Prediction of Chemical Composition of Ancient Glass Relics before Weathering

Jiehua Sun, Huazhou Chen, Yao Liu, Hongquan Lin, Huiwen Zheng, Yingzhen Qiu
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Abstract

Ancient glass relics are easily weathered by the influence of buried environment, and the internal elements exchange with the environmental elements in large quantities, resulting in changes in their composition ratio. Archaeological research can often detect the component content of glass relics after weathering, but it is difficult to obtain the corresponding component content before weathering. It is necessary to predict the chemical composition of glass relics before weathering in order to accurately identify the type of glass relics and repair them. To solve this problem, this paper proposes a distributed matching strategy, and studies the influence of weathering on the composition content of glass through compositional correlation analysis and linear regression statistical methods, so as to build a prediction model of the composition content of glass relics before weathering. The results show that the composition prediction model of glass cultural relics constructed by the distribution matching strategy has a good prediction ability, which is consistent with the change trend of the composition ratio of linear regression analysis. Moreover, the model is simple and easy to operate, which is convenient for popularization and application, and provides theoretical basis and reference value for further research on the composition and accurate classification of glass cultural relics.
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古玻璃遗迹风化前化学成分预测
古代玻璃文物易受埋藏环境的影响而风化,内部元素与环境元素大量交换,导致其组成比例发生变化。考古研究往往可以检测到风化后玻璃文物的成分含量,但很难获得风化前相应的成分含量。为了准确识别玻璃文物的类型并进行修复,有必要在风化前对玻璃文物的化学成分进行预测。针对这一问题,本文提出分布式匹配策略,通过成分相关分析和线性回归统计方法研究风化对玻璃成分含量的影响,从而建立风化前玻璃遗迹成分含量的预测模型。结果表明,采用分布匹配策略构建的玻璃文物成分预测模型具有较好的预测能力,与线性回归分析的成分比变化趋势一致。而且该模型简单易操作,便于推广应用,为进一步研究玻璃文物的成分和准确分类提供理论依据和参考价值。
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