CN109189120A - Data-driven applied to dangerous waste incineration rotary kiln models method for controlling furnace temperature - Google Patents
Data-driven applied to dangerous waste incineration rotary kiln models method for controlling furnace temperature Download PDFInfo
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- CN109189120A CN109189120A CN201811043429.3A CN201811043429A CN109189120A CN 109189120 A CN109189120 A CN 109189120A CN 201811043429 A CN201811043429 A CN 201811043429A CN 109189120 A CN109189120 A CN 109189120A
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- rotary kiln
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D23/00—Control of temperature
- G05D23/19—Control of temperature characterised by the use of electric means
- G05D23/20—Control of temperature characterised by the use of electric means with sensing elements having variation of electric or magnetic properties with change of temperature
Abstract
The present invention relates to a kind of data-drivens applied to dangerous waste incineration rotary kiln to model method for controlling furnace temperature, including S1: carrying out Basic Physical Properties Data sample detecting to hazardous waste to be processed, obtains hazardous waste Basic Physical Properties Data library；S2: rotary kiln running data are acquired using incinerator DCS system；S3: according to rotary kiln running data and hazardous waste Basic Physical Properties Data library, kiln temperature fitting prediction model is established using autoregressive moving average modeling method；S4: prediction model is fitted according to kiln temperature and prediction is carried out to the temperature change in rotary kiln running and according to predicted temperature proposition control parameter correction value；S5: carrying out self adaptive control to rotary kiln running in real time according to revised control parameter, the operation of rotary kiln automatic steady.The present invention is realized to rotary kiln charging, overall process Automatic Optimal control that is combustion-supporting, mending wind, revolving speed adjustment, and the economic benefit for promoting the disposition of hazardous waste rotary kiln is very helpful.
Description
Technical field
The present invention relates to Rotary Kiln Control technical fields, and in particular to a kind of number applied to dangerous waste incineration rotary kiln
Method for controlling furnace temperature is modeled according to driving.
Background technique
Along with the rapid development of China's economy, industrial capacity and living standards of the people are greatly improved, but same
When also produce a large amount of solid waste and need rationally appropriate disposition.With hazardous waste, this special sort should most draw especially among these
Play concern.Hazardous waste often has toxic, inflammability, explosivity, corrosion as a kind of special solid waste
Property, one or more of for human health and natural environment, there are the characteristics of potential considerable damage power for former infectiousness etc. of causing a disease.
In various hazardous waste processing methods, incineration method can have due to it using the overwhelming majority in pyrolytic oxidation hazardous waste
Evil substance simultaneously can effectively achieve the purpose that waste is reduced, and be the preferred processing means of hazardous waste processing center.And with environmental protection
Consciousness step up and the increase of each place environmental protection pressure, processing especially burning disposal for hazardous waste it is also proposed that
Higher requirement.
Since different types of hazardous waste has different physical property, the built dangerous waste in various regions focuses on center
It mostly uses Rotation error as preferred garbage incinerating system, and arranges in pairs or groups and utmostly reduce burning using high temperature dual firing chamber
Harmful substance in tail gas.Rotation error itself can handle solid-state, sludge, liquid and gaseous state class waste simultaneously, have
Very strong compatibility, be suitable for a plurality of types of refuse burning systems, be especially suitable for hazardous waste it is this kind of needs and meanwhile handle
The case where multiphase waste.In furnace in burning process, hazardous waste can be converted into gaseous state by solid-state, liquid, then by into one
The heating of step is reacted with oxygen, and the solid residue that generates gaseous product in final furnace and cannot burn away (generally comprises
Clinker and flying dust).After burning process, the volume of most solid-state hazardous wastes can reduce 80% or more, heavy metal etc.
Aphlogistic nuisance will remain in clinker and flying dust, and the flammable hazardous material such as organic matter will be titanium dioxide by exhaustive oxidation
The harmless components safety dumping such as carbon and water is into atmosphere.It can be seen that can be reached simultaneously using incinerator processing hazardous waste
Decrement and innoxious purpose, while waste heat boiler recycling and reusing can be used in the heat for generation of burning, and is a kind of ideal
Hazardous waste processing technique.
