Detecting internal defects,particularly voids behind linings,is critical for ensuring the structural integrity of aging high-speed rail(HSR)tunnel networks.While ground-penetrating radar(GPR)is widely employed,systema...Detecting internal defects,particularly voids behind linings,is critical for ensuring the structural integrity of aging high-speed rail(HSR)tunnel networks.While ground-penetrating radar(GPR)is widely employed,systematic quantification of performance boundaries for air-coupled(A-CGPR)and ground-coupled(G-CGPR)systems within the complex electromagnetic environment of multilayer reinforced HSR tunnels remains limited.This study establishes physics-based quantitative performance limits for A-CGPR and G-CGPR through rigorously validated GPRMax finite-difference time-domain(FDTD)simulations and comprehensive field validation over a 300 m operational HSR tunnel section.Key performance metrics were quantified as functions of:(a)detection distance(A-CGPR:2.0–4.5 m;G-CGPR:≤0.1 m),(b)antenna frequency(A-CGPR:300 MHz;G-CGPR:400/900 MHz),(c)reinforcement configuration(unreinforced,single-layer,multilayer rebar),and(d)void geometry(axial length:0.1–1.0 m;radial depth:0.1–0.5 m).Key findings demonstrate:a.A-CGPR(300 MHz):Reliably detects axial voids≥0.3 m at distances≤3 m in minimally reinforced(single-layer rebar)linings(field R2=0.89).Performance degrades significantly at distances>3 m(>60%signal attenuation at 4.5 m)or under multilayer rebar interference,causing 25%–40%accuracy loss for voids<0.3 m.Optimal distance:2.0–2.5 m.b.G-CGPR(900 MHz):Achieves<5%size measurement error for axial voids≥0.1 m and radial voids≥0.2 m in unreinforced linings.Resolution degrades under multilayer reinforcement due to severe signal attenuation,increasing axial void detection error to 10%–20%for voids≥0.3 m and constraining radial size measurement.c.Synergistic Framework:A hybrid inspection protocol is proposed,integrating A-CGPR(20 km/h)for rapid large-area screening and targeted G-CGPR(3 km/h)for high-resolution verification of identified anomalies.This framework enhances NDT efficiency while reducing estimated lifecycle inspection costs by 34%compared to G-CGPR alone.This research provides the first physics-derived quantitative detection thresholds for A-CGPR and G-CGPR in multi-rebar HSR tunnels,validated through field-correlated simulations.Future work will focus on multi-frequency antenna arrays and deep learning algorithms to mitigate reinforcement interference.The established performance boundaries and hybrid framework offer critical guidance for optimizing tunnel lining inspection strategies in extensive HSR networks.展开更多
基金funded by the Key Project of Science&Technology Research ofChina Academy of Railway Sciences,grant number 2023YJ022.
文摘Detecting internal defects,particularly voids behind linings,is critical for ensuring the structural integrity of aging high-speed rail(HSR)tunnel networks.While ground-penetrating radar(GPR)is widely employed,systematic quantification of performance boundaries for air-coupled(A-CGPR)and ground-coupled(G-CGPR)systems within the complex electromagnetic environment of multilayer reinforced HSR tunnels remains limited.This study establishes physics-based quantitative performance limits for A-CGPR and G-CGPR through rigorously validated GPRMax finite-difference time-domain(FDTD)simulations and comprehensive field validation over a 300 m operational HSR tunnel section.Key performance metrics were quantified as functions of:(a)detection distance(A-CGPR:2.0–4.5 m;G-CGPR:≤0.1 m),(b)antenna frequency(A-CGPR:300 MHz;G-CGPR:400/900 MHz),(c)reinforcement configuration(unreinforced,single-layer,multilayer rebar),and(d)void geometry(axial length:0.1–1.0 m;radial depth:0.1–0.5 m).Key findings demonstrate:a.A-CGPR(300 MHz):Reliably detects axial voids≥0.3 m at distances≤3 m in minimally reinforced(single-layer rebar)linings(field R2=0.89).Performance degrades significantly at distances>3 m(>60%signal attenuation at 4.5 m)or under multilayer rebar interference,causing 25%–40%accuracy loss for voids<0.3 m.Optimal distance:2.0–2.5 m.b.G-CGPR(900 MHz):Achieves<5%size measurement error for axial voids≥0.1 m and radial voids≥0.2 m in unreinforced linings.Resolution degrades under multilayer reinforcement due to severe signal attenuation,increasing axial void detection error to 10%–20%for voids≥0.3 m and constraining radial size measurement.c.Synergistic Framework:A hybrid inspection protocol is proposed,integrating A-CGPR(20 km/h)for rapid large-area screening and targeted G-CGPR(3 km/h)for high-resolution verification of identified anomalies.This framework enhances NDT efficiency while reducing estimated lifecycle inspection costs by 34%compared to G-CGPR alone.This research provides the first physics-derived quantitative detection thresholds for A-CGPR and G-CGPR in multi-rebar HSR tunnels,validated through field-correlated simulations.Future work will focus on multi-frequency antenna arrays and deep learning algorithms to mitigate reinforcement interference.The established performance boundaries and hybrid framework offer critical guidance for optimizing tunnel lining inspection strategies in extensive HSR networks.
