Research on multimodal techniques for arc detection in railway systems with limited data
Southwest Jiaotong University · Institute for Systems Engineering and Computers · +1 more institution
Abstract
The pantograph–catenary system is a critical component of railway vehicles, and its performance directly affects the quality of current collection. Accurately measuring the arcing rate is essential for monitoring the system’s condition and ensuring safe operation. However, traditional arc detection methods are prone to increased false detection rates and reduced measurement accuracy in complex railway environments due to the diversity of arc sizes and shapes, environmental interference, instability in current collection, and power fluctuations. While deep learning-based methods can effectively address environmental interference, obtaining sufficient labeled training data is challenging because arc events occur…
Citation impact
- FWCI
- 43.12
- Percentile
- 100%
- References
- 61
Authors
9Topics & keywords
- Computer science
- Arc (geometry)
- Data science
- Systems engineering
- Engineering
- Mechanical engineering
Funding
- NNNational Natural Science Foundation of ChinaAwards: Grant No. 52302444, Grant No. 52202424
- NSNatural Science Foundation of Sichuan ProvinceAwards: Grant No. 2022NSFSC1873, Grant No. 2024NSFSC0908
- NKNational Key Research and Development Program of ChinaAward: Grant No. 2021YFB340070402
- FRFundamental Research Funds for the Central UniversitiesAward: Grant No. 2682023GF012
- BABasic and Applied Basic Research Foundation of Guangdong ProvinceAward: Grant No. 2023A1515011230