Abstract: With the continuous improvement of railway train operation safety requirements, it is urgent to detect and deal with hidden dangers in train operation in time. The traditional automatic detection method of railway train operation was mainly based on machine vision algorithm, which had the problems of poor adaptability to complex natural scenes and high false alarm rate. In order to solve the problem of low detection accuracy of traditional methods, multi-layer neural network transmission structure was simulated, where hidden trouble scanning materials were input and identified, and a train operation safety detection method based on deep learning algorithm was proposed. Then, a simulation experiment is carried out to verify the relevant algorithm by taking the detection of foreign matter as an example. The results show that the new detection method can reduce the false alarm rate under the premise of ensuring the detection rate.

Key words: train, safety inspection, deep learning, confusion matrix, iteration