用粒子群算法选择体育馆监测系统中传感器的最优布点
|
摘要
如何合理、有效地确定传感器的位置,是结构健康监测系统正常、高效运行的前提.基于模态能量和粒子群算法进行传感器优化布置研究.首先,讨论了粒子群算法的基本原理和优点;其次,根据结构模态应变能的大小挑选出结构的主要贡献模态,进而确定监测模态阶数;然后,针对不同的传感器类型,基于位移模态定义适用于加速度传感器的适应度函数,基于应变模态定义适用于应变传感器的适应度函数;最后,以西宁市体育馆钢结构为工程背景,采用粒子群算法对其监测系统中加速度传感器和应变传感器分别进行优化布置.结果表明,该方法优化结果稳定可靠且收敛迅速.
The optimal sensor placement is a primary problem to be solved to ensure that the structural health monitoring system works normally and efficiently. A method of sensor placement based on the modal energy and particle swarm optimization is proposed. Firstly, the basic principle and the advantages of the particle swarm optimization(PSO) are discussed. Secondly, the modal shape order for optimal sensor placement is the order of significant modes selected by the modal strain energy. Thirdly, on the basis of displacement and strain modes, two expressions of the fitness function are defined for different sensors and tasks. Finally, taking the steel structure of Xining gymnasium as a case, the acceleration sensors and the strain sensors in modal parameter testing are optimized by the proposed method. The results show that the PSO method gives reliable and stable results with rapid convergence.
The optimal sensor placement is a primary problem to be solved to ensure that the structural health monitoring system works normally and efficiently. A method of sensor placement based on the modal energy and particle swarm optimization is proposed. Firstly, the basic principle and the advantages of the particle swarm optimization(PSO) are discussed. Secondly, the modal shape order for optimal sensor placement is the order of significant modes selected by the modal strain energy. Thirdly, on the basis of displacement and strain modes, two expressions of the fitness function are defined for different sensors and tasks. Finally, taking the steel structure of Xining gymnasium as a case, the acceleration sensors and the strain sensors in modal parameter testing are optimized by the proposed method. The results show that the PSO method gives reliable and stable results with rapid convergence.
引文
[1] 李壮.大跨度空间网格健康监测中传感器优化布置研究[D].青岛:青岛理工大学,2012.LI Zhuang. Resarch on Optimal Sensor Placement of Health Montioring Large Span Space Grid Structures [D]. Qingdao: Qingdao University of Technology,2012.
[2] 欧进萍.重大工程结构智能传感网络与健康监测系统的研究与应用[J].中国科学基金,2005,19(1): 8-12.OU Jin-ping. The research and application in the important engineering structure intelligent sensor network and health monitoring system [J]. Bulletin of National Natural Science Foundation of China, 2005,19(1): 8-12.
[3] ZHU Da-peng, YI Xiao-hua, WANG Yang, et al. Mobile sensor networks: a new approach for structural health monitoring [C]// 19th Analysis & Computation Specialty Conference, 2010:159-168.
[4] 董石麟,邢栋,赵阳.现代大跨空间结构在中国的应用与发展[J].空间结构.2012,18(1): 3-16.DONG Shi-lin, XING Dong, ZHAO Yang. Application and development of modern long-span space structures in China [J]. Spatial Structures, 2012,18(1): 3-16.
[5] SEPULVEDA A E, JIN I M, SCHMIT J L A. Optimal placement of active element in control augmented structural systhesis [J]. AIAA Journal, 1993,31(10):1906-1915.
[6] SEPULVEDA A E, SCHMIT J L A. Optimal placement of actuators and sensors in control augmented structural optimization[C]// Proceedings of SDM Conference, AIAA-90-10550cp,1990: 217-230.
[7] SUNAR M, RAO S S. Thermo piezoelectric control design and actuator placement [J]. AIAA Journal,1997,35(2): 534-539.
