Fractal Dimension-Based Damage Imaging for Composites

Abstract

In this paper, a damage imaging algorithm based on fractal dimension is developed for quantitative damage detection of composite structures. Box-counting dimension, a typical fractal dimension, is employed to analyze the difference of Lamb wave signals, extract damage feature and define damage index. An enhanced reconstruction algorithm for probabilistic inspection of damage is developed for damage imaging. Experimental investigation in a composite laminate and a stiffened composite panel shows that the developed algorithm could quantitatively predict the location and size of not only single but also multiple damages. The influence of parameters in the developed algorithm on the imaging quality and accuracy is studied, and reference values for parameters are presented.

Baseline-free damage imaging for metal and composite plate-type structures based on similar paths

“…ERAPID is used to image the damage based on the damage index in Figure 7. When b = 1:02 and a = 5, which are suggested in the Zhou et al, 26 Figure 8 shows that the identified damage has a perfect location and size with the real damage, which verifies that the proposed method is effective. paths in detail 1 24 S1-S2, S2-S3, S3-S4, S4-S5, S5-S6, S6-S7, S7-S8, S8-S9, S9-S10, S10-S11, S11-S12, S12-S1, vice versa 2 24 S1-S3, S2-S4, S3-S5, S4-S6, S5-S7, S6-S8, S7-S9, S8-S10, S9-S11, S10-S12, S11-S1, S12-S2, vice versa 3 24 S1-S4, S2-S5, S3-S6, S4-S7, S5-S8, S6-S9, S7-S10, S8-S11, S9-S12, S10-S1, S11-S2, S12-S3, vice versa 4 24 S1-S5, S2-S6, S3-S7, S4-S8, S5-S9, S6-S10, S7-S11, S8-S12, S9-S1, S10-S2, S11-S3, S12-S4, vice versa 5 24 S1-S6, S2-S7, S3-S8, S4-S9, S5-S10, S6-S11, S7-S12, S8-S1, S9-S2, S10-S3, S11-S4, S12-S5, vice versa 6 12 S1-S7, S2-S8, S3-S9, S4-S10, S5-S11, S6-S12, vice versa…”

Identification and Compensation Technique of Non-Uniform Temperature Field for Lamb Wave-and Multiple Sensors-Based Damage Detection

“…Pfalse(x,yfalse) is the probability of damage at position false(x,yfalse). β is a scaling parameter, which decides the influencing area of each sensing path [7]. Therefore, the determination of its value is related to the placement of the sensors.…”

“…Therefore, the determination of its value is related to the placement of the sensors. In order to get a more accurate damage location in the case of the sensor setting in this paper, β is set at 1.45 [7]. Rk is defined as Rk={truetrueRDk,RDk<ββ,RDk>β where RDk=false(x−xakfalse)2+false(y−yakfalse)2+false(x−xakfalse)2+false(y−yakfalse)2false(xak−xskfalse)2+false(yak−yskfalse)2 false(xak,yakfalse) and …”

“…Lamb wave-based structural health monitoring (SHM) technique has been proved to be one of the strongest techniques for online and real-time damage detection of aircraft structures because of the superior capability of travelling long distances and covering large monitoring area with limited numbers of piezoelectric sensors [1]. Plenty of Lamb wave-based damage detection algorithms, including delay and sum [2,3], phased array [4,5], tomography [6,7,8,9,10,11], and migration [12,13], have been developed. Comprehensive reviews on the application of Lamb wave for structural health monitoring can be found in the literature [1,14,15].…”

“…Comprehensive reviews on the application of Lamb wave for structural health monitoring can be found in the literature [1,14,15]. Depending on whether reference data of Lamb wave in the pristine structure is needed or not, these algorithms can be divided into two categories, i.e., reference-free algorithms [16,17,18,19] and reference-dependent ones [2,3,4,5,6,7,8,9,10,11,12,13]. Reference-dependent algorithms are more practical than reference-free ones for real application in aircraft structures due to the complex nature of the Lamb wave, including multiple mode, modes conversion and scattering at the boundary.…”