China Plastics ›› 2019, Vol. 33 ›› Issue (8): 69-75.DOI: 10.19491/j.issn.1001-9278.2019.08.012

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Study on Dispersion Performance Prediction of Pigment Based on BP Neural Network

  

  • Received:2019-04-08 Revised:2019-04-17 Online:2019-08-26 Published:2019-08-26

Abstract: Based on the orthogonal experiment, the influence factors of color difference of plastic products were analyzed and discussed, and the data-prediction function of BP neural network was utilized to construct the prediction model of pigment dispersion performance. The results indicated that the factors affecting the color difference of plastic products were listed in an order of rotor speed > mixing time > mixing temperature. The increase of rotor speed could facilitate the dispersion and distribution of pigment particles in the plastic matrix, and the coloring quality of the product was improved accordingly. The relative error predicted by the BP neural network model did not exceed 10 %, and therefore this model could predict the dispersion performance of pigments in the plastic coloring process.