一种数控机床及基于深度学习的自适应控制系统
By integrating multi-axis robotic arms, modular machining heads, and deep learning systems into CNC machine tools, the machine tool status can be monitored and optimized in real time. This solves the problem of insufficient adaptability of traditional CNC machine tools, realizes efficient and automated machining control and fault prediction, and improves production efficiency and quality.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XIAMEN DINGYUN SOFTWARE
- Filing Date
- 2023-11-07
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional CNC machine tools cannot adapt to changes in workpiece material, tool condition, or processing environment, resulting in decreased processing accuracy, low production efficiency, reliance on manual operation and difficulty in optimization, and insufficient data utilization.
It employs a multi-axis robotic arm, a modular machining head, a data collection module, a deep learning processing unit, and a machine tool controller, combined with multiple sensors to monitor the machine tool status in real time, and performs adaptive control and optimization through a deep learning model.
It enables machine tools to adaptively adjust, predict and prevent faults, optimize production processes, reduce the impact of human factors, improve processing quality and efficiency, and reduce costs.
Smart Images
Figure CN117348528B_ABST