Research on the "shape-performance-control" integrated digital twin system for boom-type roadheaders.

Area of Science:

• * Mining Engineering
• * Mechanical Engineering
• * Computer Science

Background:

• * Roadheaders are vital for coal mining, but real-time performance monitoring and adaptive cutting are challenging.
• * Dynamic cutting processes require advanced solutions for operational efficiency and safety.

Purpose of the Study:

• * To develop a digital twin system for boom-type roadheaders.
• * To integrate shape, performance, and control elements for enhanced functionality.
• * To enable real-time monitoring and adaptive cutting in dynamic mining environments.

Main Methods:

• * A three-component system: physical space, service space, and twin space.
• * Service space utilizes numerical simulation, AI, and data fusion for twin and control models.
• * Physical space employs robot kinematics and sensor data transmission; twin space uses rendering engines and 3D modeling.

Main Results:

• * Digital twin system achieved an average absolute error of 10.38 MPa for strain gauge data.
• * Real-time stress monitoring with an average update interval of 0.34 seconds.
• * Adaptive control model adjusted swing speed in approximately 0.3 seconds, enhancing cutting capabilities.

Conclusions:

• * The digital twin system provides accurate real-time mechanical performance prediction and monitoring.
• * Enhanced adaptive cutting capabilities improve roadheader efficiency in complex formations.
• * The system prevents damage from overload and optimizes dynamic cutting processes.