关键词: 跳汰机, 床层松散度, AP聚类算法, 多模型, 最小二乘支持向量机

Abstract: Mobility of bed is the important factor for jigging separation process.A soft sensing modeling method based on the least squares-support vector machine(LS-SVM)is developed to deal with the problem that mobility cannot be measured directly online.In full consideration of highly nonlinear and strong coupling characteristic of separation process,an LS-SVM multi-model method based on affinity propagation(AP)clustering is presented and applied to avoid bad accuracy of single model expressing multiple working positions.In the presented method,AP-clustering algorithm is used to cluster training samples.Then,the sub-models are trained by LS-SVM.Finally,the predicted values of the testing samples are estimated by the sub-models after it is classified by switchover.Simulation results show that a better prediction for mobility of jig bed is obtained by the LS-SVM multi-model method based on AP-clustering algorithm.

Key words: jig, mobility of bed, AP-clustering, multi-model, LS-SVM