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Distributed Decision-Making in Wireless Sensor Networks for Online Structural Health Monitoring

机译:在线结构健康监测的无线传感器网络中的分布式决策

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摘要

In a wireless sensor network (WSN) setting, this paper presents a distributed decision-making framework and illustrates its application in an online structural health monitoring (SHM) system. The objective is to recover a damage severity vector, which identifies, localizes, and quantifies damages in a structure, via distributive and collaborative decision-making among wireless sensors. Observing the fact that damages are generally scarce in a structure, this paper develops a nonlinear 0-norm minimization formulation to recover the sparse damage severity vector, then relaxes it to a linear and distributively tractable one. An optimal algorithm based on the alternating direction method of multipliers (ADMM) and a heuristic distributed linear programming (DLP) algorithm are proposed to estimate the damage severity vector distributively. By limiting sensors to exchange information among neighboring sensors, the distributed decision-making algorithms reduce communication costs, thus alleviate the channel interference and prolong the network lifetime. Simulation results in monitoring a steel frame structure prove the effectiveness of the proposed algorithms.
机译:在无线传感器网络(WSN)设置中,本文提出了一种分布式决策框架,并说明了其在在线结构健康监测(SHM)系统中的应用。目的是通过无线传感器之间的分布式和协作决策来恢复损坏严重性向量,以识别,定位和量化结构中的损坏。观察到损伤通常很少出现在结构中的事实,本文开发了一种非线性0范数最小化公式来恢复稀疏损伤严重性矢量,然后将其松弛为线性且易于处理的线性矢量。提出了一种基于乘法器交替方向法(ADMM)的最优算法和启发式分布式线性规划(DLP)算法来分布式估计损伤严重度矢量。通过限制传感器在相邻传感器之间交换信息,分布式决策算法降低了通信成本,从而减轻了信道干扰并延长了网络寿命。监测钢框架结构的仿真结果证明了所提算法的有效性。

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