Validation and evaluation of damage identification using probability-based diagnostic imaging on a stiffened composite panel

Abstract

Probability-based diagnostic imaging, as one of the damage identification methods using ultrasonic guided waves, has been attracting increasing attention by researchers in the community of structural health monitoring. However, the probability-based diagnostic imaging algorithm’s influencing parameters, including the selection of certain damage index and frequency, the network of sensing paths, and the size of the effective elliptical distribution area, are empirically determined. This experience dependency limits the application of the method to identify damages in real-world practices. Therefore, it is important to clarify the influences of the above-mentioned various factors on the damage identification. However, the complexity of these factors makes it almost impossible to interpret the influencing mechanisms directly. Thus, a fusion image approach of multiple frequencies is employed to eliminate the influence of different frequencies, while a histogram-based method is proposed to evaluate the reliability of the fusion result. Meanwhile, a unit weight distribution function, considering both the network of sensing paths and the size of the effective elliptical distribution area, is presented in the analysis. Then, the influencing mechanisms are studied and discussed in detail, and a methodology is proposed to optimize the network and the scaling parameter which controls the affected zone.

Identification of Barely Visible Impact Damages on a Stiffened Composite Panel with a Probability-based Approach

“…The usual transducer network configuration employed to identify damage with the RAPID algorithm consists of the transducer network located around the damage (see [2][3][4]). This study aims at damage identification in any part of the structure with a transducer network regularly distributed on the structure.…”

“…Zhao et al [2] detected and localized rivet cracks and corrosion on an aircraft aluminum wing, Wu et al [3] used the RAPID with a composite panel with bonded T-stringers, combining several frequencies for an improved damage assessment, and Wang et al [4] identified a through-thickness hole in a composite stiffened panel.…”

Influence of the PZT Sensor Array Configuration on Lamb Wave Tomography Imaging with the RAPID Algorithm for Hole and Crack Detection

“…Zhao [6] compared the theoretical resolutions in a reconstruction image with that of circular, square, and parallel linear PZT sensor arrays. Wu [16] placed PZT sensors in a square pattern on a stiffened composite panel, and compared the performance with related sensing paths enclosed in a circle and square area. Dziendzikowski [17] defined a signature function for an inhomogeneous noncircular PZT sensor array to normalize the intensity map in a reconstruction image.…”

An Aircraft Pallet Damage Monitoring Method Based on Damage Subarea Identification and Probability-Based Diagnostic Imaging

“…e anisotropy of the aircra pallet will be highlighted by the complex structure and structural characteristic changes, which makes it di cult to accurately obtain the Lamb wave velocity. e probability-based diagnostic imaging method is a fast and simple damage imaging method that does not use the Lamb wave velocity [3,52]. e damage index of each path in the pitch-catch sensor network is used in this method.…”