CN106885228A - A kind of boiler coal-air ratio optimization method and system - Google Patents
A kind of boiler coal-air ratio optimization method and system Download PDFInfo
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- CN106885228A CN106885228A CN201710073547.8A CN201710073547A CN106885228A CN 106885228 A CN106885228 A CN 106885228A CN 201710073547 A CN201710073547 A CN 201710073547A CN 106885228 A CN106885228 A CN 106885228A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F22—STEAM GENERATION
- F22B—METHODS OF STEAM GENERATION; STEAM BOILERS
- F22B35/00—Control systems for steam boilers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23N—REGULATING OR CONTROLLING COMBUSTION
- F23N5/00—Systems for controlling combustion
- F23N5/20—Systems for controlling combustion with a time programme acting through electrical means, e.g. using time-delay relays
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23N—REGULATING OR CONTROLLING COMBUSTION
- F23N2223/00—Signal processing; Details thereof
- F23N2223/06—Sampling
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23N—REGULATING OR CONTROLLING COMBUSTION
- F23N2223/00—Signal processing; Details thereof
- F23N2223/10—Correlation
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23N—REGULATING OR CONTROLLING COMBUSTION
- F23N2223/00—Signal processing; Details thereof
- F23N2223/44—Optimum control
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- Regulation And Control Of Combustion (AREA)
Abstract
The invention discloses a kind of boiler coal-air ratio optimization method and system, the history data of the measuring points such as coal-supplying amount, air output, main steam flow, main steam pressure, main steam temperature, feed temperature is obtained；Based on history data, training obtains the training relational model between boiler effective thermal efficiency and coal-supplying amount, air output and main steam flow, and using training relational model, the best proportion of corresponding coal-supplying amount and air output when boiler effective thermal efficiency is maximum is being obtained under setting constraints.The data of above-mentioned measuring point are easy to collection, history data based on collection, obtain training relational model using neural network algorithm, and herein in relation using genetic algorithm optimizing in the case where constraints is set, obtain the optimum combination ratio of the coal-supplying amount and air output when boiler effective thermal efficiency is maximum under boiler given load, optimum combination ratio according to obtaining adjusts the coal-supplying amount and air output of boiler operatiopn in time, realizes the optimal technique effect of boiler combustion efficiency.
Description
Technical field
It is to be related to a kind of boiler coal-air ratio to optimize specifically the invention belongs to combustion of industrial boiler optimisation technique field
Method and system.
Background technology
In power industry, boiler efficiency influences great to its economic benefit, in superheated steam boiler operation, coal-air ratio
Selection directly affects boiler operatiopn operating mode, and coal-air ratio is excessive, easily causes air excess, and wasted heat, efficiency of combustion is low, wind coal
Than too low, insufficient, boiler efficiency reduction of burning is easily caused.
In order that burning boiler reaches peak efficiency, it is necessary to control coal-supplying amount and air output, adjust in time between the two
Ratio.Existing optimisation technique parameter acquisition is single, and boiler efficiency calculation procedure is cumbersome, required parameter measuring point obtain difficulty compared with
Greatly, and the change of the unit load adjustment coal-air ratio effect optimal to reach boiler combustion efficiency in time can not be followed.
The content of the invention
This application provides a kind of boiler coal-air ratio optimization method and system, adjustment coal-air ratio example in time is realized, reach pot
The technique effect of stove combustion efficiency optimization.
In order to solve the above technical problems, the application is achieved using following technical scheme：
A kind of boiler coal-air ratio optimization method is proposed, including：Obtain measuring point history data；
Based on the history data, training obtain boiler effective thermal efficiency and coal-supplying amount, air output and main steam flow it
Between training relational model；Based on the training relational model, obtained in boiler effective thermal efficiency most in the case where constraints is set
The best proportion of corresponding coal-supplying amount and air output when big.
Further, the measuring point includes coal-supplying amount, air output, main steam flow and boiler effective thermal efficiency；The base
In the history data, training obtains the instruction between boiler effective thermal efficiency and coal-supplying amount, air output and main steam flow
Practice relational model, specially：With the history data of the coal-supplying amount, the history data of the air output and the master
History data between steam flow is training input, defeated to train with the history data of boiler effective thermal efficiency
Go out, the training relational model is obtained using neural metwork training.
