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| 基于ANFIS模糊神经网络的微钻头破损监测 | |
| 引用本文： | 孙艳红,杨兆军,李雪,张立新.基于ANFIS模糊神经网络的微钻头破损监测[J].润滑与密封,2006(11):66-68,70. |
| 作者姓名： | 孙艳红 杨兆军 李雪 张立新 |
| 作者单位： | 1. 吉林工程技术师范学院,吉林长春,130052;吉林大学,吉林长春,130025 2. 吉林大学,吉林长春,130025 3. 吉林工程技术师范学院,吉林长春,130052 |
| 摘 要： | 使用轴向力和扭矩信号监测微孔钻削过程，提出了基于ANFIS模糊神经网络作为微钻头破损状态监测模型。该模型能够较准确描述钻头破损和信号特征之间的非线性关系，和常用的BP神经网络相比，具有收敛速度快和局部学习能力等优点。实验结果表明：采用ANFIS模糊神经网络对提高微钻头监测的准确性非常有效。 |
| 关 键 词： | 微钻头 破损 ANFIS模糊神经网络 状态监测 |
| 文章编号： | 0254-0150（2006）11-066-3 |
| 收稿时间： | 2006-04-03 |
| 修稿时间： | 2006-04-03 |
Micro-drill Breakage Monitoring Based on ANFIS Fuzzy Neural Networks |
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| Sun Yanhong,Yang Zhaojun,Li Xue,Zhang Lixin.Micro-drill Breakage Monitoring Based on ANFIS Fuzzy Neural Networks[J].Lubrication Engineering,2006(11):66-68,70. | |
| Authors: | Sun Yanhong Yang Zhaojun Li Xue Zhang Lixin |
| Affiliation: | 1. Jilin Teachers Institute of Engineering and Technology, Changchun Jilin 130052, China; 2. Jilin University, Changchun Jilin 130025, China |
| Abstract: | Micro-role drilling process was monitored in thrust and torque signals, and ANFIS fuzzy neural networks were constructed, which describe the nonlinear relationship between signal feature and micro-drill breakage, and have the advantages of fast convergence rate and local learning ability comparing with BP neural networks, experiments validate that the rate of checking out micro-drills breakage is very high by using ANFIS fuzzy neural networks, and the system has practical value very well. |
| Keywords: | micro-drill breakage ANFIS fuzzy neural networks condition monitoring |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |