A Robust Non-destructive Method for the Identification of Areal Weight and Fiber Orientation Based on Image Processing

In addition to the textile industry, natural fibers attract other sectors, such as automotive and construction. The customer requires a time cycle, and the expansion requires an increase in production rate. Moreover, in the field of composites, the local properties of a composite are highly dependent on the reinforcement volume fraction and technical fiber orientation. Therefore, this work presents a new non-destructive method to identify the areal weight of a UD veil of natural fiber and the orientation of their technical fibers. The proposed method combines first and second-order image processing and statistical techniques to determine the orientation of the technical fibers and the areal weight of a UD veil of natural fiber. The method is based on the computation of each grey level’s areal weight as a sample mass function. In this method, the SVD (Single Value Decomposition) truncation technique has been implemented to reduce the effect of measurement noise. A second-order statistical study was performed to consider pixel-grey-level arrangements to identify the technical fiber orientation of a UD veil of the natural fiber sample. In this approach, the MDV (Mean Directional Vector) regularization technique was implemented in the formulation to determine the technical fiber orientation. Both methods were tested with digitally created images as a first step. Both approaches allow identifying the basis weight and orientation of the simulated samples satisfactorily, even with the addition of numerical noise. Identifying the areal weight and orientation of the technical fibers of a commercially available UD veil of natural fiber shows good agreement with conventional measurement methods.