Intelligent Management and Control of Crushing Equipment in Gold Ore Beneficiation

1. Introduction

Current intelligent technologies in metal mines have gradually covered excavation, transportation, and beneficiation processes. However, the complexity of ore beneficiation equipment and insufficient data modeling remain challenges. Although a gold mine achieved full-process automation, gaps exist in equipment coordination and intelligent regulation. This paper discusses the specific solutions and outcomes of intelligent transformation in its crushing system.

2. Overview of Crushing Process

The system includes coarse crushing, medium/fine crushing, and closed-circuit screening:

Coarse Crushing: Underground ore is fed to a jaw crusher via a vibrating feeder, then conveyed to screening.

Medium/Fine Crushing: A double-deck screen directs materials to HP300 (medium) and HP500 (fine) cone crushers.

Closed Circuit: Crushed products return to the screen via conveyors, ensuring particle size compliance.

3. Key Intelligent Technologies

3.1 Intelligent Start-Stop Control

One-Touch Operation: Centralized remote control enables sequential start-stop, minimizing manual intervention.

Fault Handling: Real-time monitoring pauses upstream equipment upon failure and triggers alarms.

Mode Switching: Flexible "remote" and "local" control modes support maintenance and emergencies.

3.2 Process Monitoring and Protection

Conveyor Protection: Detects deviations, slippage, tears, and triggers emergency stops.

Equipment Health Monitoring: Analyzes vibration and current data to predict failures.

Motor Overload Protection: Prevents damage by monitoring real-time current.

3.3 Image Recognition

Foreign Object Detection: Cameras on conveyors identify metal debris and trigger alarms.

Particle Size Analysis: Monitors ore size, adjusts parameters to stabilize production quality.

3.4 Operational Optimization

Bin Level Control: Radar sensors optimize start-stop cycles, reducing energy consumption.

Discharge Port Warning: Calculates ore ratios via belt scales to detect abnormal discharge.

Parameter Adjustment: Dynamically regulates feed rates based on vibration and power data.

4. Implementation Results

Efficiency: Effective operation time increased by 15% through intelligent scheduling.

Cost Reduction: Energy consumption decreased by 10%, saving RMB 120,000 annually.

Environmental Benefits: Dust concentration reduced by 90%, enhancing safety.

Management: Data-driven decisions support maintenance and production planning.

5. Conclusion

The intelligent transformation achieved efficient, safe, and low-consumption closed-loop management. Further integration of big data and AI will advance mine intelligence to higher levels.