Blast Control Device for Blast Furnace
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Solution Overview
Problem
Current methods for controlling blast volume in blast furnaces are inefficient due to limited real-time monitoring of particle size and distribution of charging materials, leading to instability and reduced operational efficiency.
Innovation Solution
A device and method that utilize image analysis and sensors to collect data on particle size and distribution, combined with a predictive model to automatically adjust the hot-blast volume, ensuring optimal furnace conditions through real-time monitoring and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual sampling and measurement of particle size is performed three to four times a day, then basic particle size information is obtained, but real-time particle size and distribution data cannot be confirmed
Solution Approach 1:
The patent replaces manual mechanical sampling and measurement with an optical imaging system. Images of charging materials are captured by imaging devices, and particle size data are automatically extracted through image analysis algorithms, enabling continuous real-time monitoring without manual intervention
Solution Approach 2:
The system performs self-measurement by automatically capturing images of charging materials and extracting particle size data through image analysis. The charging materials themselves serve as the measurement target, eliminating the need for separate sampling operations
2Productivity
If blast volume is increased to improve operation efficiency, then pig iron production increases, but furnace operation stability deteriorates when permeability is poor
Solution Approach 1:
The patent implements a closed-loop feedback control system where particle size data and permeability parameters are continuously monitored, fed into a predictive model to forecast optimal blast volume, and then used to adjust the actual blast volume. This feedback mechanism enables dynamic optimization of both productivity and stability
Solution Approach 2:
The system performs preliminary prediction of blast volume using a predictive model that analyzes particle size data and permeability parameters before actual blast furnace operation. This preliminary action allows operators to pre-determine optimal blast volume settings, preventing instability before it occurs
3Stability of the object's composition
If operator manually decreases blast volume to stabilize operation when permeability is bad, then operation stability is maintained, but operation efficiency decreases
Solution Approach 1:
The predictive model continuously receives feedback from permeability sensors and particle size imaging data, automatically adjusting blast volume predictions to optimize both stability and efficiency. The system learns from historical data to make intelligent decisions without manual intervention
Solution Approach 2:
The system performs self-optimization by automatically determining the optimal blast volume based on real-time particle size and permeability data. The predictive model autonomously balances stability and efficiency requirements without operator intervention, eliminating the trade-off between these two parameters
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach stabilizes blast furnace operations and increases efficiency by providing real-time adjustments to blast volume based on particle size and distribution data, minimizing condition changes and improving permeability.
Implementation Method 1
The data collector may obtain the particle size and the particle size distribution of the charging material according to an image analysis of the image
Data Source
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AI summary
A device for controlling a blast in a blast furnace includes: an imaging device for capturing an image of a charging material charged into the blast furnace; at least one sensor for measuring a condition of the blast furnace; a data collector for obtaining particle size data of the charging material from the image; a blast volume predictor for obtaining a blast volume predictive value of the blast furnace from the particle size data; and a blast volume controller for controlling a hot-blast volume supplied into the blast furnace according to the blast volume predictive value.