The Coal Slurry Pipeline Pressure Prediction Research Based on Quantum Genetic BP Neural Network

Xue Cun Yang; Yuan Bin Hou; Ling Hong Kong

doi:10.4028/www.scientific.net/AMM.336-338.722

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 336-338The Coal Slurry Pipeline Pressure Prediction...

The Coal Slurry Pipeline Pressure Prediction Research Based on Quantum Genetic BP Neural Network

Abstract:

According to the coal slime pipeline blockage problem of coal gangue thermal power plant, after the analysis of the actual scene, it is sure that thick slurry pump master cylinder pressure prediction is the necessary premise of blockage prediction. The thick slurry pump master cylinder pressure prediction model is proposed, which is based on QGA-BP (Quantum genetic Algorithm BP neural network). The simulation results show that the prediction model based on QGA-BP can be used to predict the paste pump outlet pressure, and the relative error is less than 8%, which can satisfy the engineering requirement .And compared with prediction model based on GA-BP(the genetic Algorithm BP neural network), The QGA-BP prediction model is better than GA-BP model in prediction accuracy and optimization time.

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Periodical:

Applied Mechanics and Materials (Volumes 336-338)

Pages:

722-727

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.336-338.722

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Online since:

July 2013

Authors:

Xue Cun Yang, Yuan Bin Hou, Ling Hong Kong

Keywords:

Blockage, Coal Slurry Pipeline, Pressure Prediction, QGA-Bp

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