Further, the measuring point also includes main steam pressure, main steam temperature and feed temperature；The then effective thermal effect of boiler
The acquisition methods of the history data of rate include：History data and the main steam temperature based on the main steam pressure
The history data of degree, saturated vapor enthalpy is obtained using least-squares regression approach；History based on the feed temperature
Service data, boiler feedwater enthalpy is obtained using least-squares regression approach；It is based onObtain
The history data of the boiler effective thermal efficiency；Wherein, L is the main steam flow, and H is the saturated vapor enthalpy,
GH is the boiler feedwater enthalpy, and M is the coal-supplying amount, and Q is coal net calorific value as received basis.
Further, the setting constraints includes inequality constraints condition and equality constraint；The inequality
Constraints is the upper lower limit value of coal-supplying amount and air output, wherein, the higher limit of the coal-supplying amount and air output gives coal for described
The lower limit of the maximum of the history data of amount and the air output, the coal-supplying amount and the air output gives coal for described
The minimum value of the history data of amount and the air output；The equality constraint is the real-time of the main steam flow
Value.
Further, after measuring point history data is obtained, methods described also includes：By the measuring point history run
The unit conversion of data is setting unit.
Propose a kind of boiler coal-air ratio optimization system, including multiple measuring points, history data acquisition module, training module
And optimization module；The history data acquisition module, the history data for obtaining the multiple measuring point；The instruction
Practice module, for based on the history data, training to obtain boiler effective thermal efficiency and coal-supplying amount, air output and main steam
Training relational model between flow；The optimization module, for based on the training relational model, in the case where constraints is set
Obtain the best proportion of corresponding coal-supplying amount and air output when boiler effective thermal efficiency is maximum.
Further, the measuring point includes coal-supplying amount, air output, main steam flow and boiler effective thermal efficiency；The instruction
Practice module specifically for：With the history data of the coal-supplying amount, the history data of the air output and the main steaming
History data between steam flow amount is training input, is that training is exported with the history data of boiler effective thermal efficiency,
The training relational model is obtained using neural metwork training.
Further, the measuring point also includes main steam pressure, main steam temperature and feed temperature；The system also includes pot
Stove effective thermal efficiency history data acquisition module, is used for：History data based on the main steam pressure and described
The history data of main steam temperature, saturated vapor enthalpy is obtained using least-squares regression approach；Based on the feed temperature
History data, boiler feedwater enthalpy is obtained using least-squares regression approach；It is based on
Obtain the history data of the boiler effective thermal efficiency；Wherein, L is the main steam flow, and H is the saturated vapor enthalpy
Value, GH is the boiler feedwater enthalpy, and M is the coal-supplying amount, and Q is coal net calorific value as received basis.
Further, the optimization module includes constraints setup unit, for setting inequality constraints condition and waiting
Formula constraints；The inequality constraints condition is the upper lower limit value of coal-supplying amount and air output, wherein, the coal-supplying amount and air-supply
The higher limit of amount is the maximum of the history data of the coal-supplying amount and the air output, the coal-supplying amount and the air-supply
The lower limit of amount is the minimum value of the history data of the coal-supplying amount and the air output；The equality constraint is institute
State the instantaneous value of main steam flow.
Further, the system also includes unit conversion module, for being obtained in the history data acquisition module
Take after measuring point history data, be setting unit by the unit conversion of the measuring point history data.
Compared with prior art, the advantage and good effect of the application are：The boiler coal-air ratio optimization side that the application is proposed
In method and system, coal-supplying amount, air output, main steam flow, main steam pressure, main steam temperature, feed temperature etc. are obtained easily
The history data of the measuring point of acquisition, is trained using the history data of these measuring points and obtains boiler effective thermal efficiency
Training relation between coal-supplying amount, air output, main steam flow, using the training relation, with coal-supplying amount, air output and main steaming
The history data of steam flow amount, with boiler effective thermal efficiency as object function, is being set as independent variable using genetic algorithm
Inequality constraints condition and equality constraint under carry out optimizing, obtain under boiler given load, boiler effective thermal efficiency is most
The best proportion of coal-supplying amount and air output when big；Coal-supplying amount and air output are adjusted using the best proportion in time, pot can be made
Stove operation is more stable more efficient, realizes the optimal technique effect of boiler combustion efficiency.
