The Dynamic Control of Railway Power Systems (DCRPS) conference continues to be one of the most important events for experts working on railway electrification and infrastructure monitoring. This year, PANTOhealth CEO Farzad Vesali participated once again in the conference, presenting new research developed in collaboration with Leipziger Verkehrsbetriebe (LVB).
The presentation focused on a key challenge faced by urban rail operators: detecting infrastructure defects early enough to prevent service disruptions and costly emergency maintenance.
Detecting Overhead Line Defects Using Signal-Based Analysis
The research presented at DCRPS explored a signal-based approach to detecting features and defects in tram overhead contact lines within urban DC railway networks.
The study, titled:
“Signal-based Feature and Defect Detection for Predictive Maintenance of Tram Overhead Lines in Urban DC Networks”
demonstrates how pantograph acceleration signals and infrastructure measurements can be used to identify abnormalities in overhead line equipment.
When a pantograph interacts with components of the overhead contact line system, it generates measurable vibration and acceleration patterns. By analyzing these signals, it becomes possible to identify:
- infrastructure features such as section insulators or clamps
- irregularities in contact wire geometry
- potential defects that could develop into operational problems
This approach allows operators to move beyond traditional periodic inspections and toward continuous, data-driven monitoring of overhead line infrastructure.
Collaboration with Leipziger Verkehrsbetriebe
The research was carried out in collaboration with Leipziger Verkehrsbetriebe, the public transport operator serving the city of Leipzig.
Urban tram networks present unique monitoring challenges. Unlike high-speed rail environments, dense city networks operate under frequent stops, varying speeds, and complex infrastructure layouts. These conditions make accurate defect detection both more difficult and more valuable.
Through the collaboration with LVB, PANTOhealth was able to test and refine its signal analysis methods in a real operational environment, improving the reliability of predictive insights.
Toward Predictive Maintenance for Urban Rail
Traditional infrastructure inspection methods often rely on manual inspections or systems that generate large volumes of false positives, increasing operational workload for maintenance teams.
By combining signal analysis, data processing, and AI-driven interpretation, PANTOhealth aims to help operators:
- detect infrastructure degradation earlier
- reduce false alarms
- optimize maintenance planning
- improve service reliability
This research represents another step toward making predictive maintenance practical for urban rail networks.
Engaging with the Rail Innovation Community
Events like DCRPS provide an important platform for collaboration between researchers, operators, and technology developers working to improve railway systems.
PANTOhealth is proud to contribute to these discussions and to share real-world research results developed together with rail operators.
As urban rail systems continue to grow in importance for sustainable transportation, advanced monitoring and predictive maintenance technologies will play a critical role in keeping networks reliable and safe.
Learn More
To learn more about PANTOhealth’s predictive maintenance solutions for rail infrastructure, visit:
