top of page
futuristic wire frame coal freight train dynamic motion background digital vector.jpg

Vision for the Future of Rail

Eyes on the Tracks: Precision Monitoring for Rail Safety 

Detect Predict Protect 

Overview

At Check Pass, we deliver state-of-the-art machine vision systems designed specifically for rail: robust, precise, and built for safety. Our wayside monitoring and defect detection solutions use high-resolution cameras, intelligent algorithms, and in-house engineering to detect faults in real time, reducing unplanned maintenance and improving fleet reliability. 

​

Combined with our pedigree in condition monitoring, vibration sensing and weighing (through our partnership with Qlar), we offer a complete suite of tools for infrastructure owners, rolling stock operators and maintenance teams to move from reactive to predictive maintenance. 

​

Keep your trains running safely, reliably, and cost-efficiently with machine vision solutions from Check Pass. 

• Real-time detection of defects / wear and tear before they escalate 
• Reduced downtime & maintenance costs through early alerts 
• Enhanced safety for passengers and staff via automated monitoring 
• Fully integrated condition monitoring — vibration, weight, vision — for holistic performance insights 

​

Because safety doesn’t take a break. Neither should your systems. 

 

Why Choose Check Pass Vision Systems: 

  • Precision & speed: detect defects at line speed, without stopping traffic 

  • Local expertise: in-house design, local field support across Australia 

  • Agile: Built as a start-up with decades of rail experience 

  • Full spectrum monitoring: vision + vibration + weighing to cover all risk vectors 

  • Scalable & future-ready: modular systems, AI-driven analytics, seamless integration 

Detect and Assess

Is it there? Is it missing? 

  • E.g. bolts, pins, links, cables, damage 

Rail wagon bogie with machine vision object detection

Measure it’s size, speed. 

  • Defect size 

  • Spring Height 

  • Door Speed – Mech/Elec condition 

 

Has it changed? 

  • Is there new damage? 

  • Is the known damage getting worse? 

  • Component wear. 

Object Detection Example

Counting wheels and checking all axle bolts are present.

bottom of page