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An optimal soft measurement instrument for a propylene polymerization production process of a convolutional neural network

A convolutional neural network and optimal soft-sensing technology, applied in biological neural network models, neural architectures, neural learning methods, etc., can solve problems such as low measurement accuracy and being easily affected by human factors

Inactive Publication Date: 2019-04-30
ZHEJIANG UNIV
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  • Application Information

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Problems solved by technology

[0005] In order to overcome the shortcomings of the current existing propylene polymerization production process, which are not high in measurement accuracy and easily affected by human factors, the purpose of the present invention is to provide an on-line measurement, on-line parameter optimization, fast forecasting speed, automatic model update, and anti-interference Optimal Soft Sensor Instrument for Propylene Polymerization Production Process Based on Improved Gravity Search Algorithm Optimizing Convolutional Neural Network with Strong Capability and High Accuracy

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  • An optimal soft measurement instrument for a propylene polymerization production process of a convolutional neural network
  • An optimal soft measurement instrument for a propylene polymerization production process of a convolutional neural network
  • An optimal soft measurement instrument for a propylene polymerization production process of a convolutional neural network

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Embodiment 1

[0058] refer to figure 1 , figure 2 , a convolutional neural network optimal soft-sensing instrument for propylene polymerization production process, including propylene polymerization production process 1, on-site intelligent instrument 2 for measuring easy-to-measure variables, control station 3 for measuring operating variables, and data storage DCS database 4 and melt index soft measurement value display instrument 6, the on-site intelligent instrument 2, the control station 3 are connected to the propylene polymerization production process 1, the on-site intelligent instrument 2, the control station 3 are connected to the DCS database 4, the soft The measuring instrument also includes the optimal soft sensor model 5 based on the improved gravity search algorithm to optimize the convolutional neural network, the DCS database 4 and the input end of the optimal soft sensor model 5 based on the improved gravity search algorithm to optimize the convolutional neural network C...

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Abstract

The invention discloses an optimal soft measurement instrument for a propylene polymerization production process of a convolutional neural network. The system comprises a propylene polymerization production process, an on-site intelligent instrument, a control station, a DCS database for storing data, an optimal soft measurement model for optimizing a convolutional neural network based on an improved gravitation search algorithm and a melt index soft measurement value display instrument, and the on-site intelligent instrument and the control station are connected with the propylene polymerization production process and are connected with the DCS database; and the optimal soft measurement model is connected with the DCS database and the soft measurement value display instrument. The optimalsoft measurement model for optimizing the convolutional neural network based on the improved gravitational search algorithm comprises a data preprocessing module, a convolutional neural network module, a model updating module and an improved gravitational search algorithm optimization module. The invention also provides a soft measurement method realized by using the soft measurement instrument.Online measurement is achieved, the structure and parameters are dynamically adjusted, the optimization and popularization capacity is high, the model is automatically updated, the noise interferenceresistance is high, and the precision is high.

Description

technical field [0001] The invention relates to an optimal soft measuring instrument, in particular to an optimal soft measuring instrument for the propylene polymerization production process of a convolutional neural network. Background technique [0002] Polypropylene is a thermoplastic resin produced by propylene polymerization. The most important downstream product of propylene, 50% of the world's propylene and 65% of my country's propylene are used to make polypropylene. It is one of the five general-purpose plastics. are closely related to daily life. Polypropylene is the fastest growing general-purpose thermoplastic resin in the world, second only to polyethylene and polyvinyl chloride in total. In order to make my country's polypropylene products have market competitiveness, develop impact copolymer products, random copolymer products, BOPP and CPP film materials, fibers, and non-woven fabrics with good balance of rigidity, toughness, and fluidity, and develop polypr...

Claims

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Application Information

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IPC IPC(8): G06N3/04G06N3/08G06N3/00G06F17/16
CPCG06F17/16G06N3/006G06N3/08G06N3/045
Inventor 张泽银黄国权刘兴高
Owner ZHEJIANG UNIV
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