Prediction Method of Coal Dust Explosion Flame Propagation Characteristics Based on Principal Component Analysis and BP Neural Network

被引：13
|
作者：
Liu, Tianqi [1 ]
Cai, Zhixin [1 ]
Wang, Ning [1 ]
Jia, Ruiheng [1 ]
Tian, Weiye [1 ]
机构：
[1] Shenyang Aerosp Univ, Sch Safety Engn, Shenyang 110136, Liaoning, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2022年 / 2022卷
基金：
中国国家自然科学基金;
关键词：
SEDIMENT TRANSPORT; AIR MIXTURES; BEHAVIORS; MECHANISM; MODEL; PIPE;
D O I：
10.1155/2022/5078134
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
To study the flame propagation characteristics of coal dust explosion, principal component analysis and BP neural network are used to predict the farthest distance and the maximum speed of flame propagation. Among the eight influencing factors of flame propagation characteristics, three principal components are extracted and named "the factor of volatility," "the factor of intermediate diameter," and "the factor of environmental temperature." By using BP neural network, it is found that the minimum prediction error of the farthest distance of flame propagation is 2.4%, and the minimum prediction error of the maximum speed of flame propagation is 0.4%, which also proves the necessity of principal component analysis by comparing the prediction errors. The research results provide a theoretical method for predicting the flame propagation characteristics of coal dust explosion.
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页数：8
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