Efficient combustion control system of back pressure boiler
By introducing a combustion chamber and intelligent control module into the back-pressure boiler, uniform mixing and staged combustion of fuel and air are achieved, solving the problems of low combustion efficiency and excessive pollutant emissions, and realizing efficient and stable combustion control.
Patent Information
- Application Number
- CN202510959747.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-11
- Publication Date
- 2025-10-28
AI Technical Summary
The existing back-pressure boiler combustion control system is unable to adapt to load and fuel changes, resulting in low combustion efficiency, uneven temperature distribution and excessive pollutant emissions, and lacks a real-time monitoring and feedback adjustment mechanism.
It employs a combustion chamber, a dynamic parameter matching module, a status monitoring module, a feedback module, and a performance self-optimization module to achieve uniform mixing and staged combustion of fuel and air, adjust combustion process parameters in real time, and optimize the combustion process through closed-loop control and deep learning models.
Improve combustion efficiency, reduce fuel consumption, reduce pollutant generation and emissions, ensure operational stability, meet environmental protection standards, and avoid efficiency degradation caused by equipment aging.
Smart Images
Figure CN120845787A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of power generation equipment technology, and specifically relates to a high-efficiency combustion control system for a back-pressure boiler. Background Technology
[0002] As a commonly used industrial equipment, the optimization of combustion control in aluminum back-pressure boilers is crucial for energy conservation and emission reduction. Existing technologies generally suffer from the following shortcomings: First, combustion control methods often employ fixed airflow ratios and single fuel injection strategies. When boiler load or fuel characteristics change, the system cannot adaptively adjust, leading to uneven fuel-air mixing, low combustion efficiency, and excessive pollutant emissions. Second, the airflow organization design lacks systematic optimization. An unreasonable aerodynamic field within the furnace results in uneven temperature distribution, easily forming localized high-temperature zones or oxygen-deficient zones. This not only exacerbates nitrogen oxide formation but also affects combustion stability. Third, existing control systems generally lack precise real-time monitoring and feedback adjustment mechanisms. They cannot form closed-loop control based on key indicators such as oxygen content, carbon monoxide, nitrogen oxide concentration, and combustion zone temperature gradient in the flue gas at the furnace outlet. This makes it difficult to dynamically optimize the combustion process and continuously verify and optimize control strategies during long-term operation to maintain optimal combustion conditions. Summary of the Invention
[0003] In view of the deficiencies in the prior art, the present invention provides a high-efficiency combustion control system for back-pressure boilers to solve the above-mentioned technical problems.
[0004] A high-efficiency combustion control system for a back-pressure boiler includes the following:
[0005] The combustion chamber is used to achieve uniform mixing of fuel and air and staged combustion;
[0006] The parameter dynamic matching module is used to calculate and output combustion process parameters in real time based on boiler load, fuel characteristics and air preheating temperature. The combustion process parameters include primary air volume, secondary air volume, fuel supply rate and air-fuel ratio.
[0007] The status monitoring module is used to monitor the oxygen content of the flue gas at the furnace outlet, the concentration of carbon monoxide and nitrogen oxides in the tail flue, and the temperature gradient in the combustion zone in real time.
[0008] The feedback module is used to dynamically adjust the combustion process parameters based on the deviation between the output data of the status monitoring module and the preset target value through a closed-loop control algorithm.
[0009] The performance self-optimization module is used to continuously evaluate comprehensive performance indicators and automatically start the optimization program when the indicators fail to meet the standards, while simultaneously correcting the parameter dynamic matching module.
[0010] Preferably, the system also includes a combustion regulation module for maintaining the air-fuel ratio within a set combustion range based on combustion process parameters and controlling the combustion chamber temperature within a set range.
[0011] Preferably, the combustion regulation module is equipped with a multivariate regression algorithm and a deep learning model.
[0012] The multivariate regression algorithm is used to adjust the fuel supply rate based on the air-to-fuel ratio and combustion chamber temperature.
[0013] The deep learning model is used to automatically adjust the parameters of the multivariate regression algorithm based on historical operating data to adapt to changes in different operating conditions.
[0014] Preferably, when dynamically adjusting the combustion process parameters through a closed-loop control algorithm, the following is specifically included:
[0015] When the oxygen content of the flue gas is below 3.5% and the carbon monoxide concentration exceeds the set range, increase the secondary air volume by 10%-15% and reduce the fuel supply rate.
