摘要
针对工业过程中普遍存在的时延特性和动态特性,提出一种基于联合互信息的动态软测量方法。以联合互信息最大化作为准则,从各辅助变量的历史输入数据矩阵中选取一个连续子变量集,组成包含过程时延信息和动态信息的新数据集,进而确定各辅助变量的时延参数、历史数据长度。各辅助变量参数完全基于过程历史数据确定,与后续软测量模型的建立无关,因此建立动态软测量模型的形式可根据对象非线性程度自主选择。针对实际脱丁烷塔塔底丁烷浓度软测量的仿真研究验证了方法的有效性。
In order to deal with time delay characteristic as well as dynamic characteristic widely exist in industrial process systems, this paper puts forward a dynamic soft sensor method based on joint mutual information. In the proposed method, maximizing the joint mutual information is taken as the criterion for selecting the continuous sub-variable set from each auxiliary variable’s historical input data matrix. The selected sub-variable set forms a new data set containing the process’s time delay information and dynamic information, which can be used to determine the time delay and historical data length of each auxiliary variable. The determination of the parameters of each auxiliary variable involves only the process’s historical data and thus is independent of the following establishment of soft sensor model. As a result, the algorithm for constructing dynamic soft sensor models can be freely chosen according to the nonlinear degree of the specific application. The proposed soft sensor is applied to real-life debutanizer column process and its effectiveness is verified by the simulation results.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2014年第11期4497-4502,共6页
CIESC Journal
基金
国家自然科学基金项目(61273160)
中央高校基本科研业务费专项基金项目(13CX5021A
14CX06067A)
中国博士后科学基金项目(2013M541964)~~
关键词
软测量
互信息
时延估计
动态建模
soft sensor
mutual information
time delay estimation
dynamic modeling