After the detailed description of the application implementation method is read in conjunction with the figure, other features and advantage of the application will become more
Plus it is clear.
Brief description of the drawings
Fig. 1 is the flow chart of the boiler coal-air ratio optimization method that the application is proposed；
Fig. 2 is the system block diagram that the boiler coal-air ratio that the application is proposed optimizes system.
Specific embodiment
The specific embodiment to the application is described in more detail below in conjunction with the accompanying drawings.
The boiler coal-air ratio optimization method that the application is proposed, as shown in figure 1, comprising the following steps：
Step S11：Obtain measuring point history data.
Use DCS system（Distributed Control System）The history data of measuring point is gathered, measuring point includes coal-supplying amount, air-supply
Amount, wind-warm syndrome, feed temperature, confluent, main steam flow, main steam pressure and main steam temperature etc., the data phase of these measuring points
It is easier to obtain than existing boiler parameter.
History data can according to the actual requirements set the acquisition time period, for example, obtain preceding 3 forward of current time
It service data etc., the embodiment of the present application refuses limitation.
It is setting unit by the unit conversion of these data, as shown in following table one after the service data for getting measuring point：
Table one
| Measuring point | Setting unit |
| Coal-supplying amount | Ton hour |
| Air output | Ton hour |
| Wind-warm syndrome | Degree Celsius |
| Feed temperature | Degree Celsius |
| Confluent | Ton hour |
| Main steam flow | Ton hour |
| Main steam pressure | MPa |
| Main steam temperature | Degree Celsius |
Then, hot water enthalpy table and steam enthalpy table data are obtained, data preparation is done to obtain enthalpy and temperature pressure relation, it is to avoid it
Calculate the complex process that will be tabled look-up every time afterwards.
Step S12：Based on history data, training obtains boiler effective thermal efficiency and coal-supplying amount, air output and main steaming
Training relational model between steam flow amount.
Specifically, obtaining boiler effective thermal efficiency and coal-supplying amount, air output and master with the training of radial base neural net method
Relation between steam flow, training precision is controlled 0.01：With the history data of coal-supplying amount, the history run of air output
History data between data and main steam flow is training input, and the history data with boiler effective thermal efficiency is
Training output, obtains training relational model using radial base neural net training, and the training relational model can be with approximate expression pot
Relation between stove effective thermal efficiency and training input data.
The history data of boiler effective thermal efficiency is obtained in accordance with the following methods：Going through based on main steam pressure
The history data of history service data and main steam temperature, saturated vapor is obtained using least-squares regression approach
Enthalpy, is fitted saturated vapor enthalpy and the relation between main steam pressure and main steam temperature, and the relational expression for obtaining is as follows：, wherein, H is saturated vapor enthalpy, and unit K J/Kg, P are main steam pressure value,
Unit MPa（MPa）, T is main steam temperature, degrees Celsius；Then, the history data based on feed temperature, using most
A young waiter in a wineshop or an inn multiplies homing method and obtains boiler feedwater enthalpy, obtains following relational expression：, wherein, GH is boiler feedwater enthalpy
Value, unit K J/Kg, T are feed temperature, degrees Celsius；Finally, it is based onObtaining boiler has
Imitate the history data of the thermal efficiency；Wherein, L is main steam flow, and H is saturated vapor enthalpy, and GH is boiler feedwater enthalpy, M
It is coal-supplying amount, Q is coal net calorific value as received basis.
Step S13：Based on training relational model, when obtaining maximum in boiler effective thermal efficiency under setting constraints pair
The coal-supplying amount and the best proportion of air output answered.
Calculated under boiler given load using genetic algorithm, the best proportion of coal-supplying amount and air output.Setting constraints
It is divided into inequality constraints condition and equality constraint, inequality constraints condition is the upper lower limit value of coal-supplying amount and air output, its
In, the higher limit of coal-supplying amount and air output is coal-supplying amount and the maximum of the history data of air output, coal-supplying amount and air-supply
The lower limit of amount is the minimum value of the history data of coal-supplying amount and air output；Equality constraint is the reality of main steam flow
Duration.
