Intelligent detection of rail transit vehicle wheelsets combined with structured light technology

Real-time monitoring of rail transit vehicle wheelsets is of great significance to the stable operation and maintenance of packing vehicles. This paper aims to design a system that can accurately detect rail transit vehicle wheelsets in real time, improve the intelligent detection efficiency of rail transit vehicle wheelsets, and ensure the safety and efficiency of rail transit running. Aiming at the complex multi-line structured light (MLSL) fringe centre line extraction problem in the original image of the system, this paper studies the light fringe matching segmentation method based on blob analysis and the improved Steger centre line extraction algorithm. The test results show that the measurement accuracy of wheel diameter and rim width is ±0.2 mm, the measurement accuracy of rim width and height is ±0.25 mm, and the measurement error of QR value is less than 0.25 mm. The detection result curve of the system proposed basically coincides with the standard value, which shows that the measured results in this paper can be consistent with the standard value. Therefore, the system proposed provides some technical support for intelligent detection of rail transit vehicle wheelsets. The system proposed can also be extended to other rail transit industries.