GB2605904A - Burner control - Google Patents

Burner control Download PDF

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Publication number
GB2605904A
GB2605904A GB2209144.1A GB202209144A GB2605904A GB 2605904 A GB2605904 A GB 2605904A GB 202209144 A GB202209144 A GB 202209144A GB 2605904 A GB2605904 A GB 2605904A
Authority
GB
United Kingdom
Prior art keywords
image data
mask
flame
smoke
combustion
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
GB2209144.1A
Other versions
GB202209144D0 (en
Inventor
Toussaint Charles
BENSLIMANE Salma
Trifol Hugues
Allouche Francis
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Schlumberger Technology BV
Original Assignee
Schlumberger Technology BV
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Schlumberger Technology BV filed Critical Schlumberger Technology BV
Publication of GB202209144D0 publication Critical patent/GB202209144D0/en
Publication of GB2605904A publication Critical patent/GB2605904A/en
Pending legal-status Critical Current

Links

Classifications

    • 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
    • F23G5/08—Incineration of waste; Incinerator constructions; Details, accessories or control therefor having supplementary heating
    • F23G5/12—Incineration of waste; Incinerator constructions; Details, accessories or control therefor having supplementary heating using gaseous or liquid fuel
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23N—REGULATING OR CONTROLLING COMBUSTION
    • F23N5/00—Systems for controlling combustion
    • F23N5/02—Systems for controlling combustion using devices responsive to thermal changes or to thermal expansion of a medium
    • F23N5/08—Systems for controlling combustion using devices responsive to thermal changes or to thermal expansion of a medium using light-sensitive elements
    • F23N5/082—Systems for controlling combustion using devices responsive to thermal changes or to thermal expansion of a medium using light-sensitive elements using electronic means
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
    • F23G7/00—Incinerators or other apparatus for consuming industrial waste, e.g. chemicals
    • F23G7/06—Incinerators or other apparatus for consuming industrial waste, e.g. chemicals of waste gases or noxious gases, e.g. exhaust gases
    • F23G7/08—Incinerators or other apparatus for consuming industrial waste, e.g. chemicals of waste gases or noxious gases, e.g. exhaust gases using flares, e.g. in stacks
    • F23G7/085—Incinerators or other apparatus for consuming industrial waste, e.g. chemicals of waste gases or noxious gases, e.g. exhaust gases using flares, e.g. in stacks in stacks
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23N—REGULATING OR CONTROLLING COMBUSTION
    • F23N1/00—Regulating fuel supply
    • F23N1/02—Regulating fuel supply conjointly with air supply
    • F23N1/022—Regulating fuel supply conjointly with air supply using electronic means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23J—REMOVAL OR TREATMENT OF COMBUSTION PRODUCTS OR COMBUSTION RESIDUES; FLUES 
    • F23J2900/00—Special arrangements for conducting or purifying combustion fumes; Treatment of fumes or ashes
    • F23J2900/15004—Preventing plume emission at chimney outlet
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23N—REGULATING OR CONTROLLING COMBUSTION
    • F23N5/00—Systems for controlling combustion
    • F23N5/18—Systems for controlling combustion using detectors sensitive to rate of flow of air or fuel
    • F23N2005/181—Systems for controlling combustion using detectors sensitive to rate of flow of air or fuel using detectors sensitive to rate of flow of air
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23N—REGULATING OR CONTROLLING COMBUSTION
    • F23N5/00—Systems for controlling combustion
    • F23N5/18—Systems for controlling combustion using detectors sensitive to rate of flow of air or fuel
    • F23N2005/185—Systems for controlling combustion using detectors sensitive to rate of flow of air or fuel using detectors sensitive to rate of flow of fuel
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23N—REGULATING OR CONTROLLING COMBUSTION
    • F23N2229/00—Flame sensors
    • F23N2229/20—Camera viewing
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23N—REGULATING OR CONTROLLING COMBUSTION
    • F23N2900/00—Special features of, or arrangements for controlling combustion
    • F23N2900/05006—Controlling systems using neuronal networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/56—Extraction of image or video features relating to colour

Landscapes

  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Theoretical Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Combustion & Propulsion (AREA)
  • Chemical & Material Sciences (AREA)
  • Environmental & Geological Engineering (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Physics & Mathematics (AREA)
  • Databases & Information Systems (AREA)
  • Multimedia (AREA)
  • Medical Informatics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Regulation And Control Of Combustion (AREA)

Abstract

Methods of controlling hydrocarbon burner systems described herein include acquiring image data during operation of a burner system that, via combustion of hydrocarbons, generates a flame and smoke; processing the image data using at least one trained machine learning model to generate a flame mask and a smoke mask; characterizing the combustion by applying the flame mask to the image data and by applying the smoke mask to the image data; and, based on the characterizing, controlling the operation of the burner system.

