Improved ultrasonic differentiation model for structural coal types based on neural network

被引：0
|
作者：
TIAN Zi-jian1
机构：
来源：
International Journal of Mining Science and Technology | 2009年 / 19卷 / 02期
基金：
中国国家自然科学基金;
关键词：
ultrasonic; structural coal types; BP neural network; coal ultrasonic attenuation coefficient; coal ultrasonic speed;
D O I：
暂无
中图分类号：
TD713 [煤（岩石）与瓦斯突出的预防和处理];
学科分类号：
081903 ;
摘要：
In order to solve the difficulty of detailed recognition of subdivisions of structural coal types,a differentiation model that combines BP neural network with an ultrasonic reflection method is proposed.Structural coal types are recognized based on a suitable consideration of ultrasonic speed,an ultrasonic attenuation coefficient,characteristics of ultrasonic transmission and other parameters relating to structural coal types.We have focused on a computational model of ultrasonic speed,attenuation coefficient in coal and differentiation algorithm of structural coal types based on a BP neural network.Experiments demonstrate that the model can distinguish structural coal types effectively.It is important for the improved ultrasonic differentiation model to predict coal and gas outbursts.
引用
收藏
页码：199 / 204
页数：6
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