Elliptical ring distribution probability-based damage imaging method for complex aircraft structures

Abstract

In engineering applications, the robustness and effectiveness of damage diagnostic imaging for guided wave-based structural health monitoring could be affected by the complexity of structures. In this study, an elliptical ring distribution probability-based diagnostic imaging algorithm is proposed to mitigate this effect using the estimated wave velocity and damage index. This algorithm improves the ability of damage localization by modifying the defect distribution probability of probability-based diagnostic imaging. The elliptical ring distribution probability of the presence of defect is used for each sensing path in the algorithm. The width of the elliptical ring distribution probability is determined by the range of estimated wave velocity. The amplitude of the elliptical ring distribution probability is determined by the damage index. The damage location is determined by the cross region of different elliptical rings for different sensing paths. The capability of the algorithm is validated by identifying damages at different locations on a complex composite fuselage panel. The results show that the proposed algorithm can identify a single damage accurately and it can identify multiple damages effectively as well.

A Microcrack Location Method Based on Nonlinear S0 Mode Lamb Wave and Probability Scan Positioning Imaging Matrix

“…Thereby, maintenance personnel can repair or carry out a further evaluation of the remaining life in time. At present, damage imaging algorithms mainly include the elliptical positioning method, the time inversion method, and the delay superposition algorithm [13,[29][30][31][32]. These algorithms are needed to determine accurate wave velocity and modal information.…”

Transverse Damage Localization and Quantitative Size Estimation for Composite Laminates Based on Lamb Waves

“…Bayes' theorem updated the probability distributions of the parameters by combining the prior information and measured ToF data for damage localization in composite laminates [4]. In order to improve the imaging capability for damage localization in complex structures, the defect distribution probability of PDI algorithm was modified to develop an elliptical ring distribution probability-based diagnostic imaging algorithm [24]. Two ToF based damage localization methods were proposed for composite laminates [25]: the first algorithm used the probabilistic approach by constructing a probability matrix for locating the defects with large errors, and the second algorithm based on the artificial neural networks was then used to improve the accuracy of defect localization.…”

“…In the aforementioned methods, the researchers mostly simulated the defects using circular [3], [9], [10], [13], [14], [18]- [20], [22]- [24], square [12], [25] and rectangular [15], [17] shapes, which may not be the best representation of the actual damage in composite laminates. Studies performed at the microscopic level reveal that the more realistic representation of damage is the thin and elongated ellipse-like shape [31], which has been used to simulate the damage in composite laminates [27]- [30].…”

“…In addition to that, the methods discussed here have used a large number of PZT transducers just to locate the damage of simplistic shapes. For example, the methods for locating the circular damage have used 16 transducers with 56 pitch-catch signal acquisition paths [14], 30 distributed transducers [15], 16 transducers with 28 sensing paths [24] and 12 transducers with 84 sensing paths [11]. The use of too many PZT transducers requires a big amount of data to be processed during the SHM process.…”

“…Therefore, there is a need to develop fast and in situ SHM methods for on-line monitoring of composite structures with minimum data recording. Furthermore, most of the existing elliptical reconstruction methods are image-based which focus only on damage localization [3], [9], [10], [12]- [14], [18]- [22], [24], [25], [31], and do not provide the quantitative estimation of damage size/extent.…”