CN106054608A - Fuzzy control method and system for waste incineration flue gas denitration SNCR (Selective Non Catalytic Reduction) - Google Patents

Abstract

The invention provides a fuzzy control method and system for waste incineration flue gas denitration SNCR (Selective Non Catalytic Reduction). The method comprises: receiving a detection input quantity sent by a detection device, and calculating a deviation between the detection input quantity and a given value and a change rate of the deviation as input variables of fuzzy control; fuzzifying the input variables into fuzzy input quantities, performing fuzzy reasoning and decision making based on the fuzzy input quantities to obtain a fuzzy output quantity, and de-fuzzifying the fuzzy output quantity into a control output quantity; and outputting the control output quantity to an ammonia water allocation controller to control the flow rates of an upper layer of ammonia water and a lower layer of ammonia water, wherein the detection input quantity comprises nitrogen oxide content in flue gas, and the control output quantity is given data of the adding amount of ammonia water. According to the method and the system, the stability of a nitrogen oxide content index in the flue gas is realized by adopting a fuzzy control strategy and controlling the adding amount of ammonia water, so that frequent intervention of equipment operators on a flue gas denitration system is reduced, and stable operation of the flue gas denitration system is realized.

Description

Fuzzy control method and system for flue gas of refuse burning denitration SNCR

Technical field

The present invention relates to the denitration process field in incinerator, in particular to one for flue gas of refuse burning The fuzzy control method of denitration SNCR and system.

Background technology

The flue gas of waste incineration discharge (includes NO, NO containing substantial amounts of nitrogen oxide NOx₂、N₂O₃、N₂O etc.), at present China's flue gas of refuse burning denitration processes SNCR denitration technology in the widely used stove of technique.Denitrating flue gas SNCR using ammonia as one Plant medicament and spray in incinerator the 1st flue, reduce content of nitric oxide in flue gas, reach the purpose of denitration, the dosage of ammonia It is directly connected to nitric oxide production content in flue gas with distribution.

Denitrating flue gas SNCR control system is the important component part that flue gas of refuse burning processes, the quality that this system is run Fume emission index will be directly affected.Smoke temperature change in Refuse Incineration Process is fast, and the fluctuation of nitrogen oxides index is difficult to greatly Control, accordingly, it would be desirable to equipment operations staff frequently intervening so that denitrating flue gas SNCR is controlled denitrating system, cause and be The instability that system runs.

Summary of the invention

For the deficiencies in the prior art, the present invention provides a kind of fuzzy control side for flue gas of refuse burning denitration SNCR Method, including:

The detection input quantity that receiving detection device sends, and calculate deviation between described detection input quantity and set-point with And the rate of change of described deviation is using the input variable as fuzzy control；

Turn to Indistinct Input amount by fuzzy for described input variable, carry out fuzzy reasoning and decision-making based on described Indistinct Input amount To obtain fuzzy output amount, and by described fuzzy output amount defuzzification for controlling output；

By described control output output to ammonia dispensing controller to control upper strata ammonia and the flow of lower floor's ammonia,

Wherein, described detection input quantity includes the amount of nitrogen oxides in flue gas, contains with the nitrogen oxides in described flue gas Measure corresponding control output be ammonia add total amount data-oriented.

In one example, described turn to Indistinct Input amount include reflecting described input variable by fuzzy for described input variable Penetrate and transform to discrete input domain.

In one example, described input variable quantifies according to the following formula:

$Y=\frac{2n\×\[x-(a+b)\÷2\]}{b-a}$

Wherein, x represents described input variable, and Y represents the input variable after quantization, and a represents the lower limit of described input variable, B represents the upper limit of described input variable, and n represents quantification gradation.

In one example, described defuzzification is carried out according to the following formula:

$Y=\frac{x+n}{2\×n}\×(b-a)+a$

Wherein, x represents described fuzzy output amount, and Y represents described control output, and a represents under described fuzzy output amount Limit, b represents the upper limit of described fuzzy output amount, and n represents quantification gradation.

