Abstract: This study addresses typical defects observed during long-term operation of the Liangjiashan heavy-haul railway tunnel, including lining cracks, water leakage, and subgrade mud pumping, by proposing an integrated tunnel defect diagnosis method based on multi-source data fusion from geological and structural perspectives. The methodology systematically combines geological survey analysis, historical seismic data, 3D laser scanning of surface defects, ground-penetrating radar detection of lining quality, concrete strength testing, permeable groundwater analysis, core drilling verification, historical maintenance records, and manual inspections to perform comprehensive correlation analysis of defect characteristics, development patterns, and causative factors, thereby providing a scientific basis for systematic tunnel rehabilitation. Diagnostic results classify the tunnel's deterioration level as Grade AA, with proposed countermeasures including valley drainage, radial grouting reinforcement, crack repair,drainage system optimization, and implementation of an intelligent monitoring system.