Synchronous Acquisition Control System and Coordinate Correction Algorithm for Subway Tunnel Comprehensive Detection Equipment
Crack, cavity, and leakage defects in subway tunnels significantly threaten tunnel operational safety. Due to the limited detection time window, the trend in the tunnel detection has shifted toward using multiple types of devices for comprehensive and rapid detection. However, the varying working methods and data structures of these devices present a significant challenge in achieving synchronous acquisition control and obtaining high-precision positioning data. The author’s team proposed a comprehensive detection vehicle equipped with multiple devices. A synchronous acquisition control system was designed and developed based on the devices mounted on the detection vehicle. This system includes pulse signal processing, acquisition circuits, and corresponding software, enabling synchronous acquisition control and data association storage for different types of devices. To address the challenge of high-precision positioning of multisource heterogeneous data, a coordinate correction algorithm based on tunnel ring seam information was introduced. This algorithm significantly improves upon conventional tunnel positioning methods by positioning across different detection data, enhancing accuracy to the millimeter level. Through simulation experiments and field experiments in tunnels, the effectiveness of the synchronous acquisition control system and coordinate correction algorithm was verified. This method is particularly effective in long-distance detection, as it reduces cumulative mileage error and improves positioning accuracy. This study can provide effective technical support for the precise positioning of subway tunnel detection results and enhances the overall operational safety of subway tunnels.
Authors
- Xianlei Xu (ORCID: https://orcid.org/0000-0003-3934-2924)
- Xinyao He (ORCID: https://orcid.org/0000-0003-0217-9510)
- Donglin Zhou (ORCID: https://orcid.org/0000-0001-5987-646X)
- Jinglin Li (ORCID: https://orcid.org/0000-0002-8590-5487)
- Minghao Sun (ORCID: https://orcid.org/0000-0002-1657-0740)
Institutions
- China University of Mining and Technology (CN)
- Chinese Academy of Surveying and Mapping (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1109/jsen.2024.3496926
- Citations
- 3
- Primary Topic
- Advanced Decision-Making Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.34
Funders
- National Key Research and Development Program of China