In one example, input domain corresponding to described input variable is set to 4, corresponding defeated of described fuzzy output amount Go out domain and be set to 6.

In one example, the Linguistic Value fuzzy subset of described Indistinct Input amount is that [negative big (NB), bears little (NS), zero (O), the least (PS), honest (PB)].

In one example, the Linguistic Value fuzzy subset of described fuzzy output amount is that [negative big (NB), in bearing (NM), bears little (NS), zero (O), the least (PS), hit exactly (PM), honest (PB)].

In one example, the membership function of the Linguistic Value fuzzy subset of described Indistinct Input amount and described fuzzy output amount The membership function of Linguistic Value fuzzy subset be triangular function.

In one example, the deviation range of the amount of nitrogen oxides in described flue gas is [-50,50], in described flue gas The deviation variation rate scope of amount of nitrogen oxides be [-20,20], the total amount data-oriented scope that adds of described ammonia for [38, 63]。

The present invention also provides for a kind of Fuzzy control system for flue gas of refuse burning denitration SNCR, including:

Input module, the detection input quantity sent for receiving detection device, and calculate described detection input quantity with given Deviation between value and the rate of change of described deviation are using the input variable as fuzzy control；

Processing module, for turning to Indistinct Input amount by fuzzy for described input variable, is carried out based on described Indistinct Input amount Fuzzy reasoning and decision-making are to obtain fuzzy output amount, and are control output by described fuzzy output amount defuzzification；

Output module, for exporting described control output to ammonia dispensing controller to control upper strata ammonia and lower floor The flow of ammonia,

Wherein, described detection input quantity includes the amount of nitrogen oxides in flue gas, contains with the nitrogen oxides in described flue gas Measure corresponding control output be ammonia add total amount data-oriented.

According to the present invention, fuzzy control strategy is used to aoxidize by ammonia adds the nitrogen in the control realization flue gas of total amount Stablizing of thing content's index, reduces the equipment operations staff frequent intervention to flue gas denitrification system, contributes to flue gas denitrification system Stable operation.

Accompanying drawing explanation

The drawings below of the present invention is used for understanding the present invention in this as the part of the present invention.Shown in the drawings of this Bright embodiment and description thereof, be used for explaining the principle of the present invention.

In accompanying drawing:

Fig. 1 shows the stream of the fuzzy control method for flue gas of refuse burning denitration SNCR according to embodiments of the present invention Cheng Tu；

Fig. 2 shows that the fuzzy control method for flue gas of refuse burning denitration SNCR according to embodiments of the present invention is applied Signal data flow graph when exemplary scenario；

Fig. 3 shows the knot of the Fuzzy control system for flue gas of refuse burning denitration SNCR according to embodiments of the present invention Structure block diagram.

Detailed description of the invention

In the following description, a large amount of concrete details is given to provide more thorough understanding of the invention.So And, it is obvious to the skilled person that the present invention can be able to without these details one or more Implement.In other example, in order to avoid obscuring with the present invention, technical characteristics more well known in the art are not entered Line description.

In order to thoroughly understand the present invention, detailed method step and/or structure will be proposed in following description.Obviously, The execution of the present invention is not limited to specific details appreciated by those skilled in the art.Presently preferred embodiments of the present invention is detailed It is described as follows, but in addition to these describe in detail, the present invention can also have other embodiments.

It should be appreciated that the present invention can implement in different forms, and should not be construed as being limited to propose here Embodiment.On the contrary, it is open thoroughly with complete to provide these embodiments to make, and will fully convey the scope of the invention to Those skilled in the art.In the accompanying drawings, in order to clear, the size in Ceng He district and relative size may be exaggerated.From start to finish Same reference numerals represents identical element.

It should be appreciated that when using term " to comprise " in this manual and/or time " including ", it indicates that existence is described Feature, entirety, step, operation, element and/or assembly, but do not preclude the presence or addition of other features one or more, entirety, Step, operation, element, assembly and/or combinations thereof." one ", " one " and " described/to be somebody's turn to do " of singulative is also intended to include Plural form, unless context is expressly noted that other mode.

