The main objective is to add robustness to automated monitoring systems based on embedded transducers in order to transition from laboratory applications to field monitoring, to overcome potential sensor failure as well as the high sensitivity of the measured indicators to environmental and operational variations, which are responsible for false alarms (not due to damage). The WP will develop tools to filter out environmental and operational effects:
i. with statistical methods,
ii. with artificial intelligence,
iii. For robustness to potential sensor failure.

The Work Package Leader is Dr. Arnaud Deraemaeker ULB.

3 PhD positions already filled

• DC08 - Filtering of environmental effects for ultrasonic based monitoring using embedded piezoelectric transducers
• DC09 - Study on environmental and operational conditions for SHM systems
• DC10 - Sensor data fusion and analysis for reliable premature detection of degradation in full-scale assets