中国化学工程学报(英文版)
中國化學工程學報(英文版)
중국화학공정학보(영문판)
CHINESE JOURNAL OF CHEMICAL ENGINEERING
2004年
2期
234-239
,共6页
刘瑞兰%苏宏业%牟盛静%贾涛%陈渭泉%褚健
劉瑞蘭%囌宏業%牟盛靜%賈濤%陳渭泉%褚健
류서란%소굉업%모성정%가도%진위천%저건
purified terephthalic acid%4-carboxybenzaldchydc%fuzzy neural network%soft sensor%input variables selection%fuzzy curve%dead time detection
A fuzzy neural network (FNN) model is developed to predict the 4-CBA concentration of the oxidation unit in purified terephthalic acid process. Several technologies are used to deal with the process data before modeling.First, a set of preliminary input variables is selected according to prior knowledge and experience. Secondly, a method based on the maximum correlation coefficient is proposed to detect the dead time between the process variables and response variables. Finally, the fuzzy curve method is used to reduce the unimportant input variables. The simulation results based on industrial data show that the relative error range of the FNN model is narrower than that of the American Oil Company (AMOCO) model. Furthermore, the FNN model can predict the trend of the 4-CBA concentration more accurately.