Ammonia is sprayed in incinerator the 1st flue as a kind of medicament by denitrating flue gas SNCR, reduces nitric oxide in flue gas Content, reaches the purpose of denitration, and the dosage of ammonia and distribution are directly connected to nitric oxide production content in flue gas.Denitrating flue gas SNCR control system is the important component part that flue gas of refuse burning processes, and the quality that this system is run will directly affect flue gas row Put index.Smoke temperature change in Refuse Incineration Process is fast, and the fluctuation of nitrogen oxides index is difficult to greatly control, accordingly, it would be desirable to set Received shipment administrative staff frequently intervening so that denitrating flue gas SNCR to be controlled denitrating system, cause the instability that system is run.

In order to solve the problems referred to above, the present invention proposes a kind of fuzzy control side for flue gas of refuse burning denitration SNCR Method, fuzzy controller is by the nitrogen oxides (NO in flue gas_X) amount of nitrogen oxides that content is given and actual, calculate ammonia The actual total amount that adds, ammonia dispensing controller according to the actual measured value of incinerator the 1st flue outlet infrared temperature by ammonia The actual total amount that adds be set as upper strata ammonia dosage and lower floor's ammonia dosage, ammonia flow PID controller is according to setting Ammonia dosage control ammonia converter operating frequency with realize to upper strata ammonia and the flow-control of lower floor's ammonia, thus Ensure the stability of nitrogen oxides in effluent content's index.

Fig. 1 shows the stream of the fuzzy control method for flue gas of refuse burning denitration SNCR according to embodiments of the present invention Cheng Tu.As it is shown in figure 1, the fuzzy control method for flue gas of refuse burning denitration SNCR comprises the steps:

Step 101: receiving detection device send detection input quantity, and calculate detection input quantity and set-point between inclined The rate of change of difference and this deviation is using the input variable as fuzzy control.

Wherein it is possible to demand for control based on the design parameter to waste incineration arrange required detection input parameter and Corresponding detection device.Such as, in an example of the present invention, need the amount of nitrogen oxides in flue gas is controlled System, then corresponding sensor can be set to the amount of nitrogen oxides detecting in flue gas.

Calculate detection input quantity and set-point between deviation (or referred to as error) E and this deviation rate of change (or Be referred to as error transform rate) DE time, can be by actual value (the also referred to as process of the amount of nitrogen oxides in detected flue gas Value) corresponding set-point compares and obtains deviation signal, and deviation signal carries out differential to obtain the rate of change of deviation. Fuzzy control can be using above-mentioned deviation and deviation variation rate as input variable.

Step 102: turn to Indistinct Input amount by fuzzy for input variable, carry out fuzzy reasoning and decision-making based on Indistinct Input amount To obtain fuzzy output amount, and by fuzzy output amount defuzzification for controlling output.

Specifically, can be by input variable mapping transformation to discrete input domain, to obtain Indistinct Input amount.Continue Above example, the deviation range of the amount of nitrogen oxides in flue gas is [-50,50], the amount of nitrogen oxides in flue gas inclined Difference rate of change scope is [-20,20].

In an example of the present invention, input variable can quantify according to formula (1-1):

$Y=\frac{2n\×\[x-(a+b)\÷2\]}{b-a}---(1-1)$

Wherein, in formula (1-1), x represent input variable, Y represent quantization after input variable, a represents input variable Lower limit, b represents the upper limit of input variable, and n represents quantification gradation.

Due to less demanding to the control accuracy of the amount of nitrogen oxides in flue gas, in one example, input is become Amount domain is set to 4, and the fuzzy subset of variable Linguistic Value can be [NB, NS, O, PS, PB], it is possible to meets requirement.At one In example, for output variable, in order to anti-locking system shakes, output variable domain is set to 6, the fuzzy subset of variable Linguistic Value Can be [NB, NM, NS, O, PS, PM, PB] that wherein, NB represents negative big, NM represent negative in, NS represents negative little, and O represents zero, PS Representing the least, PM represents that center, PB represent honest.Membership function for input/output variable uses relatively simple triangle Shape function.

