CN106705072A - Ship incineration furnace hearth negative-pressure automatic control method and system - Google Patents
Ship incineration furnace hearth negative-pressure automatic control method and system Download PDFInfo
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- CN106705072A CN106705072A CN201611056021.0A CN201611056021A CN106705072A CN 106705072 A CN106705072 A CN 106705072A CN 201611056021 A CN201611056021 A CN 201611056021A CN 106705072 A CN106705072 A CN 106705072A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- F23G5/00—Incineration of waste; Incinerator constructions; Details, accessories or control therefor
- F23G5/50—Control or safety arrangements
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Abstract
The invention relates to a ship incineration furnace hearth negative-pressure automatic control method and a system. The method comprises the following steps: data parameters in a hearth are obtained; input variables of slip form controllers are obtained according to deviation values between the data parameters and performance evaluation indexes; a slip form controller training sample set based on a support vector machine is built according to the input variables and corresponding output values output by the preferable slip form controllers; a SVM-SMC controller fits structure parameter calculation reference negative-pressure values of conventional slip form controllers according to the slip form controller training sample set; when approximate errors of the reference negative-pressure values are located in an acceptable numerical value neighborhood, new training samples are generated through controlling parameter self-optimization, and are selectively stored in the slip form controller training sample set; and SVM-SMC controller parameters are optimized in real time according to the preferable new training samples. The method realizes self-optimization of controller structure parameters through slip form control and support vector machine algorithms, and guarantees safe and stable operation of the incineration process.
Description
Technical field
The present invention relates to incinerator automatic control technology field, and in particular to a kind of marine incinerator combustion chamber draft is controlled automatically
Method and system processed.
Background technology
Due to the increasingly increase of ships quantity, pollution of the ship garbage to marine environment is also increasingly severe, waste incineration
Treatment technology is used widely on ship.Because the combustion process in marine incinerator stove is extremely complex physical chemistry
Process, is a nonlinear system for the multiple-input and multiple-output large time delay of close coupling, if combustion stability decline can cause it is secondary
Pollution and aggravation high temperature corrosion, external dynamic interference may sacrificial system efficiency and security and stability, control strategy
Selection is closely related with the working condition of system, therefore the control system of marine incinerator is one of its core technology.
The content of the invention
The technical problems to be solved by the invention are the shortcomings for overcoming prior art, there is provided a kind of marine incinerator burner hearth
Negative pressure autocontrol method and system, by seeking certainly for sliding formwork control and implement the algorithm of support vector machine controller architecture parameter
It is excellent, it is ensured that burning process safe and stable operation.
In order to solve the above technical problems, the present invention provides a kind of marine incinerator combustion chamber draft autocontrol method, bag
Include following steps：
Step 1, the data parameters obtained in burner hearth；
Step 2, the input variable that sliding mode controller is tried to achieve according to the deviation of data parameters and Performance Evaluating Indexes；
Step 3, the corresponding output valve exported according to input variable and preferred sliding mode controller are set up and are based on supporting vector
The sliding mode controller training sample set of machine；
Step 4, SVM-SMC controllers are fitted the structure ginseng of conventional sliding mode controller according to sliding mode controller training sample set
Number calculating refers to negative pressure value；
Step 5, it is within acceptable numerical value neighborhood when the approximate error with reference to negative pressure value, by control parameter from seeking
The training sample of eugenic Cheng Xin, and new training sample is selectively stored in sliding mode controller training sample concentration；Further according to
Preferred new training sample real-time optimization SVM-SMC controller parameters.
The technical scheme that further limits of the invention is：Data parameters include in step 1：Burner hearth oxygen content, fire box temperature,
Flue-gas temperature and combustion chamber draft.
As a further improvement on the present invention, in step 4, formula is passed through with reference to negative pressure value：
Wherein b is biasing；θi=αi-α*i, αiWith α *iLagrange multiplier；K(xi, x) it is kernel function.
