CN106897540A - Method is monitored and optimized and revised to a kind of boiler-burner fired state on-line - Google Patents
Method is monitored and optimized and revised to a kind of boiler-burner fired state on-line Download PDFInfo
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- CN106897540A CN106897540A CN201710192353.XA CN201710192353A CN106897540A CN 106897540 A CN106897540 A CN 106897540A CN 201710192353 A CN201710192353 A CN 201710192353A CN 106897540 A CN106897540 A CN 106897540A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/06—Power analysis or power optimisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
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Abstract
A kind of burner combustion state on_line monitoring and optimize and revise method, spectral fire inspection device is arranged at boiler-burner, collect the monitoring signals of spectral fire inspection device and furnace pressure sensor, processed on intelligent processor, obtain related characteristic parameter, as |input paramete, by artificial neural network algorithm, obtain the parameter of fired state and burner hearth NOx emission, judge the reasonability of fired state, and related adjust instruction is passed into DCS system, and then boiler combustion is adjusted, realization more becomes more meticulous and intelligentized control to boiler.
Description
Technical field
The invention belongs to firing optimization field, more particularly to a kind of boiler-burner fired state on-line monitoring and optimization are adjusted
Adjusting method.
Background technology
For boiler, in order to realize more advanced energy management, it is necessary to enter to the running status of each burner
Row monitoring and analysis.It is even more so for low NO, because this burner is transported to the change of coal supply system and boiler
The change of row state is more sensitive.
Traditional combustion monitoring system is all to provide the average result of multiple burners, and not Real-time Feedback, and time
Span is larger.Traditional combustion control system, depends on the monitoring of procedure parameter, including fuel flow, the flow of air, cigarette
Oxygen content and CO concentration in gas etc., but for burner, optimal combustion state is realized, the measurement of these parameters is
Inadequate.Due to the imbalance of coal-air ratio, the uneven distribution of local burnup and air, or burner body setting and maintenance
Problem etc., causes the fired state of adjacent burners in the presence of certain difference, it is necessary to the state for being directed to each burner is entered respectively
Row monitoring, diagnosis and control.Combustion diagnosis should reflect prolonged mean state, should also reflect the transient state of short time
Change.
The content of the invention
In order to overcome the shortcoming of above-mentioned prior art, it is an object of the invention to provide a kind of boiler-burner fired state
Monitor and optimize and revise method on-line, the state to single burner is monitored, diagnoses and controls, and then realize whole to boiler
What body burnt becomes more meticulous and Intelligentized regulating and controlling.
To achieve these goals, the technical solution adopted by the present invention is：
A kind of boiler-burner fired state is monitored on-line and optimizes and revises method, and spectral is arranged at boiler-burner
Fire inspection device 1, collects the monitoring signals of spectral fire inspection device 1 and furnace pressure sensor 2, is located on intelligent processor 3
Reason, obtains related characteristic parameter, as |input paramete, by artificial neural network algorithm, obtains fired state and burner hearth NOx
The parameter of discharge, judges the reasonability of fired state, and related adjust instruction is passed into DCS system 4, and then to boiler combustion
It is adjusted；
The spectral fire inspection device 1, is the combustion flame emission spectrum that will be monitored, and by optical splitter, is divided into infrared, visible
Light and ultraviolet three spectral signals, record the data that three kinds of spectral radiance values are changed over time respectively；
The characteristic parameter includes infrared spectrum, visible light, ultraviolet spectra and the furnace pressure signal of combustion flame
Hourly value, mean square deviation, standard deviation, power spectral density, Power Spectral Entropy and wavelet energy entropy；
The reasonability of the fired state, in optimum value, excess air coefficient is 1.1 to refer to coal-air ratio example during burning
~1.3, burned flame stabilization, without bounce and swing, flame is produced and extended in the middle of burner hearth from burner nozzle, outward
See shape and show column or slight taper；
Describe in detail：(1) when coal-air ratio is reasonable, flame is in preferable and stabilization state, and flame is produced from burner nozzle
Give birth to and extend in the middle of burner hearth, face shaping shows column or slight taper；(2) when coal-air ratio is slightly higher or lower slightly
When, the situation that flame sporadicly extinguishes occurs in burner nozzle, the state for showing is exactly at burner nozzle, before flame front
After move, form the intermittent disengaging of flame and burner, will now cause serious pollutant emission problem；(3) when wind coal
Than it is too high or too low when, flame front thoroughly departs from burner nozzle；(4) during Secondary Air irrational distribution, flame can be presented
Go out the state of swing, pollute the fluctuation of thing discharge；(5) the too fast mixing of primary and secondary air, or too high heat is returned
Stream, flame is close to burner nozzle, and outward appearance is presented tubbiness shape, easily causes burner temperature too high and damage.
