全向感知型传感器覆盖率优化研究
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摘要
为了降低全向感知型应变传感器网络的节点布置数量以及提高传感网络的测量精度,研究全向感知型传感器覆盖率优化问题。分析了全向感知传感器数学模型,对覆盖率优化问题进行数学化描述,建立优化函数,确定优化目标。使用全局人工鱼群算法对所建立的传感器覆盖率优化函数进行求解,得出最优传感器节点布置方案。研究结果表明:在传感器节点数量较少时,使用优化方法得到的覆盖率提升较为明显;随着节点数量的增多,使用优化方法得到的覆盖率曲线逐渐平缓。使用所研究的优化方法后,测量的应变相比人工随机布置传感器测量值更接近真实值,具有较高的测量精度。
In order to reduce the number of nodes in the omnidirectional sensing strain sensor network and improve the measurement accuracy of the sensor network, the coverage optimization problem of omnidirectional sensing sensor is studied. The mathematical model of the omnidirectional sensing sensor is analyzed. The coverage optimization problem is mathematical described. The optimization function is established and the optimization target is determined. The global artificial fish swarm algorithm is used to solve the proposed sensor coverage optimization function and the optimal sensor node layout scheme is obtained. The research results show that when the number of sensor nodes is small, the coverage increased by using the optimization method is more obvious. With the increase of the number of nodes, the coverage curve obtained by the optimization method is gradually flat. By using the studied optimized method, the measured strain is closer to the real value than the artificially randomly arranged sensor and has a higher measurement accuracy.
In order to reduce the number of nodes in the omnidirectional sensing strain sensor network and improve the measurement accuracy of the sensor network, the coverage optimization problem of omnidirectional sensing sensor is studied. The mathematical model of the omnidirectional sensing sensor is analyzed. The coverage optimization problem is mathematical described. The optimization function is established and the optimization target is determined. The global artificial fish swarm algorithm is used to solve the proposed sensor coverage optimization function and the optimal sensor node layout scheme is obtained. The research results show that when the number of sensor nodes is small, the coverage increased by using the optimization method is more obvious. With the increase of the number of nodes, the coverage curve obtained by the optimization method is gradually flat. By using the studied optimized method, the measured strain is closer to the real value than the artificially randomly arranged sensor and has a higher measurement accuracy.
引文
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[4]梁栋,范志锋.结构健康监测系统的软件主体协作规范[J].测控技术,2015,34(12):108-112.
[5]凌骐,王军涛,邓检华.光纤光栅传感器在公路隧道衬砌结构安全监测中的应用[J].测控技术,2015,34(11):5-8.
[6]张玉兵,吴子燕,杨海峰.基于MFC的智能结构健康监测系统软件开发与验证[J].测控技术,2012,31(11):88-91.
[7]沈健.基于多传感器信息融合的桥梁健康监测系统的研究与实现[D].南京:南京邮电大学,2017.
[8]张青青.复杂应力状态下基于区域分布传感技术的结构识别及性能预测理论[D].南京:东南大学,2017.
[9]陈亚,李萍.人工鱼群神经网络在短期负荷预测中的应用陈亚,李萍[J].计算机技术与发展,2017(9):1-4.
[10]洪蕾.粒子群及人工鱼群算法优化研究[J].软件,2014,35(8):83-86.
[11]王延菲.基于改进量子遗传算法的无线多媒体传感器网络覆盖研究[D].太原:太原理工大学,2013.
[12]王瑞雪,刘渊.GAFSA优化SVR的网络流量预测模型研究[J].计算机应用研究,2013,30(3):856-860.
[13]王联国.人工鱼群算法及其应用研究[D].兰州:兰州理工大学,2009.
[14]王闯.人工鱼群算法的分析及改进[D].大连:大连海事大学,2008.