Comparative evaluation of in situ stress monitoring with Rayleigh waves. (January 2019)

• Record Type: Journal Article
• Authors: Hughes, James Martin; Vidler, James; Ng, Ching-Tai; Khanna, Aditya; Mohabuth, Munawwar; Rose, LR Francis; Kotousov, Andrei
• Other Names: Nguyen Andy guest-editor.; Chan Tommy HT guest-editor.; Zhu Xinqun guest-editor.
• Is Part Of: Structural health monitoring. Volume 18:Number 1(2019)
• Page Start: 205
• Page End: 215
• Publication Date: 2019-01
• Subjects: Stress monitoring -- Rayleigh wave -- second harmonic generation -- acoustoelastic effect -- guided waves; Structural health monitoring -- Periodicals; Structural stability -- Periodicals; Strength of materials -- Periodicals; Nondestructive testing -- Periodicals; Constructions -- Stabilité -- Périodiques; Résistance des matériaux -- Périodiques; Contrôle non destructif -- Périodiques; Electronic journals; 624.17
• DOI: 10.1177/1475921718798146
• Languages: English
• ISSNs: 1475-9217

Abstract

The in situ monitoring of stresses provides a crucial input for residual life prognosis and is an integral part of structural health monitoring systems. Stress monitoring is generally achieved by utilising the acoustoelastic effect, which relates the speed of elastic waves in a solid, typically longitudinal and shear waves, to the stress state. A major shortcoming of methods based on the acoustoelastic effect is their poor sensitivity. Another shortcoming of acoustoelastic methods is associated with the rapid attenuation of bulk waves in the propagation medium, requiring the use of dense sensor networks. The purpose of this article is twofold: to demonstrate the application of Rayleigh (guided) waves rather than bulk waves towards stress monitoring based on acoustoelasticity, and to propose a new method for stress monitoring based on the rate of accumulation of the second harmonic of large-amplitude Rayleigh waves. An experimental study is conducted using the cross-correlation signal processing technique to increase the accuracy of determining Rayleigh wave speeds when compared with traditional methods. This demonstrates the feasibility of Rayleigh wave–based acoustoelastic structural health monitoring systems, which could easily be integrated with existing sensor networks. Second harmonic generation is then investigated to demonstrate the sensitivity of higher order harmonics to stress-induced nonlinearities. The outcomes of this study demonstrate that the sensitivity of the new second harmonic generation method is several orders of magnitude greater than the acoustoelastic method, making the proposed method more suitable for development for online stress monitoring of in-service structures.