Dynamic tread wear measurement method for train wheels against vibrations

Dynamic tread wear measurement is difficult but significant for railway transportation safety and efficiency. The accuracy of existing methods is inclined to be affected by environmental vibrations since they are highly dependent on the accurate calibration of the relative pose between vision sensors. In this paper, we present a method to obtain full wheel profiles based on automatic registration of vision sensor data instead of traditional global calibrations. We adopt two structured light vision sensors to recover the inner and outer profiles of each wheel, and register them by the iterative closest point algorithm. Computer simulations show that the proposed method is insensitive to noises and relative pose vibrations. Static experiments demonstrate that our method has high accuracy and great repeatability. Dynamic experiments show that the measurement accuracy of our method is about 0.18 mm, which is a twofold improvement over traditional methods.