Processing and Analysis of Acoustic Emission Signals from Wind Turbine Blades Using Wavelet Analysis

GUAN Yunan; WANG Chao; SONG Boyang

doi:10.7652/xjtuxb202505020

您当前的位置：

首页 >

文章列表页 >

Processing and Analysis of Acoustic Emission Signals from Wind Turbine Blades Using Wavelet Analysis

更新时间：2025-08-26

- Processing and Analysis of Acoustic Emission Signals from Wind Turbine Blades Using Wavelet Analysis
- Journal of Xi’an Jiaotong University Vol. 59, Issue 5, Pages: 209-216(2025)
- 作者机构：
  
  1.西北工业大学航海学院， 710072，西安
  2.中国船舶集团有限公司， 200011，上海
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202505020
  CLC： TM315
- Received：18 July 2024，
  
  Online First：22 October 2024，
  
  Published：10 May 2025
- 稿件说明：
移动端阅览
GUAN Yunan, WANG Chao, SONG Boyang. Processing and Analysis of Acoustic Emission Signals from Wind Turbine Blades Using Wavelet Analysis[J]. Journal of Xi’an Jiaotong University, 2025, 59(5): 209-216.
DOI：

GUAN Yunan, WANG Chao, SONG Boyang. Processing and Analysis of Acoustic Emission Signals from Wind Turbine Blades Using Wavelet Analysis[J]. Journal of Xi’an Jiaotong University, 2025, 59(5): 209-216. DOI： 10.7652/xjtuxb202505020.

摘要

为有效对风力机叶片损伤进行在线监测，采用小波分析技术对风力机叶片运行状态下的声发射信号进行降噪和时频分析。采用多通道高频采集设备搭配声发射传感器，搭建双通道声发射信号在线检测系统，实时采集某型全尺寸叶片带伤运行声发射信号，改进了小波阈值降噪方法并对该方法在真实叶片损伤定位和模态分析中的表现进行检验。实验结果表明：与传统的维纳滤波降噪、谱减法降噪等方法相比，改进的小波阈值降噪方法应用于在线监测系统时具有精度高、速度快、稳定性好的优势：对模拟损伤的声发射信号进行时差定位，精度达到2.2%；同时，采用改进的小波分析也能够从风力机叶片的声发射信号中准确检出叶片的运行模态信息。改进的小波阈值降噪在风力机叶片损伤定位和模态信息检测方面表现良好，具备实际的应用价值。

Abstract

To effectively conduct online monitoring of the damage to wind turbine blades

wavelet analysis technology was adopted to reduce noise and perform time-frequency analysis on the acoustic emission signals of wind turbine blades during operation. A dual-channel acoustic emission signal online detection system consisting of a multi-channel high-frequency acquisition device and several domestic acoustic emission sensors was established to collect real-time acoustic emission signals from a certain type of full-scale blade operating with damage. The wavelet threshold denoising method was optimized and its performance in the localization and operation modal analysis of actual blade damage was also examined. As revealed by experimental results

in contrast to traditional methods such as Wiener filtering denoising and spectral subtraction denoising

the optimized wavelet threshold denoising method features high precision

fast speed

and good stability when applied to the online monitoring system: The time difference positioning accuracy for the acoustic emission signals of simulated damage reaches 2.2%; wavelet analysis can also effectively detect the operation modal information of the blades. The experiment reveals that wavelet threshold denoising performs well in the aspects of damage localization and modal information detection of wind turbine blades and holds practical application value.

关键词

Keywords

references

陈露露 . 风电叶片无损检测技术和标准现状研究 [J ] . 装备制造技术 , 2017 ( 12 ): 44 - 46 .

CHEN Lulu . Non-destructive testing techniques of wind turbine blades and standard research [J ] . Equipment Manufacturing Technology , 2017 ( 12 ): 44 - 46 .

朱静 . 风电机组传动系统故障检测及诊断研究 [D ] . 南京 : 东南大学 , 2017 .

GHOLIZADEH S , LEMAN Z , BAHARUDIN B T H T . A review of the application of acoustic emission technique in engineering [J ] . Structural Engineering and Mechanics , 2015 , 54 ( 6 ): 1075 - 1095 .

