Image Analysis Techniques Applied in the Drilling of a Carbon Fibre Reinforced Polymer and Aluminium Multi-Material to Assess the Delamination Damage

Abstract

Due to the high abrasiveness and anisotropic nature of composites, along with the need to machine different materials at the same time, drilling multi-materials is a difficult task, and usually results in material damage, such as uncut fibres and delamination, hindering hole functionality and reliability. Image processing and analysis algorithms can be developed to effectively assess such damage, allowing for the calculation of delamination factors essential to the quality control of hole inspection in composite materials. In this study, a digital image processing and analysis algorithm was developed in Python to perform the delamination evaluation of drilled holes on a carbon fibre reinforced polymer (CFRP) and aluminium (Al) multi-material. This algorithm was designed to overcome several limitations often found in other algorithms developed with similar purposes, which frequently lead to user mistakes and incorrect results. The new algorithm is easy to use and, without requiring manual pre-editing of the input images, is fully automatic, provides more complete and reliable results (such as the delamination factor), and is a free-of-charge software. For example, the delamination factors of two drilled holes were calculated using the new algorithm and one previously developed in Matlab. Using the previous Matlab algorithm, the delamination factors of the two holes were 1.380 and 2.563, respectively, and using the new Python algorithm, the results were equal to 3.957 and 3.383, respectively. The Python results were more trustworthy, as the first hole had a higher delamination area, so its factor should be higher than that of the second one.