【作者】 赵维刚； 杜彦良； 刘明月；

【Author】 Zhao Weigang~1, Du Yanliang~1, Liu Mingyue~2(1 Structural Health Monitoring and Control Institute & 2 Research Institute of National Defense Communication, Shijiazhuang Railway Institute, Shijiazhuang 050043, China)

【机构】 石家庄铁道学院大型结构诊断与健康监测研究所； 石家庄铁道学院国防交通研究所；

【摘要】 本文基于掘进机施工技术发展的要求,主要进行了全断面掘进机掘进状况的分类识别研究。首先分析了全断面隧道掘进机施工采集数据的特性并提出了相应的预处理方法;在特征提取的基础上采用无监督模式识别技术进行掘进机掘进状况分类识别,成功地进行了掘进状况的判别和掘进模式的建立。对于今后掘进机施工的快速、高效掘进与科学管理以及设计制造的国产化研究具有重要意义。更多还原

【Abstract】 In order to adapt the developing requirements of construction technology of TBM, the paper has accomplished the pattern recognition of full face TBM boring performance. At the first, we analyze the characters of the spot boring datum and put forward the signal pre—processing methods. As well as on the basis of the different clustering features extracting, applying the unsupervised pattern recognition to the classification of TBM boring performance, at last finished this work and established the mode of boring. So the work and result of this paper is helpful to realize the TBM high efficiency and rapid boring, and provides a new methods of processing and using the field boring datum.更多还原