制备氮化铀陶瓷预测最佳烧结温度数据

将采集到的数据使用一元线性回归模型用来预测制备陶瓷过程中的最佳烧结温度。该模型在泥浆比重、泥浆水分、稠化性、回坯泥比重、釉浆细度等数据为固定量条件下，通过该预测模型来预测最佳坯体收缩率时的烧结温度，从而能够为制备陶瓷预测出最佳的烧结温度，为广大的陶瓷生产企业提高了产品质量和生产效率提供技术支持。将采集到的数据使用一元线性回归模型用来预测制备陶瓷的最佳烧结温度。该模型在泥浆比重、泥浆水分、稠化性、回坯泥比重、釉浆细度等数据为固定量条件下，烧结温度与坯体收缩率构成一元函数关系（y（坯体收缩率）=F(烧结温度)），通过该函数公式来反推根据因变量变化的变化，在最佳坯体收缩率时根据极大似然法取概率分布最大的烧结温度的取值，从而能够为制备陶瓷预测出最佳的烧结温度。

The collected data is applied with a univariate linear regression model to predict the optimal sintering temperature during ceramic preparation. When key parameters including slurry specific gravity, slurry moisture content, thickening property, specific gravity of returned green body slurry, and fineness of glaze slurry are held constant, the model establishes a univariate functional relationship between sintering temperature and green body shrinkage rate, expressed as y (green body shrinkage rate) = F(sintering temperature). Through this functional formula, inverse deduction is conducted: by tracking changes in the dependent variable, the maximum likelihood estimation method is adopted to select the sintering temperature value corresponding to the maximum probability distribution when the green body shrinkage rate reaches its optimal level, thus obtaining the predicted optimal sintering temperature for ceramic preparation. This work provides technical support for ceramic manufacturing enterprises to enhance product quality and production efficiency.

搜集汇总

数据集介绍

特点

该数据集记录了制备氮化铀陶瓷的多项参数和不同烧结温度下的坯体收缩率，用于通过一元线性回归模型预测最佳烧结温度，以提高陶瓷生产的质量和效率。