李孟珠 , 刘纲 , 黎华 , 等 . 大型风力机叶片状态监测方法研究进展 [J ] . 热力发电 , 2022 , 51 ( 12 ): 18 - 29 .

LI Mengzhu , LIU Gang , LI Hua , et al . Research progress on condition monitoring methods of large scale wind turbine blades [J ] . Thermal Power Generation , 2022 , 51 ( 12 ): 18 - 29 .

LIU Zepeng , ZHANG Long , CARRASCO J . Vibration analysis for large-scale wind turbine blade bearing fault detection with an empirical wavelet thresholding method [J ] . Renewable Energy , 2020 , 146 : 99 - 110 .

LIU Zepeng , YANG Boyuan , WANG Xuefei , et al . Acoustic emission analysis for wind turbine blade bearing fault detection under time-varying low-speed and heavy blade load conditions [J ] . IEEE Transactions on Industry Applications , 2021 , 57 ( 3 ): 2791 - 2800 .

BEALE C , NIEZRECKI C , INALPOLAT M . An adaptive wavelet packet denoising algorithm for enhanced active acoustic damage detection from wind turbine blades [J ] . Mechanical Systems and Signal Processing , 2020 , 142 : 106754 .

XUE Xinyu , SUN Dabiao , GU Lei , et al . Application of synchrosqueezed wavelet transforms in Lamb wave based structural health monitoring of wind turbine blades [C ] // 2019 Chinese Control and Decision Conference (CCDC) . Piscataway, NJ, USA : IEEE , 2019 : 3190 - 3195 .

孙永军 . 小波理论及其在信号处理中的应用 [J ] . 空间电子技术 , 2009 , 6 ( 4 ): 25 - 30 .

SUN Yongjun . Wavelet theory and its applications in signal processing [J ] . Space Electronic Technology , 2009 , 6 ( 4 ): 25 - 30 .

GUO Tiantian , ZHANG Tongpo , LIM E , et al . A review of wavelet analysis and its applications: challenges and opportunities [J ] . IEEE Access , 2022 , 10 : 58869 - 58903 .

ZHAO Qian , LI Wei , SHAO Yichuan , et al . Damage detection of wind turbine blade based on wavelet analysis [C ] // 2015 8th International Congress on Image and Signal Processing (CISP) . Piscataway, NJ, USA : IEEE , 2015 : 1406 - 1410 .

张瑞 , 邓艾东 , 司晓东 , 等 . 一种新的声发射信号消噪及故障诊断方法 [J ] . 振动与冲击 , 2018 , 37 ( 4 ): 75 - 81 .

ZHANG Rui , DENG Aidong , SI Xiaodong , et al . A new method for acoustic emission signal de-noised and fault diagnosis [J ] . Journal of Vibration and Shock , 2018 , 37 ( 4 ): 75 - 81 .

ZHU Yongqiang , LANG Xianming , ZHANG Lin , et al . Leak localization method of jet fuel pipeline based on second-generation wavelet transform and short-time energy time delay estimation [J ] . IEEE Sensors Journal , 2023 , 23 ( 3 ): 2823 - 2832 .

PRATUMNOPHARAT P , LEUNG P S , COURT R S . Application of Morlet wavelet in the stress-time history editing of horizontal axis wind turbine blades [C ] // 2012 2nd International Symposium on Environment Friendly Energies and Applications . Piscataway, NJ, USA : IEEE , 2012 : 396 - 401 .

OGAILI A A , HAMZAH M N , JABER A A , et al . Application of discrete wavelet transform for condition monitoring and fault detection in wind turbine blades: an experimental study [J ] . Engineering and Technology Journal , 2024 , 42 ( 1 ): 104 - 116 .

JANELIUKSTIS R . Continuous wavelet transform-based method for enhancing estimation of wind turbine blade natural frequencies and damping for machine learning purposes [J ] . Measurement , 2021 , 172 : 108897 .