The assignment table of the deviation (input variable) of the amount of nitrogen oxides in flue gas is as shown in the table:

Table 1:NOx deviation E assignment table

The assignment table of the deviation variation rate (input variable) of the amount of nitrogen oxides in flue gas is as shown in the table:

Table 2:NOx deviation variation rate DE assignment table

Ammonia add total amount (output variable) assignment table as shown in the table:

Table 3: ammonia adds total amount OUTPUT1 assignment table

According to one embodiment of present invention, the design in Fuzzy strategy storehouse can be as follows:

If deviation is honest and deviation variation rate is honest, then it is output as negative big；

If deviation is honest and deviation variation rate is center, then it is output as negative big；

If deviation is honest and deviation variation rate is zero, then in being output as bearing；

If deviation is honest and deviation variation rate is in negative, then be output as negative in；

If deviation is honest and deviation variation rate is for negative big, then it is output as negative little；

If deviation is honest for center and deviation variation rate, then it is output as negative big；

If deviation is center for center and deviation variation rate, then in being output as bearing；

If deviation is zero for center and deviation variation rate, then in being output as bearing；

If deviation in negative, is then output as negative little for center and deviation variation rate；

If deviation is big for bearing for center and deviation variation rate, then it is output as negative little；

If deviation is zero and deviation variation rate is honest, then it is output as negative little；

If deviation is zero and deviation variation rate is center, then it is output as zero；

If deviation is zero and deviation variation rate is zero, then it is output as negative zero；

If deviation is zero and deviation variation rate is in negative, then it is output as zero little；

If deviation is zero and deviation variation rate is for negative big, then it is output as the least；

If deviation is in negative and deviation variation rate is honest, then it is output as the least；

If deviation is in negative and deviation variation rate is center, then it is output as the least；

If deviation is in negative and deviation variation rate is zero, then it is output as center；

If deviation is in negative and deviation variation rate is in negative, then it is output as center；

If deviation is in negative and deviation variation rate is for negative big, then it is output as honest；

If deviation is honest for negative big and deviation variation rate, then it is output as the least；

If deviation is center for negative big and deviation variation rate, then it is output as the least；

If deviation is zero for negative big and deviation variation rate, then it is output as center；

If deviation in negative, is then output as center for negative big and deviation variation rate；

If deviation is negative big for negative big and deviation variation rate, then it is output as honest.

Membership function according to fuzzy language value and Fuzzy strategy storehouse, can obtain fuzzy relation.Mamdani is used to push away Logos, fuzzy relationship matrix r is drawn by following formula:

R=E × DE × OUTPUT1 (1-2)

Wherein, in formula (1-2), R represents fuzzy relation matrix；E represents that the deviation of the amount of nitrogen oxides in flue gas is (defeated Enter variable)；DE represents the deviation variation rate (input variable) of the amount of nitrogen oxides in flue gas；OUTPUT1 represents the throwing of ammonia Add total amount (output variable).

Based on Indistinct Input amount and fuzzy relation, fuzzy output amount can be obtained.

First, the membership vector of output variable is drawn by following formula:

U=E × DE × R (1-3)

Wherein, in formula (1-3), U represents the membership vector of output variable；R represents fuzzy relation matrix；E represents cigarette The deviation (input variable) of the amount of nitrogen oxides in gas；DE represents that the deviation variation rate of the amount of nitrogen oxides in flue gas is (defeated Enter variable).

Then, fuzzy output amount is drawn by following formula:

$u=\frac{\underset{k=-6}{\overset{k=6}{\Σ}}{\mathrm{ku}}_k}{\underset{k=-6}{\overset{k=-6}{\Σ}}{u}_k}---(1-4)$

Above-mentioned draw fuzzy output amount during, the control table of fuzzy reasoning is as shown in the table:

Table 4: optimum control table

Fuzzy output amount can obtain final control output through defuzzification.

In an example of the present invention, the defuzzification of fuzzy output amount can be carried out according to formula (1-5):

$Y=\frac{x+n}{2\×n}\×(b-a)+a---(1-5)$

Wherein, in formula (1-5), x represents fuzzy output amount, and Y represents control output, and a represents under fuzzy output amount Limit, b represents the upper limit of fuzzy output amount, and n represents quantification gradation.