[0016] Preferably, the status monitoring module specifically includes:
[0017] Oxygen sensor used to detect the oxygen content of flue gas at the furnace outlet;
[0018] A carbon monoxide sensor used to detect the carbon monoxide concentration in the tail flue;
[0019] A nitrogen oxide sensor used to detect the concentration of nitrogen oxides in the tail flue;
[0020] Temperature sensor used to detect the temperature of the combustion zone furnace.
[0021] Preferably, multiple temperature sensors are provided, and the vertical installation height of the multiple temperature sensors is different.
[0022] Preferably, the performance self-optimization module sets the following indicators: combustion efficiency not less than 90%, exhaust gas temperature not higher than 160℃, incomplete combustion loss not higher than 1.5%, and nitrogen oxide emission concentration not higher than 200mg / Nm³.
[0023] Preferably, when the combustion efficiency is below 90%, the performance self-optimization module adjusts the swirl angle and wind speed of the primary air to enhance the initial mixing of fuel and air.
[0024] Preferably, when the nitrogen oxide emission concentration exceeds 200 mg / Nm³, the performance self-optimization module optimizes the stratified arrangement and injection angle of the secondary air to further suppress the formation of thermal nitrogen oxides.
[0025] Preferably, the optimization procedure is as follows: primary air is injected at an incident angle of 25°-35°, accounting for 35%-45% of the total air volume, to form a central recirculation zone; secondary air is arranged in layers in the upper part of the combustion chamber, injected at an incident angle of 40°-50°, and the wind speed is controlled at 30m / s-40m / s, so as to achieve staged combustion.
[0026] The beneficial effects of this invention are as follows: Through dynamic and intelligent closed-loop control, it completely solves the fundamental defect of traditional fixed-ratio methods that cannot adapt to changes in operating conditions, ensuring that fuel can achieve optimal mixing and staged combustion with air under any load and fuel quality fluctuations, thereby significantly improving combustion efficiency and reducing fuel consumption. Simultaneously, through precise control of the furnace temperature field and flue gas composition, it effectively suppresses the formation of local high-temperature zones and oxygen-deficient zones, significantly reducing the generation and emission of pollutants such as nitrogen oxides and carbon monoxide from the source, easily meeting increasingly stringent environmental standards. Furthermore, the system's continuous monitoring and self-optimization capabilities avoid efficiency degradation caused by equipment aging or improper operation, ultimately achieving multiple goals of energy saving, environmental protection, and operational stability. Attached Figure Description
[0027] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0028] Figure 1 A schematic diagram of a high-efficiency combustion control system for a back-pressure boiler provided by the present invention;
[0029] Figure 2 This is a schematic diagram of the status monitoring module of a back-pressure boiler high-efficiency combustion control system provided by the present invention. Detailed Implementation
[0030] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.
[0031] The following disclosure provides many different embodiments or examples for implementing different structures of the present invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Of course, these are merely examples and are not intended to limit the present invention.
[0032] The embodiments of the invention will now be described in detail with reference to the accompanying drawings.
[0033] like Figure 1 As shown, a high-efficiency combustion control system for a back-pressure boiler includes the following:
[0034] The combustion chamber is used to achieve uniform mixing of fuel and air and staged combustion;
[0035] The parameter dynamic matching module is used to calculate and output combustion process parameters in real time based on boiler load, fuel characteristics and air preheating temperature. The combustion process parameters include primary air volume, secondary air volume, fuel supply rate and air-fuel ratio.
[0036] The status monitoring module is used to monitor the oxygen content of the flue gas at the furnace outlet, the concentration of carbon monoxide and nitrogen oxides in the tail flue, and the temperature gradient in the combustion zone in real time.
[0037] The feedback module is used to dynamically adjust the combustion process parameters based on the deviation between the output data of the status monitoring module and the preset target value through a closed-loop control algorithm.
[0038] The performance self-optimization module is used to continuously evaluate comprehensive performance indicators and automatically start the optimization program when the indicators fail to meet the standards, while simultaneously correcting the parameter dynamic matching module.
