Sensor-Efficient Condition monitoring using Undersampled Reconstruction for Engine safety - Aero-Engine Rotating blade On-board monitoring

Blade tip timing (BTT) is a promising non-contact vibration measurement technique for rotating blades. But, it has the undersampling issue and heavy reliance on excessive probes (typically 5~7); such a high-intervention measurement brings high installation cost and potential foreign object debris hazards, hindering its application in operational aero-engines. This proposal addresses the key challenge in aero-engine health monitoring by a reliable and cost-effective condition monitoring of rotating blades using extremely few probes and undersampled measurements. The main objective is to overcome the undersampling barrier and establish a low-intervention BTT-based rotating blade condition monitoring system that relies on only one or two probes and minimizes the installation cost and potential foreign object debris risk. To achieve this goal, the project will develop new mathematical models and recovery criteria for undersampled BTT signals, and design deterministic compressive sensing frameworks with efficient reconstruction algorithms. These methods will be validated through numerical and experimental investigations. A co-design strategy, integrating hardware and algorithms, will ensure that the resulting system is scientifically sound, practical, and cost-effective.The research will be conducted under the supervision of leading experts in signal processing and structural health monitoring, supported by access to modern laboratories and interdisciplinary training. Dissemination will include journal papers, conferences, workshops, and outreach events. Engagement with industry will promote technology transfer and potential exploitation.Aligned with the MSCA Work Programme, the project advances excellence in scientific research, researcher mobility, and career development. By enabling condition-based maintenance in aero-engines, the project can significantly improve safety, reduce maintenance and computation costs, and contribute to more sustainable aviation.