Specifically, for example, with the coal-supplying amount of nearest 3 days, the maximum of air output（GUB、SUB）And minimum value（GLB、
SLB）Respectively as the upper lower limit value of inequality constraints condition, then have ready conditions 1, GLB≤coal-supplying amount≤GUB, condition 2, SLB≤send
Air quantity≤SUB, by main steam flow, namely boiler load instantaneous value（EQ）As equality constraint, then 3, pot of having ready conditions
Stove given load=EQ.
Using condition 1, condition 2 and condition 3 as setting constraints, three conditions in setting are calculated using genetic algorithm
Under constraint, when boiler efficiency is maximum, under the value of corresponding coal-supplying amount and air output, i.e. boiler given load, coal-supplying amount and air-supply
The optimum combination value of amount.
The best proportion or combined value of coal-supplying amount and air output feed back to boiler operatiopn under the boiler given load that will be obtained
Personnel, boiler operatiopn personnel have found the deviation of the two by the optimum combination value for contrasting real time execution parameter He obtain, and operation sets
Standby regulation coal-supplying amount and air output, are close to the optimum combination value being calculated such that it is able to realize boiler stability and high efficiency
Operation.
In the boiler coal-air ratio optimization method that above-mentioned the application is proposed, coal-supplying amount, air output, main steam flow, main steam
The measuring points such as pressure, main steam temperature, feed temperature belong to the measuring point for easily getting service data, using the history of these measuring points
Service data is trained the training relation obtained between boiler effective thermal efficiency and coal-supplying amount, air output, main steam flow, adopts
It is effectively hot with boiler using the history data of coal-supplying amount, air output and main steam flow as independent variable with the training relation
Efficiency is object function, and optimizing is carried out under the inequality constraints condition and equality constraint of setting using genetic algorithm, is obtained
To under boiler given load, the best proportion of coal-supplying amount and air output when boiler effective thermal efficiency is maximum；Using the most ratio of greater inequality
Example adjusts coal-supplying amount and air output in time, and boiler operatiopn can be made more stable more efficient, realizes the optimal skill of boiler combustion efficiency
Art effect.Among these, saturated vapor enthalpy and boiler feedwater enthalpy have directly used least square regression calculation without computation of table lookup
Method obtains computing formula, facilitates easy-to-use, improves optimization efficiency.
Based on boiler coal-air ratio optimization method set forth above, the application also proposes a kind of boiler coal-air ratio optimization system,
As shown in Fig. 2 including multiple measuring points, history data acquisition module 21, training module 22 and optimization module 23；History run
Data acquisition module 21 is used to obtain the history data of multiple measuring points；Training module 22 is used to be based on history data,
Training obtains the training relational model between boiler effective thermal efficiency and coal-supplying amount, air output and main steam flow；Optimization module
23 are used to, based on training relational model, the corresponding coal-supplying amount when boiler effective thermal efficiency is maximum is being obtained under setting constraints
With the best proportion of air output.
Measuring point includes coal-supplying amount 201, air output 202, main steam flow 203, main steam pressure 204, main steam temperature
205th, feed temperature 206；Training module 22 specifically for：With the history data of coal-supplying amount 201, the history of air output 202
History data between service data and main steam flow 203 is training input, with the history of boiler effective thermal efficiency 241
Service data is exported for training, obtains training relational model using neural metwork training.
The system also includes boiler effective thermal efficiency history data acquisition module 24, is used for：Based on main steam pressure
204 history data and the history data of main steam temperature 205, obtain saturation and steam using least-squares regression approach
Vapour enthalpy；Based on the history data of feed temperature 206, boiler feedwater enthalpy is obtained using least-squares regression approach；Base
InObtain the history data of boiler effective thermal efficiency 241；Wherein, L is main steam flow
Amount, H is saturated vapor enthalpy, and GH is boiler feedwater enthalpy, and M is coal-supplying amount, and Q is coal net calorific value as received basis.
