AI for Rail Wheelset & Track Condition Monitoring |…

AI for Rail Wheelset & Track Condition Monitoring

Monitor wheelsets and track health with vibration, vision, and AI to prevent derailments, reduce delays, and optimize maintenance.

Wheel defects and track faults drive derailment risk and service disruption. AI uses vibration/AE sensors, wayside cameras, and onboard data to detect flats, spalls, misalignment, corrugation, and geometry issues early.

Substructure issues (ballast/formation) inferred from vibration.

Operations & Maintenance

Risk-based work orders; grinding/tamping scheduling.

live demo · related simulation● LIVE

Stream wayside/onboard sensors; time sync to wheelset ID/train.

Data quality, calibration, and sensor health checks.

Feature store keyed by asset/wheelset/track segment.

Frequently asked questions

How can I integrate existing computer vision detectors and CV models into mysimulator.uk, and label identified defects using the platform's maintenance outcomes?

Integrate existing detectors/CV; label defects with maintenance outcomes.

What steps should I take to train and validate defect classifiers, and how do I set appropriate severity thresholds for detected issues?

Train and validate defect classifiers; set severity thresholds.

How can I initiate alerts in advisory mode, and connect mysimulator.uk to existing work order systems for automated notifications?

Launch alerts in advisory mode; connect to work order systems.

What is the process of scaling coverage by refining risk scores, and how do I close the feedback loop with maintenance teams to improve future predictions?

Scale coverage; refine risk scores; close loop with maintenance feedback.

▶ Try it live

Everything above runs in your browser — open Hash Function Avalanche Visualizer and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Hash Function Avalanche Visualizer simulation