[0039] First, by optimizing the airflow organization of the combustion chamber, it is ensured that the fuel and combustion air form a strong rotation and mixing upon entering the furnace. Air is supplied at different speeds and proportions in different zones according to the combustion stage, achieving uniform fuel mixing and staged combustion. Next, a deployed parameter dynamic matching module collects real-time data on the boiler's load demand, fuel calorific value and moisture content analyzed by sensors, and the air preheater outlet temperature. Based on a built-in multivariate regression algorithm and fuzzy control model, this module abandons a fixed air-fuel ratio and dynamically calculates a series of optimal combustion process parameters under the current operating conditions, such as primary air volume, secondary air volume, and fuel supply rate, and sends instructions to the corresponding actuators, such as the fan frequency converter and fuel feeder. Simultaneously, the condition monitoring module uses multiple sensors located at key positions such as the furnace outlet and tail flue to continuously measure the oxygen content, carbon monoxide and nitrogen oxide concentrations in the flue gas, as well as the combustion zone temperature gradient sensed by a thermocouple array, transmitting these real-time data streams to the feedback module. The core of the feedback module is a closed-loop control algorithm that compares the monitored actual data with the system's preset ideal target values. If a deviation occurs, it immediately fine-tunes the various process parameters output by the parameter dynamic matching module, forming a fast and precise dynamic closed-loop adjustment to ensure the combustion process always stays close to optimal conditions. Furthermore, the performance self-optimization module continuously records and comprehensively evaluates macroscopic performance indicators such as combustion efficiency, exhaust temperature, and total pollutant emissions. When it determines that the overall system performance has not reached the preset optimal standard or that efficiency is declining due to equipment aging, it automatically initiates an optimization program. For example, it tests the effects of different parameter combinations through small perturbations and analyzes the results using machine learning algorithms. Ultimately, it not only adjusts the current operating parameters but also corrects and calibrates the basic model within the parameter dynamic matching module, thereby achieving system self-evolution and long-term efficient operation.
[0040] Compared to existing technologies, this system, through dynamic and intelligent closed-loop control, completely solves the fundamental flaw of traditional fixed-ratio methods in adapting to changing operating conditions. It ensures optimal mixing and staged combustion of fuel with air under any load and fuel quality fluctuations, thereby significantly improving combustion efficiency and reducing fuel consumption. Simultaneously, through precise control of the furnace temperature field and flue gas composition, it effectively suppresses the formation of localized high-temperature and oxygen-deficient zones, significantly reducing the generation and emission of pollutants such as nitrogen oxides and carbon monoxide at the source, easily meeting increasingly stringent environmental standards. Furthermore, the system's continuous monitoring and self-optimization capabilities prevent efficiency degradation due to equipment aging or improper operation, ultimately achieving multiple goals of energy saving, environmental protection, and operational stability.
[0041] More specifically, it also includes a combustion regulation module, which is used to maintain the air-fuel ratio within a set combustion range based on combustion process parameters and to control the combustion chamber temperature within a set range.
[0042] Instead of waiting for the entire feedback module to complete a slow-cycle evaluation based on flue gas composition, the combustion regulation module directly issues fine-tuning commands to actuators such as fuel valves, feeders, and dampers / frequency converters for primary and secondary air. By rapidly increasing or decreasing fuel or air volume, it quickly pulls key combustion parameters back to the set narrow band range.
[0043] More specifically, the combustion regulation module is equipped with a multivariate regression algorithm and a deep learning model.
[0044] The multivariate regression algorithm is used to adjust the fuel supply rate based on the air-to-fuel ratio and combustion chamber temperature.
[0045] The deep learning model is used to automatically adjust the parameters of the multivariate regression algorithm based on historical operating data to adapt to changes in different operating conditions.
[0046] During boiler operation, the multivariate regression algorithm continuously receives high-frequency data streams from the condition monitoring module, including the current actual air-fuel ratio and combustion zone temperature gradient. This data is then substituted into the regression equation to calculate a fuel supply rate adjustment command aimed at stabilizing combustion and suppressing pollutants. This command is sent to the feeder for execution, while simultaneously adjusting the damper opening to maintain the air-fuel ratio. The model continuously collects and learns from massive amounts of historical operating data, including not only the air-fuel ratio and temperature used in the regression algorithm but also operating condition information such as boiler load, fuel batch characteristics, air humidity, final combustion efficiency, and pollutant emissions. Through deep learning of this high-dimensional data, the model can gain insights into the profound impact of slowly changing factors such as equipment aging, fuel characteristic variations, or different operating habits on the combustion process. Based on these insights, the deep learning model periodically and automatically corrects and optimizes the internal parameters of the multivariate regression algorithm running in the foreground, then pushes the updated parameters back to the regression algorithm. This constitutes a two-layer intelligent structure, enabling continuous self-evolution of the control strategy.
[0047] More specifically, when dynamically adjusting the combustion process parameters through a closed-loop control algorithm, the following are included:
[0048] When the oxygen content of the flue gas is below 3.5% and the carbon monoxide concentration exceeds the set range, increase the secondary air volume by 10%-15% and reduce the fuel supply rate.
