基于NSGA-Ⅱ的离体皮肤组织激光融合工艺参数的多目标优化
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摘要
以激光功率、激光脉冲频率、扫描速度为优化变量,建立了激光离体皮肤组织融合工艺参数的多目标优化模型。基于MATLAB软件,应用第二代非支配排序遗传算法(NSGA-Ⅱ)寻求帕累托最优解集,得到了最优工艺参数,分析了优化目标对工艺参数变化的响应灵敏度。在优化的工艺参数下,测试了切口黏结强度,分析了微观组织。结果表明:切口黏结强度对激光工艺参数具有更高的灵敏度,激光功率对切口黏结强度、组织峰值温度的影响比较显著;所提优化工艺可以实现离体皮肤组织的全层融合,在组织峰值温度降低的情况下,离体皮肤组织切口的黏结强度比单目标优化结果提高了5.6%。
By selecting laser power, laser pulse frequency and scanning speed as optimization variables, we establish a multi-objective optimization model of laser closure process parameters in vitro skin tissue. Based on MATLAB software, we use second generation non-dominant sequencing genetic algorithm(NSGA-II) to find the Pareto optimal solution set, obtain the optimal process parameters, and then analyze the response sensitivity of optimization objectives to the variation of process parameters. Under the optimized process parameters, the tensile strength of the incision is tested and the microstructure is analyzed. The results show that the incision tensile strength has high sensitivity to the laser process parameters, and the laser power has significant effect on the incision tensile strength and the tissue peak temperature. The proposed optimized process can achieve the in vitro skin tissue closure in full-thickness. In the case of tissue peak temperature decreasing, the tensile strength of in vitro skin tissue incision is 5.6% higher than that of single-objective optimization.
By selecting laser power, laser pulse frequency and scanning speed as optimization variables, we establish a multi-objective optimization model of laser closure process parameters in vitro skin tissue. Based on MATLAB software, we use second generation non-dominant sequencing genetic algorithm(NSGA-II) to find the Pareto optimal solution set, obtain the optimal process parameters, and then analyze the response sensitivity of optimization objectives to the variation of process parameters. Under the optimized process parameters, the tensile strength of the incision is tested and the microstructure is analyzed. The results show that the incision tensile strength has high sensitivity to the laser process parameters, and the laser power has significant effect on the incision tensile strength and the tissue peak temperature. The proposed optimized process can achieve the in vitro skin tissue closure in full-thickness. In the case of tissue peak temperature decreasing, the tensile strength of in vitro skin tissue incision is 5.6% higher than that of single-objective optimization.
引文
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[15] Jonasson T H, Zancan R, de Oliveira Azevedo L, et al. Effects of low-level laser therapy and platelet concentrate on bone repair: histological, histomorphometric, immunohistochemical, and radiographic study[J]. Journal of Cranio-Maxillofacial Surgery, 2017, 45(11): 1846-1853.
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[18] Nóbrega S, Coelho P J. A parametric study of thermal therapy of skin tissue[J]. Journal of Thermal Biology, 2017, 63: 92-103.
[2] Tripathi P B, Nelson J S, Wong B J. Posttraumatic laser treatment of soft tissue injury[J]. Facial Plastic Surgery Clinics of North America, 2017, 25(4): 617-628.
[3] Leclère F M, Schoofs M, Vogt P, et al. 1950-nm diode laser-assisted microanastomoses (LAMA): an innovative surgical tool for hand surgery emergencies[J]. Lasers in Medical Science, 2015, 30(4): 1269-1273.
[4] Belfort M, Bateni Z, Haydel D M, et al. Evaluation of the effects of laser tissue welding on the spinal cord and skin in a 30 day study of simulated spina bifida repair in rabbits[J]. American Journal of Obstetrics and Gynecology, 2017, 216(1): S60.
[5] Vincelette R, Noojin G D, Harbert C A, et al. Porcine skin damage thresholds for 0.6 to 9.5 cm beam diameters from 1070-nm continuous-wave infrared laser radiation[J]. Journal of Biomedical Optics, 2014, 19(3): 035007.
[6] Sudhagar S, Sakthivel M, Mathew P J, et al. A multi criteria decision making approach for process improvement in friction stir welding of aluminum alloy [J]. Measurement, 2017, 108: 1-8.
[7] Yan W, Zhang H, Jiang Z G, et al. Multi-objective optimization of arc welding parameters: the trade-offs between energy and thermal efficiency[J]. Journal of Cleaner Production, 2017, 140: 1842-1849.
[8] Shao Q, Xu T, Yoshino T, et al. Multi-objective optimization of gas metal arc welding parameters and sequences for low-carbon steel (Q345D) T-joints[J]. Journal of Iron and Steel Research, International, 2017, 24(5): 544-555.
[9] Saha A, Mondal S C. Multi-objective optimization of manual metal arc welding process parameters for nano-structured hardfacing material using hybrid approach[J]. Measurement, 2017, 102: 80-89.
[10] Yang Y, Cao L C, Zhou Q, et al. Multi-objective process parameters optimization of Laser-magnetic hybrid welding combining Kriging and NSGA-II[J]. Robotics and Computer-Integrated Manufacturing, 2018, 49: 253-262.
[11] Jiang P, Wang CC, Zhou Q, et al. Optimization of laser welding process parameters of stainless steel 316L using FEM, Kriging and NSGA-II[J]. Advances in Engineering Software, 2016, 99: 147-160.
[12] Cao L C, Yang Y, Jiang P, et al. Optimization of processing parameters of AISI 316L laser welding influenced by external magnetic field combining RBFNN and GA[J]. Results in Physics, 2017, 7: 1329-1338.
[13] Liu Q M, Huang J, Wang K H, et al. Multivariate nonlinear regression model of laser fusion in vitro skin incision performance based on RSM[J]. Chinese Journal of Lasers, 2018, 45(8): 0807002. 刘其蒙, 黄俊, 王克鸿, 等. 基于响应面法的离体皮肤组织激光融合切口性能多元非线性回归模型[J].中国激光, 2018, 45(8): 0807002.
[14] Huang J, Li C, Wang K H,et al. Laser welding characteristics of biological tissue in vitro[J]. Chinese Journal of Lasers, 2017, 44(4): 0407001. 黄俊, 李聪, 王克鸿, 等. 离体生物组织激光焊接特性实验研究[J]. 中国激光, 2017, 44(4): 0407001.
[15] Jonasson T H, Zancan R, de Oliveira Azevedo L, et al. Effects of low-level laser therapy and platelet concentrate on bone repair: histological, histomorphometric, immunohistochemical, and radiographic study[J]. Journal of Cranio-Maxillofacial Surgery, 2017, 45(11): 1846-1853.
[16] Zhou Q, Yang Y, Jiang P, et al. A multi-fidelity information fusion metamodeling assisted laser beam welding process parameter optimization approach[J]. Advances in Engineering Software, 2017, 110: 85-97.
[17] Li C, Wang K H, Huang J. Simulation of the effect of spot size on temperature field and weld forming in laser tissue welding[J]. Optik, 2018, 155: 315-323.
[18] Nóbrega S, Coelho P J. A parametric study of thermal therapy of skin tissue[J]. Journal of Thermal Biology, 2017, 63: 92-103.