STUDY ON DAMAGE CHARACTERISTICS OF WIND TURBINE BLADE MATERIALS BASED ON SENTINEL FUNCTION AND S-TRANSFORM

Liao Lida; Shu Wangyong; Zhang Zhiming; Liu Liang; Feng Fei; Chen Weiqiang

doi:10.19912/j.0254-0096.tynxb.2023-0472

PDF(5615 KB)

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (7) : 656-663. DOI: 10.19912/j.0254-0096.tynxb.2023-0472

STUDY ON DAMAGE CHARACTERISTICS OF WIND TURBINE BLADE MATERIALS BASED ON SENTINEL FUNCTION AND S-TRANSFORM

Liao Lida¹, Shu Wangyong¹, Zhang Zhiming¹, Liu Liang¹, Feng Fei², Chen Weiqiang²

Author information +

History +

Abstract

This paper studies the damage characteristics of fiberglass reinforced epory resin composite using acoustic emission detection technology. In this process, the sentinel function is used to characterize the degree of damage to the material, and the acoustic emission signals are analyzed through the S-transform and fuzzy C-means （FCM） clustering to obtain the damage characteristics of the material. After the three-point bending experiment, SEM （Scanning Electron Microscope） photos of the fracture surface of the test piece are taken for verification, and the following conclusions are obtained： Analysis of SEM photos reveals four damage modes： matrix cracking, fiber debonding, delamination damage, and fiber breakage; Sentinel function analysis of the entire acoustic emission event observed that the sentinel function curve showed a clear downward trend during the bending process of the test piece; The signals at different stages divided according to the sentinel function are denoised by VMD, and then the S transform is used for time-frequency analysis to obtain the characteristic frequencies of different damages, and finally verified by the FCM clustering. The results show that the sudden change of the sentinel function value can serve as an early warning signal for material fracture, and the identification of the type of material damage can be determined according to the frequency distribution results of the S transform.

Key words

wind turbine blades / composite materials / acoustic emissions / damage characteristics / sentry function / S transform

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Liao Lida, Shu Wangyong, Zhang Zhiming, Liu Liang, Feng Fei, Chen Weiqiang. STUDY ON DAMAGE CHARACTERISTICS OF WIND TURBINE BLADE MATERIALS BASED ON SENTINEL FUNCTION AND S-TRANSFORM[J]. Acta Energiae Solaris Sinica. 2024, 45(7): 656-663 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0472

