Simon Tait

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About

Simon Tait is a researcher advancing the field of non-destructive evaluation, with a core focus on acoustic sensing and signal processing for infrastructure monitoring. His primary research areas include microphone array analysis, defect localization in pipelines, and the application of sparse representation techniques for robotic inspection. Tait’s major contributions lie in developing innovative methods to detect and localize pipe defects with unprecedented resolution and efficiency. His 2024 paper, "Microphone array analysis of the first non-axisymmetric mode for the detection of pipe conditions," introduces a Bayesian maximum a posteriori algorithm combined with mode decomposition, enabling precise defect localization using as few as six microphones—a significant leap over traditional approaches. This work has garnered 7 citations, reflecting its early impact. In 2025, Tait further advanced the field with "Sparse representation for artefact/defect localization with an acoustic array on a mobile pipe inspection robot," which has already earned 4 citations. This research integrates acoustic arrays onto mobile robots, enhancing the practicality of automated pipeline inspection. Tait’s work is notable for its potential to reduce inspection costs and improve safety in critical infrastructure, marking him as a promising voice in acoustic-based structural health monitoring.