[0049] In actual operation, the status monitoring module transmits key data such as the oxygen content, carbon monoxide concentration, and nitrogen oxide concentration of the flue gas at the furnace outlet to the feedback module in real time at a high frequency. The control algorithm within the feedback module continuously compares these real-time values with preset thresholds. Once the combined condition of "flue gas oxygen content below 3.5% and carbon monoxide concentration exceeding the set range" is triggered, the system immediately determines that the current combustion state is incomplete combustion, i.e., excessive fuel and insufficient air. At this time, the control algorithm sends a command to the frequency converter or damper actuator of the secondary air fan to increase its output by 10% to 15% to quickly replenish the combustion air in the rear of the furnace, ensuring that unburned carbon monoxide can be fully oxidized; at the same time, it appropriately reduces the fuel supply rate to reduce the imbalance between fuel and air at the source.
[0050] like Figure 2 As shown, more specifically, the status monitoring module includes:
[0051] Oxygen sensor used to detect the oxygen content of flue gas at the furnace outlet;
[0052] A carbon monoxide sensor used to detect the carbon monoxide concentration in the tail flue;
[0053] A nitrogen oxide sensor used to detect the concentration of nitrogen oxides in the tail flue;
[0054] Temperature sensor used to detect the temperature of the combustion zone furnace.
[0055] More specifically, there are multiple temperature sensors, and the vertical installation height of the multiple temperature sensors is different.
[0056] On the furnace wall of the boiler combustion chamber, several representative cross-sectional heights are selected vertically, and at least one temperature sensor is installed at each height. The lowest layer of sensors may be positioned slightly above the main burner or grate to monitor fuel ignition and the temperature of the initial combustion zone. The middle layer of sensors is positioned in the core combustion zone where the flame is most vigorous to capture peak combustion temperatures. Higher layers of sensors are located below the burnout zone to monitor the degree of burnout of refractory materials such as coke and the afterburning effect of secondary air. The top layer of sensors is close to the furnace outlet to measure the outlet flue gas temperature at the end of combustion. Through this vertically layered, staggered three-dimensional layout, multiple sensors together form a longitudinal stepped temperature range. This allows for the dynamic calculation of the "temperature gradient" or temperature difference between adjacent or any two vertical points, enabling real-time and precise depiction of the temperature evolution profile of the entire combustion process from bottom to top within the furnace.
[0057] More specifically, the performance self-optimization module sets the following indicators: combustion efficiency not less than 90%, exhaust gas temperature not higher than 160℃, incomplete combustion loss not higher than 1.5%, and nitrogen oxide emission concentration not higher than 200mg / Nm³.
[0058] Under normal circumstances, as long as all indicators are within the set acceptable range, the module will silently record and accumulate data. However, once any one or more indicators are detected to have exceeded the set boundaries, the module will be immediately activated, automatically launching its built-in optimization program. The core of this optimization program is usually an intelligent search algorithm that aims to pull all deviating indicators back into the acceptable range and optimize them as much as possible to the objective function. The algorithm uses its long-term learned data model to strategically and incrementally adjust the parameters to dynamically match the module's underlying control logic, continuously iterating and correcting until it finds a new set of control parameters that allows all objectives to be met. Then, it solidifies this new set of control parameters into the system's control model, completing its self-evolution.
[0059] More specifically, when the combustion efficiency is below 90%, the performance self-optimization module adjusts the swirl angle and wind speed of the primary air to enhance the initial mixing of fuel and air.
[0060] More specifically, when the nitrogen oxide emission concentration exceeds 200 mg / Nm³, the performance self-optimization module optimizes the stratified arrangement and injection angle of the secondary air to further suppress the formation of thermal nitrogen oxides.
[0061] More specifically, the optimization procedure is as follows: primary air is injected at an incident angle of 25°-35°, accounting for 35%-45% of the total air volume, to form a central recirculation zone; secondary air is arranged in layers in the upper part of the combustion chamber, injected at an incident angle of 40°-50°, and the wind speed is controlled at 30m / s-40m / s, so as to achieve staged combustion.
