PANDAS-V®
Overhead Line Monitoring Impact Event Detection Capabilities
Faulty Dropper Wires
Droppers can fail very often; for instance, the ECML between Cambridge Junction and Stoke Junction reported an average of four dropper failures weekly in the year 2020. The impact of a single failure can be minor to very significant, often resulting in compounding delays to railway services. PANDAS-V® routinely provides rapid fault detection, identifying and reporting a wide range of faulty dropper wires with differing failure modes, ranging from mild damage to fully detached or broken.
Bird Strikes
Pantograph bird strikes are more than just a rare occurrence; they’re a real and frequent challenge that can cause damage ranging from mild to severe. Our pantograph camera provides precise impact detection, automatically recording and reporting bird strikes so stakeholders can evaluate damage and allocate resources effectively.
Slack Headspan Wire
In this incident, PANDAS-V® swiftly detected and reported a slack headspan wire minutes after the fault occurred. Without immediate remediation, this issue led to a dewirement within two hours of the initial fault detection. This highlights the importance of fast, automated overhead line fault detection to prevent escalation of faults.
Broken Branch Detection
Following a series of storms in the UK. PANDAS-V® has proven essential in overhead line fault detection, particularly in detecting broken brand impacts. During Storm Isha, PANDAS-V® detected a broken branch impacting the overhead catenary system and sent an automatic report to key stakeholders, enabling swift response measures.
Cross Contact Wire Detection
PANDAS-V® detected and reported a faulty cross contact wire within minutes of the fault occurring. Key stakeholders responded immediately, and measures were put in place to mitigate further damage. This capability reinforces how PANDAS-V® enhances fault detection across critical infrastructure.
Converging Wires
PANDAS-V® detects high impact loads as a result of converging overhead line wires. Converging wires often feature a change in height, leading to mild to severe impacts. PANDAS-V® provides accurate pantograph impact detection in these scenarios, ensuring faults are reported before they escalate.
Hard Spots
PANDAS-V® identifies hard spots within the rail catenary system, pinpointing the exact GPS location. For instance, the example above shows a hard spot caused by a registration arm that lacks vertical movement, creating a large impact every time a pantograph passes.
Broken Bridle
PANDAS-V® detected and reported a broken bridle wire within minutes. Key stakeholders responded immediately, and measures were put in place to mitigate further damage through accurate overhead line fault detection.
Benefits of using PANDAS-V®
Maximised Operational Efficiencies
Through preventative rather than reactive maintenance, operations and maintenance teams can plan, mobilise, and act as issues occur, supported by reliable rail fault detection insights.
Enhanced Safety
PANDAS-V® provides visibility of the entire network during live passenger service. Using these insights, supported by continuous monitoring from the onboard pantograph camera, prevents incidents associated with pantograph and overhead line defects exponentially increases the safety of the network, its passengers, and its workers.
Reduced Delays
Infrastructure faults and unplanned maintenance cause significant delays to the rail network, with dropper wires alone causing more than 10,000 minutes of delays in one region of the UK network. PANDAS-V® detects and automatically reports faults within one minute of occurrence, providing a vast impact on service reliability.
Reduced Costs
PANDAS-V® not only enhances safety and reliability but also offers a cost-effective solution for rail operators by reducing downtime, preventing costly repairs, and streamlining maintenance processes.
BETTER REPORTING
Automated reports and alerts, performance trends and management via an intuitive portal. This not only streamlines maintenance operations, but also enables strategic planning for long-term asset and infrastructure management.
BOOTS OFF BALLAST
With real-time AI analysis and remote monitoring, PANDAS-V® reduces boots on ballast, meaning maintenance personnel can respond proactively to issues without extensive on-site inspections, thereby minimising operational disruptions.
Want to know more?
Interested in learning how PANDAS-V® can transform your rail maintenance with real-time impact event detection and predictive AI? Get in touch with our team to explore how our cutting-edge technology can help you improve safety, reduce delays, and streamline maintenance. Fill out the form below, and we’ll get back to you promptly.
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