Thermographic inspection of water ingress in composite honeycomb sandwich structure: a quantitative comparison among Lock-in thermography algorithms. Issue 2 (15th March 2021)

• Record Type: Journal Article
• Authors: Shrestha, Ranjit; Choi, Manyong; Kim, Wontae
• Is Part Of: Quantitative infrared thermography. Volume 18:Issue 2(2021)
• Page Start: 92
• Page End: 107
• Publication Date: 2021-03-15
• Subjects: Honeycomb structures -- water ingress -- Lock-in thermography -- Fast Fourier transform -- Harmonic approximation -- Principle component analysis -- signal to noise ratio; Infrared technology -- Periodicals; Thermography -- Periodicals; Infrared technology; Thermography; Periodicals; 621.362
• DOI: 10.1080/17686733.2019.1697848
• Languages: English
• ISSNs: 1768-6733

Abstract

ABSTRACT: The increasing use of honeycomb structures in the aircraft industry has demonstrated the need for the development of more effective evaluation methodologies. In recent years, thermography has received vast and growing attention as a reliable technique for non-destructive testing and evaluation of composite materials due to its remarkable advantages of non-contact, full area coverage, high speed, safe and convenient operation, qualitative and quantitative inspection capabilities. In this paper, Lock-in thermography is employed to inspect water ingress in aircraft honeycomb structures, and an investigation into the effect of water content on the quantitative estimation has been carried out. A square-shaped composite honeycomb panel of dimension 300 × 300 mm with four equal size defective areas of 50 × 50 mm as the groups of cells filled with water by 25%, 50%, 75% and 100% of the cell volume was considered as a test sample. The sample was excited at multiple modulation frequencies, viz., 0.5 Hz, 0.2 Hz, 0.1 Hz, 0.05 Hz, 0.02 Hz, and 0.01 Hz. Three Lock-in thermography algorithms, namely, Fast Fourier transform, Harmonic approximation, and Principle component analysis, are discussed for quantitative assessment; and their performance is compared in terms of Signal to noise ratio.