裂失效分析[J]. 太阳能学报, 2016, 37(9): 2230-2235.

KHOMENKO A, KORICHO E G, HAQ M, et al.Bolt tension monitoring with reusable fiber Bragg-grating sensors[J]. The journal of strain analysis for engineering design, 2016, 51(2): 101-108.

MA T J, FENG Q, TAN Z S, et al.Optical phase mode analysis method for pipeline bolt looseness identification using distributed optical fiber acoustic sensing[J]. Structural health monitoring, 2024, 23(3): 1547-1559.

杨帅杰. 风力发电塔螺栓松动监测系统的建立与应用[J]. 建筑结构, 2023, 53(S1): 2131-2136.

魏泰, 吴坤, 黄军威. 风机塔筒螺栓防松检测技术[J]. 机械与电子, 2013, 31(8): 78-80.

武金, 屈文忠, 肖黎. 基于3/2维谱的螺栓松动非线性检测及定位[J]. 振动与冲击, 2020, 39(5): 157-163.

XIE C Q, LUO J, TANG K S, et al.Image-based bolt self-localization and bolt-loosening detection using deep learning and an improved homography-based prospective rectification method[J]. Advances in structural engineering, 2023, 26(7): 1242-1259.

SAMANTARAY S K, MITTAL S K, MAHAPATRA P, et al.An impedance-based structural health monitoring approach for looseness identification in bolted joint structure[J]. Journal of civil structural health monitoring, 2018, 8(5): 809-822.

LIAO W L, SUN H, WANG Y S, et al.A novel damage index integrating piezoelectric impedance and ultrasonic guided wave for damage monitoring of bolted joints[J]. Structural health monitoring, 2023, 22(5): 3514-3533.

MOHARANA S, SEVUGAPERUMAL ARUN V.Piezo impedance-based monitoring of loosening of bolts: experimental and numerical study[J]. Journal of intelligent material systems and structures, 2022, 33(8): 1056-1071.

何先龙, 佘天莉, 徐兵, 等. 基于塔筒振动特性识别风机塔螺栓松动的研究[J]. 振动与冲击, 2016, 35(14): 112-118.

WEN G R, ZHAO L, LIU Z C, et al.Research on loose bolt localization technology for transmission towers[J]. Structural health monitoring, 2024, 23(5): 3134-3155.

NGUYEN T C, HUYNH T C, YI J H, et al.Hybrid bolt-loosening detection in wind turbine tower structures by vibration and impedance responses[J]. Wind and structures, 2017, 24(4): 385-403.

张则荣, 李鹏飞, 韩桐桐, 等. 基于应变模态的风机塔筒法兰螺栓断裂损伤监测研究[J]. 机电工程, 2021, 38(10): 1348-1354.

LI S Z, LI H, ZHOU X H, et al.Damage detection of flange bolts in wind turbine towers using dynamic strain responses[J]. Journal of civil structural health monitoring, 2023, 13(1): 67-81.

赵思钛, 吕伟荣, 戚菁菁, 等. 基于柔度系数影响线的风力机塔架法兰螺栓松动识别方法研究[J]. 工程力学, 2023, 40(12): 185-193.

刘永杰, 邓雅琼, 栗娜, 等. 车用阻尼板辐射噪声建模分析方法技术研究[J]. 噪声与振动控制, 2019, 39(6): 222-225.

张磊, 曹跃云, 郭光林. 机械振动系统的频响函数估计方法研究[J]. 武汉理工大学学报(交通科学与工程版), 2014, 38(6): 1286-1290.

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