Study on Soft-sensing Model for Condenser Vacuum Based-on Support Vector Regression
In this paper, depending on tbe interrelation of condensers operational parameters, the factors which affect the vacuum of condenser are analyzed. And a soft-sensing model for condenser vacuum is given by using Support Vector Regression (SVR), then the model is verified and parameters are discussed based on the data of the 300MW steam turbine unit, and the prognostication precision is compared with a RBF model. The results indicate that model based-on SVR has forcible generalization ability and stability and can be adapted to application. The condenser vacuum can be calculated by using the soft-sensing model when the vacuum measuring point is fault, so the model based-on SVR provides a redundancy method for the measurement and diagnosis of condenser vacuum.
support vector regression soft-sensing steam turbine condenser vacuum
Lei WANG Rui-qing ZHANG
Thermal Power Engineering Department, Shenyang Institute of Engineering, Shenyang 110136, Liaoning, China
国际会议
The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)
沈阳
英文
497-499
2010-03-27（万方平台首次上网日期，不代表论文的发表时间）