为有效解决地铁隧道表观病害检测车的适用性和病害识别的精准性问题，以A市轨道交通B线为例，采用隧道表观病害检测车开展表观病害数据采集、处理、分析和健康评估，并从检测效率、检测精度和病害识别率3个方面，将设备检测结果与人工检测结果对比分析。结果表明： 1）该隧道表观病害以裂缝为主，约占65%，渗漏水和剥落掉块占比相对较小； 2）裂缝最大宽度主要集中在0.2~0.5 mm，裂缝最长达3.7 m，剥落掉块面积基本在0.04 m2内，二者健康度以2级为主；渗漏水面积集中在0~0.5 m2，健康度评定为1级； 3）与人工检测相比，设备检测优势明显，大幅提高检测速度，节约人工71%，病害总体识别率达到928%，可检测出0.2 mm以上宽度的裂缝，以及1 cm2以上面积的渗漏水和剥落掉块，大幅提高表观病害检测质量和效率，节约隧道养护成本。并根据表观病害检测结果提出地铁隧道合理化维修建议。

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.