NDLI: Dynamic soft sensor modeling based on state detection and impulses response template

Content Provider	IEEE Xplore Digital Library
Author	Zhi Fan Jie Cao Yujie Wei
Copyright Year	2014
Description	Author affiliation: Depts. of Autom., Tsinghua Univ., Beijing, China (Yujie Wei) \|\| Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou, China (Zhi Fan; Jie Cao)
Abstract	Accurate and reliable prediction of melt mass flow rate is crucial in polypropylene production. In order to establish an accurate prediction model, a process state detection method and a novel dynamic modeling method is proposed, and the model parameters are identified by improved swarm optimization algorithm. A polypropylene product melt mass flow rate soft sensor model is established based on process state detection and impulses response template. According to the research on the data from real plant, the experiments demonstrate that even under dynamic state, the proposed approach can improve the prediction accuracy, and the soft sensor model has good tracking ability and meets the requirement of on-line optimal control.
Starting Page	4031
Ending Page	4037
File Size	208339
Page Count	7
File Format	PDF
ISBN	9781479937073
e-ISBN	9781479937080
DOI	10.1109/CCDC.2014.6852886
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heuristic algorithms Hydrogen Melt Mass Flow Rate Soft Sensor Impulses Response Template Steady-state Polymers Mathematical model Indexes Inductors Particle Swarm Optimization State Detection
Content Type	Text
Resource Type	Article

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