Data processing for measuring tread contour of a train wheel based on computer vision

Qiancheng Zhao; Shanxi Deng; Yingfu Guo; Yongyue Yang

doi:10.1117/12.716319

13 October 2006 Data processing for measuring tread contour of a train wheel based on computer vision

Qiancheng Zhao, Shanxi Deng, Yingfu Guo, Yongyue Yang

Proceedings Volume 6280, Third International Symposium on Precision Mechanical Measurements; 628025 (2006) https://doi.org/10.1117/12.716319
Event: Third International Symposium on Precision Mechanical Measurements, 2006, Urumqi, China

Abstract

Dimension and form of a train wheel tread contour are the key controlled parameters in manufacturing and running process. Projecting laser light line to the tread contour, the left image and the right one of the light line in the measured countour are caught by using two CCD cameras. After calibrating the two images and other processing, the two images are pieced together to form a free-form curve. Measuring and data processing are completed in two steps as using "Bi-measurement Evaluation Test", the first step is modeling and the second is testing. Comparing the real coordinate values of Testing points with their theoretical ones reconstructed from the form model, the problem whether the model expresses the contour features enough can be resolved. If the answer is yes, the number and position distribution of sampling points are rational, then we can estimate the standard deviation (σ) of noise in the measuring sequence made up of coordinate values of sampling points. The fact that the standard deviation (σ) of noise in the real measuring sequence is about 0.1600mm is estimated by real measuring and data analysis.

Citation Download Citation

Qiancheng Zhao, Shanxi Deng, Yingfu Guo, and Yongyue Yang "Data processing for measuring tread contour of a train wheel based on computer vision", Proc. SPIE 6280, Third International Symposium on Precision Mechanical Measurements, 628025 (13 October 2006); https://doi.org/10.1117/12.716319

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KEYWORDS

Data processing

Image processing

Computer vision technology

Machine vision

Manufacturing

Error analysis

Calibration

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