Damage detection in 3D printed plates using ultrasonic wave propagation supported with weighted root mean square calculation and wavefield curvature imaging

Abstract

3D printing (additive manufacturing, AM) is a promising approach to producing light and strong structures with many successful applications, e.g., in dentistry and orthopaedics. Many types of filaments differing in mechanical properties can be used to produce 3D printed structures, including polymers, metals or ceramics. Due to the simplicity of the manufacturing process, biodegradable polymers are widely used, e.g., polylactide (polylactide – PLA) with a practical application for manufacturing complex-shaped elements. The current work dealt with the application of ultrasonic guided waves for non-destructive damage detection and imaging in AM plates. Two specimens with defects were manufactured from PLA filament. Different sizes of damage areas were considered. The specimens were tested using the guided wave propagation technique. The waves were excited using a PZT actuator and recorded contactless with the scanning laser Doppler vibrometry (SLDV) in a set of points located at one surface of the sample. The collected signals were processed with two methods. The first was the weighted root mean square (WRMS) algorithm. Different values of the calculation parameters, namely, averaging time and weighting factor were considered. The WRMS damage maps for both samples were prepared to differentiate between intact and damaged areas. The second approach was wavefield curvature imaging (WCI) which allowed the determination of damage maps based on the curvature of the wavefront. The compensation of wave signals was performed to enhance the quality of results. It was observed that the size of the defect strongly influenced the efficiency of imaging with both methods. The limitations of the proposed approaches were characterized. The presented results confirmed that guided waves are promising for non-destructive damage imaging in AM elements.