Application of linear frequency modulated laser ultrasonic radar in reflective thickness and defect non-destructive testing. (March 2019)

• Record Type: Journal Article
• Authors: Huan, Huiting; Mandelis, Andreas; Liu, Lixian; Lashkari, Bahman; Melnikov, Alexander
• Is Part Of: NDT & E international. Volume 102(2019)
• Page Start: 84
• Page End: 89
• Publication Date: 2019-03
• Subjects: Linear frequency modulation -- Chirp -- Quantitative non-destructive testing -- Laser ultrasound radar -- Defect detection; Nondestructive testing -- Periodicals; Contrôle non destructif -- Périodiques; Electronic journals; 620.1127
• DOI: 10.1016/j.ndteint.2018.11.006
• Languages: English
• ISSNs: 0963-8695

Abstract

Abstract: Radar technology plays an important role in modern aviation and navigation. Radar systems use pulse-compression and match-filtering to detect large moving objects in the sky or in water, or small defects hidden inside industrial components, the object of this paper. We introduce a nondestructive testing (NDT) modality based on frequency-domain laser ultrasound (FDLU) by means of implementing radar principles: Linear-frequency-modulated (LFM chirp) excitation CW laser-beam intensity to perform, ultrasonic signal cross-correlation with the reference signal using pulse-compression and match-filtering, leading to reconstruction of time-domain sequences through inverse Fourier transformation at acceptable signal-to-noise ratios. Theoretically, the laser ultrasound radar (LUR) signal was modelled with both one- and three-dimensional thermoelastic equations, a combination of which was used to simultaneously predict the correct location and relative amplitude of experimental targets with relatively simple mathematical expressions that could not be used either in the 1-D (too simplistic) or in the 3-D (too complicated) approach alone. This methodology was further used to detect buried defects inside a metal alloy. The results demonstrated that the LUR system is capable of determining the thickness of the alloy material and quantitatively estimate the subsurface depth of defects in a signal generation process akin to echolocation.