中国激光, 2013, 40 (9): 0903001, 网络出版: 2013-09-04   

基于神经网络和遗传算法的激光多层熔覆厚纳米陶瓷涂层工艺优化

Process Optimization of Thick Nanostructured Ceramic Coating by Laser Multi-Layer Cladding Based on Neural Network and Genetic Algorithm
作者单位
1 南京航空航天大学机电学院, 江苏 南京 210016
2 铜陵学院机械工程学院, 安徽 铜陵 244000
引用该论文

王东生, 杨友文, 田宗军, 沈理达, 黄因慧. 基于神经网络和遗传算法的激光多层熔覆厚纳米陶瓷涂层工艺优化[J]. 中国激光, 2013, 40(9): 0903001.

Wang Dongsheng, Yang Youwen, Tian Zongjun, Shen Lida, Huang Yinhui. Process Optimization of Thick Nanostructured Ceramic Coating by Laser Multi-Layer Cladding Based on Neural Network and Genetic Algorithm[J]. Chinese Journal of Lasers, 2013, 40(9): 0903001.

参考文献

[1] 冯淑容, 张述泉, 王华明. 钛合金激光熔覆硬质颗粒增强金属间化合物复合涂层耐磨性[J]. 中国激光, 2012, 39(2): 0203002.

    Feng Shurong, Zhang Shuquan, Wang Huaming. Wear resistance of laser clad hard particles reinforced intermetallic composite coating on TA15 alloy[J]. Chinese J Lasers, 2012, 39(2): 0203002.

[2] 王东生, 田宗军, 沈理达, 等. 激光表面熔覆制备纳米结构涂层的研究进展[J]. 中国激光, 2008, 35(11): 1698-1709.

    Wang Dongsheng, Tian Zongjun, Shen Lida, et al.. Research development of nanostructured coatings prepared by laser cladding[J]. Chinese J Lasers, 2008, 35(11): 1698-1709.

[3] T M Yue, Y P Su. Laser multi-layer cladding of Zr65Al7.5Ni10Cu17.5 amorphous alloy on magnesium substrates[J]. J Materials Science, 2007, 42(15): 6153-6160.

[4] 吴培桂, 张光钧. 激光多层熔覆技术的研究现状及发展[J]. 上海工程技术大学学报, 2009, 23(4): 374-378.

    Wu Peigui, Zhang Guangjun. Status and development of multi-layer laser cladding technology[J]. J Shanghai University of Engineering Science, 2009, 23(4): 374-378.

[5] 黄安国, 李刚, 汪永阳, 等. 基于人工神经网络的铝合金激光熔覆层特征与性能的预测[J]. 中国激光, 2008, 35(10): 1632-1636.

    Huang Anguo, Li Gang, Wang Yongyang, et al.. Prediction of characteristic and performance of laser cladding for Al alloy based on artificial neural network[J]. Chinese J Lasers, 2008, 35(10): 1632-1636.

[6] 姜淑娟, 刘伟军, 南亮亮. 基于神经网络的激光熔覆高度预测[J]. 机械工程学报, 2009, 45(3): 269-274.

    Jiang Shujuan, Liu Weijun, Nan Liangliang. Laser cladding height prediction based on neural network[J]. J Mechanical Engineering, 2009, 45(3): 269-274.

[7] 丁周华, 郑启光, 童杏林, 等. 基于神经网络的Co基硬质合金激光熔覆工艺优化[J]. 光电子·激光, 2004, 15(3): 352-355.

    Ding Zhouhua, Zheng Qiguang, Tong Xinglin, et al.. Optimizing of laser cladding parameters of Co-based hard alloy coating based on artificial neural networks[J]. J Optoelectronics·Lasers, 2004, 15(3): 352-355.

[8] 倪立斌, 刘继常, 伍耀庭, 等. 基于神经网络和粒子群算法的激光熔覆工艺优化[J]. 中国激光, 2011, 38(2): 0203003.

    Ni Libin, Liu Jichang, Wu Yaoting, et al.. Optimization of laser cladding processs variables based on neural network and particle swarm optimization algorithms[J]. Chinese J Lasers, 2011, 38(2): 0203003.

[9] E Toyserkani, A Khajepour, S Corbin. Application of experimental-based modeling to laser cladding[J]. J Laser Application, 2002, 14(3): 165-173.

[10] M Alimardani, E Toyserkani. Prediction of laser solid freeform fabrication using neuro-fuzzy method[J]. Applied Soft Computing Journal, 2008, 8(1): 316-323.

[11] 杨东辉, 马良, 黄卫东. 基于人工神经网络的激光立体成形件成形表面质量预测[J]. 中国激光, 2011, 38(8): 0803004.

    Yang Donghui, Ma Liang, Huang Weidong. Component′s surface quality predictions by laser rapid forming based on artificial neural networks[J]. Chinese J Lasers, 2011, 38(8): 0803004.

[12] 张成, 王霄, 王凯, 等. 基于响应曲面和遗传算法人工神经网络的热塑性塑料激光透射连接强度的优化[J]. 中国激光, 2011, 38(11): 1103006.

    Zhang Cheng, Wang Xiao, Wang Kai, et al.. Optimization of weld strength for laser transmission welding of thermoplastic based on response surface methodology and genetic algorithm-artificial neural network[J]. Chinese J Lasers, 2011, 38(11): 1103006.

[13] 张健, 杨锐. 脉冲激光焊接钛合金薄板的熔池深度预测[J]. 中国激光, 2012, 39(3): 0303001.

