摘要
为了提高地下水污染源在线监测准确性,提出一种环保工程中地下水污染源在线监测及阻截方法。将模拟模型作为等式约束条件,以模拟输出值和实际观测值间的偏差极小化作为目标函数,利用BP神经网络组建数值模拟模型的代替模型,通过自适应权重粒子群优化算法对模型求解,辨识地下水污染源。根据时/空连续图像信息自检方法对采集到的水体图像展开在线分析,结合智能视觉技术实现地下水污染源在线监测,通过监测结果给出对应的阻截方案。实验结果表明,所提方法可以有效提升地下水污染源在线监测结果的准确性,同时给出最佳的阻截方案。
In order to improve the accuracy of online monitoring of groundwater pollution sources,a method for online monitoring and interception of groundwater pollution sources in environmental protection engineering is proposed.Using the simulation model as an equality constraint and minimizing the deviation between the simulated output value and the actual observation value as the objective function,a substitute model for the numerical simulation model is constructed using a BP neural network.The model is solved using an adaptive weight particle swarm optimization algorithm to identify groundwater pollution sources.Based on the self inspection method of time/space continuous image information,the collected water body images are analyzed online,and intelligent vision technology is used to achieve online monitoring of groundwater pollution sources.Corresponding interception schemes are provided based on the monitoring results.The experimental results show that the proposed method can effectively improve the accuracy of online monitoring of groundwater pollution sources and provide the best interception scheme.
作者
陈思思
杨浩锋
张建中
秦雯
虞丽俊
Chen Sisi;Yang Haofeng;Zhang Jianzhong;Qin Wen;Yu Lijun(Huadong Engineering Corporation Limited,Hangzhou 311122,China)
出处
《环境科学与管理》
2025年第5期161-166,共6页
Environmental Science and Management
关键词
环保工程
地下水
污染源
在线监测
阻截方法
environmental engineering
groundwater
pollution sources
online monitoring
interception method
