Solid Fuel Switching Prediction in Combustion Feed Systems
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Solution Overview
Problem
Existing combustion devices struggle to accurately predict the time when types of solid fuels are switched due to a time lag between storage and combustion, necessitating close monitoring of operation conditions, which is challenging and inefficient.
Innovation Solution
A prediction device that includes an acquisition unit to measure the level of solid fuels, temperature of gas, and concentration of chemical substances, and a prediction unit to extrapolate these changes to determine a threshold value for predicting the switching time of solid fuels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If close monitoring of operation conditions is performed to detect fuel switching, then prediction accuracy is improved, but monitoring costs and operational complexity increase
Solution Approach 1:
The system performs preliminary action by predicting the fuel switching time before the actual switching occurs. The prediction unit uses the bulk density difference between first and second solid fuels, combined with the supply rate, to calculate when switching will occur. This allows operators to prepare in advance rather than relying on reactive monitoring after switching has already happened.
Solution Approach 2:
The invention introduces bulk density as an intermediary parameter that connects the physical properties of different fuels to the timing of fuel switching. By measuring or specifying the bulk density of stored fuels and comparing it with the supplied fuel's bulk density, the system can predict switching events without requiring complex real-time monitoring of combustion conditions.
2Measurement precision
If multiple parameters are monitored to predict fuel switching, then prediction accuracy is improved, but data processing complexity increases
Solution Approach 1:
The invention extracts and focuses on the critical parameter of bulk density, separating it from other less relevant parameters. By identifying bulk density as the key differentiator between fuel types, the system simplifies data collection and processing requirements while maintaining high prediction accuracy. Only the bulk density values and supply rate are needed for the prediction calculation.
Solution Approach 2:
The system utilizes parameter changes in bulk density as fuels are consumed and replaced. When the bulk density of the fuel in the storage unit changes due to switching from first solid fuel to second solid fuel, this parameter change serves as the basis for prediction. The prediction unit detects these parameter changes and translates them into switching time predictions.
Data Source
AI summary
A combustion system including a fuel storage stores solid fuel, a supply device connected to the fuel storage, a combustion device combusts supplied solid fuel, and a prediction device for predicting a switching time for types of solid fuel supplied from the fuel storage to the combustion device via the supply device. The prediction device comprises at least one processor configured to acquire a level of solid fuel stored in the fuel storage, predict, as the switching time, a future time when a level obtained by extrapolating time-dependent change in decrease in the level of the solid fuel reaches a threshold value, and display the switching time on a display device.