[8] 李戈,秦权,董聪.用遗传算法选择悬索桥监测系统中传感器的最优布置点[J].工程力学,2000,17(1): 25-34.LI Ge, QIN Quan, DONG Cong. Optimal placement of sensors for monitoring systems on suspension bridges using genetic algorithms [J]. Engineering Mechanics, 2000,17(1): 25-34.
[9] 伊廷华,李宏男,顾明.基于模型聚缩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 Ting-hua, LI Hong-nan, GU Ming. Research on optimal sensor placement of Guangzhou new TV Tower based on model reduction [J]. Engineering Mechanics,2012, 29(3): 55-61.
[10] 李擎,张超,陈鹏,等.一种基于粒子群参数优化改进蚁群算法[J].控制与决策,2013,28(6): 873-878.LI Qing, ZHANG Chao, CHEN Peng, et al. Improved ant colony optimization algorithm based on particle swarm optimization[J]. Control and Decision, 2013,28(6): 873-878.
[11] 鹿伟.基于粒子群算法的网架结构健康监测传感器优化布置研究[D].西安:西安建筑科技大学,2016.LU Wei. Space Truss Structure Health Monitoring Based on Particle Swarm Algorithm of Optimal Placement of the Sensor[D]. Xi’an: Xi’an University of Architecture and Technology, 2016.
[12] 黄平,于金杨,元泳泉.一种改进的小生境多目标粒子群优化算法[J].计算机工程,2011,37(18):1-3.HUANG Ping, YU Jin-yang, YUAN Yong-quan. Improved niching multi-objective particle swarm optimization algorithm [J]. Computer Engineering, 2011, 37(18): 1-3.
[13] 徐菁,李壮,刁延松.基于粒子群算法大跨度空间结构监测系统中应变传感器最优布点研究[J].建筑钢结构进展,2013,15(1): 57-64.XU Jing, LI Zhuang, DIAO Yan-song. Optimal placement of strain sensors for monitoring systems on reticulated shells using particle swarm optimization [J]. Progress in Steel Building Structures, 2013,15 (1): 57-64.
[14] 王秀丽,陈文博.西宁体育场空间管桁架结构温度响应及模拟分析[J].空间结构,2013,19(4):81-87.WANG Xiu-li, CHEN Wen-bo. Health monitoring and simulation analysis of space pipe truss structue forXi’ning Stadium[J]. Spatial Structures, 2013,19(4): 81-87.
[15] KENNEDY J, EBERHART R. Particle swarm optimization [C]// IEEE International Conference on Neural Networks, Australia,1995: 1942-1948.
[16] 滕军,朱焰煌.大跨空间钢结构模态参数测试传感器优化布置[J].工程力学,2011,28(3): 150-156.TENG Jun, ZHU Yan-huang. Optimal sensor placement for modal parameters test of large span spatial steel structural [J]. Engineering Mechanics, 2011,28(3): 150-156.
[17] 孙湘,周大为,张希望.惯性权重粒子群算法模型收敛性分析及参数选择[J].计算机工程与设计,2010,31(18): 4068-4071.SUN Xiang, ZHOU Da-wei, ZHANG Xi-wang. Convergence analysis and parameter selection of PSO model with inertia weight [J]. Computer Engineering and Design, 2010,31(18): 4068-4071.
[2] 欧进萍.重大工程结构智能传感网络与健康监测系统的研究与应用[J].中国科学基金,2005,19(1): 8-12.OU Jin-ping. The research and application in the important engineering structure intelligent sensor network and health monitoring system [J]. Bulletin of National Natural Science Foundation of China, 2005,19(1): 8-12.
[3] ZHU Da-peng, YI Xiao-hua, WANG Yang, et al. Mobile sensor networks: a new approach for structural health monitoring [C]// 19th Analysis & Computation Specialty Conference, 2010:159-168.
[4] 董石麟,邢栋,赵阳.现代大跨空间结构在中国的应用与发展[J].空间结构.2012,18(1): 3-16.DONG Shi-lin, XING Dong, ZHAO Yang. Application and development of modern long-span space structures in China [J]. Spatial Structures, 2012,18(1): 3-16.
