Vision method of inspecting missing fastening components in high-speed railway.

The increasing train speed on railways generates an urgent need for more powerful automatic inspection of railway tracks, including real-time fastening component inspection. To obtain better high-speed performance with lower cost, this paper has proposed a novel structured light method based on motion image (SLMMI) for moving object inspection. The motion images in the proposed method are insensitive to motion, abundant with information, and easy to process, resulting in a low performance requirement of the hardware. Compared to the conventional unstructured light method and structured light method, the proposed method inherits the virtues of both thus offering a fresh perspective when inspecting missing fastening components on high-speed railways. By using the SLMMI and the recognition method based on a neural network, the experimental results yield good performance in terms of speed and accuracy. Furthermore, the robustness of the proposed method is also discussed and simulated by adding typical interferences, such as ambient light, vibration, and obstacles.