摘要
对柔性制造系统 (FMS)质量控制技术的重要工具——质量控制图的模式识别问题进行了深入的研究 ,提出了一种基于神经网络的质量控制图模式识别的方法 ,实现了质量控制图的自动识别。该方法具有结构简单、识别能力强、训练时间短的特点 ,经过训练的神经网络能够识别质量控制图的 6种基本模式 ,并给出仿真结果。
The quality control chart is the main tool of quality control in FMS. The pattern recognition of the quality control chart using neural network is presented. Thus the pattern recognition of the quality control chart can be implemented automatically. The configuration of the neural network is more simple, the capability of recognition is more powerful and training time is less. The six basic patterns can be quickly identified by this approach. The simulation results are given in this paper.
出处
《机械与电子》
2001年第1期41-44,共4页
Machinery & Electronics
关键词
柔性制造系统
神经网络
模式识别
质量控制图
flexible manufacturing system
neural network
pattern recognition
quality control chart
