Signal and Information Processing

Diameter Control Technology of Ultra-fine Sutures Based on DMA and Improved GPC Algorithm

Expand
  • 1. School of Mechanical Engineering, Tianjin Polytechnic University, Tianjin 300387, China;
    2. Tianjin Key Laboratory of Advanced Mechatronics Equipment Technology, Tianjin Polytechnic University, Tianjin 300387, China

Received date: 2018-05-22

  Revised date: 2018-09-29

  Online published: 2019-05-31

Abstract

In order to solve the problem of suture diameter inhomogeneity caused by slow and imprecise wire diameter detection and uncontrollable forming process, a control system is designed by a rapid measurement and accurate control method. The system, based on the embedded system STM32, consists of a linearly coupled charge-coupled device (CCD) image sensor, 14-bit CCD signal processor AD9822, direct memory access (DMA), and improved adaptive generalized predictive control (GPC) algorithm. The suture samples satisfying the requirements of the 32th United States Pharmacopoeia Suture standard have been produced on the JK1601 spinning machine by the control system, and the uniformity of the wire diameter has increased from 74.6% to 95%.

Cite this article

WANG Deming, SUI Xiuwu, ZHANG Yang, WAN Kaixin, SHI Feng . Diameter Control Technology of Ultra-fine Sutures Based on DMA and Improved GPC Algorithm[J]. Journal of Applied Sciences, 2019 , 37(3) : 349 -358 . DOI: 10.3969/j.issn.0255-8297.2019.03.005

References

[1] 季益萍. 医用缝合线研究动态[J]. 产业用纺织品,2004(12):34-37. Ji Y P. Newest research and development of surgical suture[J]. Technical Textiles, 2004(12):34-37. (in Chinese)
[2] Sui X W, Wang D M. Application of self-adaptive generalized predictive control in the spinning process of absorbable suture[C]//International Conference on Imaging Systems and Techniques. IEEE, 2017:173-179.
[3] Christopher D, Swaminathan S, Sunita N. Suture materials-current and emerging trends[J]. Journal of Biomedical Materials Research, 2016, 104(6):1544-1559.
[4] 隋修武,王硕,李瑶. 胶原蛋白与壳聚糖可吸收缝合线成型的有限元分析与精确纺丝工艺参数控制[J]. 材料科学与工艺,2017, 25(1):84-91. Sui X U, Wang S, LI Y. Finite element analysis of collagen and chitosan absorbable suture forming and precision spinning process parameters control[J]. Materials Science and Technology, 2017, 25(1):84-91. (in Chinese)
[5] Wang W, Wang Z B. A technological research of high temperature float glass thickness untouch detection based on CCD sensor[J]. Journal of Computational Methods in Sciences and Engineering, 2015, 15(2):251-260.
[6] 童秋阶. 预测控制策略应用及其自控设计工作[J]. 石油化工自动化,2013(1):1-5. Tong Q J. Application of prediction control strategy and process control design work[J]. Automation in Petro-chemical Industry, 2013(1):1-5. (in Chinese)
[7] 曹秒,刘畅,林昀. 基于CCD成像自动对准技术的玻璃折射率测量系统研究[J]. 仪器仪表学报,2013, 34(11):2565-2571. Cao M, Liu C, Lin Y. Research on the glass refractive index measurement system based on CCD imaging self aligning technology[J]. Chinese Journal of Scientific Instrument, 2013, 34(11):2565-2571. (in Chinese)
[8] 付天舒,赵春晖. 基于Verilog的线阵CCD驱动时序设计[J]. 光学技术,2010, 36(5):740-743. Fu T S, Zhao C H. Design of linear CCD driving sequence based on Verilog[J]. Optical Technique, 2010, 36(5):740-743. (in Chinese)
[9] 徐美华, 樊裕乐, 李科. CCD图像采集系统的低功耗流水线ADC设计[J]. 微电子学与计算机, 2010, 27(7):164-167. Xu M H, Fan Y L, Li K. The design of low power dissipation pipeline ADC in CCD image processor[J]. Microelectronics & Computer, 2010, 27(7):164-167. (in Chinese)
[10] Beschi M, Berenguel M, Visioli A. On reduction of control effort in feedback linearization GPC strategy applied to a solar furnace[J]. Optimal Control Applications and Methods, 2016, 37(3):521-536.
[11] 田中大,高宪文,李琨. 网络控制系统的自适应预测控制[J]. 应用科学学报,2013, 31(3):303-308. Tian Z D, Gao X W, Li K. Adaptive predictive control of networked control system[J]. Journal of Applied Sciences, 2013, 31(3):303-308. (in Chinese)
[12] Margarita T, Lyubka D, Michail P. Implicit GPC based on semi-fuzzy neural network model[M].[S.l]:Springer International Publishing, 2015.
[13] 荀倩,王培良,李祖欣. 基于递推最小二乘法的永磁伺服系统参数辨识[J]. 电工技术学报,2016, 31(17):161-169. Xun Q, Wang P L, Li Z X. PMSM parameters identification based on recursive least square method[J]. Transactions of China Electrotechnical Society, 2016, 31(17):161-169. (in Chinese)
Outlines

/