Automation Defect Detection Using Ultrasound in Honeycomb Sandwich Panels

This work introduces a sophisticated ultrasonic testing (UT) methodology tailored for the efficient detection of interface defects in honeycomb sandwich panels, which are prevalent in aerospace, automotive, marine, and civil engineering applications. These panels are prized for their exceptional strength-to-weight ratio and insulation properties but are susceptible to various interface defects between the composite facesheet and the honeycomb core. Such defects often arise during manufacturing processes or through operational environments, potentially undermining the structural integrity and functionality of the panels. To address this challenge, our research employs an advanced non-destructive testing (NDT) approach, utilizing high-frequency, full-waveform ultrasonic waves in an immersion setup. This technique is specifically designed to probe the interface zone, effectively identifying and characterizing critical internal defects such as missing adhesive layers and embedded foreign materials, including Teflon and Kapton films. The application of full waveform capture not only facilitates deeper penetration into the material but also enhances the resolution and accuracy of the defect imaging process. A key component of our methodology is the integration of a MATLAB-based signal processing framework, which processes the ultrasonic data to isolate and quantify the defects. This digital signal processing is crucial for distinguishing between normal variations in material properties and actual flaw signatures. Additionally, the entire defect detection process is automated, enhancing efficiency and repeatability, and reducing human error. Our results have demonstrated a high level of accuracy in detecting missing adhesives, aligning closely with confirmatory microscopic measurements. However, the detection of defects involving Kapton and PTFE films has shown greater variability. Overall, this study not only advances the field of ultrasonic testing for honeycomb sandwich panels but also offers significant insights into the complexities of defect detection at material interfaces. The findings contribute to the broader discourse on enhancing the reliability and safety of critical structural components used across various industries.