The adjust instruction, refers to the instruction being adjusted to combustor parameter, including secondary air flow, First air angle
Degree, Secondary Air angle, First air eddy flow degree and Secondary Air eddy flow degree.
The calculating process of the artificial neural network algorithm is as follows：
By collecting the historical data and picture of boiler operatiopn, and experiment is carried out at scene, parameter is collected, mainly including wind
Coal than, the radiation value of the radiation value of the radiation value of infrared spectrum, visible light, ultraviolet spectra, furnace pressure signal, burning shape
State and NOx emission, and spectrum and pressure signal are processed, characteristic parameter is extracted, set up database；Using artificial neuron
Network algorithm, allows machine constantly to learn these data, so as to set up between fired state and NOx emission and characteristic parameter
Corresponding relation；So, in actual applications, by current characteristic parameter, machine just can automatic decision go out current burning
State and NOx are in a kind of which type of state, so as to send adjust instruction.
The intelligent processor 3 is comprising signal transacting, information diagnosis and three main modulars such as optimizes and revises.
Compared with prior art, the beneficial effects of the invention are as follows：
1st, real-time monitoring, diagnosis can be respectively carried out to the state of each burner and is controlled；
2nd, combustion diagnosis can reflect the transient changing of short time.
Brief description of the drawings
Fig. 1 is the inventive method flow chart.
Specific embodiment
The present invention is described in detail with reference to the accompanying drawings and examples.
As shown in figure 1, spectral fire examines the signal of device 1, the information such as including the flicker frequency and radiation intensity of flame passes through
A piece optical fiber passes to intelligent processor 3, and the pressure signal of furnace pressure sensor 2 passes to intelligence by an other optical fiber
Processor 3.Intelligent processor 3 is comprising signal processing module, information diagnosis are with module and optimize and revise three main modulars of module.
The signal of be passed back is compiled and processed by signal processing module first, by the method for statistical analysis, obtains each signal
Characteristic parameter, including the infrared spectrum of combustion flame, visible light, ultraviolet spectra and furnace pressure signal hourly value,
Mean square deviation, standard deviation, power spectral density, Power Spectral Entropy and wavelet energy entropy.Signal diagnostic module is analyzed to statistical parameter,
By artificial neural network algorithm, judge which kind of fired state burner is currently at.Optimizing and revising module is examined according to signal
The judgement structure of disconnected module, provides corresponding optimizing and revising and instructs to DCS system 4, mainly to secondary air flow, First air angle
Degree, Secondary Air angle, First air eddy flow degree, Secondary Air eddy flow degree etc. are adjusted.Combustor parameter is carried out by DCS system 4
Optimize and revise.
The above, only present pre-ferred embodiments, each part is disposed with various ways, therefore can not be limited with this
The scope that the fixed present invention is implemented, i.e., the equivalence changes made according to scope of the present invention patent and description and modification, all
Should still remain within the scope of the patent.
Claims (2)
1. method is monitored and optimized and revised to a kind of boiler-burner fired state on-line, it is characterised in that at boiler-burner
Arrangement spectral fire inspection device (1), collects the monitoring signals of spectral fire inspection device (1) and furnace pressure sensor (2), in intelligence
Processor is processed on (3), obtains related characteristic parameter, as |input paramete, by artificial neural network algorithm, is obtained
The parameter of fired state and burner hearth NOx emission, judges the reasonability of fired state, and related adjust instruction is passed into DCS systems
System (4), and then boiler combustion is adjusted；
Spectral fire inspection device (1), is the combustion flame emission spectrum that will be monitored, and by optical splitter, is divided into infrared, visible ray
With ultraviolet three spectral signals, the data that three kinds of spectral radiance values are changed over time are recorded respectively；
The infrared spectrum of the characteristic parameter including combustion flame, visible light, ultraviolet spectra and furnace pressure signal when
Average, mean square deviation, standard deviation, power spectral density, Power Spectral Entropy and wavelet energy entropy；
The reasonability of the fired state, refers to during burning coal-air ratio example in optimum value, and excess air coefficient is 1.1~
1.3, burned flame stabilization, without bounce and swing, flame is produced and extended in the middle of burner hearth from burner nozzle, outward appearance
Shape shows column or slight taper；
The adjust instruction, refers to the instruction being adjusted to combustor parameter, including secondary air flow, First air angle, two
Secondary wind angle, First air eddy flow degree and Secondary Air eddy flow degree.
