The purpose of this article is to study the materials physics behind dye-doped polymethyl metharcylate (PMMA) that is important for the optical fiber drawing process. We report effects of the fabrication process on the mechanical properties of the final fiber. The qualitative degree of polymer chain alignment is found to increase with the drawing force, which in turn decreases with the drawing temperature and increases with the drawing ratio. The chain alignment relaxes when the fibers are annealed at 95 °C with a commensurate decrease in fiber length and increase in diameter. The annealed fiber has higher ductility but lower strength than the unannealed fiber. Both the yield and tensile strengths are dependent on the strain rate. The relationship between tensile strength, σb, and fiber diameter, d, is found empirically to be σb∝d−0.5. The yield strength appears to be less sensitive to the fiber diameter than the tensile strength. For PMMA doped with disperse red 1 azo dye, the yield strength, tensile strength, and Young’s modulus peak at a dye concentration of 0.0094 wt %. These results are useful for designing polymer optical fibers with well-defined mechanical properties.

Machine vision is a promising technique to promote intelligent production. It strikes a balance between product quality and production efficiency. However, the existing metal surface defect detection algorithms are too general, and deviate from electrical production equipment in the level of response time to the target image. To address the two problems, this paper designs a detection algorithm for various types of metal surface defects based on image processing. Firstly, each metal surface image was preprocessed through average graying and nonlocal means filtering. Next, the principle of the composite model scale expansion was explained, and an improved EfficientNet was constructed to classify metal surface defects, which couples spatial attention mechanism. Finally, the backbone network of the single shot multi-box detector (SSD) network was improved, and used to fuse the features of the target image. The proposed model was proved effective through experiments.