探地雷达(Ground Penetrating Radar, GPR)作为一种非破坏性的电磁探测技术,已广泛应用于市政工程、交通、军事等领域的探测.复杂的地下环境中,电磁波传播规律变得复杂,背景介质的介电常数难以准确获得.后向投影(Back Projection,BP)成...探地雷达(Ground Penetrating Radar, GPR)作为一种非破坏性的电磁探测技术,已广泛应用于市政工程、交通、军事等领域的探测.复杂的地下环境中,电磁波传播规律变得复杂,背景介质的介电常数难以准确获得.后向投影(Back Projection,BP)成像算法需要预知背景介质的相对介电常数,且需逐个计算各成像网格的散射强度值,计算效率低.本文提出一种基于深度学习的探地雷达自聚焦后向投影(Deep learning based Auto focusing BP,DABP)成像方法,设计了目标感兴趣区域(Region Of Interest,ROI)的检测模块,基于地下目标的空间稀疏特征,将YOLOX网络和BP成像机理相结合,快速检测出目标潜在区域,仅对该区域中的成像网格进行成像处理,避免全域的后向投影计算,大幅降低运算量.其次,针对介电常数未知情况下BP成像难以聚焦的问题,设计了一个自聚焦后向投影(Auto Focusing BP,AF-BP)成像模块,构建了BS-YOLOv5网络和相应的数据集,实现基于改进二分法的地下介质介电常数估计和自聚焦成像.然后,设计了一个基于双阈值和积分聚焦的伪影抑制(artifact suppression based on Double Threshold and Integral Focusing,DTIF)模块,进一步提高成像结果的聚焦度.开展了仿真和实测数据的成像处理和对比分析,与BP成像方法相比,仿真数据成像结果的ISLR指标下降了250%、SCR指标提升了131%;实测数据成像结果的ISLR指标下降了322%、SCR指标提升了72%,仿真实验和实测实验的成像速度均提升了300%,验证了所提方法在提高GPR成像效率和成像质量方面的有效性.展开更多
In this paper,we discuss (1) whether a significant change in dominant creep mechanism will occur at 400 km discontinuity in some subducting slabs as a result of olivine-spinel phase transition;(2) could the result inf...In this paper,we discuss (1) whether a significant change in dominant creep mechanism will occur at 400 km discontinuity in some subducting slabs as a result of olivine-spinel phase transition;(2) could the result influence phase boundary strength and deep seismicity? Through this study,we noticed that a transition of creep mechanism from dislocation to diffusion (or superplasticity) could occur at the olivine-spinel phase boundary where temperature effect on phase transition dominates over pressure,which will result in a weakening phase boundary.Triggered by this phase transition weakening,a deep strong earthquake might be generated in the relatively strengthening region above the phase boundary so that the phase boundary is naturally the ceasing boundary of deep seismicity.Contrasting to this,the transition of the creep mechanism from dislocation glide to dislocation climb may be common at the phase boundary where pressure effect on phase transition dominates over temperature.In this case。展开更多
文摘探地雷达(Ground Penetrating Radar, GPR)作为一种非破坏性的电磁探测技术,已广泛应用于市政工程、交通、军事等领域的探测.复杂的地下环境中,电磁波传播规律变得复杂,背景介质的介电常数难以准确获得.后向投影(Back Projection,BP)成像算法需要预知背景介质的相对介电常数,且需逐个计算各成像网格的散射强度值,计算效率低.本文提出一种基于深度学习的探地雷达自聚焦后向投影(Deep learning based Auto focusing BP,DABP)成像方法,设计了目标感兴趣区域(Region Of Interest,ROI)的检测模块,基于地下目标的空间稀疏特征,将YOLOX网络和BP成像机理相结合,快速检测出目标潜在区域,仅对该区域中的成像网格进行成像处理,避免全域的后向投影计算,大幅降低运算量.其次,针对介电常数未知情况下BP成像难以聚焦的问题,设计了一个自聚焦后向投影(Auto Focusing BP,AF-BP)成像模块,构建了BS-YOLOv5网络和相应的数据集,实现基于改进二分法的地下介质介电常数估计和自聚焦成像.然后,设计了一个基于双阈值和积分聚焦的伪影抑制(artifact suppression based on Double Threshold and Integral Focusing,DTIF)模块,进一步提高成像结果的聚焦度.开展了仿真和实测数据的成像处理和对比分析,与BP成像方法相比,仿真数据成像结果的ISLR指标下降了250%、SCR指标提升了131%;实测数据成像结果的ISLR指标下降了322%、SCR指标提升了72%,仿真实验和实测实验的成像速度均提升了300%,验证了所提方法在提高GPR成像效率和成像质量方面的有效性.
文摘In this paper,we discuss (1) whether a significant change in dominant creep mechanism will occur at 400 km discontinuity in some subducting slabs as a result of olivine-spinel phase transition;(2) could the result influence phase boundary strength and deep seismicity? Through this study,we noticed that a transition of creep mechanism from dislocation to diffusion (or superplasticity) could occur at the olivine-spinel phase boundary where temperature effect on phase transition dominates over pressure,which will result in a weakening phase boundary.Triggered by this phase transition weakening,a deep strong earthquake might be generated in the relatively strengthening region above the phase boundary so that the phase boundary is naturally the ceasing boundary of deep seismicity.Contrasting to this,the transition of the creep mechanism from dislocation glide to dislocation climb may be common at the phase boundary where pressure effect on phase transition dominates over temperature.In this case。
