Dynamic tread wear measurement method for train wheels against vibrations

Area of Science:

• Railway Engineering
• Metrology
• Computer Vision

Background:

• Dynamic tread wear measurement is critical for railway safety and efficiency.
• Existing methods are susceptible to environmental vibrations and require precise sensor calibration.
• Accurate measurement of wheel profiles is essential for predictive maintenance.

Purpose of the Study:

• To develop a robust method for dynamic tread wear measurement insensitive to environmental vibrations.
• To improve the accuracy and repeatability of wheel profile measurements.
• To overcome limitations of traditional calibration-dependent methods.

Main Methods:

• Utilizing two structured light vision sensors to capture inner and outer wheel profiles.
• Employing the iterative closest point (ICP) algorithm for automatic registration of sensor data.
• Validating the method through computer simulations, static, and dynamic experiments.

Main Results:

• The proposed method demonstrates insensitivity to noise and relative pose vibrations.
• Static experiments confirm high accuracy and excellent repeatability.
• Dynamic experiments achieved a measurement accuracy of approximately 0.18 mm, a twofold improvement.

Conclusions:

• The developed automatic registration method offers a significant advancement in dynamic tread wear measurement.
• This technique enhances railway transportation safety and operational efficiency.
• The method provides a more reliable and accurate alternative to traditional approaches.