As a further improvement on the present invention, the screening technique of preferred new training sample is specially in step 5：Using public affairs
Formula：Δ=(1- δ) E { (CCO-CCOrational)/(E { Δ CCT }+E {-Δ FGT })+δ E { | Δ CCP | } ＜ ξ wherein, CCO and
CCOrationalRespectively actual furnace oxygen content and standard oxygen content, Δ CCT and-Δ FGT are respectively fire box temperature and flue gas temperature
The variable quantity of degree, │ Δ CCP │ are the absolute value of combustion chamber draft change, and E { } is the average statistical of correlated variables in bracket, and ξ is
The neighborhood value of definition, expression formula Section 1 represents and fire box temperature and flue gas temperature is rationally controlled under the premise of burner hearth oxygen content is met
Degree；Section 2 represents that the fluctuation amplitude of combustion chamber draft regulation is minimum, and the balance between this two is adjusted by weight coefficient δ.
As a further improvement on the present invention, step 5 includes：
Step 5-1, determine the reasonable sampling period, sequential configuration new samples (snew,CCPnew)；
Step 5-2, preferably new samples, remove irrational new samples；
Step 5-3, using increment type algorithm of support vector machine on-line training；
Step 5-4, calculating SVM-SMC controller outputs ACTsvmAnd add disturbed value to be applied to system；
Step 5-5, wait next sampling period, it is recycled to step 5-1.
The present invention also provides a kind of marine incinerator combustion chamber draft automatic control system, including：
Acquisition module, for obtaining the data parameters in burner hearth；
First computing module, for trying to achieve the defeated of sliding mode controller with the deviation of Performance Evaluating Indexes according to data parameters
Enter variable；
MBM, the corresponding output valve for being exported according to input variable and preferred sliding mode controller is set up based on branch
Hold the sliding mode controller training sample set of vector machine；
Second computing module, conventional sliding formwork control is fitted for SVM-SMC controllers according to sliding mode controller training sample set
The structural parameters of device processed are calculated and refer to negative pressure value；
Parameter optimization module, for being within acceptable numerical value neighborhood when the approximate error for referring to negative pressure value, passes through
Control parameter generates new training sample from optimizing, and new training sample is selectively stored in into sliding mode controller training sample
Concentrate；Further according to preferred new training sample real-time optimization SVM-SMC controller parameters.
As a further improvement on the present invention, acquisition module obtain data parameters include burner hearth oxygen content, fire box temperature,
Flue-gas temperature and combustion chamber draft.
As a further improvement on the present invention, the second computing module includes：Pass through formula with reference to negative pressure value：Wherein b is biasing；θi=αi-α*i, αiWith α *iLagrange multiplier；K(xi, x) it is core
Function.
As a further improvement on the present invention, the screening technique of preferred new training sample includes in parameter optimization module：
Using formula：Δ=(1- δ) E { (CCO-CCOrational)/(E { Δ CCT }+E {-Δ FGT })+δ E { | Δ CCP | } ＜ ξ wherein,
CCO and CCOrationalRespectively actual furnace oxygen content and standard oxygen content, Δ CCT and-Δ FGT are respectively fire box temperature and cigarette
The variable quantity of temperature degree, │ Δ CCP │ are the absolute value of combustion chamber draft change, and E { } is the average statistical of correlated variables in bracket,
ξ is the neighborhood value of definition, and expression formula Section 1 represents and fire box temperature and flue gas are rationally controlled under the premise of burner hearth oxygen content is met
Temperature；Section 2 represents that the fluctuation amplitude of combustion chamber draft regulation is minimum, and the balance between this two is adjusted by weight coefficient δ.
