工矿自动化2018，Vol.44Issue(6)：35-39,5.DOI:10.13272/j.issn.1671-251x.2017110060
煤巷顶板稳定性评价方法研究
Research on roof stability assessment method of coal roadway
耿越 1段迎娟 1任家敏1
作者信息
- 1. 中国矿业大学(北京)机电与信息工程学院,北京 100083
- 折叠
摘要
Abstract
Existing roof stability assessment methods of coal roadway were summarized and analyzed,which included single index method and compound index method in classic methods and supervised learning method and unsupervised learning method in machine learning methods.It was pointed out that the classic methods assessed roof by single index or for a certain type of coal rock so that assessment result is incomplete or unreliable,and the machine learning method needed a large number of hand-crafted labeling of roof monitoring data with large workload and poor actual application effect.A new roof stability assessment mode of coal roadway based on generative adversarial network in deep learning was proposed according to advantage of extracting features from roof monitoring data automatically of the deep learningmethod,so as to decrease labor workload.关键词
煤巷/围岩/顶板稳定性评价/机器学习/深度学习/生成对抗网络Key words
coal roadway/surrounding rock/roof stability assessment/machine learning/deep learning/generative adversarial network分类
矿业与冶金引用本文复制引用
耿越,段迎娟,任家敏..煤巷顶板稳定性评价方法研究[J].工矿自动化,2018,44(6):35-39,5.