Although rotary kiln incineration method is a kind of widely used hazardous waste processing technique, also can in operation
There is the possibility for generating secondary pollution, issuable extremely toxic substance dioxin, is in burning disposal mistake especially during combustion
The important environment protection control index that must be taken into consideration in journey.Additionally, due to the compositing cause of hazardous waste itself, wherein often containing sulphur,
The elements such as chlorine, these elements deleterious acidic gaseous sulfur dioxide easy to form and hydrogen chloride during the burning process, if directly arranged
It is put into atmosphere, serious harm will be caused to environment.Therefore in incinerator actual motion, there is " 3T " principle, it is both burned
Journey will keep sufficiently high temperature, flue gas to have enough residence times in furnace, to have sufficiently strong turbulent flow so as to sky in furnace
Gas can be sufficiently mixed with hazardous waste.Suitably control adjustment, especially furnace in actual danger incineration of waste disposal process
The adjustment of temperature is to determine the most critical factor of dangerous waste incineration treatment effect.
Existing kiln temperature control technology focus mostly on study the feed materials such as cement burning rotary kiln composition it is relatively stable,
Inlet amount fluctuates little situation at any time.And for hazardous waste rotary kiln, due to feed composition complexity, inlet amount fluctuation
Greatly, traditional method is difficult to effectively be controlled.And the temperature stability in dangerous waste treatment process for rotary kiln has ratio
Higher requirement, temperature is excessively high to will lead to the damage of furnace inner thermal insulating layer, a large amount of coking and slaggings in furnace；Temperature is too low to will cause dangerous give up
Object burns not exclusively, cannot effectively destroy harmful substance.Site operation personnel is relied primarily in treatment process empirically at present
It adjusts accordingly, low efficiency is easy to appear situations such as furnace temperature is too high or too low, causes non-programmed halt, brings great economy
Loss.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of data-drivens applied to dangerous waste incineration rotary kiln to build
Mould method for controlling furnace temperature, by acquisition rotary kiln running data and application autoregressive moving average modeling method is to rotary kiln furnace temperature
It is fitted, PREDICTIVE CONTROL is carried out to rotary kiln running using the temperature model of foundation, to realize at enhancing dangerous waste incineration
Process control automation degree is managed, manual intervention uncertainty is reduced, improves rotary kiln running process stability, reduction was run
Furnace temperature fluctuation in journey is avoided to greatest extent because of non-programmed halt caused by exhaust emissions is not up to standard or slagging slagging.
To achieve the above object, the present invention adopts the following technical scheme:
A kind of data-driven modeling method for controlling furnace temperature applied to dangerous waste incineration rotary kiln, comprising the following steps:
Step S1: Basic Physical Properties Data sample detecting is carried out to hazardous waste to be processed, obtains hazardous waste Basic Physical Properties
Database；
Step S2: rotary kiln running data are acquired using incinerator DCS system；
Step S3: according to rotary kiln running data and hazardous waste Basic Physical Properties Data library, using autoregressive moving average
Modeling method establishes kiln temperature fitting prediction model；
Step S4: prediction model is fitted according to kiln temperature and predict simultaneously root to the temperature change in rotary kiln running
It is predicted that temperature proposes control parameter correction value；
Step S5: self adaptive control is carried out to rotary kiln running in real time according to revised control parameter, rotary kiln is automatic
Even running.
Further, the hazardous waste Basic Physical Properties Data includes: material density data, calorific value data, Industrial Analysis
Data, Elemental analysis data.
Further, the rotary kiln running data specifically include: incinerator charging type, inlet amount, rotary kiln revolving speed,
Mend air quantity, auxiliary fuel dosage.
Further, the step S3 specifically:
Step S31: according to the influence of each condition of kiln operation process, the corresponding relationship base of operating condition and temperature is established
This formula:
A(z-1)Tx=B (z-1)u1x+C(z-1)u2x+D(z-1)mx+ε(z-1)δx
Step S32: it is using Matlab System Discrimination kit that collected operation data is associated with basic form, it obtains
Basic form configuration parameters nA、nB、nC、nD, determine that model is constituted；
Step S33: rotary kiln running data and hazardous waste Basic Physical Properties Data library are brought into and utilizes recursion augmentation minimum
Square law estimates most suitable model parameter a1、a2、b1、b2, obtain kiln temperature fitting prediction model.
