Abstract A new cyber-physical adaptive control system (CPACS) is presented for drilling hybrid stacks. A generalized approach for features recognition, and learning, of spindle power signals was developed for real-time detection of tool wear level. Subsequently, a high fidelity model predicts the drilling forces and the damage at the layers and interfaces of the stacked panel. The CPACS uses these predictions to maximize the feedrate while maintaining the damage-free force limit at each layer. The system communicates with the CNC machine controller to continuously update the drilling conditions. Validation test showed improved productivity and extended tool life while preserving part quality.

中文翻译：

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一种用于混合电堆钻孔的新型信息物理自适应控制系统

摘要 提出了一种新的信息物理自适应控制系统（CPACS）用于钻井混合堆。开发了一种通用的主轴功率信号特征识别和学习方法，用于实时检测刀具磨损水平。随后，高保真模型预测了钻孔力和堆叠面板的层和界面处的损坏。CPACS 使用这些预测来最大化进给率，同时保持每一层的无损伤力限制。系统与数控机床控制器通信，不断更新钻孔条件。验证测试表明，提高了生产率并延长了刀具寿命，同时保持了零件质量。