    Zhang Jian, Yang Rui. Weld penetration depth prediction of pulsed laser welding titanium alloy thin plate[J]. Chinese J Lasers, 2012, 39(3): 0303001.

[14] R J Wang, X H Li, Q D Wu, et al.. Optimizing process parameters for selective laser sintering based on neural network and genetic algorithm[J]. International J Advanced Manufacturing Technology, 2009, 42(11/12): 1035-1042.

[15] Y W Park, S Rhee. Process modeling and parameter optimization using neural network and genetic algorithms for aluminum laser welding automation[J]. International J Advanced Manufacturing Technology, 2008, 37(9/10): 1014-1021.

[16] 刘云, 徐德, 谭民. 基于遗传算法的人工神经网络方法在激光切割工艺参数选取中的应用[J]. 制造业自动化, 2006, 28(12): 20-22.

    Liu Yun, Xu De, Tan Min. A genetic algorithm based artificial neural network approach for parameter selection of laser cutting[J]. Manufacturing Automation, 2006, 28(12): 20-22.

[17] 张连宝, 范青武, 左演声, 等. 混合智能技术在激光淬火工艺优化中的应用[J]. 材料科学与工艺, 2004, 12(6): 654-657.

    Zhang Lianbao, Fan Qingwu, Zuo Yansheng, et al.. The appliance of mixed intelligent technique to optimization of procedure parameter of laser surface quenching[J]. Materials Science & Technology, 2004, 12(6): 654-657.

[18] 潘清跃, 宋仁国, 张奇志, 等. 基于人工神经网络遗传算法的1Cr18Ni9Ti钢激光表面熔凝工艺优化[J]. 材料研究学报, 1998, 12(3): 251-256.

    Pan Qingyue, Song Renguo, Zhang Qizhi, et al.. On optimization of laser surface melting technology for 1Cr18Ni9Ti steel based upon artificial neural[J]. Chinese J Materials Research, 1998, 12(3): 251-256.

[19] 徐大鹏, 周建忠, 郭华锋, 等. 基于进化神经网络的激光熔覆层质量预测[J]. 激光技术, 2007, 31(5): 511-514.

    Xu Dapeng, Zhou Jianzhong, Guo Huafeng, et al.. Quality prediction of laser cladding layer based on improved neural network[J]. Laser Technology, 2007, 31(5): 511-514.

[20] 王东生, 周杏花. 一种激光多层熔覆制备纳米厚陶瓷涂层的方法[P]. 中国, 发明专利: 201110364330.5.

    Wang Dongsheng, Zhou Xinhua. A New Preparation Method of Nanostructured Thick Ceramic Coating by Laser Multi-Layer Cladding[P]. China, Patent of Invention: 201110364330.5.

[21] 王东生, 田宗军, 王泾文, 等. 激光多层熔覆制备厚陶瓷涂层试验[J]. 焊接学报, 2012, 33(5): 67-70.

    Wang Dongsheng, Tian Zongjun, Wang Jingwen, et al.. Experimental research on preparation of thick ceramic coating by laser multi-layer cladding[J]. Transactions of the China Welding Institution, 2012, 33(5): 67-70.

[22] 王东生, 田宗军, 段宗银, 等. 压片预置式激光多层熔覆厚纳米陶瓷涂层结合性能[J]. 中国激光, 2012, 39(2): 0203003.

    Wang Dongsheng, Tian Zongjun, Duan Zongyin, et al.. Bonding strength of thick nanostructured ceramic coating by squash presetting type laser multi-layer cladding[J]. Chinese J Lasers, 2012, 39(2): 0203003.

[23] 王东生, 田宗军, 张少伍, 等. 激光多层熔覆纳米陶瓷涂层工艺参数优化研究[J]. 材料保护, 2012, 45(2): 67-70.

    Wang Dongsheng, Tian Zongjun, Zhang Shaowu, et al.. Process parameters optimization of nanostructured ceramic coating by laser multi-layer cladding[J]. Materials Protection, 2012, 45(2): 67-70.

[24] 朱剑英. 智能系统非经典数学方法[M]. 武汉: 华中科技大学出版社, 2001.

    Zhu Jianying. Intelligent System Non-Classical Mathematical Methods[M]. Wuhan: Huazhong University of Science and Technology Press, 2001.

[25] 史峰, 王辉, 郁磊, 等. MATLAB智能算法30案例分析[M]. 北京: 北京航空航空大学出版社, 2011. 28-31.

    Shi Feng, Wang Hui, Yu Lei, et al.. 30 Cases Analysis of MATLAB Intelligent Algorithm[M]. Beijing: Beijing University of Aeronautics and Astronautics Press, 2011. 28-31.

[26] 王霄, 张成, 王凯, 等. 基于遗传算法响应曲面方法的激光透射焊接聚碳酸酯工艺的多目标优化[J]. 中国激光, 2012, 39(6): 0603003.

    Wang Xiao, Zhang Cheng, Wang Kai, et al.. Multi-objective optimization of laser transmission welding of polycarbonate process based on genetic algorithm-response suface methodology[J]. Chinese J Lasers, 2012, 39(6): 0603003.

王东生, 杨友文, 田宗军, 沈理达, 黄因慧. 基于神经网络和遗传算法的激光多层熔覆厚纳米陶瓷涂层工艺优化[J]. 中国激光, 2013, 40(9): 0903001. Wang Dongsheng, Yang Youwen, Tian Zongjun, Shen Lida, Huang Yinhui. Process Optimization of Thick Nanostructured Ceramic Coating by Laser Multi-Layer Cladding Based on Neural Network and Genetic Algorithm[J]. Chinese Journal of Lasers, 2013, 40(9): 0903001.

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