Further, the step S4 specifically:
Step S41:DCS system acquires kiln temperature data T in real timeopt(k)；
Step S42: by operational parameter control CrKiln temperature fitting prediction model is inputted to calculate in currently revolution kiln temperature
The kiln temperature T of estimated subsequent time under degree and operating conditionpredict；
Step S43: by TpredictWith the practical subsequent time temperature data T of DCS acquisitionopt(k+1)Compare calculating
Tpredict', if TpredictWith Topt(k+1)Between error in tolerance interval εTIt is interior, then receive Tpredict'=Tpredict, otherwise adopt
With amendment scheme Tpredict'=Topt(k+1), simultaneously because simulation and forecast calculating speed is faster than actual motion, in Topt(k+1)It does not acquire
Then default Tpredict'=Tpredict；
Step S44: by Tpredict' and preset rotary kiln standard running temperature TsetError analysis, if error analysis result
Receiving range αTWithin, then default and keeps existing operation control parameter CrIt is constant and by Tpredict' calculated as next step
Topt(k)Continue to predict furnace temperature, receives range α until error analysis result exceedsTWhen, then modify rotary kiln running control parameter Cr
And recalculate updated Tpredict', receive range α when error analysis result comes back toTWithin when, export it is revised
Control parameter Cr′；When occurring needing using amendment scheme Tpredict'=Topt(k+1)The case where when, then after deleting current time
All predicted values and S42 that gos to step is recalculated；
Step S45: revised control parameter C is exportedr′；
Further, the operational parameter control CrSpecifically include hazardous waste at be grouped as, inlet amount, auxiliary fuel use
Amount mends air quantity and rotary kiln revolving speed.
Compared with the prior art, the invention has the following beneficial effects:
The present invention is based on hazardous waste rotary kiln running data, are fitted prediction to kiln temperature, with realize to return
The anticipation and automatic control of rotary kiln operating condition.Previous control technology is compared, the present invention is kept away using the method that data-driven models
Exempt from for feeding complicated brought operation control difficulty when hazardous waste processing, prediction model itself can be supported well
During rotary kiln running the features such as big inertia, long time lag, it is achieved that using set of system to rotary kiln charging, combustion-supporting, benefit
The overall process Automatic Optimal control that wind, revolving speed adjust greatly reduces hazardous waste rotary kiln running control difficulty, reduces revolution
For the degree of dependence of Field Force's experimental technology in kiln operation, the stability of dangerous waste incineration processing is greatly improved,
Economic benefit for promoting the disposition of hazardous waste rotary kiln is very helpful.
Detailed description of the invention
Fig. 1 is Model Predictive Control flow chart of the present invention
Fig. 2 is Rotary Kiln Control block diagram of the present invention
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and embodiments.
Fig. 1 is please referred to, the present invention provides a kind of data-driven modeling furnace temperature control applied to dangerous waste incineration rotary kiln
Method processed, comprising the following steps:
Step S1: Basic Physical Properties Data sample detecting is carried out to hazardous waste to be processed, obtains hazardous waste Basic Physical Properties
Database；
Step S2: rotary kiln running data are acquired using incinerator DCS system；
Step S3: according to rotary kiln running data and hazardous waste Basic Physical Properties Data library, using autoregressive moving average
Modeling method establishes kiln temperature fitting prediction model；
Step S4: prediction model is fitted according to kiln temperature and predict simultaneously root to the temperature change in rotary kiln running
It is predicted that temperature proposes control parameter correction value；
Step S5: self adaptive control is carried out to rotary kiln running in real time according to revised control parameter, rotary kiln is automatic
Even running.
In one embodiment of the invention, the hazardous waste Basic Physical Properties Data include: material density data, calorific value data,
Industrial Analysis data, Elemental analysis data.
In one embodiment of the invention, the rotary kiln running data are specifically included: incinerator feeds type, inlet amount, returns
Rotary kiln revolving speed mends air quantity, auxiliary fuel dosage.
