204. NON-DESTRUCTIVE EVALUATION METHODS FOR DETECTING MAJOR DAMAGE IN INTERNAL COMPOSITE STRUCTURAL COMPONENTS
Name: Hyung Suk Kim
Grad Year: 2018
Margherita Capriotti, email@example.com
Internal damage of modern aircraft components, such as fuselage frames, is not always visually-detectable from the exterior. Such damage can potentially be caused by a high energy wide area blunt impact event from ground service equipment. The objectives of the current project are focused on: (i) establishing non-destructive evaluation (NDE) methods based on ultrasonic guided wave propagation for detecting major sub-surface damage to internal composite fuselage members (such as cracks in frames and shear ties), and (ii) relating NDE-measurements to damage location and severity. First, guided wave propagation phenomenon in an aluminum plate has been characterized, and its phase velocity and group velocity dispersion curves have been extracted from signal processing of data collected from different transduction mechanisms at various ranges of frequency. Narrowband piezoelectric transducers have been employed as suitable sensors for wave propagation and damage detection in composite panels, followed by characterization of their frequency response. Piezoelectric transducer excitation, from aluminum block through transmission, has been used to characterize transfer functions of the piezoelectric transducer detection. This method was then extended to examine wave propagation modes through a composite panel system. Customized data control and acquisition equipment was acquired, assembled and programmed to enable narrowband frequency sweep tests to extract corresponding frequency transmissibility curves. A "sensing head" prototype, which is a sensor holding mold, has been designed to use excitation in the center with a pair of receivers located at symmetric positions with respect to the excitation. This enables "unbalanced" signals reception between sensors for damage detection. The comparison between "unbalanced" signals is being used within a statistical Outlier Analysis framework. By normalizing the measurements from the statistically gathered baseline data of the structure, this will minimize "false positive" damage indications while maximizing true damage detection sensitivity.
Industry Application Area(s)
Aerospace, Defense, Security | Civil/Structural Engineering