As for low forecast accuracy of cobalt ion concentration by least square support vector machine(LS-SVM)method in the purification process of zinc hydrometallurgy，a multi-model fusion soft sensor modeling method based on combination LS-SVM with ARMA model was introduced in purification of zinc.Firstly the series of cobalt ion concentration was decomposed by wavelet transform

the decomposed sub-sequences were reconstructed by phase space reconstruction.Each sub-sequence was modeled by LS-SVM method in phase space

then the output of each model was integrated by wavelet reconstruction.Secondly correction was made for error of LS-SVM modeling output in ARMA model.Finally the output of two models were integrated

the integration value was the estimated value of cobalt ion concentration.The method was applied in prediction of cobalt ion concentration in the entrance of purification process of zinc hydrometallurgy. The results showed that this method had better generalization performance and high prediction accuracy than LS-SVM method

which showed good potential for application.