煤灰熔融温度多项式模型的偏回归函数分析

为了考察煤灰中的化学组分对熔融特性温度的贡献，借助我国69种重要的商业用煤的灰熔融特性温度和灰中SiO2和Al2O3等6种主要化学组分的测试数据，利用多项式模型的偏回归函数分析方法，对煤灰的熔融特性温度进行一至四阶多项式模型回归分析，获得了各化学组分的偏回归函数。研究结果表明：各化学组分的偏回归函数能够表现熔融温度对应于该组分变化的趋势；同一组分偏回归函数不同，该组分对变形温度、软化温度和熔融温度的影响存在较大的差异；CaO和TiO2的偏回归函数反映熔融温度变化趋势的可信度最高。实验为进一步研究煤灰熔融特性温度的数学模型和参数选择提供参考。

Analysis of Coal Ash Fusion Temperature Using Polynomial Partial Regression Functions

In order to investigate the contribution of oxides to ash fusion temperature (AFT), the AFT and chemical compositions of 69 important Chinese commodity coals were accomplished in this work. The ash fusion temperature of them was regression analyzed by using from first to fourth order polynomial models via six main chemical compositions of coal ash including SiO_2, Al_2O_3 and other oxides, and the partial regression functions were got via mathematically analyzing polynomial regression equations. The studies illustrate that, the partial regression functions can show the variety trend of AFT on the variation of a specific component, and CaO and TiO_2 are of the highest credit value. It is also shown that different components play quite different influences on the fusion temperature. This method can work more sufficiently and briefly than the traditional experiments and can make references to further studies on the model of coal ash fusion temperature.