Soft Sensor of Concentration of Sodium Aluminate Solution Based on Reduction Robust LSSVM

Abstract

Abstract: Taking into account of poor stability, radioactive, higher maintenance costs and lack of manual detection of serious lag issues for online testing instrument of sodium aluminate concentration, combined with the mechanism analysis of the evaporation process, selecting parameters that affect the concentration of sodium aluminate solution as the auxiliary variables, using weighted loss function of the least squares support vector machine (Least Squares Support Vector Machine, LSSVM), a robust soft measuring for the concentration of sodium aluminate solution was achieved. Schmidt method was used to simplify the matrix and reduce the computational complexity. Industrial process data simulation results show that the soft measurement model can detect continuously sodium aluminate solution concentration online, and receive more than standard LSSVM, weight LSSVM higher prediction accuracy, and fully meet the industrial requirements.

Key words: DE algorithm, least squares support vector machine, Sodium aluminate Solution, Robust

CLC Number:

TP18

Sun Rongling, Qian Xiaoshan. Soft Sensor of Concentration of Sodium Aluminate Solution Based on Reduction Robust LSSVM[J]. Journal of System Simulation, 2015, 27(9): 2203-2207.

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