In one embodiment of the invention, the step S3 specifically:
Step S31: according to the influence of each condition of kiln operation process, the corresponding relationship base of operating condition and temperature is established
This formula:
A(z-1)Tx=B (z-1)u1x+C(z-1)u2x+D(z-1)mx+ε(z-1)δx
Step S32: it is using Matlab System Discrimination kit that collected operation data is associated with basic form, it obtains
Basic form configuration parameters nA、nB、nC、nD, determine that model is constituted；
Step S33: rotary kiln running data and hazardous waste Basic Physical Properties Data library are brought into and utilizes recursion augmentation minimum
Square law estimates most suitable model parameter a1、a2、b1、b2, obtain kiln temperature fitting prediction model.
In one embodiment of the invention, the step S4 specifically:
Step S41:DCS system acquires kiln temperature data T in real timeopt(k)；
Step S42: by operational parameter control CrKiln temperature fitting prediction model is inputted to calculate in currently revolution kiln temperature
The kiln temperature T of estimated subsequent time under degree and operating conditionpredict；
Step S43: by TpredictWith the practical subsequent time temperature data T of DCS acquisitionopt(k+1)Compare calculating
Tpredict', if TpredictWith Topt(k+1)Between error in tolerance interval εTIt is interior, then receive Tpredict'=Tpredict, otherwise adopt
With amendment scheme Tpredict'=Topt(k+1), simultaneously because simulation and forecast calculating speed is faster than actual motion, in Topt(k+1)It does not acquire
Then default Tpredict'=Tpredict；
Step S44: by Tpredict' and preset rotary kiln standard running temperature TsetError analysis, if error analysis result
Receiving range αTWithin, then default and keeps existing operation control parameter CrIt is constant and by Tpredict' calculated as next step
Topt(k)Continue to predict furnace temperature, receives range α until error analysis result exceedsTWhen, then modify rotary kiln running control parameter Cr
And recalculate updated Tpredict', receive range α when error analysis result comes back toTWithin when, export it is revised
Control parameter Cr′；When occurring needing using amendment scheme Tpredict'=Topt(k+1)The case where when, then after deleting current time
All predicted values and S42 that gos to step is recalculated；
Step S45: revised control parameter C is exportedr′；
In one embodiment of the invention, the operational parameter control CrSpecifically include hazardous waste at be grouped as, inlet amount, it is auxiliary
Firing rate is helped, air quantity and rotary kiln revolving speed are mended.
Embodiment 1:
The present embodiment wants history data to carry out prediction model fitting using revolution, is modeled by autoregressive moving average
Method establishes the non-linear relation of Rotary Kiln Control parameter and kiln temperature and obtains model structure parameter and model estimation
Parameter.Obtained temperature prediction model is inputted into rotary kiln Model Predictive Control unit.
Rotary kiln will be prepared to enter into and carry out the hazardous waste category sampling of burning disposal, analyze, obtains hazardous waste
Physical data, Industrial Analysis data and Elemental analysis data.By obtained data preparation, it is packaged as hazardous waste database,
To be called during model prediction computation.
Rotary kiln booting sprays into auxiliary fuel so that kiln temperature rises to predetermined operation temperature.It is steady to kiln temperature
After fixed, start to put into treating material, while acquiring rotary kiln inlet amount in real time by DCS system, auxiliary fuel consumption, mending air quantity
With control parameters and the rotary kiln running temperature such as rotary kiln revolving speed, collected data are transmitted to Model Predictive Control list
Member.
The data that DCS transmission comes are imported kiln temperature prediction model and calculated by Model Predictive Control unit, are passed through
Rotary Kiln Control parameter after the output optimization of model prediction method.
DCS system is transmitted back to by the new control parameter that control unit is calculated and is applied in the control of rotary kiln,
Optimal Parameters adjustment rotary kiln inlet amount, auxiliary fuel consumption, benefit air quantity and the rotary kiln provided according to Model Predictive Control unit
Revolving speed.
After above-mentioned control parameter adjustment, rotary kiln running state can change, and new running temperature can become as input
Amount is transmitted into model predictive control system and starts new primary PREDICTIVE CONTROL.
By repeating above-mentioned control process, realize that the automatic stabilisation of hazardous waste rotary kiln incineration treatment process runs control
System.
The foregoing is merely presently preferred embodiments of the present invention, all equivalent changes done according to scope of the present invention patent with
Modification, is all covered by the present invention.
