Paper
12 January 2018 Online measurement for geometrical parameters of wheel set based on structure light and CUDA parallel processing
Kaihua Wu, Zhencheng Shao, Nian Chen, Wenjie Wang
Author Affiliations +
Abstract
The wearing degree of the wheel set tread is one of the main factors that influence the safety and stability of running train. Geometrical parameters mainly include flange thickness and flange height. Line structure laser light was projected on the wheel tread surface. The geometrical parameters can be deduced from the profile image. An online image acquisition system was designed based on asynchronous reset of CCD and CUDA parallel processing unit. The image acquisition was fulfilled by hardware interrupt mode. A high efficiency parallel segmentation algorithm based on CUDA was proposed. The algorithm firstly divides the image into smaller squares, and extracts the squares of the target by fusion of k_means and STING clustering image segmentation algorithm. Segmentation time is less than 0.97ms. A considerable acceleration ratio compared with the CPU serial calculation was obtained, which greatly improved the real-time image processing capacity. When wheel set was running in a limited speed, the system placed alone railway line can measure the geometrical parameters automatically. The maximum measuring speed is 120km/h.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kaihua Wu, Zhencheng Shao, Nian Chen, and Wenjie Wang "Online measurement for geometrical parameters of wheel set based on structure light and CUDA parallel processing", Proc. SPIE 10621, 2017 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 106211Z (12 January 2018); https://doi.org/10.1117/12.2295595
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KEYWORDS
Image segmentation

Image processing

Image acquisition

Image processing algorithms and systems

Parallel processing

Detection and tracking algorithms

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