As a further improvement on the present invention, parameter optimization module includes：
Structural unit, for determining reasonable sampling period, sequential configuration new samples (snew,CCPnew)；
Preferred cell, for preferred new samples, removes irrational new samples；
Modeling unit, for setting up new sample set using increment type algorithm of support vector machine；
Computing unit, for calculating SVM-SMC controllers output ACTsvmAnd add disturbed value to be applied to system；
Cycling element, for waiting next sampling period, is recycled to structural unit.
The beneficial effects of the invention are as follows：The method by Refuse Incineration Process influence Incineration performance furnace pressure,
Fire box temperature, air inflow and flue-gas temperature are analyzed, and determine the major parameter of burning process, and use sliding formwork control and support
Vector machine algorithm is combined method, and foundation meets the sample database of evaluation index, and global optimal control device structural parameters are being obtained
While obtaining controller fast-response, strong robustness, it is ensured that whole burning process safe and stable operation.
Brief description of the drawings
Fig. 1 is marine incinerator combustion chamber draft autocontrol method flow chart of the invention；
Fig. 2 is marine incinerator combustion chamber draft automatic control system structure chart of the invention.
Specific embodiment
Embodiment 1
With reference to shown in Fig. 1, a kind of marine incinerator combustion chamber draft autocontrol method that the present embodiment is provided, including it is as follows
Step：
Step 1, the data parameters obtained in burner hearth；
Step 2, the input variable s that sliding mode controller is tried to achieve according to the deviation of data parameters and Performance Evaluating Indexesi=
(CCO-CCOrational)/(E{ΔCCT}+E{-ΔFGT}+E{|ΔCCP|})；
Step 3, according to input variable siThe corresponding output valve CCP exported with preferred sliding mode controlleri* set up based on branch
Hold the sliding mode controller training sample set (s of vector machinei,CCPi*)；
Step 4, SVM-SMC controllers are fitted the structure ginseng of conventional sliding mode controller according to sliding mode controller training sample set
Number calculating refers to negative pressure value；
Step 5, it is within acceptable numerical value neighborhood when the approximate error with reference to negative pressure value, by control parameter from seeking
The training sample of eugenic Cheng Xin, and new training sample is selectively stored in sliding mode controller training sample concentration；Further according to
Preferred new training sample real-time optimization SVM-SMC controller parameters.
Data parameters include in step 1：Burner hearth oxygen content, fire box temperature, flue-gas temperature and combustion chamber draft.
Burner hearth oxygen content, thermocouple collection fire box temperature and flue-gas temperature, B/P EGR Back Pressure Transducer EGR collection are gathered using oxygen-containing instrument
Combustion chamber draft.
In step 2, the computational methods of the input variable of sliding mode controller are s=(CCO-CCOrational)/(E{ΔCCT}
+ E {-Δ FGT }+E { | Δ CCP | }), wherein CCO and CCOrationalRespectively actual furnace oxygen content and standard oxygen content, Δ
CCT and-Δ FGT are respectively the variable quantity of fire box temperature and flue-gas temperature.
In step 4, formula is passed through with reference to negative pressure value：Wherein b is biasing；θi=αi-
α*i, αiWith α *iLagrange multiplier；K(xi, x) it is kernel function.
The screening technique of preferred new training sample is specially in step 5：
Using formula：Δ=(1- δ) E { (CCO-CCOrational)}/(E{ΔCCT}+E{-ΔFGT})+δE{|ΔCCP|}
＜ ξ wherein, CCO and CCOrationalRespectively actual furnace oxygen content and standard oxygen content, Δ CCT and-Δ FGT are respectively burner hearth
The variable quantity of temperature and flue-gas temperature, │ Δ CCP │ are the absolute value of combustion chamber draft change, and E { } is correlated variables in bracket
Average statistical, ξ is the neighborhood value of definition, and expression formula Section 1 represents and burner hearth temperature is rationally controlled under the premise of burner hearth oxygen content is met
Degree and flue-gas temperature；Section 2 represents that the fluctuation amplitude of combustion chamber draft regulation is minimum, and the balance between this two is by weight coefficient δ
Regulation.
