BL450 + IEPE + AI: Smart Prediction for Tunnel and Mine Safety
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BL450 + IEPE + AI Intelligent Prediction: Empowering Tunnel and Mine Safety Forecasting

AI-powered collapse prediction for tunnels and mines using BL450 + IEPE module. Real-time vibration data analysis with on-device AI ensures early warnings, no manual intervention, and high reliability in harsh environments. Redefining underground safety.
BL450 + IEPE + AI Intelligent Prediction: Empowering Tunnel and Mine Safety Forecasting
Case Details

Beilai introduces an AI-powered collapse prediction solution based on the BL450 platform.

Application Scenarios

  • Large-scale tunnel excavation

  • Underground coal mining

  • Subway construction sites

  • Geological disaster early-warning zones
 

Hardware Configuration

🔸 BL450 Main Controller Powered by Rockchip RK3588J processor with 6TOPS NPU, enabling real-time processing of multi-channel sensor data.

🔸 IEPE Module (Model Y37) Accurately captures rock resonance frequency signals. Supports 4-channel IEPE sensor input with strong anti-interference capability.

🔸 Industrial-grade Design Operates in extreme conditions from -40°C to +85°C. IP30-rated protection. Certified through GB/T electromagnetic compatibility and vibration tests—ideal for complex underground environments.

Implementation Workflow

  • Data Acquisition The IEPE module captures vibration signals in real time and transmits them via RS485 or high-speed USB to the BL450.
  • AI Inference Running on pre-installed Linux-RT, the system processes data using TensorFlow/PyTorch models, analyzing resonance features to output risk coefficients. 
  • Real-Time Alerting Results are pushed via MQTT to the monitoring center or on-site displays, triggering visual and audible alarms when necessary.

Solution Advantages

Fully Automated: Operates independently—ideal for high-risk environments

High Accuracy: Models trained with industrial data for superior adaptability

On-Device AI Inference: No cloud dependency, ultra-low latency

Modular Design: Easily expandable with customizable interfaces

Built for Harsh Conditions: Operates from -40°C to +85°C with IP30 protection

 Conclusion
The BL450 series ARM embedded computer, combined with an IEPE module and AI inference, offers a fully automated, high-precision, real-time collapse risk prediction solution—redefining safety standards in underground engineering.
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