Rao Xiaokang, Huang Shengxiang
School of Geodesy and Geomatics, Wuhan University, Wuhan, 430079, China.
Sci Rep. 2023 Aug 21;13(1):13557. doi: 10.1038/s41598-023-40728-y.
Blasting is widely used in mining, subway, demolition and groundwater-sealed tunnel, among them, the last one is widely concerned because of its many adjacent tunnels, high anti-seepage requirements, strict blasting control, etc. The identification of blasting characteristics is of great significance to the blasting construction and the safety evaluation of the groundwater-sealed tunnel. In view of the problem that conventional feature identification methods are less explored in groundwater-sealed tunnel, a complementary ensemble empirical mode decomposition with adaptive noise and multiscale permutation entropy and Hilbert-Huang transform (HHT) method was proposed. Then, the proposed method was verified by the numerical simulation and the Huangdao groundwater-sealed tunnel engineering. The results show that the proposed method can suppress modal aliasing and signal noise and identify the blasting characteristics of groundwater-sealed tunnel effectively. In addition, the blasting vibration energy which accounts for 94.7% in the frequency range of 0-200 Hz, 72.5% of 0-50 Hz was summarized. Furthermore, the safety status of each monitoring point was evaluated through HHT and the feasibility of millisecond blasting was identified. The method proposed can identify the vibration characteristics and safety status of groundwater-sealed tunnel from the perspective of time-frequency and energy effectively.
爆破广泛应用于采矿、地铁、拆除工程和地下水封洞库等领域，其中，地下水封洞库因其相邻巷道众多、防渗要求高、爆破控制严格等因素而备受关注。爆破特性的识别对于地下水封洞库的爆破施工及安全评价具有重要意义。针对传统特征识别方法在地下水封洞库中研究较少的问题，提出了一种基于自适应噪声的互补总体经验模态分解、多尺度排列熵和希尔伯特-黄变换（HHT）的方法。然后，通过数值模拟和黄岛地下水封洞库工程对所提方法进行验证性分析。结果表明，所提方法能够抑制模态混叠和信号噪声，有效识别地下水封洞库的爆破特性。此外，总结了爆破振动能量在0-200Hz频率范围内占比94.7%，在0-50Hz频率范围内占比72.5%。进一步通过HHT对各监测点的安全状态进行评估，确定了微差爆破的可行性。所提方法能够从时频和能量角度有效识别地下水封洞库的振动特性及安全状态。
