Mobile laser Doppler vibrometry motion tracking and vibration compensation for in-field vehicular deployments

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The laser Doppler vibrometer (LDV) has been a pivotal tool in vibration engineering, providing superior bandwidths and spatial resolutions compared to traditional contacting accelerometers. This thesis delves into LDV's deployment from mobile platforms like terrestrial or airborne vehicles, a strategy that promises to increase land coverage rates and enable access to hazardous or remote areas. Initially, this thesis addresses the challenge of LDV's sensitivity to self-vibration, which generally prevents mobile deployments. New time domain and revised frequency domain-based processing techniques were developed, resulting in an eight-fold improvement in performance. This innovation is crucial for handling transient vibration signals and is validated experimentally. Secondly, this thesis describes a novel tracking system specifically for drone-mounted LDVs, focusing on adjustments in pitch and roll. This system employs a standard galvanometer steering mirror setup, effectively reducing beam motion by 68% during extreme flight conditions. Lastly, the thesis explores the integration of LDVs into autonomous systems, notably the development of non-contact vibro-acoustic object recognition using convolutional neural networks, achieving up to 99.8% accuracy, opening the door for autonomous systems to "see" the acoustic environment. The combination of the work in this thesis represents a significant advancement in LDV applications and in-field mobile utilisation.
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