冲床保护装置的人手与坯料神经网络分类器模型  

Classification model of man-hand and billet based on BP algorithm in safety protector for puncher

作　　者：孙伟东[1] 袁昌明[2] 王强[2] 蒋庆[2] 

机构地区：[1]上海理工大学光学与电子工程学院,上海200093 [2]中国计量学院计量技术工程学院,浙江杭州310018

出　　处：《机电工程》2007年第3期67-70,共4页Journal of Mechanical & Electrical Engineering

基　　金：中国计量学院科技发展基金资助项目(XZ0513)

摘　　要：为建立冲压作业过程中人手与坯料的神经网络分类器模型,以解决冲压时不能连续进料的问题,采用了BP算法对人手和坯料的温度数据对进行训练,并利用样本估计其错误率小于4%。实验结果表明,此BP分类器模型结构简单,错误率低,对冲压设备智能安全保护装置的研究有很好的指导作用。In order to construct a neural network classifier of man-hand and billet in stamping process of factory, datasets of temperature of man-hand and billet was trained with BP algorithm. Error rate was estimated with sample estimation and it was up to less than 4%. Experimental results show the classifier is simple and effectively reduce computation burden. The model can guide the study of the intelligent protection against safety accident in the process of stamping.

关 键 词：冲床 BP算法 分类器模型 样本估计 错误率 

分 类 号：TP271[自动化与计算机技术—检测技术与自动化装置]