Ultrasonic and Piezoelectric Sensing for Structural Health Monitoring and Damage Detection
This community develops and applies non-destructive testing techniques to monitor the condition of engineered structures, specifically identifying damage, defects, and material degradation in composites, concrete, and metal assemblies.
The work centers on the propagation and analysis of mechanical waves, with a heavy emphasis on Lamb waves and ultrasonic guided waves for inspecting plates and shells. Piezoelectric transducers, particularly PZT sensors, are the dominant hardware for generating and receiving these signals, often utilized through electromechanical impedance methods to track local changes in material properties. The target structures include carbon fiber reinforced polymers, reinforced concrete, and other composite materials. Recent methodological developments integrate deep learning and machine learning algorithms to process acoustic emission data and improve the accuracy of damage localization and identification.
The community is most heavily represented in research tracked for titanium, zirconium, and lead, accounting for 0.5%, 0.9%, and 0.6% of all research in those respective elements. Titanium also contributes the highest absolute number of papers to this group, with 1,499 entries.
The community comprises 4,180 papers, published primarily in Smart Materials and Structures, Ultrasonics, and Mechanical Systems and Signal Processing.
Recent work continues to focus on applying these sensing technologies to aerospace composites, bridge infrastructure, and pipeline corrosion monitoring, with specific studies exploring laser ultrasonic techniques for metal-composite defects and machine learning frameworks for identifying damage in carbon fiber reinforced polymers.