Case Study – OLErt Video Analysis
Customer: Network Rail
The Challenge
Following a dewirement event at Proof House Junction in July 2025, Network Rail required support to better understand the conditions leading up to the incident.
The investigation was constrained by the available data:
- No dedicated measurement systems installed on the train
- Reliance on pantograph-mounted video footage
- Need to compare multiple train runs under similar conditions
- Difficulty extracting quantitative engineering insight from visual data
These challenges made it difficult to objectively assess pantograph–overhead line interaction and identify any contributing factors.
The Solution
Incremental applied its OLErt system to analyse existing pantograph video footage captured from Class 730 units operating over the affected section. OLErt uses computer vision and advanced processing techniques to convert video into structured engineering data, including:
- Pantograph height
- Contact wire stagger
- Dynamic interaction behaviour
By processing the footage frame-by-frame and aligning multiple datasets, OLErt enabled direct comparison between runs recorded before, during, and after the incident.
Implementation
The analysis was delivered as a targeted, post-incident study using existing data provided by Network Rail.
The approach included:
- Preparation and alignment of video datasets across multiple runs
- Application of OLErt analytics to extract key parameters
- Comparative analysis of pantograph performance across the same infrastructure section
- Identification of trends, anomalies, and areas of interest
This enabled a structured and repeatable assessment without requiring additional onboard instrumentation.
Results
The analysis provided clear, data-driven insight to support the investigation:
Consistent infrastructure performance
No statistically significant differences in pantograph height or overall behaviour were observed across runs, indicating no systemic issue within the OLE.
Identification of localised anomalies
Specific areas of interest were identified prior to the incident, including unusually large stagger values and subtle changes in pantograph dynamics.
Comparative performance insight
Analysis across multiple runs enabled differentiation between normal variation and behaviours specific to particular trains or conditions.
Customer Perspective
“Incremental’s analysis provided valuable, evidence-based insight that helped us better understand pantograph behaviour leading up to the incident.”
Network Rail
The Impact
This project demonstrated how OLErt can support rapid, data-driven incident investigation using existing onboard data. By transforming standard video footage into actionable engineering insight, OLErt enables:
- Faster understanding of complex incidents
- Evidence-based decision making
- Reduced reliance on dedicated measurement trains
Summary
The Network Rail study highlights the flexibility of OLErt as both a continuous monitoring system and a powerful analytical tool.
Even without prior deployment, OLErt was able to extract meaningful, engineering-grade insight from video data—supporting investigation, improving understanding, and helping inform future operational and maintenance decisions.