ULRIKSEN M D , TCHERNIAK D , KIRKEGAARD P H , et al . Operational modal analysis and wavelet transformation for damage identification in wind turbine blades [J ] . Structural Health Monitoring , 2016 , 15 ( 4 ): 381 - 388 .

XU D , LIU P F , CHEN Z P . Damage mode identification and singular signal detection of composite wind turbine blade using acoustic emission [J ] . Composite Structures , 2021 , 255 : 112954 .

ULRIKSEN M D , SKOV J F , KIRKEGAARD P H , et al . Wavelet transformation for damage identification in wind turbine blades [C ] // Structural Health Monitoring . Cham, Switzerland : Springer International Publishing , 2014 : 187 - 193 .

刘崇春 , 裘正定 , 杜锡钰 . 小波变换理论及其在信号处理中的应用 [J ] . 北方交通大学学报 , 1997 , 21 ( 1 ): 24 - 31 .

LIU Chongchun , QIU Zhengding , DU Xiyu . Wavelet transform theory and its application in signal processing [J ] . Journal of Northern Jiaotong University , 1997 , 21 ( 1 ): 24 - 31 .

耿艳峰 , 冯叔初 . 小波构造综述 [J ] . 石油大学学报(自然科学版) , 2004 , 28 ( 1 ): 127 - 131 .

GENG Yanfeng , FENG Shuchu . Overview of wavelet construction [J ] . Journal of the University of Petroleum, China , 2004 , 28 ( 1 ): 127 - 131 .

SAHOO G R , FREED J H , SRIVASTAVA M . Optimal wavelet selection for signal denoising [J ] . IEEE Access , 2024 , 12 : 45369 - 45380 .

裴嵩 , 孙超 . 声发射信号的小波阈值降噪研究 [J ] . 舰船电子对抗 , 2023 , 46 ( 5 ): 88 - 91 .

PEI Song , SUN Chao . Research into wavelet threshold value de-noising of AE signals [J ] . Shipboard Electronic Countermeasure , 2023 , 46 ( 5 ): 88 - 91 .

高琳 , 曹建国 . 基于输气管道泄漏声发射信号特征的小波基构造研究 [J ] . 振动与冲击 , 2023 , 42 ( 10 ): 128 - 135 .

GAO Lin , CAO Jianguo . Research on wavelet basis construction based on the characteristics of acoustic emission signals in gas pipe leakage [J ] . Journal of Vibration and Shock , 2023 , 42 ( 10 ): 128 - 135 .

秦永晋 , 郭亮 , 付力扬 , 等 . 基于LabVIEW的大功率海上风电机组增速箱轴承试验机测控系统设计 [J ] . 制造技术与机床 , 2022 ( 7 ): 85 - 90 .

QIN Yongjin , GUO Liang , FU Liyang , et al . Design of measurement and control system of bearing tester for speed increase box of high-power offshore wind turbine based on LabVIEW [J ] . Manufacturing Technology & Machine Tool , 2022 ( 7 ): 85 - 90 .

轩亮 , 董帅 , 董嘉欣 , 等 . 基于LabVIEW的风电主轴承螺栓预紧力监测系统 [J ] . 中国工程机械学报 , 2024 , 22 ( 2 ): 270 - 275 .

XUAN Liang , DONG Shuai , DONG Jiaxin , et al . The monitoring system of bolt preload of wind power main bearing based on LabVIEW [J ] . Chinese Journal of Construction Machinery , 2024 , 22 ( 2 ): 270 - 275 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Study on Wave Guide and Open Cavity Transient Response

Research on the Electrohydrodynamic Effects of Ionic Liquid-Modified Fuels

Numerical Simulation of the Energy Conversion Process in Thermoacoustic Engines with Different Stack Materials

Integrated and Joint Design Optimization of Centrifugal Compressor Impeller and Casing Treatment at Multiple Working Points

Effects of Steam Addition on the Swirl Combustion and Emission Characteristics of Cracked Ammonia

Related Author

张安学

师振盛

蒋延生

汪文秉

Related Institution

School of Electronics and Information Engineering, Xi'an Jiaotong University

⁰