智能水利多模态感知与决策优化系统
The intelligent water conservancy multimodal perception and decision optimization system solves the problems of single perception dimension and insufficient data fusion accuracy in traditional water conservancy management systems. It realizes accurate perception of pipeline network, water quality and hydrological dynamics and early diagnosis of abnormal events, provides highly reliable risk inference and multi-objective collaborative optimization, dynamically balances water supply security and energy consumption efficiency, and reduces on-site commissioning risks.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- JIANGSU MAIDING TECH (GRP) CO LTD
- Filing Date
- 2026-03-13
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional water conservancy management systems suffer from limitations such as single perception dimensions, insufficient data fusion accuracy, low anomaly location accuracy, high false alarm rate, lack of accurate prediction of risk evolution, control strategies that easily lead to an imbalance between water supply security and energy efficiency, insufficient credibility of inference models lacking physical constraint support, lack of effective verification before the implementation of control strategies, and high risks in on-site debugging.
A smart water conservancy multimodal perception and decision optimization system is adopted, including a multimodal perception and fusion module, an intelligent diagnosis and early warning module, a physical constraint risk inference module, and a multi-objective collaborative control module. Data fusion is performed through a spatiotemporal tensor alignment algorithm and adaptive wavelet threshold denoising technology. Abnormal events are located using continuous wavelet transform and time-frequency energy focusing analysis. Risk inference is performed by combining a physical constraint solution model. Multi-objective collaborative optimization is performed using a meta-policy gradient reinforcement learning framework. Virtual verification is performed through a digital twin and policy pre-simulation module.
It achieves comprehensive and accurate perception of pipeline vibration, water quality parameters and hydrological dynamics, can locate abnormal events at the sub-meter level and perform early diagnosis, provides highly reliable risk simulation support, dynamically balances water supply safety, energy efficiency and equipment life, significantly reduces on-site commissioning risks, and provides a systematic water network management solution.
Smart Images
Figure CN121836438B_ABST
Abstract
Citation Information
Patent Citations
Intelligent water operation management and control system based on Internet of Things
CN121169092A