According to technological parameter, control output (ammonia adds total amount) is in the range of [38,63], and i.e. minimum 38L/h, maximum 63L/h。

Step 103: output output will be controlled to ammonia dispensing controller to control upper strata ammonia dosage and lower floor's ammonia Water dosage.The example continued the above, when detecting input quantity and being the amount of nitrogen oxides in flue gas, corresponding control output Total amount is added for ammonia.

This ammonia adds total amount data-oriented and is sent to ammonia dispensing controller, is exported by ammonia dispensing controller Layer ammonia dosage and lower floor's ammonia dosage are to corresponding ammonia flow PID controller, it is achieved to upper strata ammonia and lower floor's ammonia The flow-control of water, thus ensure the stability of nitrogen oxides in effluent content's index.Fig. 2 shows according to embodiments of the present invention Signal data flow graph when being applied to above-mentioned example of the fuzzy control method for flue gas of refuse burning denitration SNCR, Ke Yijie Close Fig. 2 and understand principle and the process of said method.In order to prevent the ammonia overheated burning generation volume of gasification spraying in incinerator Outer NOx, it is to be ensured that the ammonia slow reaction that lower floor sprays into, to upper strata, controls to close between upper strata ammonia and the flow of lower floor's ammonia The balance controller of system can be controlled by by the temperature that the infrared thermometer of incinerator the 2nd flue records.

According to a further aspect of the invention, also provide for a kind of Fuzzy control system for flue gas of refuse burning denitration SNCR, Fig. 3 shows the structural frames of the Fuzzy control system 300 for flue gas of refuse burning denitration SNCR according to embodiments of the present invention Figure.As it is shown on figure 3, the Fuzzy control system 300 for flue gas of refuse burning denitration SNCR includes input module 301, processes mould Block 302 and output module 303.

Wherein, the detection input quantity that input module 301 sends for receiving detection device, and calculate detection input quantity with to Deviation between definite value and the rate of change of deviation are using the input variable as fuzzy control.Processing module 302 will be for inputting Variable is fuzzy turns to Indistinct Input amount, carries out fuzzy reasoning and decision-making to obtain fuzzy output amount based on Indistinct Input amount, and will Fuzzy output amount defuzzification is for controlling output.Output module 303 controls to ammonia distribution for controlling output output Device is to control upper strata ammonia and the flow of lower floor's ammonia.Wherein, detection input quantity includes the amount of nitrogen oxides in flue gas, with cigarette The corresponding control output of amount of nitrogen oxides in gas is that ammonia adds total amount data-oriented, is referred to combine Fig. 1 and retouches The embodiment stated understands the detailed process of each module operation, and here is omitted.

The modules of the embodiment of the present invention can realize with hardware, or to run on one or more processor Software module realize, or with combinations thereof realize.It will be understood by those of skill in the art that and can use in practice Microprocessor or digital signal processor (DSP) realize according to embodiments of the present invention for flue gas of refuse burning denitration The some or all functions of the some or all parts in the Fuzzy control system of SNCR.The present invention is also implemented as using In part or all the equipment or device program (such as, computer program and the meter that perform method as described herein Calculation machine program product).The program of such present invention of realization can store on a computer-readable medium, or can have one Individual or the form of multiple signal.Such signal can be downloaded from internet website and obtain, or carries on memory carrier Confession, or provide with any other form.

The above-mentioned fuzzy control method for flue gas of refuse burning denitration SNCR and system use fuzzy control strategy to pass through Ammonia is added stablizing of the amount of nitrogen oxides index in the control realization flue gas of total amount, reduces equipment operations staff to flue gas The frequent intervention of denitrating system, contributes to the stable operation of flue gas denitrification system.

