基于最大似然原理的电厂混煤均匀性确定

采用传统采样分析法对电厂混煤混合均匀性进行评估存在较大困难。将掺混原煤看作是各种成分符合不同概率分布的混合物，在原煤掺混而成的混煤中，某种成分的概率分布由原煤该成分分布、混合比例以及颗粒混合状态共同决定。以挥发分作为示踪成分，考察了掺混过程中挥发分概率分布的变化，在给定原煤挥发分分布和混煤挥发分样本集的情况下，采用最大似然原理对混煤中各种原煤掺混比例和标准差进行估计，进而对混合状态进行评估。研究表明，掺混模型对实际掺混系统的预测结果与原煤消耗量的统计数据吻合良好；多工况仿真实验也表明，掺混系统混合质量越差，模型的预测精度越高。

Determination of Coal Blending Uniformity in Power Plant Based on Maximum Likelihood Estimation

It is difficult to evaluate the mixing uniformity of powder or particle mixing material by traditional sampling analysis method. The mixed raw coal is regarded as a mixture with different probability distributions of various components. In the mixed coal formed by mixing raw coal, the probability distribution of a certain component is determined by the composition distribution, mixing ratio and particle mixing state of the raw coal. Taking volatile as the tracer component, the change of the probability distribution of volatile in the mixing process was investigated. At given mine coal volatile distributions and mixed coal sample data set, the maximum likelihood principle was used to estimate the mixing ratio and standard deviation of various raw coal in the mixed coal, and then the mixing state was evaluated. The results show that the prediction results of the mixing model for the actual mixing system are in good agreement with the statistical data of raw coal consumption. The multiple blending conditions simulation experiments also show that the worse particle homogeneity of the mixing system, the higher the prediction accuracy of the model.