The railway sector has undergone constant transformations due to technological advances and the need to optimize safety and operational efficiency. Automation and monitoring of track geometry are critical factors for reducing failures, increasing infrastructure durability and ensuring the reliability of the railway system. This project proposes the application of innovative solutions to improve the monitoring and predictive maintenance of railway tracks.
Objectives
Develop and implement an automated system for monitoring and analyzing railway track geometry, aiming to increase safety, reduce operating costs and improve maintenance efficiency.
Specific Objectives
- Implement sensors and measurement systems for real-time monitoring of track geometry.
- Use artificial intelligence and machine learning for predictive analysis of failures.
- Develop software for visualization and interpretation of collected data.
- Integrate the collected data into railway management systems.
Sensing and Data Collection
Sensors will be installed along the railway track and in inspection vehicles to capture information about alignment, leveling, gauge, rail wear and irregularities on the track.
Data Processing and Analysis
The collected data will be processed by Machine Learning algorithms, which will identify patterns and predict failures before they compromise railway operations.
Development of Monitoring Software
Software will be developed to analyze and visualize the collected data, allowing integration with railway maintenance and operation systems.
Testing and Validation
The system will be tested on a pilot railway section, with assessment of sensor accuracy, algorithm performance and impact on maintenance operations.
Expected Benefits
- Reduction of costs with corrective maintenance.
- Increased operational safety.
- Greater availability of railway infrastructure.
- Optimization of maintenance processes.
The implementation of automation technologies and analysis of railway track geometry will allow significant advances in railway operations, making the system safer and more efficient. This project represents an important step towards the modernization of the sector, promoting innovation and sustainability.