From analyzing the constitution of thedust in coal tunneling face, the paper draws a conclusion that cutting dust is the basiccause effecting the dust in coal tunneling face.
本论文的论题选自国家自然科学基金项目“采掘机械截割粉尘的成因及控制方法的研究”。
By investigating and analyzing, quantitative relation between cutting dust on mechanized tunneling faces and affecting factors is established in the paper, through constructing a model of artificial neural network, dust density on the face is forecasted, which creates favorable conditions for making better roadheader design, reducing cutting dust to a minimum, improving the face env.
通过调研分析,建立了机掘工作面截割产生与其影响因素间的数量关系,通过组建人工神经网络模型,对工作面的粉尘浓度进行了预测,为改进机器设计,极大限度地降低截割粉尘,改善掘进工作面环境,提高掘进生产的安全性创造了有利的条件。