Analysis of Preparation Conditions of Low-Temperature Curing Powder Coatings Based on Local Clustering Algorithm

Abstract

The coating industry is gradually developing towards a green and efficient direction. Powder coating has the advantages of energy saving, nonpolluting, high efficiency, and easy production automation. Its output has grown rapidly and has become one of the development directions of the coating industry. Powder coatings have expanded into new end markets with their well-known advantages. In order to analyze the preparation conditions of low-temperature curing powder coatings, this study selects low-temperature curing powder coatings and ordinary powder coatings to compare, analyzes the realization mechanism of low-temperature curing powder coatings, and uses actual cases for research and analysis. Low-temperature curing powder coatings were prepared with trimethylolpropane (TMP) as the main raw material. Using a combination of single-factor analysis and orthogonal experiments, the effects of TMP addition, curing temperature and curing time on the gloss and impact properties of coatings were studied, and a local clustering algorithm was proposed to intelligently determine the optimal coating condition. Low-temperature curing powder coatings are optimized and screened by algorithms.