Online Images Detection for Pantograph Slide Abrasion

Pantograph slide abrasion is one of the key factors that affect urban rail transit vehicles current-collecting quality. In order to measure the abrasion value of pantograph slide in real time, an online-image detecting method was proposed in this paper based on a vehicle-mounted panoramic camera. First, the image preprocessing methods which include enhancement, horizontal correction and morphological processing were performed on pantograph slide in images. Then, a denoising method with wavelet transform and an adaptive threshold method with the Canny operator were used to detect the slide edge. After optimizing the bi-directional edge-growth method based on image gradient, the upper and lower edge of the pantograph slide was extracted by reduplicative detection. Finally, the slide's thickness and abrasion value could be got from the calculation of edges curve. Verified by online operation videos of TSG18G pantograph, results show that the detection method proposed in this paper can run fast enough to meet the requirement of real-time detection under the premise of boosting the accuracy of monitoring slide wear mutation.