Optimization module 23 includes constraints setup unit 231, for setting inequality constraints condition and equality constraint bar
Part；Inequality constraints condition is the upper lower limit value of coal-supplying amount and air output, wherein, the higher limit of coal-supplying amount and air output is to coal
The lower limit of the maximum of the history data of amount and air output, coal-supplying amount and air output is coal-supplying amount and the history of air output
The minimum value of service data；Equality constraint is the instantaneous value of main steam flow.
The system also includes unit conversion module 25, for obtaining measuring point history fortune in history data acquisition module 21
It is setting unit by the unit conversion of measuring point history data after row data.
The working method of specific boiler coal-air ratio optimization system is detailed in above-mentioned boiler coal-air ratio optimization method
State, it will not go into details herein.
Boiler coal-air ratio optimization method and system that above-mentioned the application is proposed, collection are easily obtained the measuring point of service data
History data, based on history data, boiler effective thermal efficiency is obtained with coal-supplying amount, air-supply using neural network algorithm
Relation between amount and main steam flow, and herein in relation using genetic algorithm optimizing in the case where constraints is set, obtain pot
The optimum combination ratio of coal-supplying amount and air output when boiler effective thermal efficiency is maximum under stove given load, it is optimal according to what is obtained
Portfolio ratio adjusts the coal-supplying amount and air output of boiler operatiopn in time so that boiler operatiopn is more stable more efficient, realizes that boiler fires
Burn the technique effect of efficiency optimization.
It should be noted that described above is not limitation of the present invention, the present invention is also not limited to the example above,
Change, remodeling, addition or replacement that those skilled in the art are made in essential scope of the invention, also should
Belong to protection scope of the present invention.
Claims (10)
1. a kind of boiler coal-air ratio optimization method, it is characterised in that including：
Obtain measuring point history data；
Based on the history data, training obtain boiler effective thermal efficiency and coal-supplying amount, air output and main steam flow it
Between training relational model；
Based on the training relational model, obtaining corresponding to coal when boiler effective thermal efficiency is maximum under setting constraints
The best proportion of amount and air output.
2. boiler coal-air ratio optimization method according to claim 1, it is characterised in that the measuring point includes coal-supplying amount, send
Air quantity, main steam flow and boiler effective thermal efficiency；
It is described based on the history data, training obtains boiler effective thermal efficiency and coal-supplying amount, air output and main steam flow
Training relational model between amount, specially：
With between the history data of the coal-supplying amount, the history data of the air output and the main steam flow
History data is input into for training, is exported by training of the history data of boiler effective thermal efficiency, using neutral net
Training obtains the training relational model.
3. boiler coal-air ratio optimization method according to claim 2, it is characterised in that the measuring point also includes main steam pressure
Power, main steam temperature and feed temperature；
Then the acquisition methods of the history data of boiler effective thermal efficiency include：
The history data of history data and the main steam temperature based on the main steam pressure, using a most young waiter in a wineshop or an inn
Multiply homing method and obtain saturated vapor enthalpy；
Based on the history data of the feed temperature, boiler feedwater enthalpy is obtained using least-squares regression approach；
It is based onObtain the history data of the boiler effective thermal efficiency；
Wherein, L is the main steam flow, and H is the saturated vapor enthalpy, and GH is the boiler feedwater enthalpy, and M gives for described
Coal amount, Q is coal net calorific value as received basis.
4. boiler coal-air ratio optimization method according to claim 2, it is characterised in that the setting constraints is included not
Equality constraint and equality constraint；
The inequality constraints condition is the upper lower limit value of coal-supplying amount and air output, wherein, the coal-supplying amount and air output it is upper
Limit value is the maximum of the history data of the coal-supplying amount and the air output, under the coal-supplying amount and the air output
Limit value is the minimum value of the history data of the coal-supplying amount and the air output；
The equality constraint is the instantaneous value of the main steam flow.
5. boiler coal-air ratio optimization method according to claim 1, it is characterised in that obtaining measuring point history data
Afterwards, methods described also includes：
It is setting unit by the unit conversion of the measuring point history data.