References

[1] GONZÁLEZ-GONZÁLEZ A, JIMENEZ CORTADI A, GALAR D, et al. Condition monitoring of wind turbine pitch controller: a maintenance approach[J]. Measurement, 2018, 123: 80-93.
[2] 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.
[3] GHOLIZADEH S, LEMAN Z, BAHARUDIN B T H T. State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite(GFRP) using acoustic emission[J]. Ultrasonics, 2023, 132: 106998.
[4] 俞方艾, 周勃, 张雪岩, 等. 含分层缺陷的叶片复合材料层合板损伤识别方法的研究[J]. 机械强度, 2022, 44(6): 1327-1334.
YU F A, ZHOU B, ZHANG X Y, et al.A study on fatigue damage identification method of a blade composite laminate with delamination defects[J]. Journal of mechanical strength, 2022, 44(6): 1327-1334.
[5] XU D, LIU P F, CHEN Z P, et al.Achieving robust damage mode identification of adhesive composite joints for wind turbine blade using acoustic emission and machine learning[J]. Composite structures, 2020, 236: 111840.
[6] 黄喜鹏, 王波, 常杰. 基于声发射技术的陶瓷基复合材料声速特性[J]. 复合材料学报, 2021, 38(5): 1517-1525.
HUANG X P, WANG B, CHANG J.Acoustic emission-based sound velocity characteristics of ceramic matrix composites[J]. Acta materiae compositae sinica, 2021, 38(5): 1517-1525.
[7] ZHAO W Z, ZHOU W.Cluster analysis of acoustic emission signals and tensile properties of carbon/glass fiber-reinforced hybrid composites[J]. Structural health monitoring, 2019, 18(5/6): 1686-1697.
[8] WANG X H, XIE H, TONG Y G, et al.Three-point bending properties of 3D_C/C_TiC_Cu composites based on acoustic emission technology[J]. Mechanical systems and signal processing, 2023, 184: 109693.
[9] PANEK M, BLAZEWICZ S, KONSZTOWICZ K J.Correlation of acoustic emission with fractography in bending of glass-epoxy composites[J]. Journal of nondestructive evaluation, 2020, 39(3): 63.
[10] HOSEINLAGHAB S, FARAHANI M, SAFARABADI M, et al.Tension-after-impact analysis and damage mechanism evaluation in laminated composites using AE monitoring[J]. Mechanical systems and signal processing, 2023, 186: 109844.
[11] 邢广怀, 商雅静, 邢浩, 等. 三维编织复合材料拉伸损伤声发射监测与显微CT表征[J]. 工程塑料应用, 2021, 49(5): 108-113.
XING G H, SHANG Y J, XING H, et al.Acoustic emission monitoring and micro-CT characterization of tensile damage for three dimensional braided composites[J]. Engineering plastics application, 2021, 49(5): 108-113.
[12] 张亚楠, 周勃, 俞方艾, 等. 基于聚类分析的含原生缺陷风力机叶片拉伸缺陷演化研究[J]. 太阳能学报, 2021, 42(4): 396-402.
ZHANG Y N, ZHOU B, YU F A, et al.Study on evolution of tensile defects in wind turbine blades with primary defects based on cluster analysis[J]. Acta energiae solaris sinica, 2021, 42(4): 396-402.
[13] 张亚楠, 周勃, 俞方艾, 等. 含缺陷风电叶片复合材料的失稳状态识别和预测[J]. 太阳能学报, 2021, 42(9): 318-325.
ZHANG Y N, ZHOU B, YU F A, et al.Identification and prediction of instability status of composites with defective wind power blades[J]. Acta energiae solaris sinica, 2021, 42(9): 318-325.
[14] CHELLIAH S K, PARAMESWARAN P, RAMASAMY S, et al.Optimization of acoustic emission parameters to discriminate failure modes in glass-epoxy composite laminates using pattern recognition[J]. Structural health monitoring, 2019, 18(4): 1253-1267.
[15] AZADI M, SAYAR H, GHASEMI-GHALEBAHMAN A, et al.Tensile loading rate effect on mechanical properties and failure mechanisms in open-hole carbon fiber reinforced polymer composites by acoustic emission approach[J]. Composites part B: engineering, 2019, 158: 448-458.
[16] BEHESHTIZADEH N, MOSTAFAPOUR A, DAVOODI S.Three point bending test of glass/epoxy composite health monitoring by acoustic emission[J]. Alexandria engineering journal, 2019, 58(2): 567-578.
[17] JUNG D, LEE B S, YU W R, et al.Effect of propagation distance on acoustic emission of carbon fiber/epoxy composites[J]. Structural health monitoring, 2021, 20(6): 3342-3353.
[18] SAEEDIFAR M, NAJAFABADI M A, ZAROUCHAS D, et al.Barely visible impact damage assessment in laminated composites using acoustic emission[J]. Composites part B: engineering, 2018, 152: 180-192.
[19] STOCKWELL R G, MANSINHA L, LOWE R P.Localization of the complex spectrum: the S transform[J]. IEEE transactions on signal processing, 1996, 44(4): 998-1001.
[20] BAKHTIARY DAVIJANI A A, HAJIKHANI M, AHMADI M. Acoustic emission based on sentry function to monitor the initiation of delamination in composite materials[J]. Materials and design, 2011, 32(5): 3059-3065.
[21] BARILE C, CASAVOLA C, PAPPALETTERA G, et al.Damage characterization in composite materials using acoustic emission signal-based and parameter-based data[J]. Composites part B: engineering, 2019, 178: 107469.
[22] VERMA L, ANDREW J J, SIVAKUMAR S M, et al.Evaluation of quasi-static indentation response of superelastic shape memory alloy embedded GFRP laminates using AE monitoring[J]. Polymer testing, 2021, 93: 106942.
[23] LOGANATHAN T G, KALIDAS V K, BARI K, et al.Structural integrity evaluation of cyclic loading glass fibre reinforced polymer composite by acoustic emission and heat transfer[J]. Journal of composite materials, 2022, 56(24): 3715-3727.