基于分级免疫萤火虫算法的桥梁振动传感器优化布置研究
|
摘要
针对结构健康监测系统设计的振动传感器优化布置问题,在基本萤火虫算法的基础上引入等级划分策略和免疫机制,提出了一种分级免疫萤火虫算法。采用二重结构编码,弥补了基本萤火虫算法只能用于连续优化问题的不足;建立等级划分制度,使不同等级种群内部形成独立的搜索空间,维持了种群多样性,并让优质个体得以保留;引进免疫机制,进行萤火虫的选择、记忆、交叉和变异,增强了算法的全局搜索能力和局部寻优能力;文末利用足尺Benchmark桥梁模型,对算法参数进行了敏感性分析,并开展了振动传感器优化布置方案的选择。结果表明,与基本离散型萤火虫算法相比,分级免疫萤火虫算法的计算效率和寻优结果均有显著提升,能够很好地解决振动传感器优化布置问题。
To find the optimal vibration sensor placement(OVSP) during designing a structural health monitoring system, the gradation-immune firefly algorithm(GIFA) was proposed by introducing the gradation strategy and the immune pattern to improve the original firefly algorithm. The dual-structure coding method was employed to overcome the shortage that the original firefly algorithm can only be applied to optimal problems with continuous variables. The gradation strategy was developed to limit individuals with different gradations in their respective search space. As a result, the diversity of population is ensured and the individuals with good performance are inherited. Furthermore, the immune pattern is utilized to perform selecting, memorizing, crossing and mutating for fireflies and enhance the capability of global searching and local optimization of the GIFA. A full-scale benchmark cable-stayed bridge was employed as a case study. The parametric sensitivity of the proposed GIFA was discussed and the optimal sensor configurations were offered. The results indicate that the computational efficiency of the GIFA and the quality of optimal solutions provided by the GIFA are dramatically improved when comparing with the simple discrete firefly algorithm. The GIFA is an excellent approach to solve OVSP problems.
To find the optimal vibration sensor placement(OVSP) during designing a structural health monitoring system, the gradation-immune firefly algorithm(GIFA) was proposed by introducing the gradation strategy and the immune pattern to improve the original firefly algorithm. The dual-structure coding method was employed to overcome the shortage that the original firefly algorithm can only be applied to optimal problems with continuous variables. The gradation strategy was developed to limit individuals with different gradations in their respective search space. As a result, the diversity of population is ensured and the individuals with good performance are inherited. Furthermore, the immune pattern is utilized to perform selecting, memorizing, crossing and mutating for fireflies and enhance the capability of global searching and local optimization of the GIFA. A full-scale benchmark cable-stayed bridge was employed as a case study. The parametric sensitivity of the proposed GIFA was discussed and the optimal sensor configurations were offered. The results indicate that the computational efficiency of the GIFA and the quality of optimal solutions provided by the GIFA are dramatically improved when comparing with the simple discrete firefly algorithm. The GIFA is an excellent approach to solve OVSP problems.
引文
[1]Lin Q,Chen J,Zhan Z,et al.A hybrid evolutionary immune algorithm for multiobjective optimization problems[J].IEEE Transactions on Evolutionary Computation,2016,20(5):711―728.
[2]李惠,鲍跃全,李顺龙.结构健康监测数据科学与工程[J].工程力学,2015,32(8):1―7.Li Hui,Bao Yuequan,Li Shunlong.Data science and engineering for structural health monitoring[J].Engineering Mechanics,2015,32(8):1―7.(in Chinese)
[3]姜绍飞,任晖,骆剑彬.基于云计算的框架结构参数并行辨识算法[J].工程力学,2018,35(4):135―143.Jiang Shaofei,Ren Hui,Luo Jianbin.A parallel identification algorithm on physical parameters of frame structures based on cloud computing[J].Engineering Mechanics,2018,35(4):135―143.(in Chinese)
[4]Taejin K,Youn B D,Oh H.Development of a stochastic effective independence(SEFI)method for optimal sensor placement under uncertainty[J].Mechanical Systems and Signal Processing,2018,111:615―627.
[5]周毅,孙利民,谢谟文.运营环境作用对跨海大桥模态频率的影响研究[J].工程力学,2018,35(增刊):34―39.Zhou Yi,Sun Limin,Xie Mowen.Influence of operational and environmental actions on modal frequencies of a sea-crossing bridge[J].Engineering Mechanics,2018,35(Suppl):34―39.(in Chinese)
[6]何文朋,雷家艳.运营实桥在线监测系统的建立及数据初步分析[J].工程力学,2018,35(增刊):234―238.He Wenpeng,Lei Jiayan.The establishment of online monitoring system for Tianyuan bridge and preliminary analysis of data[J].Engineering Mechanics,2018,35(Suppl):234―238.(in Chinese)
[7]Kammer D C,Tinker M L.Optimal placement of triaxial accelerometers for modal vibration tests[J].Mechanical Systems and Signal Processing,2004,18(1):29―41.
[8]Carne T G,Dohrmann C R.A modal test design strategy for model correlation[C]//Proceedings of the 13th International Modal Analysis Conference.New York:Union College,Schenectady,1995:927―933.
[9]Schedlinski C,Link M.An approach to optimal pick-up and exciter placement[C]//Proceedings of the 14th International Modal Analysis Conference.Orlando,USA,1996:376―382.
[10]孙晓丹,侯钢领,王月敏.基于灵敏度的平板结构多类型传感器优化布置[J].工程力学,2015,32(4):77―84.Sun Xiaodan,Hou Gangling,Wang Yuemin,et al.Optimal placement of multi-type sensor based on sensitivity for plate structures[J].Engineering Mechanics,2015,32(4):77―84.(in Chinese)
[11]伊廷华,李宏男,顾明.基于模型缩聚的广州新电视塔传感器优化布置研究[J].工程力学,2012,29(3):55―61.Yi Tinghua,Li Hongnan,Gu Ming.Research on optimal sensor placement of Guangzhou new TV tower based on model reduction[J].Engineering Mechanics,2012,29(3):55―61.(in Chinese)
[12]Yao L,Sethares W A,Kammer D C.Sensor placement for on-orbit modal identification via a genetic algorithm[J].AIAA Journal,1993,31(10):1922―1928.
[13]Sun H,Büyük?ztürk O.Optimal sensor placement in structural health monitoring using discrete optimization[J].Smart Materials and Structures,2015,24(12):125034.
[14]Yi T H,Li H N,Zhang X D.Health monitoring sensor placement optimization for Canton Tower using immune monkey algorithm[J].Structural Control&Health Monitoring,2015,22(1):123―138.
[15]Yang C,Lu Z X.An interval effective independence method for optimal sensor placement based on non-probabilistic approach[J].Institute of Solid Mechanics,2017,60(2):186―198.
[16]Yang X.Firefly algorithm,stochastic test functions and design optimization[J].International Journal of Bio-Inspired Computation,2010,2(2):78―84.
[17]Yang X,Sadat Hosseini S S,Gandomi A H.Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect[J].Applied Soft Computing,2012,12(3):1180―1186.
[18]Talatahari S,Gandomi A H,Yun G J.Optimum design of tower structures using Firefly Algorithm[J].The Structural Design of Tall and Special Buildings,2014,23(5):350―361.
[19]Zhou G D,Yi T H,Li H N.Sensor placement optimization in structural health monitoring using cluster-in-cluster firefly algorithm[J].Advances in Structural Engineering,2014,17(8):1103―1115.
[20]Zhou G D,Yi T H,Xie M X,et al.Wireless sensor placement for structural monitoring using information-fusing firefly algorithm[J].Smart Materials and Structures,2017,26(10):104002.
[21]Hamming R W.Error detecting and error correcting codes[J].Bell System Technical Journal,1950,29(2):147―160.
[22]郭静,徐江峰.一种基于BioHashing和洗牌算法的可撤销密钥绑定方案[J].计算机应用研究,2014,31(5):1511―1515.Guo Jing,Xu Jiangfeng.Cancellable key binding scheme based on BioHashing and shuffling algorithm[J].Application Research of Computers,2014,31(5):1511―1515(in Chinese)
[23]Timmis J,Neal M,Hunt J.An artificial immune system for data analysis[J].Biosystems,2000,55(1/2/3):143―150.
[24]段向阳,王永生,苏永生.基于奇异值分解的信号特征提取方法研究[J].振动与冲击,2009,28(11):30―33.Duan Xiangyang,Wang Yongsheng,Su Yongsheng.Feature extraction methods based on singular value decomposition[J].Journal of Vibration and Shock,2009,28(11):30―33.(in Chinese)
[2]李惠,鲍跃全,李顺龙.结构健康监测数据科学与工程[J].工程力学,2015,32(8):1―7.Li Hui,Bao Yuequan,Li Shunlong.Data science and engineering for structural health monitoring[J].Engineering Mechanics,2015,32(8):1―7.(in Chinese)
[3]姜绍飞,任晖,骆剑彬.基于云计算的框架结构参数并行辨识算法[J].工程力学,2018,35(4):135―143.Jiang Shaofei,Ren Hui,Luo Jianbin.A parallel identification algorithm on physical parameters of frame structures based on cloud computing[J].Engineering Mechanics,2018,35(4):135―143.(in Chinese)
[4]Taejin K,Youn B D,Oh H.Development of a stochastic effective independence(SEFI)method for optimal sensor placement under uncertainty[J].Mechanical Systems and Signal Processing,2018,111:615―627.
[5]周毅,孙利民,谢谟文.运营环境作用对跨海大桥模态频率的影响研究[J].工程力学,2018,35(增刊):34―39.Zhou Yi,Sun Limin,Xie Mowen.Influence of operational and environmental actions on modal frequencies of a sea-crossing bridge[J].Engineering Mechanics,2018,35(Suppl):34―39.(in Chinese)
[6]何文朋,雷家艳.运营实桥在线监测系统的建立及数据初步分析[J].工程力学,2018,35(增刊):234―238.He Wenpeng,Lei Jiayan.The establishment of online monitoring system for Tianyuan bridge and preliminary analysis of data[J].Engineering Mechanics,2018,35(Suppl):234―238.(in Chinese)
[7]Kammer D C,Tinker M L.Optimal placement of triaxial accelerometers for modal vibration tests[J].Mechanical Systems and Signal Processing,2004,18(1):29―41.
[8]Carne T G,Dohrmann C R.A modal test design strategy for model correlation[C]//Proceedings of the 13th International Modal Analysis Conference.New York:Union College,Schenectady,1995:927―933.
[9]Schedlinski C,Link M.An approach to optimal pick-up and exciter placement[C]//Proceedings of the 14th International Modal Analysis Conference.Orlando,USA,1996:376―382.
[10]孙晓丹,侯钢领,王月敏.基于灵敏度的平板结构多类型传感器优化布置[J].工程力学,2015,32(4):77―84.Sun Xiaodan,Hou Gangling,Wang Yuemin,et al.Optimal placement of multi-type sensor based on sensitivity for plate structures[J].Engineering Mechanics,2015,32(4):77―84.(in Chinese)
[11]伊廷华,李宏男,顾明.基于模型缩聚的广州新电视塔传感器优化布置研究[J].工程力学,2012,29(3):55―61.Yi Tinghua,Li Hongnan,Gu Ming.Research on optimal sensor placement of Guangzhou new TV tower based on model reduction[J].Engineering Mechanics,2012,29(3):55―61.(in Chinese)
[12]Yao L,Sethares W A,Kammer D C.Sensor placement for on-orbit modal identification via a genetic algorithm[J].AIAA Journal,1993,31(10):1922―1928.
[13]Sun H,Büyük?ztürk O.Optimal sensor placement in structural health monitoring using discrete optimization[J].Smart Materials and Structures,2015,24(12):125034.
[14]Yi T H,Li H N,Zhang X D.Health monitoring sensor placement optimization for Canton Tower using immune monkey algorithm[J].Structural Control&Health Monitoring,2015,22(1):123―138.
[15]Yang C,Lu Z X.An interval effective independence method for optimal sensor placement based on non-probabilistic approach[J].Institute of Solid Mechanics,2017,60(2):186―198.
[16]Yang X.Firefly algorithm,stochastic test functions and design optimization[J].International Journal of Bio-Inspired Computation,2010,2(2):78―84.
[17]Yang X,Sadat Hosseini S S,Gandomi A H.Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect[J].Applied Soft Computing,2012,12(3):1180―1186.
[18]Talatahari S,Gandomi A H,Yun G J.Optimum design of tower structures using Firefly Algorithm[J].The Structural Design of Tall and Special Buildings,2014,23(5):350―361.
[19]Zhou G D,Yi T H,Li H N.Sensor placement optimization in structural health monitoring using cluster-in-cluster firefly algorithm[J].Advances in Structural Engineering,2014,17(8):1103―1115.
[20]Zhou G D,Yi T H,Xie M X,et al.Wireless sensor placement for structural monitoring using information-fusing firefly algorithm[J].Smart Materials and Structures,2017,26(10):104002.
[21]Hamming R W.Error detecting and error correcting codes[J].Bell System Technical Journal,1950,29(2):147―160.
[22]郭静,徐江峰.一种基于BioHashing和洗牌算法的可撤销密钥绑定方案[J].计算机应用研究,2014,31(5):1511―1515.Guo Jing,Xu Jiangfeng.Cancellable key binding scheme based on BioHashing and shuffling algorithm[J].Application Research of Computers,2014,31(5):1511―1515(in Chinese)
[23]Timmis J,Neal M,Hunt J.An artificial immune system for data analysis[J].Biosystems,2000,55(1/2/3):143―150.
[24]段向阳,王永生,苏永生.基于奇异值分解的信号特征提取方法研究[J].振动与冲击,2009,28(11):30―33.Duan Xiangyang,Wang Yongsheng,Su Yongsheng.Feature extraction methods based on singular value decomposition[J].Journal of Vibration and Shock,2009,28(11):30―33.(in Chinese)