Intelligent detection and yield optimization method for HDPE (high density polyethylene) cascade polymerization reaction course

A cascade polymerization, high-density polyethylene technology, applied in the field of intelligent detection and yield optimization of high-density polyethylene cascade polymerization process, can solve problems such as reducing the fitting accuracy of a single ELM neural network, and achieve fast online The effect of fast detection, learning speed and few adjustable parameters
CN103226728AActive Publication Date: 2013-07-31BEIJING UNIV OF CHEM TECH

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING UNIV OF CHEM TECH
Publication Date
2013-07-31

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Abstract

The invention provides an intelligent detection and yield optimization method for an HDPE (high density polyethylene) cascade polymerization reaction course, which solves the problems that the HDPE cascade polymerization reaction course is complicated in technology, on-line measurement of a key quality variable is difficult, and the operating cost of a production course is high. The method comprises the steps of preprocessing by adopting data correction and data excavation techniques, searching a rule from production and analysis data, adopting an artificial neural network technique to establish an intelligent soft measuring instrument and a polyethylene product unit consumption model, and adopting an extension engineering technique to optimize an artificial neural network structure and improve the neural network modeling accuracy. The method has the characteristics of high response time, high modeling accuracy, high inferential capability and convenience in management, and assists in ensuring safe production of HDPE, improving the quality of a polymer product, and saving the production cost.
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Description

technical field

[0001] The present invention is based on the high density polyethylene (High Density Polyethylene, HDPE) cascade polymerization reaction process as the object, and aims at the soft measurement of the melt index of the two reactors and the unit consumption of polyethylene products, and proposes a complex process industrial data online ELM neural network ensemble (ELM-E) technology of preprocessing, extreme learning machine (Extreme Learning Machine, ELM) algorithm and extension clustering algorithm. Background technique

[0002] With the rapid progress of polymer material science and technology and the continuous improvement of production technology, a revolutionary progress has taken place in the field of pipelines, that is, "replacing steel with plastic". In this revolution, high-density polyethylene pipes are favored because of their extremely high mechanical strength and high-speed processing performance. At present, they have been widely used in gas trans...

Claims

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