Blasting Vibration Monitoring and Analysis in Shallow Buried Tunnel Excavation

摘要：

In order to evaluate ground vibration from excavation blasting of shallow buried tunnels, a new PB neural network method for predicting blasting vibration is presented in this paper. . With a series of real-time measurements, the relationship between the peak particle velocity of blasting vibration and the scale distance was obtained in Taishan granite. Comparison of the realtime monitoring data with the results of various theoretical methods shows that our PB neural network method is much better than the traditional method . in predicting blasting vibration. Due to the fact that blasting vibration from shallow buried tunneling is quite different from those from other blasting methods, the characteristic frequency spectrum and the energy distribution of blasting vibration from shallow tunneling was also obtained by means of wavelet transformation analysis. Consequently, these method and analysis will provide a very useful tool in improving tunnel blasting and assuring the safety of buildings nearby.

关键词： tunneling blasting vibration PB neural network wavelet analysis

作者: LIN Congmou YANG Linde CUI Jihong

作者单位: Institute of Geotechnical Eng., Huaqiao University, Fujian Quanzhou, China;Dept. of Geotechnical Eng Dept. of Geotechnical Eng., Tongji University, Shanghai, China

会议类型: 国际会议

会议名称: The Asian-Pacific Symposium on Blasting Techniques(亚洲太平洋地区爆破技术研讨会)

会议地点: 昆明

会议语种:英文

页码: 488-491

在线出版日期: 2007-05-08（万方平台首次上网日期，不代表论文的发表时间）