Positioning of the Moving and Static Contacts of the Switch Machine Based on Double-Layer Mask R-CNN
Author(s) -
Jiacheng Yin,
Zhaomin Lv,
Xingjie Chen,
Kun Yang
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/8655499
Subject(s) - computer science , robustness (evolution) , artificial intelligence , computer vision , machine vision , position (finance) , measure (data warehouse) , robot , simulation , biochemistry , chemistry , finance , database , economics , gene
With the continuous development of rail transit, the maintenance of the switch machine becomes more and more important, and the contact depth of the moving contact and static contact in the switch machine is a key part of it. At present, the manual measurement method is the main measure of contact depth, which has the problems of low efficiency and strong subjectivity. The measurement of contact depth based on machine vision includes two steps: moving and static contact positioning and distance conversion. The positioning result will have an important impact on distance measurement. Therefore, a positioning method for moving and static contact based on double-layer Mask R-CNN (DLM) is proposed in this paper: first, the moving contact is roughly positioned by Mask R-CNN to obtain the predicted target area; second, the subgraph of the target area is preprocessed; finally, the precise positioning is used to determine the precise position of the moving and static contact. The accuracy and robustness of the proposed DLM are verified by the internal image of the switch machine.
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