Continuous Annealing Furnace Pressure Control via Multi-Variable Prediction
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Solution Overview
Problem
Conventional PID double cross amplitude limiting control methods for continuous annealing furnaces fail to maintain stable furnace pressure due to fluctuations in coal gas and air flow volumes, leading to air infiltration, exhaust gas flow issues, and slow dynamic response.
Innovation Solution
A multi-variable prediction control algorithm calculates the optimum rotating speed of the exhaust gas fan and adjusts the opening degree of the regulation valve based on coal gas and air flow volumes, pre- and post-combustion gas pressures, and thermal expansion effects to stabilize furnace pressure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional PID double cross amplitude limiting control method is used to control furnace pressure, then the control system is simple to implement, but the furnace pressure stability is poor and dynamic response is slow
Solution Approach 1:
The patent applies preliminary action by predicting future furnace pressure values based on current and historical data from multiple sensors (gas flow, air flow, temperature, pressure) before the actual pressure deviation occurs. The prediction model calculates anticipated pressure changes and pre-adjusts control parameters, allowing the system to proactively maintain pressure stability rather than reactively responding to deviations.
Solution Approach 2:
The patent implements dynamics by transitioning from static PID parameters to dynamic, adaptive control parameters. The system continuously updates control parameters based on real-time operational conditions and prediction model outputs, allowing the controller to adapt its behavior to changing furnace conditions, thereby improving both stability and response speed without excessive complexity.
2Device complexity
If conventional PID control adjusts coal gas and air flow volumes to control furnace pressure, then the control mechanism is straightforward, but the dynamic response speed is slow due to furnace inertia and lag
Solution Approach 1:
The system performs preliminary calculation of optimal control actions by predicting future pressure states based on current gas flow, air flow, temperature, and pressure data. This allows the control system to determine the necessary adjustments before pressure deviations fully manifest, significantly improving response speed while maintaining a relatively simple control architecture through predictive rather than reactive control.
Solution Approach 2:
The patent enhances feedback by incorporating multiple sensor inputs (gas flow, air flow, temperature, pressure) and using prediction model outputs to continuously refine control decisions. This multi-parameter feedback mechanism allows the system to respond more quickly and accurately to changing conditions while compensating for furnace inertia and lag through predictive compensation.
3Measurement precision
If multi-variable prediction control algorithm is used to calculate optimum exhaust gas fan speed and regulation valve opening, then furnace pressure control accuracy and dynamic response are improved, but the control system complexity increases
Solution Approach 1:
The prediction control algorithm performs preliminary calculation of optimal control parameters (exhaust gas fan speed, regulation valve opening) by analyzing current and historical data from multiple sensors. This predictive capability enables the system to determine precise control actions in advance, significantly improving pressure control accuracy while keeping the control system architecture manageable through algorithmic rather than hardware complexity.
Solution Approach 2:
The system implements parameter changes by dynamically adjusting control parameters (fan speed, valve opening) based on prediction model outputs that consider multiple variables simultaneously. This multi-parameter control approach improves accuracy by accounting for interactions between different furnace parameters, while the computational nature of the complexity keeps physical system complexity relatively low.
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 enhances control accuracy and dynamic response, reducing overshoots and maintaining stable furnace pressure by directly controlling the exhaust gas fan speed and fine-tuning with PID regulation.
Implementation Method 1
calculating an opening degree for an exhaust gas fan based on the pre-combustion gas pressure in the furnace and the post-combustion gas pressure in the furnace
Implementation Method 2
detecting a pre-combustion gas temperature in the furnace by use of a thermocouple; detecting a post-combustion gas temperature in the furnace by use of a thermocouple
Implementation Method 3
calculating a post-combustion gas pressure in the furnace based on the pre-combustion gas pressure in the furnace, pre-combustion gas temperature in the furnace and the post-combustion gas temperature in the furnace; considering the impact of thermal expansion of gas on the furnace pressure
Data Source
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AI summary
A method for controlling furnace pressure of a continuous annealing furnace is disclosed. The method comprises detecting a coal gas flow volume and an air flow volume in each section by use of a coal gas flow volume detector and an air flow volume detector disposed in each section of a continuous annealing furnace, respectively, adding up the coal gas flow volume detected in each section to obtain a total input coal gas flow volume; adding up the air flow volume detected in each section to obtain a total input air flow volume, and calculating a pre-combustion gas pressure in the furnace based on the total input coal gas flow volume and the total input air flow volume; detecting compositions of the coal gas and a ratio of the coal gas to the air by use of a composition detector; detecting a pre-combustion gas temperature in the furnace by use of a thermocouple; predicting post-combustion gas compositions and a total gas volume based on chemical combustion reaction equations and based on the total input coal gas flow volume, the total input air flow volume, the coal gas compositions and the ratio of the coal gas to the air; igniting the coal gas and the air in the furnace; and detecting a post-combustion gas temperature in the furnace by use of a thermocouple; calculating a post-combustion gas pressure in the furnace based on the pre-combustion gas pressure in the furnace, pre-combustion gas temperature in the furnace and the post-combustion gas temperature in the furnace; and calculating an opening degree for an exhaust gas fan based on the pre-combustion gas pressure in the furnace and the post-combustion gas pressure in the furnace and by use of a gas increment pass algorithm, and using the opening degree to control the exhaust gas fan.