Claims (6)
1. a kind of data-driven applied to dangerous waste incineration rotary kiln models method for controlling furnace temperature, it is characterised in that: including
Following steps:
Step S1: Basic Physical Properties Data sample detecting is carried out to hazardous waste to be processed, obtains hazardous waste Basic Physical Properties Data
Library；
Step S2: rotary kiln running data are acquired using incinerator DCS system；
Step S3: it according to rotary kiln running data and hazardous waste Basic Physical Properties Data library, is modeled using autoregressive moving average
Method establishes kiln temperature fitting prediction model；
Step S4: prediction model is fitted according to kiln temperature, the temperature change in rotary kiln running is predicted simultaneously according to pre-
Testing temperature proposes control parameter correction value；
Step S5: self adaptive control, rotary kiln automatic steady are carried out to rotary kiln running in real time according to revised control parameter
Operation.
2. the data-driven according to claim 1 applied to dangerous waste incineration rotary kiln models method for controlling furnace temperature,
It is characterized by: the hazardous waste Basic Physical Properties Data includes: material density data, calorific value data, Industrial Analysis data, member
Element analysis data.
3. the data-driven according to claim 1 applied to dangerous waste incineration rotary kiln models method for controlling furnace temperature,
It is characterized by: the rotary kiln running data specifically include: incinerator feeds type, inlet amount, and rotary kiln revolving speed mends wind
Amount, auxiliary fuel dosage.
4. the data-driven according to claim 1 applied to dangerous waste incineration rotary kiln models method for controlling furnace temperature,
It is characterized by: the step S3 specifically:
Step S31: according to the influence of each condition of kiln operation process, the corresponding relationship for establishing operating condition and temperature is basic
Formula:
A(z-1)Tx=B (z-1)u1x+C(z-1)u2x+D(z-1)mx+ε(z-1)δx
Step S32: it is using Matlab System Discrimination kit that collected operation data is associated with basic form, it obtains basic
Formula configuration parameters nA、nB、nC、nD, determine that model is constituted；
Step S33: rotary kiln running data and hazardous waste Basic Physical Properties Data library are brought into and utilizes recursion augmentation least square
Method estimates most suitable model parameter a1、a2、b1、b2, obtain kiln temperature fitting prediction model.
5. the data-driven according to claim 1 applied to dangerous waste incineration rotary kiln models method for controlling furnace temperature,
It is characterized by: the step S4 specifically:
Step S41:DCS system acquires kiln temperature data T in real timeopt(k)；
Step S42: by operational parameter control CrInput kiln temperature fitting prediction model calculate in current kiln temperature and
The kiln temperature T of estimated subsequent time under operating conditionpredict；
Step S43: by TpredictWith the practical subsequent time temperature data T of DCS acquisitionopt(k+1)It compares and calculates Tpredict',
If TpredictWith Topt(k+1)Between error in tolerance interval εTIt is interior, then receive Tpredict'=Tpredict, otherwise use amendment side
Case Tpredict'=Topt(k+1), simultaneously because simulation and forecast calculating speed is faster than actual motion, in Topt(k+1)Default when not collecting
Tpredict'=Tpredict；
Step S44: by Tpredict' and preset rotary kiln standard running temperature TsetError analysis, if error analysis result is connecing
By range αTWithin, then default and keeps existing operation control parameter CrIt is constant and by Tpredict' the T calculated as next stepopt(k)
Continue to predict furnace temperature, receives range α until error analysis result exceedsTWhen, then modify rotary kiln running control parameter CrAnd again
Calculate updated Tpredict', receive range α when error analysis result comes back toTWithin when, export revised control and join
Number Cr′；When occurring needing using amendment scheme Tpredict'=Topt(k+1)The case where when, then it is all pre- after deleting current time
The measured value and S42 that gos to step is recalculated；
Step S45: revised control parameter C is exportedr′。
6. the data-driven according to claim 5 applied to dangerous waste incineration rotary kiln models method for controlling furnace temperature,
It is characterized by: the operational parameter control CrSpecifically include hazardous waste at be grouped as, inlet amount, auxiliary fuel dosage, mend
Air quantity and rotary kiln revolving speed.
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| CN114859720A (en) * | 2022-05-09 | 2022-08-05 | 电子科技大学 | Dissipative economic model prediction control method of large-time-lag forming system |
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