Research on fan blade crack fault identification based on tip timing

被引：0

作者：

Sheng, Changwen ^{[1
]}

Jiang, Yongzheng ^{[1
]}

Huang, Lei ^{[2
]}

Zeng, Liying ^{[2
]}

Su, Bangwei ^{[2
]}

机构：

[1] Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan

[2] Xiangtan Industrial and Mining Electric Drive Vehicle Quality Inspection Center, Xiangtan

来源：

Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | 2024年 / 45卷 / 04期

关键词：

crack fault; crack identification; fan blade; tip offset; tip timing;

D O I：

10.19650/j.cnki.cjsi.J2412379

中图分类号：

TN78 [脉冲技术、脉冲电路];

学科分类号：

摘要：

Fan blade is a key component of wind turbine, and its crack fault is particularly common. The presence of cracks can cause damage to the blade or unit. Therefore, based on the tip timing principle and analysis method, a method of fan blade crack fault identification is proposed. Firstly, according to the principle of tip timing, the influence of blade crack on tip offset under load is analyzed, and the mathematical model between tip offset and tip offset time is established. Secondly, through the simulation analysis of blade tip offset degree in different states, combined with the mathematical model between different working condition parameters and tip offset time, the crack characteristic signal is identified. Finally, the results show that the recognition method proposed in this paper can successfully extract more than 92% of the characteristic signal of the crack, and can complete the extraction and analysis of the crack signal in real time, indicating that this method can realize the real-time recognition of the crack fault. © 2024 Science Press. All rights reserved.

引用

页码：57 / 65

页数：8

共 17 条

[1]

ZHANG Y N, ZHOU B, YU F AI, Et al., Recognition and prediction of instability state of wind turbine blade composites with defects [J], Acta Solar-Energy Sinica, 42, 9, pp. 318-325, (2021)

[2]

HEO G, JEON J, SON B., Crack automatic detection of CCTV video of sewer inspection with low resolution[J], KSCE Journal of Civil Engineering, 23, 3, pp. 1219-1227, (2019)

[3]

CHEN CH, Research on application of UAV inspection technology for wind farm fan blades [J], Wind Power Generation, 5, (2017)

[4]

WU J ZH, TAO Y., Crack damage detection of fan blades based on short-time Fourier transform, Journal of Chinese Engineering Machinery, 12, 2, pp. 180-183, (2014)

[5]

LIU X Q, WANG H Z, LONG G S, Et al., Research on automatic positioning system of ultrasonic testing of wind turbine blade flaws [J], IOP Conference Series: Earth and Environmental Science, 93, 1, pp. 012074-012074, (2017)

[6]

ZHOU B, ZH SH W, CHEN CH ZH, Et al., Wind turbine blade crack propagation characteristics of acoustic emission signals more recognition, Chinese Journal of Scientific Instrument, 36, 1, pp. 110-117, (2015)

[7]

ZHAO J, CHEN B, LI Y ZH, Et al., Acoustic feature extraction method of fan blade crack fault under complex background noise [J], Journal of Beijing University of Posts and Telecommunications, 40, 5, pp. 117-122, (2017)

[8]

GALLEGUILLOS C, ZORRILLA A, JIMENEZ A, Et al., Thermographic non-destructive inspection of wind turbine blades using unmanned aerial systems [J], Plastics Rubber and Composites, 44, 3, pp. 98-103, (2015)

[9]

YU J, HE Y, ZHANG F, Et al., An infrared image stitching method for wind turbine blade using UAV flight data and U-Net [J], IEEE Sensors Journal, 23, pp. 8727-8736, (2023)

[10]

HE Y Z, LI X, WANG H J, Et al., Review of full cycle nondestructive testing of fan blades based on visible light and thermal imaging, Chinese Journal of Mechanical Engineering, 59, 6, pp. 32-45, (2023)

← 1 2 →