网站首页期刊简介编委会过刊目录投稿指南广告合作征订与发行联系我们English
热冲压生产中的长周期智能控制
英文标题:Longperiod intelligent control in hot stamping production
作者:王梁 苏志同 安兴运 张宜生 王义林 朱彬 
单位:1. 华中科技大学   2. 青岛科捷机器人有限公司 3. 武汉中誉鼎力智能科技有限公司 
关键词:超高强钢 热冲压 长周期控制 生产控制 信息物理系统 
分类号:TG306
出版年,卷(期):页码:2020,45(7):128-131
摘要:

 以超高强钢热冲压生产过程中温度的变化为研究对象,为了提升热冲压零件的稳定性、降低温度变化对零件性能的影响,提出了一种通用的长周期智能控制模型,并聚焦热冲压生产中的长周期因素,基于信息物理系统的传感数据,采用在线长周期智能控制方法,对热冲压成形工艺的模具温度和冷却水温度进行优化控制。通过在生产线中构建传感器网络,并对模具温度和冷却水温度进行监测和主动调节,长周期智能控制方法不仅实现了模具温度和冷却水温度的优化控制,还能够将生产节拍智能调整到较为合理的数值,是一种有效的动态控制方法。长周期智能控制是对现有热冲压生产控制系统的有益补充。

 

 For the change of temperature during the hot stamping production process of ultra-high-strength steel, in order to improve the stability of hot stamped parts and reduce the influences of temperature changes on the performance of parts, a general long-period intelligent control model was proposed, and the long-period factors in hot stamping production were focused on. Based on the sensing data from cyber-physical system, the die temperature and the cooling water temperature in the hot stamping process were optimally controlled by the on-line long-period intelligent control method. Through building a sensor network in the production line and monitoring and actively adjusting the die temperature and the cooling water temperature, the long-period intelligent control method not only realized the optimal control of the die temperature and the cooling water temperature, but also intelligently adjusted the production cycle to a more reasonable value, which was an effective dynamic control method. Thus, the long-period intelligent control is a useful supplement to the existing hot stamping production control system.

基金项目:
国家科技重大专项(2018ZX04023001);国家自然科学基金资助项目(U1760205)
作者简介:
王梁(1987-),男,博士,助理研究员 E-mail:wangliang@hust.edu.cn 通讯作者:张宜生(1951-),男,硕士,教授 E-mail:zhangys@mail.hust.edu.cn
参考文献:

 [1]Ma M T, Zhang Y S, Song L F, et al. Research and progress of hot stamping in China [J]. Advanced Materials Research, 2014, 1063:151-168.


[2]张宜生, 王子健, 王梁. 高强钢热冲压成形工艺及装备进展[J]. 塑性工程学报, 2018, 25(5): 11-23.


Zhang Y S, Wang Z J, Wang L. Progress in hot stamping process and equipment for high strength steel sheet [J]. Journal of Plasticity Engineering, 2018, 25(5):11-23.


[3]Garrett R P, Lin J, Dean T A. Solution heat treatment and cold die quenching in forming AA6xxx sheet components: Feasibility study [J]. Advanced Materials Research, 2005, 6-8:673-680.


[4]Wang L, Zhu B, Wang Q, et al. Production control and optimization of hot stamping line [A]. Proceedings of 5th International Conference on Hot Sheet Metal Forming of Highperformance Steel[C]. Toronto2015.


[5]Wang L, Zhu B, Wang Q, et al. Modeling of hot stamping process procedure based on finite state machine (FSM) [J]. The International Journal of Advanced Manufacturing Technology, 2017, 89(1-4):857-868.


[6]Liu Y, Zhu Z, Wang Z, et al. Flow and friction behaviors of 6061 aluminum alloy at elevated temperatures and hot stamping of a Bpillar [J]. Int.J.Adv.Manuf.Technol.,2018,96:4063-4083.


[7]Zhou J, Li P G, Zhou Y H, et al. Toward newgeneration intelligent manufacturing [J]. Engineering, 2018, 4(1): 11-20.


[8]蔡潇雨. 基于MES实时数据采集与控制系统的研究与设计[D]. 上海: 上海交通大学, 2012.


Cai X Y. Research and Design on Realtime Data Acquisition and Control System Based on MES [D]. Shanghai: Shanghai Jiao Tong University, 2012.


[9]Allwood J M, Duncan S R, Cao J, et al. Closedloop control of product properties in metal forming [J]. CIRP AnnalsManufacturing Technology, 2016, 65(2):573-596.


[10]胡维. DCDC变换器切换系统模型的N周期控制及稳定性[D]. 广州:华南理工大学, 2017.


Hu W. Ncycle Control and Stability of DCDC Converters Based on Switched Systems Models [D]. Guangzhou: South China University of Technology, 2017.


[11]陆顾新, 黄道平, 王永庆, . 长周期非自衡系统预测控制研究[J].计算机测量与控制, 2003,(9): 671-672,682.


Lu G X, Huang D P, Wang Y Q, et al. Study on predictive control of multiperiod nonselfregulating system [J]. Computer Measurement & Control, 2003,(9): 671-672,682.


[12]Liu J J. Multiperiod production control in a centralized fully flexible manufacturing system [J]. European Journal of Operational Research, 1992, 56(1):107-118.


[13]Haoues M, Mouss K N, Dahane M, et al. Production planning in integrated maintenance context for multiperiod multiproduct failureprone singlemachine[A]. IEEE 18th Conference on Emerging Technologies & Factory Automation[C]. Cagliari:2013.

服务与反馈:
文章下载】【加入收藏
《锻压技术》编辑部版权所有

中国机械工业联合会主管  中国机械总院集团北京机电研究所有限公司 中国机械工程学会主办
联系地址:北京市海淀区学清路18号 邮编:100083
电话:+86-010-82415085 传真:+86-010-62920652
E-mail: fst@263.net(稿件) dyjsjournal@163.com(广告)
京ICP备07007000号-9