Abstract
Train wheel sets must be periodically inspected for possible or actual premature failures and it is very significant to record the wear history for the full life of utilization of wheel sets. This means that an online measuring system could be of great benefit to overall process control. An online non-contact method for measuring a wheel set’s geometric parameters based on the opto-electronic measuring technique is presented in this paper. A charge coupled device (CCD) camera with a selected optical lens and a frame grabber was used to capture the image of the light profile of the wheel set illuminated by a linear laser. The analogue signals of the image were transformed into corresponding digital grey level values. The ‘mapping function method’ is used to transform an image pixel coordinate to a space coordinate. The images of wheel sets were captured when the train passed through the measuring system. The rim inside thickness and flange thickness were measured and analyzed. The spatial resolution of the whole image capturing system is about 0.33 mm. Theoretic and experimental results show that the online measurement system based on computer vision can meet wheel set measurement requirements.
Highlights
A railway wheel set is subject to normal wear due in large part to friction contact between the wheel set and the rails [1]
Feng et al [3] introduced a method to measure wheel set parameters based on laser displacement sensors
Zhang et al [6,7,8] developed opto-electronic measuring methods based on wavelet analysis denoising
Summary
A railway wheel set is subject to normal wear due in large part to friction contact between the wheel set and the rails [1]. When wear is severe, dressing or replacing must be applied to ensure the safety. This means that an online measuring system would be of great benefit to overall process control. Feng et al [3] introduced a method to measure wheel set parameters based on laser displacement sensors. Wu et al [4,5] presented theoretical methods to measure wheel sets’ diameters and defects online based on the image processing. Naumann et al [9] applied some opto-electronic sensors to measure wheel sets’ parameters, including the diameter, flange thickness, rim width, flange height and so on. Mian et al [10] measured wheel sets’ parameters with an opto-electronic system based on displacement sensors. Pagano et al [12] presented an ultrasonic real-time inspection system and method, which performed defect recognition on a trail wheel
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