Railway wheels are one of the important parts of railway vehicles, and it is necessary to inspect their status frequently. To measure the wheel tread geometric parameters dynamically and accurately in a train running environment, a line-structured light vision sensor-based measurement system was demonstrated in this paper. In the system, a subpixel laser stripe centre extraction algorithm based on skeleton extraction, which can significantly reduce the interference of complex lighting environments in the field and greatly improve the extraction accuracy, was proposed. To further improve the measurement accuracy and stability, the influence of the eccentricity error caused by the dynamic measurement on the results was analyzed, a mathematical model was established, and the deformed profile was corrected. The system has been successfully applied to railway maintenance sections and has become a part of train safety inspection systems. Field tests were conducted to verify the performance of the system, and the results showed that the measurement accuracy and stability are marked improved after eccentric error correction, especially for the flange height and QR value.
By mimicking the human brain behavior, artificial neural systems offer the possibility to further improve computing efficiency and solve the von Neumann bottleneck. In particular, the neural system with perceptual...
Line-structured light has been widely used in the field of railway measurement, owing to its high capability of anti-interference, fast scanning speed and high accuracy. Traditional calibration methods of line-structured light sensors have the disadvantages of long calibration time and complicated calibration process, which is not suitable for railway field application. In this paper, a fast calibration method based on a self-developed calibration device was proposed. Compared with traditional methods, the calibration process is simplified and the calibration time is greatly shortened. This method does not need to extract light strips; thus, the influence of ambient light on the measurement is reduced. In addition, the calibration error resulting from the misalignment was corrected by epipolar constraint, and the calibration accuracy was improved. Calibration experiments in laboratory and field tests were conducted to verify the effectiveness of this method, and the results showed that the proposed method can achieve a better calibration accuracy compared to a traditional calibration method based on Zhang’s method.
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