基于固有频率的风力机叶片裂纹精确定位与程度识别

吴琪强,郭帅平,王钢,李学军

振动与冲击 ›› 2019, Vol. 38 ›› Issue (24) : 18-27.

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PDF(2135 KB)
振动与冲击 ›› 2019, Vol. 38 ›› Issue (24) : 18-27.
论文

基于固有频率的风力机叶片裂纹精确定位与程度识别

  • 吴琪强,郭帅平,王钢,李学军
作者信息 +

Accurate location and degree identification of  wind turbine blade cracks based on natural frequency

  • WU Qiqiang,GUO Shuaiping,WANG Gang,LI Xuejun
Author information +
文章历史 +

摘要

针对叶片裂纹诊断问题,基于裂纹引起的叶片任意两阶固有频率变化之比只与损伤位置有关的性质, 提出了基于任意两阶固有频率变化比的裂纹位置参数、裂纹定位参数及裂纹定位准则;将叶片表面划分多个区域,每次在区域边界植入单个裂纹,计算裂纹定位参数,实现叶片裂纹所属区间定位;同时,研究叶片裂纹定位参数在裂纹区间内的变化规律,建立了裂纹定位参数与区间相对位置间的映射关系,实现了叶片裂纹区间内的精确定位。基于完好叶片与裂纹叶片一阶固有频率变化量的平方与一阶固有频率之比只与损伤程度相关的性质,建立了叶片不同裂纹位置下裂纹损伤程度函数模型,实现叶片裂纹损伤程度的识别。通过数值仿真分析及试验验证了该方法的有效性,且识别精度较高,为实际的应用提供有力的依据。

Abstract

The structure health condition of a wind turbine blade is closely related to public safety.Cracks in wind turbine blades affect safe operation of wind turbines.The diagnosis of blade cracks is of paramount importance.The cracks influence the natural frequency of the blades.In wind turbine blades, the natural frequency variation of the structure caused by the crack is related to its position.In terms of the ratio of the adjacent two-order natural frequency variation, it was found that the ratio is related to the crack position alone.Based on the ratio parameters, the blade can be fictitiously divided into multiple connected regions.The crack is implanted at each joint point of regions to establish the database of the ratio parameters for crack locating.The region where the crack exists can be ascertained.Then, a new position parameter in the region was proposed, and the mapping between this parameter and the detail position within the region was established.The crack can be located more accurate in the regions.In order to identify the degree of the crack, a parameter of crack degree, which is defined as the ratio of the variation of the natural frequency to the natural frequency itself, was proposed.Based on simulation and data analysis, the correlation between the parameter and the degree of crack was established.Based on the correlation, the degree of crack can be ascertained by the correlation after crack locating.Numerical simulation analysis and tests for blade with different cross-sectional shapes were performed, and the results all show that the method is effective and accurate.

关键词

风力机叶片 / 固有频率 / 裂纹定位 / 损伤程度

Key words

wind turbine blade / natural frequency / crack location / damage degree

引用本文

导出引用
吴琪强,郭帅平,王钢,李学军. 基于固有频率的风力机叶片裂纹精确定位与程度识别[J]. 振动与冲击, 2019, 38(24): 18-27
WU Qiqiang,GUO Shuaiping,WANG Gang,LI Xuejun. Accurate location and degree identification of  wind turbine blade cracks based on natural frequency[J]. Journal of Vibration and Shock, 2019, 38(24): 18-27

参考文献

 

