Based on the analysis and identification of ancient glass products

Abstract

The chemical composition of ancient glass in China is diverse, and it is very vulnerable to weathering under the influence of burial environment. This weathering will aggravate the difficulty of identifying ancient glass types. There are a number of relevant data on ancient glass products in China. Archaeologists have divided these cultural relics into two types: high potassium glass and lead barium glass according to their chemical composition and other detection methods. In this paper, Kappa consistency test, statistical law, principal component analysis, k-means clustering analysis, logical regression model, gray correlation analysis and other methods or models are used to analyze the composition of these glass samples and identify their types.The Kappa coefficient is used to test the consistency of these three groups of disordered classification variables, and the Kappa value is used to judge the correlation degree of the three groups of disordered classification variables. Through the test, it is found that the surface weathering of glass relics has a certain relationship with its glass type; Later, we tried to explore whether there would be a more obvious rule when the surface weathering was affected by two variables at the same time. It was found that when the glass type was fixed to high potassium, the type of its decoration would have an impact on its weathering.