The present invention is illustrated by above-described embodiment, but it is to be understood that, above-described embodiment is only intended to Citing and descriptive purpose, and be not intended to limit the invention in described scope of embodiments.In addition people in the art Member, it is understood that the invention is not limited in above-described embodiment, can also make more kinds of according to the teachings of the present invention Variants and modifications, within these variants and modifications all fall within scope of the present invention.Protection scope of the present invention by The appended claims and equivalent scope thereof are defined.

Claims (10)

1. the fuzzy control method for flue gas of refuse burning denitration SNCR, it is characterised in that described fuzzy control method Including:

The detection input quantity that receiving detection device sends, and calculate the deviation between described detection input quantity and set-point and institute State the rate of change of deviation using the input variable as fuzzy control；

Turn to Indistinct Input amount by fuzzy for described input variable, carry out fuzzy reasoning and decision-making to obtain based on described Indistinct Input amount To fuzzy output amount, and by described fuzzy output amount defuzzification for controlling output；

By described control output output to ammonia dispensing controller to control upper strata ammonia and the flow of lower floor's ammonia,

Wherein, described detection input quantity includes the amount of nitrogen oxides in flue gas, with the amount of nitrogen oxides phase in described flue gas Corresponding control output be ammonia add total amount data-oriented.

Fuzzy control method the most according to claim 1, it is characterised in that described described input variable being obscured turns to mould Stick with paste input quantity to include described input variable mapping transformation to discrete input domain.

Fuzzy control method the most according to claim 1, it is characterised in that the described input variable amount of carrying out according to the following formula Change:

$Y=\frac{2n\×\[x-(a+b)\÷2\]}{b-a}$

Wherein, x represents described input variable, and Y represents the input variable after quantization, and a represents the lower limit of described input variable, b table Showing the upper limit of described input variable, n represents quantification gradation.

Fuzzy control method the most according to claim 1, it is characterised in that described defuzzification is carried out according to the following formula:

$Y=\frac{x+n}{2\×n}\×(b-a)+a$

Wherein, x represents described fuzzy output amount, and Y represents described control output, and a represents the lower limit of described fuzzy output amount, b Representing the upper limit of described fuzzy output amount, n represents quantification gradation.

Fuzzy control method the most according to claim 1, it is characterised in that input domain corresponding to described input variable sets Being set to 4, output domain corresponding to described fuzzy output amount is set to 6.

Fuzzy control method the most according to claim 1, it is characterised in that the fuzzy son of the Linguistic Value of described Indistinct Input amount Collection is [negative big (NB), negative little (NS), zero (O), the least (PS), honest (PB)].

Fuzzy control method the most according to claim 1, it is characterised in that the fuzzy son of the Linguistic Value of described fuzzy output amount Collect for [negative big (NB) in bearing (NM), bears little (NS), zero (O), the least (PS), hit exactly (PM), honest (PB)].

Fuzzy control method the most according to claim 1, it is characterised in that the fuzzy son of the Linguistic Value of described Indistinct Input amount The membership function of the membership function of collection and the Linguistic Value fuzzy subset of described fuzzy output amount is triangular function.

Fuzzy control method the most according to claim 1, it is characterised in that the amount of nitrogen oxides in described flue gas inclined Difference scope is [-50,50], and the deviation variation rate scope of the amount of nitrogen oxides in described flue gas is [-20,20], described ammonia The total amount data-oriented scope that adds be [38,63].

10. the Fuzzy control system for flue gas of refuse burning denitration SNCR, it is characterised in that described Fuzzy control system Including:

Input module, the detection input quantity sent for receiving detection device, and calculate described detection input quantity and set-point it Between deviation and the rate of change of described deviation using the input variable as fuzzy control；

Processing module, for turning to Indistinct Input amount by fuzzy for described input variable, obscures based on described Indistinct Input amount Reasoning and decision-making are to obtain fuzzy output amount, and are control output by described fuzzy output amount defuzzification；

Output module, for exporting described control output to ammonia dispensing controller to control upper strata ammonia and lower floor's ammonia Flow,

Wherein, described detection input quantity includes the amount of nitrogen oxides in flue gas, with the amount of nitrogen oxides phase in described flue gas Corresponding control output be ammonia add total amount data-oriented.