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During operation, subway tunnel linings and track structures are subject to complex environments, leading to progressive defects that threaten operational safety. To address the limitations of conventional manual inspections, an integrated inspection system capable of simultaneous multi-defect detection at a speed of up to 15 km/h was developed. An image optimisation algorithm was constructed to enhance image quality while reducing data storage requirements. By integrating weighted defect indicators from both lining and track inspections, an evaluation framework for tunnel service condition was constructed based on cloud model theory. The proposed system and evaluation method were validated through application to Qingdao subway line 8, demonstrating their applicability in routine tunnel inspection and management.

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