基于无线传感器网络的河流中稳态扩散污染源定位研究

发布时间：2018-06-04 11:33

本文选题：无线传感器网络 + 非线性最小二乘　；参考：《传感技术学报》2014年10期

【摘要】：针对河流中污染源定位问题,首先分析了河流污染源扩散模型,给出了一种处理完全吸收边界,不完全反射边界以及完全反射边界的通用河流污染源稳态扩散模型。改进了在边界约束下以测量值与理论值之差的平方和为目标的非线性最小二乘算法,并提出了一种新的最小二乘污染源定位算法。该算法弥补了直接非线性最小二乘算法在数值计算过程中稳定性较差的缺点。最后,仿真研究了浓度测量噪声,节点漂移误差和反射系数误差对定位性能的影响。仿真结果表明:已知信息的误差越大,则定位均方根误差越大;传感器节点个数越多,估计精度越高,但当节点增加到一定数量时,继续增加节点对定位精度的影响会减小。另外,仿真结果验证了非线性最小二乘算法的优越性,说明了算法在河流污染源定位应用中的有效性。
[Abstract]:Aiming at the problem of pollution source location in rivers, this paper first analyzes the model of river pollution source diffusion, and presents a general steady state diffusion model of river pollution source, which deals with complete absorbing boundary, incomplete reflection boundary and complete reflection boundary. In this paper, a nonlinear least squares algorithm with the square sum of the difference between the measured value and the theoretical value under boundary constraints is improved, and a new least square source location algorithm is proposed. The algorithm makes up for the poor stability of the direct nonlinear least squares algorithm in the process of numerical calculation. Finally, the effects of concentration measurement noise, node drift error and reflection coefficient error on location performance are simulated. The simulation results show that the greater the error of known information, the greater the root mean square error and the higher the estimation accuracy of sensor nodes, but when the number of nodes increases to a certain number, the effect of increasing nodes on location accuracy will be reduced. In addition, the simulation results verify the superiority of the nonlinear least square algorithm, and illustrate the effectiveness of the algorithm in the application of river pollution source location.
【作者单位】：武汉科技大学冶金自动化与检测技术教育部工程研究中心;遵义医学院信息工程系;
【基金】：国家自然科学基金项目(61171160,61463053) 湖北省高等学校优秀中青年科技创新团队计划项目(T201302)
【分类号】：TP212.9;TN929.5

【参考文献】