The Forecast of Co-Rotating Twin-Screw Extruder's Screw Based on BP Neural Network Model

Guang Sheng Zeng; Hui Zhang; Hua Chen

doi:10.4028/www.scientific.net/AMM.711.257

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 711The Forecast of Co-Rotating Twin-Screw Extruder's...

The Forecast of Co-Rotating Twin-Screw Extruder's Screw Based on BP Neural Network Model

Abstract:

The established BP neural network model can forecast one of the wood-plastic composite molding equipment the screw of extruder with co-rotating twin-screw has been presented. The content of fiber and lubricant, the appropriate temperature of the extruder and the target yield are determined as the variable inputs, while the outputs are the diameters of the screw stem. This intelligent BP network model can forecast the condition of actual production precisely by setting the input properties of the material and the integration of products in order to fit the requirements of the wood-plastic composited production more successfully. Through the analysis of BP neural network model, the former simple method of choosing the screw stem’ diameters only depend on yield can be modified more efficiently.

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Periodical:

Applied Mechanics and Materials (Volume 711)

Pages:

257-260

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.711.257

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Online since:

December 2014

Authors:

Guang Sheng Zeng, Hui Zhang*, Hua Chen

Keywords:

BP Model, Extruder, Neural Network, WPC

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* - Corresponding Author

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