[1]       Herbert G M J, Iniyan S, Sreevalsan E, et al. A review of wind energy technologies[J]. Renewable and sustainable energy Reviews, 2007, 11(6): 1117-1145.
[2]       Council G W E. Global wind statistics 2011[J]. Global Wind Report, 2011.
[3]       Caithness Windfarm Information Forum. Summary of wind turbine accident data to 31 March 2019.
http://www.caithnesswindfarms.co.uk/AccidentStatistics.htm.
[4]       Burton T, Sharpe D, Jenkins N, Bossanyi E. Wind energy handbook. New York:John Wiley & Sons; 2001
[5]       Cross E J, Manson G, Worden K, et al. Features for damage detection with insensitivity to environmental and operational variations[J]. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2012, 468(2148): 4098-4122.
[6]       Larsen F M. New lightning qualification test procedure for large wind turbine blades[C]//International Conference on Lightning and Static Electricity (ICLOSE), Blackpool, 2003. 2003.
[7]       Hameed Z, Hong Y S, Cho Y M, et al. Condition monitoring and fault detection of wind turbines and related algorithms: A review[J]. Renewable and Sustainable energy reviews, 2009, 13(1): 1-39.
[8]       Yang W , Lang Z , Tian S . Condition Monitoring and Damage Location of Wind Turbine Blades by Frequency Response Transmissibility Analysis[J]. IEEE Transactions on Industrial Electronics, 2015, 62(10):1-1.
[9]       Kamath G M, Sundaram R, Gupta N, et al. Damage studies in composite structures for structural health monitoring using strain sensors[J]. Structural Health Monitoring, 2010, 9(6): 497-512.
[10]    Lucklum F, Jakoby B. Novel magnetic–acoustic resonator sensors for remote liquid phase measurement and mass detection[J]. Sensors and Actuators A: Physical, 2008, 145: 44-51.
[11]    Hanke R, Fuchs T, Uhlmann N. X-ray based methods for non-destructive testing and material characterization[J]. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2008, 591(1): 14-18.
[12]    Kopsaftopoulos F P, Fassois S D. Vibration based health monitoring for a lightweight truss structure: experimental assessment of several statistical time series methods[J]. Mechanical Systems and Signal Processing, 2010, 24(7): 1977-1997.
[13]    张宇飞,王山山.基于频响函数虚部的梁结构损伤检测[J].振动与冲击,2018,37(02):38-42.
Damage detection for a beam based on imaginary part of its FRF [J].Journal of Vibration and Shock, 2018, 37(02): 38-42.
[14]    Wang Y, Liang M, Xiang J. Damage detection method for wind turbine blades based on dynamics analysis and mode shape difference curvature information[J]. Mechanical Systems and Signal Processing, 2014, 48(1-2): 351-367.
[15]    高海洋,郭杏林,吴明勇.基于频响函数虚部的板结构损伤检测方法研究[J].振动与冲击,2012,31(12):86-91.
Gao Haiyang, Guo Xinglin, Wu Mingyong. Damage detection for a plate based on imaginary part of frequency response function[J].Journal of Vibration and Shock, 2012,31(12):86-91.
[16]    Pandey A K, Biswas M, Samman M M. Damage detection from changes in curvature mode shapes[J]. Journal of sound and vibration, 1991, 145(2): 321-332.
[17]    Zou Y, Tong L, Steven G P. Vibration-based model-dependent damage (delamination) identification and health monitoring for composite structures—a review[J]. Journal of Sound and vibration, 2000, 230(2): 357-378.
[18]    Xie Jun, Han Dajian. An improved method for structure damage detection based on frequency measurement[J]. Engineering Mechanics, 2004. 21(1); 21–25.
[19]    Bahlous S E O, Smaoui H, El-Borgi S. Experimental validation of an ambient vibration-based multiple damage identification method using statistical modal filtering[J]. Journal of sound and vibration, 2009, 325(1-2): 49-68.
[20]    Cawley P, Adams R D. The location of defects in structures from measurements of natural frequencies[J]. The Journal of Strain Analysis for Engineering Design, 1979, 14(2): 49-57.
[21]    金虎,楼文娟.基于位置和程度指标的结构损伤识别研究[J].浙江大学学报(工学版),2006(08):1393-1398.
Jin Hu, Lou Wenjuan. Structural damage identification research based on location index and extent index [J].Journal of Zhejiang University(Engineering Science), 2006(08): 1393-1398.
[22]    Zhang K, Yan X. Multi-cracks identification method for cantilever beam structure with variable cross-sections based on measured natural frequency changes[J]. Journal of Sound and Vibration, 2017, 387: 53-65.
[23]    Yu M, Fu S, Gao Y, et al. Crack detection of fan blade based on natural frequencies[J]. International Journal of Rotating Machinery, 2018, 2018.
[24]    Ercolani G D, Felix D H, Ortega N F. Crack detection in prestressed concrete structures by measuring their natural frequencies[J]. Journal of Civil Structural Health Monitoring, 2018, 8(4): 661-671.
[25]    Hearn G, Testa R B. Modal analysis for damage detection in structures[J]. Journal of Structural Engineering , 1991, 117(10): 3042-3063.

Ciang C C, Lee J R, Bang H J. Structural health monitoring for a wind turbine system: a review of damage detection methods[J]. Measurement science and technology, 2008, 19(12): 12200

[1]       Herbert G M J, Iniyan S, Sreevalsan E, et al. A review of wind energy technologies[J]. Renewable and sustainable energy Reviews, 2007, 11(6): 1117-1145.

[2]       Council G W E. Global wind statistics 2011[J]. Global Wind Report, 2011.

[3]       Caithness Windfarm Information Forum. Summary of wind turbine accident data to 31 March 2019.

http://www.caithnesswindfarms.co.uk/AccidentStatistics.htm.

[4]       Burton T, Sharpe D, Jenkins N, Bossanyi E. Wind energy handbook. New York:John Wiley & Sons; 2001

[5]       Cross E J, Manson G, Worden K, et al. Features for damage detection with insensitivity to environmental and operational variations[J]. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2012, 468(2148): 4098-4122.

