Temperature Control at the Axle Boxes of Rolling Stock Using Thermal Imaging Technologies and Wireless Monitoring Systems

This paper presents the development of an autonomous temperature monitoring system for axle boxes in high-speed railway rolling stock. The proposed system integrates the KS UR-AI640 high-resolution thermal imager with LoRa and GSM (4G/5G) wireless communication technologies to enable real-time thermal control under harsh environmental conditions, including elevated temperatures and humidity. A two-level warning mechanism has been implemented: ALARM–1 (45°C–84°C) for early anomaly detection and ALARM–2 (>85°C) for critical overheating alerts. The processing and control units are based on the Raspberry Pi microcontroller, while autonomous operation is ensured through uninterruptible power supplies (UPS) and solar panels. Field tests demonstrated high reliability and measurement accuracy (error <0.05°C), as well as rapid alarm response time (<5 seconds). Comparative analysis with traditional systems such as HOT BOX and HARD revealed significant advantages in terms of precision, mobility, energy efficiency, and operational autonomy. The proposed solution reduced operating costs by up to 80% and enhanced rail transport safety. These results confirm the feasibility of implementing intelligent thermal monitoring in modern railway systems.

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