Industrial melt index soft measurement method through combination of fuzzy neural network and group intelligent optimization

Abstract

The invention discloses an industrial melt index soft measurement method through combination of a fuzzy neural network and group intelligent optimization. The method is applied to online prediction for an industrial melt index in the propylene polymerization production process. A data preprocessing module, a fuzzy neural network module, a dragonfly optimizing algorithm module, a sliding window module and a fuzzy rule optimization module are involved. According to a sliding window method, input of the fuzzy neural network every moment is provided, by using an improved dragonfly optimizing algorithm, a fuzzy neural network parameter is intelligently optimized, and the setting problem of the fuzzy neural network parameter in the prior art is solved. According to the method, global and local information in the optimizing process is considered at the same time, a network parameter can be stably and online corrected, and the adaptivity of the system to input data fluctuation is improved. Themethod has the advantages of stable optimized model structure, good generalization performance and high anti-interference capacity.

Description

technical field [0001] The invention relates to a soft measurement method, in particular to an industrial melting index soft measurement method based on fuzzy neural network and group intelligence optimization. Background technique [0002] Polypropylene is a semi-crystalline thermoplastic polymerized from propylene. It has high impact resistance, strong mechanical properties, and resistance to various organic solvents and acid and alkali corrosion. It is widely used in the industry and is common. One of the most common polymer materials. Melt index (MI) is one of the important quality indicators to determine the grade of the final product in the production of polypropylene, which determines the different uses of the product. Accurate and timely measurement of melt index plays a very important and guiding role in production and scientific research. However, the on-line analysis and measurement of melt index is still difficult to achieve, and the lack of on-line analyzer fo...

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Problems solved by technology

[0006] In order to overcome the deficiencies of the existing melt index online prediction system in the propylene polymerization production process, such as unstable working state, low measurement accuracy, weak anti-interference ability, and poor promotion performance, the purpose of the present invention is to provide a high calculation accuracy, anti-interference Strong ability, automatic update and optimization of model structure, promotion of industrial melting index soft sensor method with good performance of fuzzy neural network and group intelligence optimization

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