稀土分离联产品质量控制研究

以稀土分离企业为背景,抽取联产品特点及质量属性,绘制单一产品的指数加权移动平均控制图和联产品的多元残差T²控制图,并将两类控制图进行对比分析,分析表明和EWMA控制图相比,联产品多元残差T²控制图能降低控制图虚发警报的概率。针对多元残差T²控制图发现的异常模式,采用支持向量机模型对异常模式进行分类处理,寻找分类规则,构造PSO-SVM分类器,运用粒子群算法对SVM参数寻优,并对得出的结果进行对比分析。分析表明该分类器能提高分类正确率,模式识别可以用于诊断稀土企业引起联产品多元残差T²控制图出现异常的原因,从而提高过程质量管理水平。

Study on Quality Control of Co-product in Rare Earth Separation

Against the background of rare earth separation enterprises, this paper summarizes the feature and quality attribute of co-product first. Then the exponentially weighted moving average(EWMA)control chart of the single product and the multiple residual T² control chart of the co-product are drawn respectively. The comparative analysis results of the two control charts show that the multiple residual T² control chart of co-product can reduce the probability of false alarm compared to EWMA control chart. Finally, based on the abnormal patterns of multiple residual T² control chart, this paper classifies the abnormal patterns using support vector machine model(SVMM), finds out the classification rules, constructs PSO-SVM classifier and optimizes the SVM parameters by the method of Particle Swarm Optimization Algorithm. The results show that the PSO-SVM classifier can greatly improve the classification accuracy. Pattern recognition can be used to diagnose the causes for the abnormality of the co-product multiple residual T² control chart and improve the level of process quality management.