A review of detection technology for structural diseases in metro shield tunnels

The structural health of subway shield tunnels is directly related to the safety of urban operations. In this paper, we systematically analyze the multi-dimensional interactive causes of water seepage, cracks, misalignments, etc., and review the limitations of mainstream inspection techniques in depth: fiber optic sensing is expensive and complicated to install; 3D laser scanning is difficult to detect internal defects; infrared thermography is insufficient to identify the deep-seated defects; geo-radar (GPR) interpretation is highly dependent on experience; methods based on dynamical properties (VMD) are susceptible to interference from ambient noise; deep learning requires massive labeled data and has limited generalization capability. The core bottleneck is that a single technology cannot meet the demand for accurate sensing of the whole life cycle and multi-dimensional diseases. The breakthrough direction requires the construction of a multi-source heterogeneous data fusion framework-integrating apparent scanning (laser/infrared), internal detection, distributed response (fiber optic), overall dynamic characteristics (vibration) and environmental parameters, and eliminating information silos through a unified spatial and temporal reference. Synchronized development of intelligent decision-making models coupled with physical mechanisms and data-driven (fusion of digital twins and Bayesian updating), realizing a three-level leap from passive detection to active warning to condition assessment to optimized maintenance decision-making. The collaborative innovation of multi-source perception and intelligent decision-making is the fundamental path to overcome the problem of hidden disease diagnosis and realize the double optimization of safety and operation and maintenance efficiency.