| POLYMERS AND POLYMER MATRIX COMPOSITES |
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| Evaluation Method of Dispersion Uniformity in Blended Composite Films Using Fusion Algorithms |
| YANG Qing1,2, LIN Jiajun1, ZHU Benshuo1, HAN Jing1,2, WU Liwei1,2, JIANG Qian1,2,*
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1 School of Textile Science and Engineering, Tiangong University, Tianjin 300387, China 2 Tianjin and Ministry of Education Key Laboratory for Advanced Textile Composite Materials, Tiangong University, Tianjin 300387, China |
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Abstract This work established an integrated evaluation method for assessing dispersion homogeneity in blended composite films by combining a natural genetic algorithm (NGA), watershed segmentation algorithm and neural network. Using maleic anhydride (MAH)-modified polypropy-lene (PP)/polylactic acid (PLA) films as a model system, a standardized pre-processing of microscopic images involving grayscale adjustment and contrast enhancement was firstly conducted to normalize brightness and contrast. Then, a precision threshold optimization via NGA was achieved with the optimal threshold of 52.785 9. Combining marker-controlled watershed segmentation for image partitioning, morphological screening of segmented regions was conducted to extract the particle size of dispersed phase targets. A three-layer backpropagation (BP) neural network was utilized to validate the accuracy of particle identification. Numerical analysis revealed that the particle size distribution of films with 0.8% MAH exhibits enhanced stability in the dispersed phase, achieving an adjusted coefficient of determination (R2=0.998 0) and a distribution closer to normal distribution. Tensile tests further demonstrated that films with 0.8% MAH simultaneously reach maximum values in both the inverse coefficient of variation (CV-1=2.632) and tensile strength (25.076 MPa), confirming the high consistency between the evaluation results and the physical properties of the films. These findings validate the reliability and applicability of the proposed method for dispersion homogeneity analysis in composite materials.
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Published: 25 April 2026
Online: 2026-05-06
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