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Tunnel Micro-deformation Monitoring Method Based on Improved PS-InSAR and Its Geophysical Application Analysis
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作者 meng-wei han Gu-hua Pu +9 位作者 Jin-zhuang Wang Zi-heng Gao Xiao-qian Yang Bo Zhang Ba-he Yang Jun Ma Hai-yun Wang Yong-can Chen Xi-can Zhao Wei-jian Liu 《Applied Geophysics》 2026年第1期152-161,429,共11页
Tunnel deformation is a direct manifestation of the stress redistribution of rock and soil masses,and high-precision monitoring of it is an important challenge in the eld of geophysical engineering.This study applies ... Tunnel deformation is a direct manifestation of the stress redistribution of rock and soil masses,and high-precision monitoring of it is an important challenge in the eld of geophysical engineering.This study applies the improved PS-InSAR technology to tunnel deformation monitoring,overcoming the limitations of traditional methods(such as total stations)with limited spatial coverage and poor continuity.Four core innovations enable millimeter-level precision breakthroughs:adaptive quality map fusion of coherence coefficientγand phase derivative variance for dynamic reliable area partitioning;branch-cutting method optimization using residual point clustering and Canny forbidden-zone constraints reduces invalid paths by 40%while suppressing lining joint phase jumps;dynamic weighted least squares(WLS)model integrating weighted coherence with blast disturbance gradient achieves 52%high-frequency noise suppression and precise separation of short-period construction disturbance signals;3D integral correction introduces DEM dynamic calibration projection coefcient k(improving by 30%in curved sections),reducing axial projection error from 15%-30%to<5%.In the Yunnan Amai Tunnel eld test,spatial resolution reaches 0.1m in sensitive zones with deformation inversion error<5%,successfully capturing instantaneous blasting deformation(0.46-0.49mm)and structural trend displacement at the face.The monitoring accuracy is more than three times higher than traditional methods,providing reliable technical support for safety warnings in high-risk sections. 展开更多
关键词 Persistent Scatterer Interferometric Synthetic Aperture Radar(PS-InSAR) Adaptive Quality Map Branch-Cutting Method Optimization Dynamic Weighted Least Squares(WLS)Model 3D Integral Correction Tunnel Deformation Monitoring Geophysical Application
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Research on design and prediction model of tunnel safety micro-deformation radar monitoring system
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作者 Zi-heng Gao Gu-hua Pu +9 位作者 Jin-zhuang Wang meng-wei han Qiang He Xiao-long Wang Jian-bo Yang Xiao-yu Yin Jia-gui Duan Liang Bao Xi-can Zhao Wei-jian Liu 《Applied Geophysics》 2026年第1期138-151,429,共15页
Tunnel micro-deformation is a progressive mechanical response process of geotechnical media under the influence of stress redistribution,environmental loads,material aging and other factors.Its millimeterlevel dynamic... Tunnel micro-deformation is a progressive mechanical response process of geotechnical media under the influence of stress redistribution,environmental loads,material aging and other factors.Its millimeterlevel dynamic evolution is difcult to eectively capture by traditional monitoring technologies.Based on the physical mechanism of microwave remote sensing,this paper uses Ground-Based Synthetic Aperture Radar(GB-SAR)for continuous,non-contact deformation perception of tunnel structures.The system transmits and receives coherent electromagnetic wave signals,and extracts millimeter-level even sub-millimeter-level deformation information by means of dierential interferometry technology.Combined with typical tunnel engineering cases,the study verifies the monitoring stability and reliability of the system under different geological conditions and complex environments.The results show that the system can realize real-time,highprecision monitoring of the full-section deformation eld of tunnels with high early warning accuracy and strong environmental adaptability,providing an effective geophysical technical means for tunnel structure health diagnosis and safe operation and maintenance. 展开更多
关键词 Highway Tunnel Ground-Based Synthetic Aperture Radar(GB-SAR) Prediction Model Microwave Remote Sensing Geophysical Monitoring
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