Analysis and Prediction of Glass Product Composition by Using Control Variable Method

This paper investigates the composition and identification of ancient glass artefacts. First, the collected data were pre-processed to determine the chemical composition content of the glass artefacts before weathering. Then, based on the variable control method, the effects of decoration and colour of two types of glass, high potassium glass and lead-barium glass, on the weathering of artefacts were determined. The statistical law of the presence or absence of weathering chemical composition on the surface of artefact samples was summarized by establishing a weathering change rate solution model. Meanwhile, based on the weathering change rate, the solution model for the content of chemical substances before weathering is summarized, and the content of different chemical components in ancient glass artefacts before weathering is predicted. Next, the second problem is carried out, which is to classify the glass and select the appropriate chemical composition for subclassification. Ancient glass artefacts were classified into the high-potassium glass and lead-barium glass based on their chemical composition and content, and the classification rules were analyzed. On this basis, the top eight indicators of chemical composition differences between the two types of artefacts were determined by comparison and subclassified by the K-means algorithm. Finally, model experiment results verified the correctness and validity of the models proposed in this paper.