To effectively solve the problems of applicability of surface defect detection equipment and accuracy of defect identification in metro tunnel, a case study is conducted on the rail transit line B of City A. The surface defect detection vehicle is adopted to carry out surface defect data collection, processing, analysis, and health assessment. The detection results of equipment and manual detection are compared and analyzed from three aspects of detection efficiency, detection accuracy, and defect identification rate. The results show the following: (1) The surface defects are mainly cracks, accounting for approximately 65%, and the proportion of water leakage and spalling is relatively small. (2) The maximum width of cracks is mainly concentrated between 0.2 mm and 0.5 mm, the maximum length of cracks is 3.7 m, and the area of spalling blocks is basically within 0.04 m2, whose health degree is mainly grade 2. The leakage area is concentrated in the range of 0~0.5 m2, the defect is rated as grade 1. (3) Compared with manual detection, the equipment detection is superior, which can greatly increase the detection speed, save the labor consumption by 71%, reach an overall defect recognition rate of 92.8%, and detect the cracks with a width of 0.2 mm or more as well as the leakage and spalling of more than 1 cm2, greatly improving the quality and efficiency of surface defect detection, and saving the tunnel maintenance costs. Finally, reasonable maintenance suggestions are put forward according to the surface defect detection results.