Single-Input and Multiple-Output Surface Acoustic Wave Sensing for Damage Quantification in Piezoelectric Sensors

Area of Science:

• Materials Science
• Sensor Technology
• Acoustics

Background:

• Anisotropic piezoelectric sensors are crucial for various applications.
• Detecting microscale damage in these sensors is challenging but vital for performance.
• Surface acoustic waves (SAWs) offer a promising non-destructive method for internal inspection.

Purpose of the Study:

• To develop and validate a novel technique for microscale damage detection in anisotropic piezoelectric sensors.
• To utilize Rayleigh wave propagation characteristics for flaw identification.
• To quantify the evolution of damage using advanced signal processing algorithms.

Main Methods:

• Fabrication of convex and angularly shaped interdigital transducers (IDTs) for SAW excitation and sensing.
• Generation of divergent SAWs and measurement of their shape evolution.
• Introduction of calibrated microscale damage using a micro-indenter.
• Application of empirical mode decomposition (EMD) and principal component analysis (PCA) for damage quantification.

Main Results:

• The developed technique successfully detected and quantified microscale cracks in piezoelectric sensors.
• The evolution of damage was accurately tracked by analyzing SAW shape changes.
• A novel condition indicator (CI) based on principal angle changes provided a robust damage metric.

Conclusions:

• The proposed SAW-based method offers a reliable approach for microscale damage assessment in piezoelectric sensors.
• The combination of EMD, PCA, and the developed CI enables accurate quantification of damage.
• This technique enhances sensor reliability and predictive maintenance capabilities.