The Automated Wheelset Test Rig, as shown in Figure 1 is a state-of-the-art solution for comprehensive inspection of railway wheelsets. Featuring precision and automation, the rig assesses wheelset profiles using advanced profiling techniques, enabling accurate wear and tear assessments.
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This work presents an automated train bogie inspection system using an Anchor-Free YOLOv8 model, achieving 10% higher accuracy than earlier methods. It enables real-time, manual-free detection and tracking of bogie parts to improve railway safety and reduce service disruptions.
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AI-powered Motor Condition Monitoring with infrared thermography enables early fault detection and predictive maintenance. It ensures higher efficiency, reduced downtime, and sustainable Industry 5.0 operations.
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This study introduces Muhafiz, a portable, automated track recording vehicle that uses axle-based acceleration for rail fault diagnosis. Compared to conventional push trolley systems, Muhafiz improves efficiency by 87%, reducing manual dependence and enhancing railway safety.
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A cost-efficient and portable solution for real-time railway track condition monitoring in Pakistan. Designed to enhance safety and reduce accidents through advanced image processing technology.
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