论文部分内容阅读
目的论述刀具切削状态识别过程中存在的模糊问题及识别方法．方法对刀具切削状态模糊性进行理论分析，将模糊划分理论与神经网络识别方法相结合，给出神经网络非线性映射作用一般扩展原理的推论以及模糊模式识别及推理规则；结果对不同切削负载，给出相应模糊推理机制和模糊判别规则．结论用实例对比方法证明了刀具切削状态识别过程中存在的模糊性问题，以及所述方法的正确性、可靠性和实用性，为刀具切削状态智能识别奠定理论基础．
Aim To discuss the fuzzy problems and identification methods in the process of tool cutting status recognition. The method is applied to the theoretical analysis of the fuzziness of the cutting state of cutting tools. The fuzzy partition theory and the neural network identification method are combined to give the deduction of general extension principle of neural network nonlinear mapping and fuzzy pattern recognition and inference rules. The corresponding fuzzy inference mechanism and fuzzy rules are given. Conclusion The example comparison method is used to prove the fuzziness problem existing in the tool cutting status recognition, as well as the correctness, reliability and practicability of the method, and lay a theoretical foundation for the intelligent recognition of the cutting status of the tool.