Field-validated wireless vertical graphene sensors for autonomous crack and leakage monitoring in metro tunnels
Year: 2026
Type: article
Abstract: Simultaneous and autonomous monitoring of crack evolution and water leakage in operational tunnels remains challenging, particularly under non-intrusive installation constraints. This study presents a physics-guided vertical graphene (VG) sensing framework for the continuous and quantitative monitoring of both deterioration processes. A VG strain sensor was developed and characterised using a physically interpretable three-stage resistance–strain constitutive model governed by microcrack evolution within an island–bridge conductive network. The same VG-based transduction principle was extended to leakage monitoring through the incorporation of a superabsorbent polymer (SAP) layer, which converts water ingress into deformation-induced resistance changes. Laboratory tests demonstrated stable sensing responses under monotonic, cyclic, and sustained loading conditions, with bounded hysteresis and limited baseline drift. The sensing components were integrated with a low-power Sub-GHz wireless platform for continuous, cable-free data acquisition in confined tunnel environments. A three-month field deployment in an operational metro tunnel demonstrated the field applicability of the framework by capturing quasi-static crack evolution, including an opening of approximately 0.53 mm, and quantifying low-rate leakage at approximately 1 mL/day. By converting resistance measurements into physically interpretable engineering quantities, including crack-opening displacement and leakage volume, the proposed framework provides continuous condition information for quantitative tunnel assessment and may support future condition-informed maintenance planning. These results demonstrate the feasibility of non-intrusive wireless VG sensing for operational tunnel monitoring, although longer-term, multi-site validation is required to assess durability and broader applicability.
Authors: Shu Yuan, Chengyu Hong
Institutions: UNSW Sydney, Shenzhen University
Language: English
Subfield: Pollution
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,820
OpenAlex ID: W7221703638