Claims (20)

What is claimed is:
1. A method, comprising: acquiring image data during operation of a burner system that, via combustion of hydrocarbons, generates a flame and smoke; processing the image data using at least one trained machine learning model to generate a flame mask and a smoke mask; characterizing the combustion by applying the flame mask to the image data and by applying the smoke mask to the image data; and based on the characterizing, controlling the operation of the burner system.
2. The method of claim 1 , wherein the at least one trained machine learning model comprises a single trained machine learning model that generates at least the flame mask and the smoke mask.
3. The method of claim 1 , wherein the at least one trained machine learning model comprises a U-Net machine learning model architecture.
4. The method of claim 1 , wherein the at least one trained machine learning model comprises a trained machine learning model that comprises a contracting path that receives the image data and an expansive path that outputs the flame mask and the smoke mask.
5. The method of claim 1, wherein the image data comprise pixel data, wherein the flame mask is applied to the image data to identify, probabilistically, flame pixels in the image data, and wherein the smoke mask is applied to the image data to identify, probabilistically, smoke pixels in the image data.
6. The method of claim 1 , wherein characterizing the combustion by applying the flame mask to the image data comprises applying the flame mask to the image data in a hue, saturation and value (HSV) color model to generate at least flame masked image data for hue.
7. The method of claim 6, comprising generating a combustion quality indicator to characterize the combustion using at least the flame masked image data for hue.
8. The method of claim 6, comprising generating a combustion quality indicator to characterize the combustion using at least the flame masked image data for hue and for saturation.
9. The method of claim 1 , wherein characterizing the combustion by applying the smoke mask to the image data comprises applying the smoke mask to the image data in a hue, saturation and value (HSV) color model to generate at least smoke masked image data for value.
10. The method of claim 9, comprising generating a smoke indicator to characterize the combustion using at least the smoke masked image data for value.
11 . The method of claim 10, wherein the smoke indicator comprises a Ringelmann smoke chart indicator.
12. The method of claim 1 , wherein characterizing the combustion by applying the smoke mask to the image data comprises utilizing a Ringelmann smoke chart indicator.
13. The method of claim 1 , wherein the processing the image data using at least one trained machine learning model generates a flame mask, a smoke mask and a sprinkler mask.
14. The method of claim 1 , wherein the processing the image data using at least one trained machine learning model generates a flame mask, a smoke mask and a fiducial mask.
15. The method of claim 14, comprising applying the fiducial mask to the image data to identify fiducials and spatially characterizing the flame using the identified fiducials.
16. The method of claim 15, wherein spatially characterizing the flame comprises determining a size of the flame.
17. The method of claim 1 , wherein characterizing the combustion comprises generating a flame to smoke ratio.
18. The method of claim 1 , wherein the acquiring acquires video image data in real time during operation of the burner system and wherein the controlling controls the operation of the burner system in real-time.
19. A system comprising: a processor; memory accessible to the processor; processor-executable instructions stored in the memory and executable by the processor to instruct the system to: acquire image data during operation of a burner system that, via combustion of hydrocarbons, generates a flame and smoke; process the image data using at least one trained machine learning model to generate a flame mask and a smoke mask; characterize the combustion by applying the flame mask to the image data and by applying the smoke mask to the image data; and based on the characterization of the combustion, control the operation of the burner system.
20. One or more computer-readable storage media comprising computer- executable instructions executable to instruct a computing system to: acquire image data during operation of a burner system that, via combustion of hydrocarbons, generates a flame and smoke; process the image data using at least one trained machine learning model to generate a flame mask and a smoke mask; characterize the combustion by applying the flame mask to the image data and by applying the smoke mask to the image data; and based on the characterization of the combustion, control the operation of the burner system.
GB2209144.1A 2020-01-06 2020-12-17 Burner control Pending GB2605904A (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US202062957648P 2020-01-06 2020-01-06
PCT/US2020/065656 WO2021141749A1 (en) 2020-01-06 2020-12-17 Burner control

Publications (2)

Publication Number Publication Date
GB202209144D0 GB202209144D0 (en) 2022-08-10
GB2605904A true GB2605904A (en) 2022-10-19

Family

ID=76788709

Family Applications (1)

Application Number Title Priority Date Filing Date
GB2209144.1A Pending GB2605904A (en) 2020-01-06 2020-12-17 Burner control

Country Status (4)

Country Link
BR (1) BR112022013081A2 (en)
GB (1) GB2605904A (en)
NO (1) NO20220761A1 (en)
WO (1) WO2021141749A1 (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6468069B2 (en) * 1999-10-25 2002-10-22 Jerome H. Lemelson Automatically optimized combustion control
EP2309186A2 (en) * 2009-10-07 2011-04-13 John Zink Company, L.L.C. Image sensing system, software, apparatus and method for controlling combustion equipment
US8138927B2 (en) * 2007-03-22 2012-03-20 Honeywell International Inc. Flare characterization and control system
WO2017058832A1 (en) * 2015-09-28 2017-04-06 Schlumberger Technology Corporation Burner monitoring and control systems

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6468069B2 (en) * 1999-10-25 2002-10-22 Jerome H. Lemelson Automatically optimized combustion control
US8138927B2 (en) * 2007-03-22 2012-03-20 Honeywell International Inc. Flare characterization and control system
EP2309186A2 (en) * 2009-10-07 2011-04-13 John Zink Company, L.L.C. Image sensing system, software, apparatus and method for controlling combustion equipment
WO2017058832A1 (en) * 2015-09-28 2017-04-06 Schlumberger Technology Corporation Burner monitoring and control systems

Also Published As

Publication number Publication date
WO2021141749A1 (en) 2021-07-15
NO20220761A1 (en) 2022-07-01
BR112022013081A2 (en) 2022-09-06
GB202209144D0 (en) 2022-08-10

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