Step 5 includes：
Step 5-1, determine the reasonable sampling period, sequential configuration new samples (snew,CCPnew)；
Step 5-2, preferably new samples, remove irrational new samples；
Step 5-3, using increment type algorithm of support vector machine on-line training, by preferred time series data sample more
New controller model；
Step 5-4, calculating SVM-SMC controller outputs ACTsvmAnd add disturbed value to be applied to system；
Step 5-5, wait next sampling period, it is recycled to step 5-1
With reference to shown in Fig. 2, the present embodiment provides a kind of marine incinerator combustion chamber draft automatic control system, including：
Acquisition module 21, for obtaining the data parameters in burner hearth；
First computing module 22, for trying to achieve sliding mode controller according to the deviation of data parameters and Performance Evaluating Indexes
Input variable；
MBM 23, the corresponding output valve for being exported according to input variable and preferred sliding mode controller is set up and is based on
The sliding mode controller training sample set of SVMs；
Second computing module 24, conventional sliding formwork is fitted for SVM-SMC controllers according to sliding mode controller training sample set
The structural parameters of controller are calculated and refer to negative pressure value；
Parameter optimization module 25, for being within acceptable numerical value neighborhood when the approximate error for referring to negative pressure value, leads to
Cross control parameter and generate new training sample from optimizing, and new training sample is selectively stored in sliding mode controller training sample
This concentration；Further according to preferred new training sample real-time optimization SVM-SMC controller parameters.
The data parameters that acquisition module 21 is obtained include burner hearth oxygen content, fire box temperature, flue-gas temperature and combustion chamber draft.
Second computing module includes：Pass through formula with reference to negative pressure value：Wherein b is inclined
Put；θi=αi-α*i, αiWith α *iLagrange multiplier；K(xi, x) it is kernel function.
The screening technique of preferred new training sample includes in parameter optimization module 25：Using formula：Δ=(1- δ) E
{(CCO-CCOrational)/(E { Δ CCT }+E {-Δ FGT })+δ E { | Δ CCP | } ＜ ξ wherein, CCO and CCOrationalRespectively
Actual furnace oxygen content and standard oxygen content, Δ CCT and-Δ FGT are respectively the variable quantity of fire box temperature and flue-gas temperature, │ Δs
CCP │ are the absolute value of combustion chamber draft change, and E { } is the average statistical of correlated variables in bracket, and ξ is the neighborhood value of definition, table
Represented up to formula Section 1 and fire box temperature and flue-gas temperature are rationally controlled under the premise of burner hearth oxygen content is met；Section 2 represents burner hearth
The fluctuation amplitude of negative pressure regulation is minimum, and the balance between this two is adjusted by weight coefficient δ.
Parameter optimization module 25 includes：
Structural unit, for determining reasonable sampling period, sequential configuration new samples (snew,CCPnew)；
Preferred cell, for preferred new samples, removes irrational new samples；
Modeling unit, for setting up new sample set using increment type algorithm of support vector machine；
Computing unit, for calculating SVM-SMC controllers output ACTsvmAnd add disturbed value to be applied to system；
Cycling element, for waiting next sampling period, is recycled to structural unit.
The present embodiment by influenceed in Refuse Incineration Process the furnace pressure of Incineration performance, fire box temperature, air inflow and
Flue-gas temperature is analyzed, and determines the major parameter of burning process, and be combined using sliding formwork control and algorithm of support vector machine
Method, foundation meets the sample database of evaluation index, and global optimal control device structural parameters are obtaining controller fast-response
Property, strong robustness while, it is ensured that whole burning process safe and stable operation.
In addition to the implementation, the present invention can also have other embodiment.All use equivalents or equivalent transformation shape
Into technical scheme, all fall within the protection domain of application claims.
