Train wheel tread defect and out-of-roundness three-dimensional image pass-type detection system

Abstract

The invention discloses a train wheel tread defect and out-of-roundness three-dimensional image pass-type detection system. The system comprises an acquisition module, a speed measurement control module, a motor moving module and a data processing module, the motor moving module is fixed on track beds on two sides of a track, and the acquisition module and the speed measurement control module aremounted on the motor moving module. The acquisition module acquires a wheel tread profile in a process of synchronously moving with a wheel, and acquires one profile at a minimum interval of 1 mm through speed measurement detection control, and an image is compressed through a preprocessing module in the acquisition process, and then is transmitted to the image processing module in time; the speedmeasurement control module measures the wheel speed and provides the wheel speed for the motor moving module; the motor moving module drives a motor to work in time according to the signal of the speed measurement control module, so that the acquisition module moves in time and keeps consistent with the wheel advancing speed; and the data processing module processes the image data compressed by the acquisition module, synthesizes the image data into a three-dimensional image of the wheel tread, and calculates out-of-roundness and tread defects.

Description

technical field [0001] The invention relates to the field of on-line detection of rail transit wheels, and is a system capable of accurately detecting out-of-roundness of wheels and tread defects. Background technique [0002] Wheel out-of-roundness and tread defects are the main causes of wheel-rail vibration, and there is no good detection method at present. The existing wheel online detection system cannot detect out-of-roundness and tread defects when railway trains, especially high-speed EMU trains are put into storage. During manual inspection, the out-of-roundness cannot be seen, and since most of the wheels are covered, only the tread defects in one-third of the wheel area can be seen, which not only takes up the time when the train stops, but also cannot see all the wheels. [0003] The existing non-linear light source image direct shooting scheme cannot accurately detect the depth information and the image analysis is more difficult due to image deformation, and t...

AI Technical Summary

Problems solved by technology

The existing wheel online detection system cannot detect out-of-roundness and tread defects when railway trains, especially high-speed EMU trains enter the warehouse

During manual inspection, the out-of-roundness cannot be seen, and since most of the wheels are covered, only one-third of the wheel tread defects can be seen, which not only takes up the train’s stopping time, but also cannot see all the wheels.

[0003] The existing non-linear light source image direct shooting scheme cannot accurately detect the depth information and the image analysis is more difficult due to image deformation, and the detection accuracy is low. It can only be used by maintenance personnel for manual viewing, and cannot automatically alarm or false alarm. very high rate

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