[5] SEPULVEDA A E, JIN I M, SCHMIT J L A. Optimal placement of active element in control augmented structural systhesis [J]. AIAA Journal, 1993,31(10):1906-1915.
[6] SEPULVEDA A E, SCHMIT J L A. Optimal placement of actuators and sensors in control augmented structural optimization[C]// Proceedings of SDM Conference, AIAA-90-10550cp,1990: 217-230.
[7] SUNAR M, RAO S S. Thermo piezoelectric control design and actuator placement [J]. AIAA Journal,1997,35(2): 534-539.
[8] 李戈,秦权,董聪.用遗传算法选择悬索桥监测系统中传感器的最优布置点[J].工程力学,2000,17(1): 25-34.LI Ge, QIN Quan, DONG Cong. Optimal placement of sensors for monitoring systems on suspension bridges using genetic algorithms [J]. Engineering Mechanics, 2000,17(1): 25-34.
[9] 伊廷华,李宏男,顾明.基于模型聚缩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 Ting-hua, LI Hong-nan, GU Ming. Research on optimal sensor placement of Guangzhou new TV Tower based on model reduction [J]. Engineering Mechanics,2012, 29(3): 55-61.
[10] 李擎,张超,陈鹏,等.一种基于粒子群参数优化改进蚁群算法[J].控制与决策,2013,28(6): 873-878.LI Qing, ZHANG Chao, CHEN Peng, et al. Improved ant colony optimization algorithm based on particle swarm optimization[J]. Control and Decision, 2013,28(6): 873-878.
[11] 鹿伟.基于粒子群算法的网架结构健康监测传感器优化布置研究[D].西安:西安建筑科技大学,2016.LU Wei. Space Truss Structure Health Monitoring Based on Particle Swarm Algorithm of Optimal Placement of the Sensor[D]. Xi’an: Xi’an University of Architecture and Technology, 2016.
[12] 黄平,于金杨,元泳泉.一种改进的小生境多目标粒子群优化算法[J].计算机工程,2011,37(18):1-3.HUANG Ping, YU Jin-yang, YUAN Yong-quan. Improved niching multi-objective particle swarm optimization algorithm [J]. Computer Engineering, 2011, 37(18): 1-3.
[13] 徐菁,李壮,刁延松.基于粒子群算法大跨度空间结构监测系统中应变传感器最优布点研究[J].建筑钢结构进展,2013,15(1): 57-64.XU Jing, LI Zhuang, DIAO Yan-song. Optimal placement of strain sensors for monitoring systems on reticulated shells using particle swarm optimization [J]. Progress in Steel Building Structures, 2013,15 (1): 57-64.
[14] 王秀丽,陈文博.西宁体育场空间管桁架结构温度响应及模拟分析[J].空间结构,2013,19(4):81-87.WANG Xiu-li, CHEN Wen-bo. Health monitoring and simulation analysis of space pipe truss structue forXi’ning Stadium[J]. Spatial Structures, 2013,19(4): 81-87.
[15] KENNEDY J, EBERHART R. Particle swarm optimization [C]// IEEE International Conference on Neural Networks, Australia,1995: 1942-1948.
[16] 滕军,朱焰煌.大跨空间钢结构模态参数测试传感器优化布置[J].工程力学,2011,28(3): 150-156.TENG Jun, ZHU Yan-huang. Optimal sensor placement for modal parameters test of large span spatial steel structural [J]. Engineering Mechanics, 2011,28(3): 150-156.
[17] 孙湘,周大为,张希望.惯性权重粒子群算法模型收敛性分析及参数选择[J].计算机工程与设计,2010,31(18): 4068-4071.SUN Xiang, ZHOU Da-wei, ZHANG Xi-wang. Convergence analysis and parameter selection of PSO model with inertia weight [J]. Computer Engineering and Design, 2010,31(18): 4068-4071.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |