AOD Carbon Endpoint Determination Using Multi-Model Flame Analysis
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Solution Overview
Problem
Current carbon endpoint values in AOD processes are unreliable and inaccurate, leading to premature sampling and prolonged process durations due to the need for restarting the AOD process to achieve target carbon levels.
Innovation Solution
A method utilizing a combination of metallurgical modeling, fuzzy logic analysis of flame parameters, and carbon vision module to calculate and compare multiple carbon concentrations in real-time, providing an improved carbon endpoint value for accurate sampling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional mathematical models are used to estimate carbon endpoint values, then the operator can obtain carbon composition estimates, but the values are unreliable and inaccurate leading to premature sampling
Solution Approach 1:
The patent combines multiple independent carbon estimation models (metallurgical model, flame model, CO model) into a unified decision-making framework. Each model contributes its own carbon endpoint estimate, and the system integrates these multiple perspectives to determine the optimal sampling time, thereby improving both accuracy and reliability compared to using any single model alone.
Solution Approach 2:
The system continuously monitors carbon composition estimates from multiple models and uses this feedback to determine when to trigger the sampling operation. The real-time comparison of carbon values from different models provides feedback that guides the operator's sampling decision, ensuring sampling occurs at the optimal moment when carbon reaches the target level.
2Measurement precision
If the operator waits for accurate carbon endpoint determination, then sampling accuracy improves, but the process duration increases due to operator speculation and delayed decisions
Solution Approach 1:
The system performs preliminary calculations and comparisons of carbon endpoint values from multiple models continuously during the AOD process. This preliminary action prepares the carbon endpoint determination in advance, so that when the optimal sampling time is reached, the operator can make an immediate decision without delay or speculation, thus maintaining both accuracy and efficiency.
Solution Approach 2:
The patent replaces the operator's subjective speculation and manual judgment with an automated computational system that objectively compares carbon values from multiple models. This substitution eliminates the time loss associated with human decision-making uncertainty while maintaining high sampling accuracy through systematic multi-model comparison.
3Adaptability or versatility
If multiple mathematical models are used to calculate carbon compositions, then estimation coverage is improved, but the variation between model values makes it difficult to determine which value to rely upon
Solution Approach 1:
The patent segments the carbon estimation task into multiple independent model calculations (metallurgical model, flame model, CO model), each handling a specific aspect of carbon composition estimation. By dividing the overall estimation problem into separate model segments, the system maintains the versatility benefits of multiple approaches while managing the complexity of value selection through structured comparison and integration.
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
Enables precise determination of the carbon endpoint, reducing process duration and gas consumption by ensuring accurate carbon sampling without operator speculation, thereby improving throughput and efficiency.
Implementation Method 1
generating a flame produced by chemical reactions above the molten metal charge
Implementation Method 2
removing carbon from a molten metal bath produced in the AOD vessel from the molten metal charge
Data Source
AI summary
The present invention generally relates to methods for determining an improved carbon endpoint concentration in an argon oxygen decarburization process. The present invention utilizes various pieces of real-time data, including parameters of the flame and soot content to estimate a carbon composition in the steel product, along with two other metallurgical models to generate corresponding carbon compositions in the steel product. A total of 3 carbon compositions are determined and continuously updated during the process. An improved carbon endpoint value is determined to be reached when at least a first value and a second value corresponding to any of the three carbon compositions are below a target carbon value. Upon such condition being satisfied, an alert notification is transmitted to enable carbon sampling to confirm that the sample has a measured carbon concentration that is below a predetermined calculated target carbon value.