Quantitative defect inspection in the curved composite structure using the modified probabilistic tomography algorithm and fusion of damage index

被引:29
作者
Jin, Hashen [1 ]
Yan, Jiajia [1 ]
Liu, Xiao [1 ]
Li, Weibin [1 ]
Qing, Xinlin [1 ]
机构
[1] Xiamen Univ, Sch Aerosp Engn, Xiamen 361005, Peoples R China
关键词
Curved composite structure; Ultrasonic guided waves; Damage index; Defect shape factor; Probabilistic tomography;
D O I
10.1016/j.ultras.2021.106358
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
The curved composite structures are popularly used in the aerospace field for their superior properties. Complexity of structure and geometry generally limit the inspection or monitoring effect of different types of defects in the curved composite structure. A feasible damage probabilistic tomography algorithm combined with ultrasonic guided wave technology is necessary to be developed for the structural health monitoring of curved composite structures. In this paper, defect zones in a curved composite structure are characterized using the modified probabilistic tomography (MPT) method and fusion of damage index (DI). The MPT with the defect shape factor beta M at each damage-impaired path and hybrid DI schemes are proposed to indicate the location and propagation of defect zones in tested sample. The feasibility of proposed approaches is verified on the curved carbon/epoxy composite structure, experimentally. The results show that the MPT and fusion DI methods successfully represent the extension of defect zones in a quantitative manner. It is suggested that the accuracy and reliability of localization results of the MPT algorithm is better than those obtained by the probabilistic tomography (PT) algorithm with the averaged beta.y
引用
收藏
页数:9
相关论文
共 38 条
[1]   A nonlinear ultrasonic SHM method for impact damage localisation in composite panels using a sparse array of piezoelectric PZT transducers [J].
Andreades, Christos ;
Fierro, Gian Piero Malfense ;
Meo, Michele .
ULTRASONICS, 2020, 108
[2]   A wave-based numerical scheme for damage detection and identification in two-dimensional composite structures [J].
Apalowo, R. K. ;
Chronopoulos, D. .
COMPOSITE STRUCTURES, 2019, 214 :164-182
[3]   Prediction of Progressive Damage State at the Hot Spots using Statistical Estimation [J].
Banerjee, Sourav ;
Qing, Xinlin P. ;
Beard, Shawn ;
Chang, Fu-Kuo .
JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES, 2010, 21 (06) :595-605
[4]   Environmental and operational conditions effects on Lamb wave based structural health monitoring systems: A review [J].
Gorgin, Rahim ;
Luo, Ying ;
Wu, Zhanjun .
ULTRASONICS, 2020, 105
[5]   High-resolution damage detection based on local signal difference coefficient model [J].
Hua, Jiadong ;
Lin, Jing ;
Zeng, Liang .
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2015, 14 (01) :20-34
[6]   Detection and monitoring of hidden fatigue crack growth using a built-in piezoelectric sensor/actuator network: II. Validation using riveted joints and repair patches [J].
Ihn, JB ;
Chang, FK .
SMART MATERIALS & STRUCTURES, 2004, 13 (03) :621-630
[7]   Pitch-catch active sensing methods in structural health monitoring for aircraft structures [J].
Ihn, Jeong-Beom ;
Chang, Fu-Kuo .
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2008, 7 (01) :5-19
[8]   Monitoring of Fatigue Crack Propagation by Damage Index of Ultrasonic Guided Waves Calculated by Various Acoustic Features [J].
Jin, Hashen ;
Yan, Jiajia ;
Li, Weibin ;
Qing, Xinlin .
APPLIED SCIENCES-BASEL, 2019, 9 (20)
[9]   Structural health monitoring and damage prognosis in fatigue [J].
Kulkarni, S. S. ;
Achenbach, J. D. .
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2008, 7 (01) :37-49
[10]   Multi-defect tomographic imaging with a variable shape factor for the RAPID algorithm [J].
Lee, Jaesun ;
Sheen, Bongjae ;
Cho, Younho .
JOURNAL OF VISUALIZATION, 2016, 19 (03) :393-402