化工学报2013，Vol.64Issue(3)：788-800,13.DOI:10.3969/j.issn.0438-1157.2013.03.003
化工过程软测量建模方法研究进展
Modeling of soft sensor for chemical process
摘要
Abstract
In the commercial chemical process, many primary product variables cannot be measured online, and soft sensor is an important means to solve this problem. Soft sensing modeling is the core issue of soft sensor. The relationship between soft sensing modeling and identification and nonlinear modeling is presented. The dynamic relationship between quality variables and variables that are easy to measure exists between the increments, and identification depends on incremental data, while soft sensing modeling depends on the measured data to get the relationship. Nonlinear modeling establishes the static relationship between these variables, ignoring the dynamic characteristics, which soft sensing modeling should take into account. With deeper understanding of the chemical process properties, the types and structures of soft sensing model have undergone a great change in the last decades, and soft sensing modeling method evolves from mechanism modeling to data-driven modeling, from linear modeling to nonlinear modeling, and from static modeling to dynamic modeling. The development of the soft sensing modeling method is reviewed. The advantages and disadvantages of the proposed methods are analyzed, and the applications of these methods are shown. In the end, the hot issues and the directions of development of soft sensing modeling method are presented.关键词
软测量/建模/辨识/非线性建模/数据驱动建模/非线性动态建模Key words
soft sensor/ modeling/ identification/ nonlinear modeling/ data-driven modeling/ nonlinear dynamic modeling分类
信息技术与安全科学引用本文复制引用
曹鹏飞,罗雄麟..化工过程软测量建模方法研究进展[J].化工学报,2013,64(3):788-800,13.基金项目
国家重点基础研究发展计划项目(2012CB720500). （2012CB720500）