[6]       Larsen F M. New lightning qualification test procedure for large wind turbine blades[C]//International Conference on Lightning and Static Electricity (ICLOSE), Blackpool, 2003. 2003.

[7]       Hameed Z, Hong Y S, Cho Y M, et al. Condition monitoring and fault detection of wind turbines and related algorithms: A review[J]. Renewable and Sustainable energy reviews, 2009, 13(1): 1-39.

[8]       Yang W , Lang Z , Tian S . Condition Monitoring and Damage Location of Wind Turbine Blades by Frequency Response Transmissibility Analysis[J]. IEEE Transactions on Industrial Electronics, 2015, 62(10):1-1.

[9]       Kamath G M, Sundaram R, Gupta N, et al. Damage studies in composite structures for structural health monitoring using strain sensors[J]. Structural Health Monitoring, 2010, 9(6): 497-512.

[10]    Lucklum F, Jakoby B. Novel magnetic–acoustic resonator sensors for remote liquid phase measurement and mass detection[J]. Sensors and Actuators A: Physical, 2008, 145: 44-51.

[11]    Hanke R, Fuchs T, Uhlmann N. X-ray based methods for non-destructive testing and material characterization[J]. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2008, 591(1): 14-18.

[12]    Kopsaftopoulos F P, Fassois S D. Vibration based health monitoring for a lightweight truss structure: experimental assessment of several statistical time series methods[J]. Mechanical Systems and Signal Processing, 2010, 24(7): 1977-1997.

[13]    张宇飞,王山山.基于频响函数虚部的梁结构损伤检测[J].振动与冲击,2018,37(02):38-42.

Damage detection for a beam based on imaginary part of its FRF [J].Journal of Vibration and Shock, 2018, 37(02): 38-42.

[14]    Wang Y, Liang M, Xiang J. Damage detection method for wind turbine blades based on dynamics analysis and mode shape difference curvature information[J]. Mechanical Systems and Signal Processing, 2014, 48(1-2): 351-367.

[15]    高海洋,郭杏林,吴明勇.基于频响函数虚部的板结构损伤检测方法研究[J].振动与冲击,2012,31(12):86-91.

Gao Haiyang, Guo Xinglin, Wu Mingyong. Damage detection for a plate based on imaginary part of frequency response function[J].Journal of Vibration and Shock, 2012,31(12):86-91.

[16]    Pandey A K, Biswas M, Samman M M. Damage detection from changes in curvature mode shapes[J]. Journal of sound and vibration, 1991, 145(2): 321-332.

[17]    Zou Y, Tong L, Steven G P. Vibration-based model-dependent damage (delamination) identification and health monitoring for composite structures—a review[J]. Journal of Sound and vibration, 2000, 230(2): 357-378.

[18]    Xie Jun, Han Dajian. An improved method for structure damage detection based on frequency measurement[J]. Engineering Mechanics, 2004. 21(1); 21–25.

[19]    Bahlous S E O, Smaoui H, El-Borgi S. Experimental validation of an ambient vibration-based multiple damage identification method using statistical modal filtering[J]. Journal of sound and vibration, 2009, 325(1-2): 49-68.

[20]    Cawley P, Adams R D. The location of defects in structures from measurements of natural frequencies[J]. The Journal of Strain Analysis for Engineering Design, 1979, 14(2): 49-57.

[21]    金虎,楼文娟.基于位置和程度指标的结构损伤识别研究[J].浙江大学学报(工学版),2006(08):1393-1398.

Jin Hu, Lou Wenjuan. Structural damage identification research based on location index and extent index [J].Journal of Zhejiang University(Engineering Science), 2006(08): 1393-1398.

[22]    Zhang K, Yan X. Multi-cracks identification method for cantilever beam structure with variable cross-sections based on measured natural frequency changes[J]. Journal of Sound and Vibration, 2017, 387: 53-65.

[23]    Yu M, Fu S, Gao Y, et al. Crack detection of fan blade based on natural frequencies[J]. International Journal of Rotating Machinery, 2018, 2018.

[24]    Ercolani G D, Felix D H, Ortega N F. Crack detection in prestressed concrete structures by measuring their natural frequencies[J]. Journal of Civil Structural Health Monitoring, 2018, 8(4): 661-671.

[25]    Hearn G, Testa R B. Modal analysis for damage detection in structures[J]. Journal of Structural Engineering , 1991, 117(10): 3042-3063.

[26]   Ciang C C, Lee J R, Bang H J. Structural health monitoring for a wind turbine system: a review of damage detection methods[J]. Measurement science and technology, 2008, 19(12): 12200


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