Proposal for RCNDE feasibility study Practical feasibility of distributed guided wave SHM systems Investigators Paul Wilcox, Bruce Drinkwater, Anthony Croxford (University of Bristol) Peter Cawley, Frederic Cegla (Imperial College)

Motivation Large structure / component Localised defects, e.g. Corrosion Impacts Permanently installed monitoring Guided waves Sparse sensor network (~1 per m 2 ) Benefits of SHM Continuous monitoring – early warning of problems Increase time between outages Reduce inspection outage time – NDE can be targeted

Example results from previous EPSRC project Multiple sensors on container panel Tested at intervals over period of weeks Defect (hole) introduced Combine data from multiple sensor pairs for defect localisation Defect

ClampOn DSP Corrosion-Erosion Monitor Measures time-of-flight of direct signal between EMAT sensors TOF related to mean wall-thickness near line of sight between sensors Rudimentary mapping capability using network of 8 sensors Designed for uniform pipe Key differences to our method TOF-based rather than scattering-based detection Sparse array does not provide 100% coverage Limited to uniform structures Existing guided wave systems

Acellent SMART Layer and ScanGenie instrument Piezoelectric sensors in flexible PCB that provides wiring Sensor spacing ~5 – 10 cm Designed for surface mounting or embedding Proprietary software – signal processing thought to be based on reference signal comparison Key differences to our method Very high sensor density Data analysis not physics-based

Proposed project – background Previous EPSRC project Airbus, Thales, BAe, Hexcel, Mecon Scientific basis of technique developed Real structures tested indoors Showed that basic concept is plausible But … Environmental changes limited Duration of tests limited to a few weeks Data not captured continuously Goal of proposed project Produce system to demonstrate continuous monitoring of realistic structures outdoors over an extended period

Proposed project – workplan Gather data from two structures in uncontrolled outdoor environment for extended period (~1 year) Develop automated data collection and ruggedise sensors Gather data hourly for one year and make raw data available on web Test and refine processing strategies to deal with other effects, e.g. Sensor degradation / failure; high temperature gradients; water loading

All aligned with challenges in RCNDE strategic core research theme on Permanently installed and autonomous NDE systems Proposed project – context in RCNDE Challenges in guided wave SHM Sensor degradation, instrumentation drift Small defect signals; large other signals Defect or environmental effect? Self-calibration Exploiting time-dependent trends in ‘continuous’ data Infrequent ‘Continuous’ Measurement Time

Proposed project – resources requested Duration 18 months Staff costs - £107k including overheads, estates etc. Bristol 33% of 1 Research Assistant for 18 months Instrumentation development, test on steel tank structure, data analysis Imperial 33% of 1 Research Assistant for 18 months Transducer development, test on aerospace structure, data analysis Other costs - £18k Dedicated signal generation/detection equipment Multiplexing devices Transducer and cabling costs Contingency for failure of transducers, instrumentation channels etc. Total cost - £125k Call on RCNDE core funds - £100k (based on 80% FEC)

Proposed project – concept Simple point-like sensors inject guided waves into structure Scattered signals from defects detected by other sensors

Proposed project – concept Simple point-like sensors inject guided waves into structure Scattered signals from defects detected by other sensors Scattering from structural features prevents direct interpretation of signals – reference signal essential

Concept of guided wave SHM Use reference signal subtraction to suppress structural signals … … and multiple sensors for localisation 2 sensors 4 sensors

Previous work Recently completed EPSRC funded project: Efficient Structural Health Monitoring Using Sparse Distributed Sensor Arrays Imperial, Bristol, Airbus, BAE Systems, Thales, Hexcel Key findings of that project Quantitative description of noise due to changing environmental conditions (especially temperature) Relationship between noise and required number of sensors 15 dB reduction in noise ≡ 10 x less sensors per unit area Strategy for overcoming environmental effects developed > 30 dB reduction in noise in controlled lab experiments ≡ 100 x less sensors Sensor density of ~1 per m 2 now feasible for typical defects (e.g. corrosion patches)