Railway roadbed blocking and protecting equipment service state evaluation method based on deep learning

The invention discloses a deep learning-based railway roadbed blocking and protecting equipment service state assessment method, and relates to the technical field of intelligent assessment of railway roadbed engineering disasters. The method comprises the following steps: acquiring a service state image of railway roadbed blocking and protecting equipment in a multi-source passing evaluation area; classifying the damage types; performing impurity removal processing on the acquired service state image of the railway roadbed protection equipment, and training the railway roadbed protection equipment damage type identification network model to perform damage type identification; clustering the identified damage types of the railway roadbed retaining and protecting equipment, and calculating the damage disease occupancy rate of the railway roadbed retaining and protecting equipment of various damage types; calculating a damage degree grade score of the railway roadbed protection equipment; calculating the diseas