Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.631437
Title: Comparative study of nonlinear acoustic and guided wave methods for structural damage detection
Author: Yang, Kai
ISNI:       0000 0004 5356 3915
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2014
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Abstract:
The overall purpose of this research work is to use nonlinear acoustic techniques and Lamb wave methods for Structural Health Monitoring (SHM). The work constitutes fatigue crack detection studies on glass and aluminium plates as well as low-velocity impact damage and compression damages on carbon fibre reinforced polymer. In addition, the SHM techniques were evaluated by detecting damage on a hammer impacted wind turbine blade. For nonlinear acoustic tests, Finite Element (FE) modeling was used to calculate the crack edge divergence for three different crack modes. After that, FE modeling extracted the modal parameters (e.g. natural frequencies and mode shapes) of vibration modes for the corresponding crack modes. These selected vibration modes were used for low frequency excitation in nonlinear acoustic experiments. Experimental work was performed to analyse the effect of nonlinear acoustics by signal wave excitation, Frequency Response Functions (FRFs) with varying excitation levels and Vibro-acoustic excitation. Various physical mechanisms to account for these effects have been investigated. The experimental results present three main nonlinear effects. These effects are non-classical Luxemburg-Gorky (L-G) type dissipation, the dissipation mechanism related to crack-wave interaction and nonlinear elasticity. The application of outlier analysis on Lamb wave tests is a novelty detection method. This method has indicated successful classification for undamaged and damaged data in fatigue tests, compression tests and impact tests. In addition, outlier analysis is able to give an indication of damage severity in the glass plate test. Moreover, outlier analysis gives the information to localise damage in the wind turbine blade test.
Supervisor: Worden, Keith ; Rongong, Jem Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.631437  DOI: Not available
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