Author: Kaushikkumar Ranchhodbhai Prajapati
Prajapati, Kaushikkumar Ranchhodbhai, 2024 Damage detection by using Scanning laser Doppler Vibrometry, Flinders University, College of Science and Engineering
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This thesis investigates the application of Scanning Laser Doppler Vibrometry (SLDV) for detecting damage in an aluminium beam with a predefined notch. Structural health monitoring (SHM) is essential for maintaining the safety and integrity of mechanical systems, and non contact methods like SLDV offer significant advantages over traditional contact based techniques. This research aims to validate the effectiveness of SLDV in identifying structural anomalies by comparing experimental results with Finite Element Analysis (FEA) simulations.
The study involves setting up an experimental rig where an aluminium beam is vibrated using an LDS shaker system, and its out-of-plane displacement is measured using a Polytec PSV-400 SLDV system. The displacement data is processed with the Savitzky-Golay differential filter to obtain velocity curvature profiles. Parallelly, an FEA model simulates the same conditions to generate strain and deformation data, providing a basis for comparison.
Results show that SLDV effectively detects damage at lower frequencies (up to 100 Hz), where noise interference is minimal, producing sharp peaks in the velocity curvature profiles around the notch. Higher frequencies (above 100 Hz) increase Noise, making damage detection unreliable. The FEA simulations closely match the experimental data, affirming the model's accuracy and the SLDV method. However, discrepancies in noise levels between experimental and FEA results highlight the need for further refinement.
This thesis contributes to the field of SHM by demonstrating that SLDV, combined with FEA, is a reliable method for non-destructive damage detection in structural components. It emphasizes the importance of frequency selection and advanced noise reduction techniques to enhance measurement accuracy. Future research should improve noise mitigation strategies and validate SLDV against diverse structural conditions to solidify its application in real-world engineering practices.
Keywords: Scanning Laser Doppler Vibrometry (SLDV), Structural Health Monitoring (SHM), Velocity Curvature, Displacement Curvature, Savitzky-Golay Filter, Noncontact Techniques, Curvature Mode Shape, Out-of-Plane Displacement, In-Plane Displacement, Harmonic Response Analysis, Beam Vibration Response, Mesh Convergence Study, Environmental Noise, Operational Noise, Structural Deterioration, Real-Time Monitoring Systems, Machine Learning Algorithms, Vibration-Based Damage Detection (VBDD), Displacement Data Processing, Polytec PSV-400 SLDV System, Analytical Modal Curvatures.
Subject: Engineering thesis
Thesis type: Masters
Completed: 2024
School: College of Science and Engineering
Supervisor: Dr Stuart Wildy