Image Based Measurement of Individual Fiber Lengths for Randomly Oriented Short Fiber Composites.

Among a wide range of fiber-reinforced composites, those with randomly oriented short fibers, which are also known as random-chopped fiber-reinforced composites (RaFCs), are the most common composites owing to its ease of manufacturing, flexibility of composite shapes, and good material properties, including light weight and high stiffness. These properties of RaFCs are involved with the lengths and distributions of fibers inside the composites. However, inspecting the fiber lengths and distribution remains a challenging problem, particularly when the lengths and locations of individual fibers need to be distinguished using only X-ray transmission images. The main difficulty arises from the variety of fiber widths and their frequent intersections. To address this problem, this paper proposes a comprehensive software system to localize fibers and measure their lengths. Our system is inspired by a previous work for tracing human hair strands. To adopt the previous method for RaFCs, our system extends classic Gabor filter to explore the locally best parameter sets to suit different fiber shapes. With this adaptive filter, we can extract the locations and orientations of local fibers more robustly for RaFCs. Then individual fibers are traced by solving an initial value problem of an ordinary differential equation. To avoid erroneous tracing which typically occurs at intersections, our method traces only the non-intersecting parts of the fibers initially. After that, we connect the fiber segments using the proximity of their endpoints and the orientations. Through experimental validations on different fiber samples, we demonstrate the stability of the fiber tracing and the robustness of the fiber length calculation. Our system works properly even for X-ray radiographic images of heavily tangled fibers in carbon-fiber-reinforced thermoplastic laminates taken by X-ray Talbot–Lau interferometer. [ABSTRACT FROM AUTHOR]