一种智能仓储中基于数字孪生的能耗监控优化系统
By constructing a digital twin and a dynamic parameterized spatial manifold for intelligent warehousing, the problem of low energy consumption monitoring accuracy in intelligent warehousing has been solved. This enables the prediction and precise control of energy consumption anomalies, reduces overall energy consumption, and improves the refinement and intelligence of energy efficiency management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XIAMEN WEICHUANG INTELLIGENT TECH CO LTD
- Filing Date
- 2026-04-10
- Publication Date
- 2026-07-17
AI Technical Summary
Existing intelligent warehousing systems suffer from low accuracy in energy consumption monitoring and difficulty in building a spatiotemporal correlation model of energy consumption across the entire domain, resulting in serious energy waste and failing to meet the needs of refined and energy-saving operations.
A digital twin-based energy consumption monitoring and optimization system is constructed. By acquiring multi-source high-frequency dynamic data, a dynamic digital twin is established, a dynamic parameterized spatial manifold is constructed, a synchronous operating state flow is generated, and numerical simulation of energy consumption surge trends is performed through isoparametric transformation and buffer boundary partitioning, thereby executing dynamic adaptive regulation and closed-loop optimization.
It achieves the spatiotemporal correlation representation of energy consumption across the entire warehousing domain and the precise alignment and fusion of multi-source heterogeneous data. It can predict and accurately control energy consumption anomalies such as harmonic impacts during stacker crane start-up and shutdown and path congestion of unmanned handling equipment, thereby reducing overall energy consumption and improving the refinement and intelligence of energy efficiency management.
Smart Images
Figure CN122022697B_ABST