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RailFOD23: A dataset for foreign object detection on railroad transmission lines
Zhichao Chen1,2, Jie Yang3,4, Zhicheng Feng1,2
1Department of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou, Jiangxi Province, 341000, China.
Scientific Data
|January 16, 2024
Summary
This study introduces a novel dataset for detecting foreign objects on railroad power lines, synthesized using AI. It evaluates mainstream models, offering insights for improved railway infrastructure monitoring and maintenance.
Area of Science:
- Computer Vision
- Artificial Intelligence
- Railway Engineering
Background:
- Effective monitoring of railroad infrastructure relies on AI for analyzing image data of foreign objects on power lines.
- Limited public datasets and data sharing challenges hinder the development of robust foreign object detection models for railways.
Purpose of the Study:
- To present a new, synthesized dataset of foreign objects on railroad transmission lines.
- To evaluate the performance of mainstream object detection models within this specific railway context.
Main Methods:
- Leveraging large-scale AI models like ChatGPT (Chat Generative Pre-trained Transformer) and text-to-image generation to synthesize foreign object data.
- Creating a dataset comprising 14,615 images with 40,541 annotated objects, covering four common foreign objects.
- Empirical evaluation of various baseline object detection models using the synthesized dataset.
Main Results:
- The study validates the performance of several baseline models for foreign object detection on railroad transmission lines.
- The synthesized dataset provides a valuable resource for training and testing AI models in this domain.
- Performance metrics offer insights into the effectiveness of current models for railway infrastructure monitoring.
Conclusions:
- The developed dataset and model evaluations offer significant contributions to the field of railway infrastructure safety.
- The findings provide practical insights for enhancing the monitoring and maintenance of railroad facilities using AI.
- This research addresses the data scarcity issue, paving the way for more reliable AI-driven railway inspection systems.
