Mem_Fac_Eng_OU_40_1_9.pdf 473 KB
貫名 高史 Dept. of Electrical and Electronic Engineering Okayama University
小西 正躬 Dept. of Electrical and Electronic Engineering Division of Industrial Innovation Sciences The Graduate School of Natural Science and Technology Okayama University
西 竜志 Dept. of Electrical and Electronic Engineering Division of Industrial Innovation Sciences The Graduate School of Natural Science and Technology Okayama University
Controls of the temperature, pressure and flowing quantity are important for the stable operation of the product quality in the distillation tower. The usual measuring way of product quality estimation is made by the off-line analysis. In this paper, online estimation method of product quality is studied for improving the product quality. The estimation method based on stochastic analysis was developed for online estimation. In this paper, the data of temperature, pressure and flow volum in the distillation tower are treated. As the estimation models, RNN (Recurrent Neural Net Work) and PLS (Partial Least Square Regression Method) were adopted. The actual plant data were used in the analysis. Both PLS and RNN models could compensate each other to improve the accuracy in estimation.
Memoirs of the Faculty of Engineering, Okayama University
Faculty of Engineering, Okayama University
|Eprints Journal Name||