Efficient waste heat recovery method and system for high-temperature solid bulk materials in ferrous metallurgy industry
By constructing a black box model to dynamically match the heat exchange medium, the problem of low waste heat recovery efficiency of high-temperature solid bulk materials is solved, realizing efficient waste heat recovery and energy utilization, adapting to high-temperature bulk materials of different forms and temperatures, and reducing production costs.
Patent Information
- Application Number
- CN202511092056.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-05
- Publication Date
- 2025-11-28
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Existing high-temperature solid bulk material waste heat recovery technologies cannot adapt to high-temperature bulk materials of different shapes and temperatures, resulting in low heat exchange efficiency and energy waste. Furthermore, traditional methods suffer from irreversible energy loss and high self-consumption of electricity.
By constructing a black-box model based on correlation analysis and neural network model, the morphology, temperature, mass and flow information of heat exchange medium and high-temperature solid bulk material are dynamically matched. Combined with deep reinforcement learning, the physical parameters of heat exchange medium are optimized to achieve efficient waste heat recovery.
It significantly improves waste heat recovery efficiency, adapts to a wide temperature range of 300-1200℃ and a particle size range of 0.05-50mm, reduces energy waste, lowers production costs, and flexibly responds to different bulk material characteristics.