Material Conveying Automation Control System

An Intelligent Monitoring and Control System for Material Conveying Systems Based on AI Visual Recognition, Laser Profile Analysis, and Multi-sensor Fusion, which achieves all-round real-time perception of belt conveyor operating status, anomaly warning, and autonomous inspection, thereby enhancing the safety and operational efficiency of the conveying system.

Core System Architecture
Intelligent Control System for Belt Conveyor
Intelligent Foreign Object Monitoring: AI visual recognition algorithms and device interlock control
Intelligent blockage monitoring and adaptive speed regulation: Real-time traffic monitoring, mathematical logic models for material-blocking prediction, and closed-loop speed control
Intelligent pipe conveyor form (twisting/anti-wrapping) monitoring: Visual form analysis algorithm, multi-level alarm linkage mechanism
Intelligent roller rubber coating status monitoring: AI image recognition and defect feature database comparison

Belt Conveyor Intelligent Inspection System
Rail-based inspection technology for the data mid-end and digital twin operation and maintenance platform: integrates pan-tilt units, high-definition cameras, infrared thermal imagers, ultrasonic radars, etc.
Belt Surface Point Monitoring System: Specialized Optical Sensor Camera + Line Laser Profiling
Data Fusion Analysis Platform: Digital Twin Display, Operation and Maintenance Diagnosis, and Report Generation

Key Features
Intelligent Control Side
Implement foreign-object detection and interlocked emergency stop; provide graded alarms and shutdown for abnormal conveyor belt conditions.
Blockage prevention and automatic speed regulation based on a throughput model; AI-based identification of drum rubber-encapsulation defects.

Intelligent Inspection Side
It realizes all-weather autonomous inspection through rail-based inspection technology, integrating vision, infrared, and radar for equipment temperature measurement, positioning, and obstacle avoidance;
Fine diagnosis of surface defects such as belt corrosion and tearing is achieved through a dedicated point-scanning unit.
All data is aggregated to the digital twin platform for visualization and health analysis.

Performance Metrics
Foreign object identification accuracy ≥ 98%
Material-blocking early warning response time < 3 seconds
Rubber-coating defect detection accuracy at the millimeter level
Inspection robot positioning accuracy: ±10 mm
System availability: ≥99.5%
Adapt to the environment

-20°C to +60°C, IP66 protection, dust- and vibration-resistant