Gasification Coal Blending Using Spectral Analysis and Ratio Optimization
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Solution Overview
Problem
Traditional coal blending technologies in the gasification process are inefficient and inaccurate, lacking a comprehensive life cycle approach, leading to unstable gasifier operations and increased costs due to fluctuating coal quality and supply issues.
Innovation Solution
An intelligence system for material blending in gasification, comprising a raw material property rapid analysis module, blended material property prediction module, blending scheme optimization module, and economy evaluation module, which establishes a prediction model based on spectral line intensities to optimize blending ratios and ensure technical economy, while also managing gasifier operation parameters and slag properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional experimental methods are used for coal blending, then blending schemes can be obtained through manual experiments, but the process is cumbersome and inefficient with low accuracy
Solution Approach 1:
The patent replaces manual experimental methods with an intelligent system that uses spectral analysis and computer algorithms to determine optimal blending ratios. The system automatically acquires spectral data, processes it through prediction models, and generates blending schemes without manual intervention, thereby improving both efficiency and accuracy simultaneously.
Solution Approach 2:
The system enables self-service by allowing the blending scheme to be determined automatically through the intelligent system without requiring extensive manual experimentation. The system uses built-in prediction models and optimization algorithms to generate blending ratios based on spectral data, making the process self-sufficient and eliminating the need for cumbersome manual experiments.
2Reliability
If coal quality fluctuates greatly, then the gasifier cannot run stably for a long period, but increasing coal quality control measures increases operational complexity
Solution Approach 1:
The system performs preliminary action by determining the optimal blending ratio before coal is fed into the gasifier. By using spectral analysis and prediction models to pre-calculate the best blending scheme based on current coal quality, the system ensures stable gasifier operation without requiring complex real-time control adjustments, thus maintaining reliability while minimizing operational complexity.
Solution Approach 2:
The system implements feedback by continuously monitoring coal quality through spectral analysis and automatically adjusting the blending ratio accordingly. The system uses the acquired spectral data to predict material properties and optimize blending schemes in real-time, creating a closed-loop control system that maintains gasifier stability without increasing overall system complexity.
3Reliability
If coal blending technology is used to solve quality fluctuations, then gasifier stability can be improved, but traditional methods have low efficiency and poor accuracy in obtaining optimal blending ratios
Solution Approach 1:
The patent replaces traditional manual trial-and-error blending methods with an intelligent system that uses spectral analysis and computer algorithms. The system automatically determines optimal blending ratios by analyzing spectral data and processing it through prediction models, achieving both high gasifier stability and high optimization efficiency simultaneously.
Solution Approach 2:
The system applies parameter changes by using spectral parameters (characteristic spectral line intensities) to determine the optimal blending ratio. Instead of relying on manual experimentation, the system transforms spectral data into material property predictions and optimization decisions, efficiently achieving gasifier stability while improving productivity in the blending scheme development process.
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 system enhances the efficiency and accuracy of coal blending, enabling precise control and reducing adverse effects of raw material property issues, thereby stabilizing gasifier operations and improving economic performance.
Implementation Method 1
receiving characteristic spectral line intensities of in-furnace raw materials, and obtaining raw material property parameters of raw materials based on said characteristic spectral line intensities
Data Source
AI summary
Described are an intelligence system and process for material blending in the gasification. The system includes a subsystem for material blending in the gasification, wherein the subsystem for material blending in the gasification includes a raw material property rapid analysis module, for obtaining raw material property parameters of raw materials according to characteristic spectral line intensities of in-furnace raw materials; a blended material property prediction module, for establishing a prediction model, and predicting blended material property parameters by means of the prediction model according to raw material property parameters and raw material proportions; a blending scheme optimization module, for establishing an optimization model, and obtaining an optimized blending scheme by means of the optimization model according to blended material property parameters; a blending scheme economy evaluation module, for outputting a blending scheme with the optimum technical economy.