Generative adversarial network for image segmentation of train wheelrail contact area
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TP391

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    Abstract:

    The open constraint condition between the train and the track determines the objective existence of the train derailment. Curve segmentation of the edge of wheelrail contact area is of great significance to the research of the train wheelrail contact relationship. In this paper, an algorithm for the curve segmentation of the edge of wheelrail contact area based on generative adversarial networks is proposed. By introducing the residual module into the generator network, the sensitivity of the network to output changes is enhanced, and the generator weight can be better adjusted. In addition, in order to effectively expand the receiving area of the feature map, the expansion residual module is introduced. The experimental results show that the accuracy of curve segmentation of the edge of wheelrail contact area reaches 9613% by improved generative adversarial networks, and the sensitivity, specificity, F1 value and area under the ROC curve is 8390%, 9713%, 8367% and 9812% respectively, which verify that this method can accurately segment the edge curve of the wheelrail contact area.

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  • Received:
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  • Online: June 08,2022
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