Claims (10)
1. a kind of marine incinerator combustion chamber draft autocontrol method, it is characterised in that comprise the following steps：
Step 1, the data parameters obtained in burner hearth；
Step 2, the input variable that sliding mode controller is tried to achieve according to the deviation of the data parameters and Performance Evaluating Indexes；
Step 3, the corresponding output valve exported according to the input variable and preferred sliding mode controller are set up and are based on supporting vector
The sliding mode controller training sample set of machine；
Step 4, SVM-SMC controllers are fitted the structure ginseng of conventional sliding mode controller according to the sliding mode controller training sample set
Number calculating refers to negative pressure value；
Step 5, it is within acceptable numerical value neighborhood when the approximate error of the reference negative pressure value, by control parameter from seeking
The training sample of eugenic Cheng Xin, and the new training sample is selectively stored in the sliding mode controller training sample set
In；Further according to preferred new training sample real-time optimization SVM-SMC controller parameters.
2. a kind of marine incinerator combustion chamber draft autocontrol method according to claim 1, it is characterised in that the step
Data parameters include described in rapid 1：Burner hearth oxygen content, fire box temperature, flue-gas temperature and combustion chamber draft.
3. a kind of marine incinerator combustion chamber draft autocontrol method according to claim 1, it is characterised in that the step
In rapid 4, the reference negative pressure value passes through formula：Wherein b is biasing；θi=αi-α*i, αi
With α *iLagrange multiplier；K(xi, x) it is kernel function.
4. a kind of marine incinerator combustion chamber draft autocontrol method according to claim 1, it is characterised in that the step
The screening technique of preferred new training sample includes in rapid 5：
Using formula：Δ=(1- δ) E { (CCO-CCOrational)/(E { Δ CCT }+E {-Δ FGT })+δ E { | Δ CCP | } ＜ ξ
Wherein, CCO and CCOrationalRespectively actual furnace oxygen content and standard oxygen content, Δ CCT and-Δ FGT are respectively stove
The variable quantity of bore temperature and flue-gas temperature, │ Δ CCP │ are the absolute value of combustion chamber draft change, and E { } is correlated variables in bracket
Average statistical, ξ is the neighborhood value of definition, and expression formula Section 1 represents under the premise of burner hearth oxygen content is met rationally control burner hearth
Temperature and flue-gas temperature；Section 2 represents that the fluctuation amplitude of combustion chamber draft regulation is minimum, and the balance between this two is by weight system
Number δ regulations.
5. a kind of marine incinerator combustion chamber draft autocontrol method according to claim 1, it is characterised in that the step
Rapid 5 include：
Step 5-1, determine the reasonable sampling period, sequential configuration new samples (snew,CCPnew)；
Step 5-2, preferably new samples, remove irrational new samples；
Step 5-3, new sample set is set up using increment type algorithm of support vector machine；
Step 5-4, calculating SVM-SMC controller outputs ACTsvmAnd add disturbed value to be applied to system；
Step 5-5, wait next sampling period, it is recycled to step 5-1.
6. a kind of marine incinerator combustion chamber draft automatic control system, it is characterised in that including：
Acquisition module, for obtaining the data parameters in burner hearth；
First computing module, for trying to achieve the defeated of sliding mode controller with the deviation of Performance Evaluating Indexes according to the data parameters
Enter variable；
MBM, the corresponding output valve for being exported according to the input variable and preferred sliding mode controller is set up based on branch
Hold the sliding mode controller training sample set of vector machine；
Second computing module, conventional sliding formwork control is fitted for SVM-SMC controllers according to the sliding mode controller training sample set
The structural parameters of device processed are calculated and refer to negative pressure value；
Parameter optimization module, for being within acceptable numerical value neighborhood when the approximate error of the reference negative pressure value, passes through
Control parameter generates new training sample from optimizing, and the new training sample is selectively stored in into the sliding mode controller
Training sample is concentrated；Further according to preferred new training sample real-time optimization SVM-SMC controller parameters.
