人工智能驱动的雨水管网智慧调度与内涝防治策略

AI-driven Intelligent Scheduling of Rainwater Pipe Networks and Urban Flood Control Strategies

摘要:

随着城市化进程加快,内涝防治问题日益突出,传统雨水管网调度策略已难以满足实际需求。通过人工智能技术赋能雨水管网智慧调度系统,构建智能感知、分析、预警和调度一体化平台,可实现对城市排水系统的精准调控。文中基于深度学习算法对历史降雨数据进行了分析,结合物联网传感设备实时监测管网运行状态,建立降雨-径流预测模型,制定科学合理的调度方案;借助边缘计算技术实现泵站、阀门等设备的自动化控制,打造分布式智能调度体系;通过建立管网水力模型,优化排水通道,提升系统调度效率。研究表明,人工智能驱动的智慧调度可显著提升雨水管网运行效能,为城市内涝防治提供有力支撑。

Abstract:

With the acceleration of urbanization, the problem of waterlogging prevention and control is becoming increasingly prominent, and the traditional rainwater pipe network scheduling strategy has been difficult to meet the actual needs. By enabling the intelligent scheduling system of rainwater pipe network through artificial intelligence technology, and building an integrated platform of intelligent perception, analysis, early warning and scheduling, precise regulation of urban drainage system can be achieved. In this paper, the historical rainfall data are analyzed based on the deep learning algorithm. Combined with the real-time monitoring of the operation status of the pipeline network by the sensor equipment of the Internet of Things, a rainfall runoff prediction model is established, and a scientific and reasonable scheduling scheme is formulated. With the help of edge computing technology, the automatic control of pump stations, valves and other equipment is realized, and a distributed intelligent dispatching system is built. By establishing a pipe network hydraulic model, the drainage channel is optimized, and the system dispatching efficiency is improved. The research shows that intelligent dispatching driven by artificial intelligence can significantly improve the operation efficiency of rainwater pipe network and provide strong support for urban waterlogging prevention.