Ma Junjie, Meng Fansheng, Zhou Yuexi, Wang Yeyao, Shi Ping
Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
China National Environmental Monitoring Centre, Beijing 100012, China.
Sensors (Basel). 2018 Feb 16;18(2):606. doi: 10.3390/s18020606.
Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.
发生在地表水尤其是饮用水源地的污染事故，对城市供水系统构成了极大威胁。在水污染源头定位过程中，污染物扩散情况复杂，污染物浓度变化范围广。本文提供了一种可扩展的整体解决方案，研究了配备移动紫外可见光谱仪探头的无线传感器网络中的分布式定位方法。定义了一个用于水质监测的无线传感器网络，其中无人水面航行器和浮标分别作为移动节点和固定节点。这两种类型的节点都携带紫外可见光谱仪探头，以获取现场多种水质参数测量值，其中设计了一种自适应光路机制来灵活调整测量范围。提出了一种名为Dual-PSO的新型分布式算法来寻找水污染源头，其中一个粒子群优化（PSO）过程利用紫外可见吸收光谱计算每个节点上的水质多参数测量值，另一个粒子群优化过程将移动节点视为粒子来寻找污染源位置的全局解。此外，该算法在搜索过程中使用熵来动态识别最敏感的参数。实验结果表明，该无线传感器网络实现了对动态范围广的饮用水源地的在线多参数监测，并且通过低成本的移动节点路径有效地定位了水污染源头。