7. a kind of marine incinerator combustion chamber draft automatic control system according to claim 6, it is characterised in that described to obtain
The data parameters that modulus block is obtained include burner hearth oxygen content, fire box temperature, flue-gas temperature and combustion chamber draft.
8. a kind of marine incinerator combustion chamber draft automatic control system according to claim 6, it is characterised in that described
Two computing modules include：Pass through formula with reference to negative pressure value：Wherein b is biasing；θi=αi-
α*i, αiWith α *iLagrange multiplier；K(xi, x) it is kernel function.
9. a kind of marine incinerator combustion chamber draft automatic control system according to claim 6, it is characterised in that parameter is excellent
The screening technique for changing preferred new training sample in module includes：
Using formula：Δ=(1- δ) E { (CCO-CCOrational)/(E { Δ CCT }+E {-Δ FGT })+δ E { | Δ CCP | } ＜ ξ
Wherein, CCO and CCOrationalRespectively actual furnace oxygen content and standard oxygen content, Δ CCT and-Δ FGT are respectively stove
The variable quantity of bore temperature and flue-gas temperature, │ Δ CCP │ are the absolute value of combustion chamber draft change, and E { } is correlated variables in bracket
Average statistical, ξ is the neighborhood value of definition, and expression formula Section 1 represents under the premise of burner hearth oxygen content is met rationally control burner hearth
Temperature and flue-gas temperature；Section 2 represents that the fluctuation amplitude of combustion chamber draft regulation is minimum, and the balance between this two is by weight system
Number δ regulations.
10. a kind of marine incinerator combustion chamber draft automatic control system according to claim 6, it is characterised in that parameter
Optimization module includes：
Structural unit, for determining reasonable sampling period, sequential configuration new samples (snew,CCPnew)；
Preferred cell, for preferred new samples, removes irrational new samples；
Modeling unit, for setting up new sample set using increment type algorithm of support vector machine；
Computing unit, for calculating SVM-SMC controllers output ACTsvmAnd add disturbed value to be applied to system；
Cycling element, for waiting next sampling period, is recycled to structural unit.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201611056021.0A CN106705072A (en) | 2016-11-23 | 2016-11-23 | Ship incineration furnace hearth negative-pressure automatic control method and system |
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| CN201611056021.0A CN106705072A (en) | 2016-11-23 | 2016-11-23 | Ship incineration furnace hearth negative-pressure automatic control method and system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108196607A (en) * | 2017-12-29 | 2018-06-22 | 西南科技大学 | The temprature control method of the electromagnetic induction heating system of uncertain stochastic Time-Delay |
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| CN103410660A (en) * | 2013-05-14 | 2013-11-27 | 湖南工业大学 | Wind power generation variable pitch self-learning control method based on support vector machine |
| CN104654311A (en) * | 2014-12-24 | 2015-05-27 | 南京中船绿洲环保有限公司 | Marine incinerator treatment system |
| CN105090991A (en) * | 2015-08-26 | 2015-11-25 | 南京中船绿洲环保有限公司 | Intelligent frequency conversion marine incinerator control system |
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2016
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10267245A (en) * | 1997-03-26 | 1998-10-09 | Nkk Corp | Combustion control method of refuse incinerator and apparatus therefor |
| CN103410660A (en) * | 2013-05-14 | 2013-11-27 | 湖南工业大学 | Wind power generation variable pitch self-learning control method based on support vector machine |
| CN104654311A (en) * | 2014-12-24 | 2015-05-27 | 南京中船绿洲环保有限公司 | Marine incinerator treatment system |
| CN105090991A (en) * | 2015-08-26 | 2015-11-25 | 南京中船绿洲环保有限公司 | Intelligent frequency conversion marine incinerator control system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108196607A (en) * | 2017-12-29 | 2018-06-22 | 西南科技大学 | The temprature control method of the electromagnetic induction heating system of uncertain stochastic Time-Delay |
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Application publication date: 20170524 |