[0062] For the primary air system, an incident angle of 25° to 35° is designed to generate sufficient rotational kinetic energy in the incoming airflow, thereby forming a low-pressure central recirculation zone in the central area of the burner outlet. This recirculation zone actively draws the high-temperature flue gas from the upper part of the furnace back to the root of the flame, immediately heating and igniting the newly entering fuel. Simultaneously, the primary air volume is strictly controlled within the range of 35%-45% of the total air volume, ensuring that only the portion of oxygen required for fuel evaporation is provided, creating a stable, fuel-rich, reducing combustion atmosphere in the flame core. Next, for the secondary air system, this large angle design of 40° to 50°, combined with a high wind speed of 30 m / s to 40 m / s, ensures that the secondary airflow can travel a distance close to the furnace wall, delaying its mixing with the main flame, thus spatially lengthening and separating the combustion process. This high-momentum secondary air ultimately penetrates and strongly draws in the combustible-rich flue gas in the latter part of the furnace, forming intense turbulent mixing, ensuring sufficient oxygen to burn off the remaining coke.
[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.
Claims
1. A high-efficiency combustion control system for a back-pressure boiler, characterized in that, The system includes the following components: a combustion chamber for achieving uniform mixing and staged combustion of fuel and air; a dynamic parameter matching module for calculating and outputting combustion process parameters in real time based on boiler load, fuel characteristics, and air preheating temperature, including primary air volume, secondary air volume, fuel supply rate, and air-fuel ratio; a status monitoring module for real-time monitoring of the oxygen content in the flue gas at the furnace outlet, the carbon monoxide and nitrogen oxide concentrations in the tail flue, and the temperature gradient in the combustion zone; a feedback module for dynamically adjusting the combustion process parameters based on the deviation between the output data of the status monitoring module and the preset target value using a closed-loop control algorithm; and a performance self-optimization module for continuously evaluating comprehensive performance indicators and automatically initiating an optimization program when indicators fail to meet standards, while simultaneously correcting the dynamic parameter matching module.
2. The high-efficiency combustion control system for a back-pressure boiler according to claim 1, characterized in that, It also includes a combustion control module, which is used to maintain the air-fuel ratio within a set combustion range based on combustion process parameters and to control the combustion chamber temperature within a set range.
3. The high-efficiency combustion control system for a back-pressure boiler according to claim 2, characterized in that, The combustion regulation module is equipped with a multivariate regression algorithm and a deep learning model. The multivariate regression algorithm is used to regulate the fuel supply rate based on the air-fuel ratio and combustion chamber temperature. The deep learning model is used to automatically adjust the parameters of the multivariate regression algorithm based on historical operating data to adapt to changes in different operating conditions.
4. The high-efficiency combustion control system for a back-pressure boiler according to claim 1, characterized in that, When dynamically adjusting the combustion process parameters through a closed-loop control algorithm, the following specific steps are included: when the oxygen content of the flue gas is below 3.5% and the carbon monoxide concentration exceeds the set range, the secondary air volume is increased by 10%-15% and the fuel supply rate is reduced.
5. The high-efficiency combustion control system for a back-pressure boiler according to claim 1, characterized in that, The status monitoring module specifically includes: an oxygen content sensor for detecting the oxygen content of flue gas at the furnace outlet; a carbon monoxide sensor for detecting the carbon monoxide concentration in the tail flue; a nitrogen oxide sensor for detecting the nitrogen oxide concentration in the tail flue; and a temperature sensor for detecting the furnace temperature in the combustion zone.
6. The high-efficiency combustion control system for a back-pressure boiler according to claim 5, characterized in that, The temperature sensor is provided in multiple units, and the vertical installation height of the multiple temperature sensors is different.
7. The high-efficiency combustion control system for a back-pressure boiler according to claim 1, characterized in that, The performance self-optimization module is set with the following indicators: combustion efficiency not less than 90%, exhaust gas temperature not higher than 160℃, incomplete combustion loss not higher than 1.5%, and nitrogen oxide emission concentration not higher than 200mg / Nm³.
8. The high-efficiency combustion control system for a back-pressure boiler according to claim 7, characterized in that, When the combustion efficiency is below 90%, the performance self-optimization module adjusts the swirl angle and wind speed of the primary air to enhance the initial mixing of fuel and air.
9. The high-efficiency combustion control system for a back-pressure boiler according to claim 7, characterized in that, When the concentration of nitrogen oxide emissions exceeds 200 mg / Nm³, the performance self-optimization module optimizes the stratified arrangement and injection angle of the secondary air to further suppress the formation of thermal nitrogen oxides.
10. The high-efficiency combustion control system for a back-pressure boiler according to claim 7, characterized in that, The optimization procedure is as follows: primary air is injected at an incident angle of 25°-35°, accounting for 35%-45% of the total air volume, to form a central recirculation zone; secondary air is arranged in layers in the upper part of the combustion chamber, injected at an incident angle of 40°-50°, and the wind speed is controlled at 30m / s-40m / s to achieve staged combustion.