Soft Sensor Modeling of Moisture Content in Drying Process Based on LSSVM

摘要：

Least Squares Support Vector Machines(LSSVM) regression principle and measure methods of moisture content during wood drying were introduced. Wood moisture content is a key parameter for regulating and controlling wood drying proces. In this paper soft sensor model based on LSSVM was established for the weakness of wood moisture content measurement in drying process, and parameters selection adopted improved exhaust algorithm. The simulation results of Fraxinus mandshurica and Xylosma racemosum showed that the LSSVM soft sensor model had well robustness and generalization ability, and could predict wood moisture content measurement in drying process accurately, which offered an effective approach for measuring the parameters in the complicated and nonlinear process of wood drying.

关键词： Wood Moisture Content Soft Sensor Least Squares Support Vector Machines(LSSVM) Modeling

作者: Dongyan Zhang Jun Cao Liping Sun

作者单位: Department of Electromechanics Engineering,Northeast Forestry University Harbin 150040,China

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 2066-2070

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）