6. a kind of boiler coal-air ratio optimizes system, it is characterised in that including multiple measuring points, history data acquisition module, instruction
Practice module and optimization module；
The history data acquisition module, the history data for obtaining the multiple measuring point；
The training module, for based on the history data, training to obtain boiler effective thermal efficiency with coal-supplying amount, air-supply
Training relational model between amount and main steam flow；
The optimization module, for based on the training relational model, being obtained in the effective thermal effect of boiler in the case where constraints is set
The best proportion of corresponding coal-supplying amount and air output when rate is maximum.
7. boiler coal-air ratio according to claim 6 optimizes system, it is characterised in that the measuring point includes coal-supplying amount, send
Air quantity, main steam flow and boiler effective thermal efficiency；
The training module specifically for：With the history data of the coal-supplying amount, the history data of the air output
And the history data between the main steam flow is training input, the history data with boiler effective thermal efficiency is
Training output, the training relational model is obtained using neural metwork training.
8. boiler coal-air ratio according to claim 7 optimizes system, it is characterised in that the measuring point also includes main steam pressure
Power, main steam temperature and feed temperature；
The system also includes boiler effective thermal efficiency history data acquisition module, is used for：Based on the main steam pressure
History data and the main steam temperature history data, saturated vapor is obtained using least-squares regression approach
Enthalpy；
Based on the history data of the feed temperature, boiler feedwater enthalpy is obtained using least-squares regression approach；
It is based onObtain the history data of the boiler effective thermal efficiency；
Wherein, L is the main steam flow, and H is the saturated vapor enthalpy, and GH is the boiler feedwater enthalpy, and M gives for described
Coal amount, Q is coal net calorific value as received basis.
9. boiler coal-air ratio according to claim 7 optimizes system, it is characterised in that the optimization module includes constraint bar
Part setup unit, for setting inequality constraints condition and equality constraint；
The inequality constraints condition is the upper lower limit value of coal-supplying amount and air output, wherein, the coal-supplying amount and air output it is upper
Limit value is the maximum of the history data of the coal-supplying amount and the air output, under the coal-supplying amount and the air output
Limit value is the minimum value of the history data of the coal-supplying amount and the air output；
The equality constraint is the instantaneous value of the main steam flow.
10. boiler coal-air ratio optimization method according to claim 6, it is characterised in that the system is also changed including unit
Module is calculated, after obtaining measuring point history data in the history data acquisition module, by the measuring point history
The unit conversion of service data is setting unit.
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| CN111859774A (en) * | 2019-04-29 | 2020-10-30 | 新奥数能科技有限公司 | Method and device for regulating and controlling air supply system of gas boiler |
| CN111859774B (en) * | 2019-04-29 | 2024-05-14 | 新奥数能科技有限公司 | Method and device for regulating and controlling air supply system of gas boiler |
| CN110397950A (en) * | 2019-07-30 | 2019-11-01 | 山东莱钢永锋钢铁有限公司 | A kind of boiler optimization combustion system |
| CN110397950B (en) * | 2019-07-30 | 2022-06-14 | 山东莱钢永锋钢铁有限公司 | Boiler optimization combustion system |
| CN111853848A (en) * | 2020-06-29 | 2020-10-30 | 东北电力大学 | Optimization method for fuel quantity distribution among different-layer combustors of coal-fired boiler |
| CN111853848B (en) * | 2020-06-29 | 2022-09-30 | 东北电力大学 | Optimization method for fuel quantity distribution among different-layer combustors of coal-fired boiler |
| CN112131780A (en) * | 2020-08-19 | 2020-12-25 | 华能南京金陵发电有限公司 | Thermal power plant circulating water system control method based on data mining |
| CN112131780B (en) * | 2020-08-19 | 2024-05-14 | 华能南京金陵发电有限公司 | Thermal power plant circulating water system control method based on data mining |
| CN112651568A (en) * | 2020-12-31 | 2021-04-13 | 新奥数能科技有限公司 | Boiler load dynamic adjustment method and device, control terminal and storage medium |
| CN113609684A (en) * | 2021-08-09 | 2021-11-05 | 工数科技(广州)有限公司 | Method for optimizing steam production of coal per ton of boiler based on industrial data and process mechanism |
| CN113654078A (en) * | 2021-08-20 | 2021-11-16 | 常州工学院 | Optimization method and system for boiler combustion air distribution structure |
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