Evaluation of the Robustness of Surface Characterisation of Carbon Fibre Composites Using Wavelet Texture Analysis

Abstract

The mechanical properties of advanced composites are essential for their structural performance, but the surface finish on exterior composite panels is of critical importance for customer satisfaction. Previous work by the authors established the feasibility of wavelet texture analysis (WTA) for the task of automatically classifying the surface finish of carbon fibre reinforced polymer (CFRP) samples based on computer image processing. This paper presents an evaluation of the robustness of the WTA method to common process errors that can occur in the imaging of material samples. WTA creates a rich representation of the texture in an image that includes features related to both scale and orientation. Principal components analysis was used to reduce the dimensionality of the texture feature vector to a single principal component that could be used as the basis for discrimination between grades of CRFP sample surface finish quality. The results obtained indicate that the WTA method is robust to: significant horizontal and/or vertical translations of the sample being imaged; significant rotation of the sample being imaged; and significant dilation of the sample being imaged. The results obtained suggest that as long as reasonable precautions are taken in sample imaging, then the WTA method will yield repeatable results.