Piezoelectric-laser ultrasonic inspection and monitoring of thin-walled structure fabricated by directed energy deposition process based on guided waves.

• A new non-destructive testing technique is proposed for Directed Energy Deposition. • A wave model describes wave propagation in both the substrate and the thin wall. • A laser vibrometer scans the thin wall fabricated by additive manufacturing. • A 0 mode Lamb wave in the thin wall is enhanced by frequency tuning. • A small defect caused by inconsistent powder delivery is detected and localized. Thin-walled metallic structures produced by the Directed Energy Deposition (DED) Additive Manufacturing (AM) process are prone to various fabrication defects, which hinder the wider applications of the technique in practice. In-situ inspection and monitoring methodologies are in high demand for improved quality control of printed parts. This paper presents an ultrasonic guided-wave-based method and a prototype that can potentially be used for in-situ inspection of thin-walled structures produced by DED. Lamb waves are excited by a Lead zirconate titanate (PZT) piezoelectric transducer bonded on the DED substrate remotely from the thin wall. The substrate works as a waveguide to transmit the waves which then propagate along the thin wall. A non-contact laser vibrometer is applied to measure the guide wave signals by scanning the surface of the thin wall. The mechanisms of guided wave generation and propagation along the substrate and printed part are theoretically studied. It allows for choosing proper inspection parameters to enhance the measurement sensitivity of guided waves and help interpret the signals for defect detection. Experiments were conducted with DED-produced stainless steel (316L) thin-walled structure. The new method is demonstrated in one example to detect and localize a small defect caused by inconsistent powder delivery of a fabricated thin wall sample, via analysing the B-scan ultrasonic guided wave signals. The new technique provides strong potential for in-situ online monitoring of the DED process. [ABSTRACT FROM AUTHOR]