Gap Measurement Method for Railway Switch Machines Based on the Fusion of Deep Vision and Geometric Features
Wenxuan Zhi, Qingsheng Feng, Shuai Xiao, Xilong He, Haowei Liu, Yiyang Zou, Hong Li · 2026
Read Gap Measurement Method for Railway Switch Machines Based on the Fusion of Deep Vision and Geometric Features by Wenxuan Zhi, Qingsheng Feng, Shuai Xiao, Xilong He, Haowei Liu, Yiyang Zou, Hong Li (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13259004.txt.
Description
Wenxuan Zhi and colleagues measure railway switch gaps by fusing deep vision with geometry in a 2026 study. Gap size reveals whether a turnout has locked correctly. Oil, glare, and vibration make ordinary camera measurement unstable in the field.
A detector first finds the gap region reliably. A segmentation network then maps soft edges, from which twenty geometric measures are built. A two stream network merges image features with those measures to estimate the gap. Field tests reached tiny average errors and passed every case within the industrial tolerance. Very dim light still degraded results, so added lighting may be needed.
Catalog record
| CREATOR | Wenxuan Zhi, Qingsheng Feng, Shuai Xiao, Xilong He, Haowei Liu, Yiyang Zou, Hong Li |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 65 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |