Yang Wei, Nan Jun, Sun Dezhi
School of Municipal and Environmental Engineering, Harbin Institute of Technology, 202 Haihe Road, Nangang District, Harbin 150090, China.
J Environ Manage. 2008 Jul;88(2):318-25. doi: 10.1016/j.jenvman.2007.03.010. Epub 2007 Apr 25.
This paper describes an online water quality monitoring and management system that was developed by combining a chemical oxygen demand sensor with an artificial neural network technology and a virtual instrument technique. The system was used to model the hydrological environment of the Liming River basin in Daqing City, China, in an effort to maintain the water quality in this basin at a level compatible with the status of Daqing City as a scenic resort. Operation of the system during the past 2 years has shown that an optimal allocation of water (including water released from an environmental reservoir to mitigate pollution events) could be achieved for the basin using the information gathered by the system; using mathematic models established for this system, the quantity of water released from the reservoir is adequate to improve the overall water environment. The results demonstrate that the system provides an effective approach to water quality control for environmental protection.
本文介绍了一种在线水质监测与管理系统,该系统是通过将化学需氧量传感器与人工神经网络技术以及虚拟仪器技术相结合而开发的。该系统用于对中国大庆市黎明河流域的水文环境进行建模,旨在将该流域的水质维持在与大庆市作为旅游胜地地位相匹配的水平。在过去两年中该系统的运行表明,利用系统收集的信息可为该流域实现水的优化配置(包括从环境水库放水以减轻污染事件);利用为该系统建立的数学模型,水库放水量足以改善整体水环境。结果表明,该系统为环境保护中的水质控制提供了一种有效方法。