Executive Summary : | Three-dimensional printing (3DP) also known as additive manufacturing, is a pioneering technology for making several complex objects through layer-by-layer process using a computer aided design (CAD) model. It can significantly reduce costs and allow more design flexibilities for fabrication of complex shapes. 3D printed composites have been widely used in many engineering structures such as aerospace, automobile, electronics, mechanical, sports, etc. One of the most common polymers 3DP or additive manufacturing methods is Extrusion Deposition or Fused Filament Fabrication (FFF) or Fused Deposition Modelling (FDM). several defects can be formed during the FDM process, such as voids, delamination, porosity, fibre and matrix cracks in fiber reinforced polymer (FRP) composites. These defects occur due to several factors such as uneven heat profile during the printing, porosity in the feedstock material, small clogs in the printing nozzle, weak layer-to-layer interaction, etc. While the 3DP composite structure is subjected to different loading conditions such as mechanical and thermal loadings. The crack initiates and propagates in relative orientation between the crack and loading direction which adversely affect the performance of structures. Therefore, it is essential to detect the crack location and orientation to avoid the catastrophic failure. several vibrations-based signal processing methods are available for damage detection, however, the shearlet-transform (sT) based damage detection method has been explored in a limited application such as detection of surface texture, edge detection in microstructure image of the machined specimen. The main advantage of the shearlet-based method is to detect line singularity with orientation. In this study, a shearlet transform based damage detection algorithm is proposed which requires input of the mode shape from experimental modal analysis to detect the crack presence, location and orientation in 3D Printed composite plate. |