High-Accuracy On-Site Measurement of Wheel Tread Geometric Parameters by Line-Structured Light Vision Sensor

Abstract

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.

Keywords

• Sensor systems and applications
• railway safety
• measurement