基于人工神经网络的轮胎硫化自适应控制  

Adaptive control on the tire vulcanization based on artificial neural net

作　　者：刘伟峰[1] 刘川来[2] 段利亚[2] 

机构地区：[1]青岛航空工程学院青岛分院,山东青岛266041 [2]青岛科技大学自动化与电子工程学院,山东青岛266042

出　　处：《轮胎工业》2008年第3期172-174,共3页Tire Industry

基　　金：国家信息产业部基金项目(20044792)

摘　　要：在对24.00-35 42PR工程机械轮胎进行硫化测温的基础上,基于人工神经网络对厚橡胶制品内部温度建模,并应用模型参考自适应控制方案对厚橡胶制品进行等效硫化控制。采用自适应等效硫化控制方案并采取变温硫化与长时间低温硫化相结合的措施可有效改善传统硫化方法的过硫和欠硫现象,大大提高厚橡胶制品的物理性能。The model of describing inner temperature field of thick rubber products was established based on artificial neural net and experimental results of the measured temperatures of 24. 00-35 42PR OTR tire during vulcanization. The model was applied in the adaptive control of the equivalent curing of thick rubber products. By using the adaptive equivalent curing control, combined with non-isothermal curing and long time curing at low temperature, the possibility of over or under vulcanization was reduced effectively, and the physical properties of thick rubber products were improved significantly.

关 键 词：硫化测温 人工神经网络 自适应控制 等效硫化 

分 类 号：TQ330.4[化学工程—橡胶工业]