2. method is monitored and optimized and revised to boiler-burner fired state on-line according to claim 1, it is characterised in that institute
The calculating process for stating artificial neural network algorithm is as follows：
By collecting the historical data and picture of boiler operatiopn, and experiment is carried out at scene, collects parameter, mainly includes wind coal
Than, the radiation value of the radiation value of the radiation value of infrared spectrum, visible light, ultraviolet spectra, furnace pressure signal, fired state
And NOx emission, and spectrum and pressure signal are processed, characteristic parameter is extracted, set up database；Using ANN
Network algorithm, allows machine constantly to learn these data, right between fired state and NOx emission and characteristic parameter so as to set up
Should be related to；So, in actual applications, by current characteristic parameter, machine just can automatic decision go out current burning shape
State and NOx are in a kind of which type of state, so as to send adjust instruction.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710192353.XA CN106897540A (en) | 2017-03-28 | 2017-03-28 | Method is monitored and optimized and revised to a kind of boiler-burner fired state on-line |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201710192353.XA CN106897540A (en) | 2017-03-28 | 2017-03-28 | Method is monitored and optimized and revised to a kind of boiler-burner fired state on-line |
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| CN106897540A true CN106897540A (en) | 2017-06-27 |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107742000A (en) * | 2017-08-31 | 2018-02-27 | 国网江西省电力公司电力科学研究院 | Boiler combustion oxygen content modeling method |
| CN108445845A (en) * | 2018-02-12 | 2018-08-24 | 国网山东省电力公司电力科学研究院 | A kind of Intelligent boiler combustion stability suitable for large-scale power station judges system and method |
| CN111366291A (en) * | 2020-02-14 | 2020-07-03 | 迈拓仪表股份有限公司 | Water supply pipeline pressure prediction and roughness calibration method based on entropy and artificial neural network |
| CN113239612A (en) * | 2021-04-07 | 2021-08-10 | 华南理工大学 | Boiler combustion state diagnosis method and system and storage medium |
| CN117451175A (en) * | 2023-09-18 | 2024-01-26 | 南京审计大学 | Software definition-based precise intelligent camera for detecting flame images with same view field and three wavelengths and flame image detection method |
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| CN204006096U (en) * | 2014-06-13 | 2014-12-10 | 南京万和测控仪表有限公司 | A kind of dynamic flame detection system |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107742000A (en) * | 2017-08-31 | 2018-02-27 | 国网江西省电力公司电力科学研究院 | Boiler combustion oxygen content modeling method |
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| CN108445845A (en) * | 2018-02-12 | 2018-08-24 | 国网山东省电力公司电力科学研究院 | A kind of Intelligent boiler combustion stability suitable for large-scale power station judges system and method |
| CN108445845B (en) * | 2018-02-12 | 2020-02-14 | 国网山东省电力公司电力科学研究院 | Intelligent boiler combustion stability judgment system and method suitable for large power station |
| CN111366291A (en) * | 2020-02-14 | 2020-07-03 | 迈拓仪表股份有限公司 | Water supply pipeline pressure prediction and roughness calibration method based on entropy and artificial neural network |
| CN111366291B (en) * | 2020-02-14 | 2021-12-21 | 迈拓仪表股份有限公司 | Water supply pipeline pressure prediction and roughness calibration method based on entropy and artificial neural network |
| CN113239612A (en) * | 2021-04-07 | 2021-08-10 | 华南理工大学 | Boiler combustion state diagnosis method and system and storage medium |
| CN117451175A (en) * | 2023-09-18 | 2024-01-26 | 南京审计大学 | Software definition-based precise intelligent camera for detecting flame images with same view field and three wavelengths and flame image detection method |
| CN117451175B (en) * | 2023-09-18 | 2024-06-25 | 南京审计大学 | Software definition-based precise intelligent camera for detecting flame images with same view field and three wavelengths and flame image detection method |
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