Boiler combustion adjusting system and method based on slag state

Abstract

The invention relates to a boiler combustion adjusting system and method based on a slag state, and the system comprises an image data sensing system which is used for detecting the contour of a slag block according to image information, matching the three-dimensional dimension of the slag block and analyzing the ash component of the slag block, so as to generate image sensing data of the slag block according to the contour, the three-dimensional dimension and the ash component; the edge-cloud collaborative computing architecture is used for constructing a combustion big data platform and calculating the theoretical slag quantity under the current combustion working condition by utilizing the combustion big data platform; and the combustion optimization decision execution system is used for determining the abnormal condition of combustion of the hearth on the basis of the difference value between the theoretical slag falling amount and the actual slag falling amount, and adjusting at least one combustion parameter of the primary air volume, the rotating speed of the coal mill, the air distribution mode and the soot blowing system. According to the embodiment of the invention, a perception-analysis-execution integrated framework is constructed, and targeted strategy optimization is carried out on the combustion abnormal working condition based on parameters such as the slag falling amount, the slag block falling position and components.

Description

Technical Field

[0001] This application relates to the technical field of boiler combustion, and particularly relates to a boiler combustion adjustment system and method based on slag conditions. Background Art

[0002] Xinjiang high-alkali coal is one of the important power coals in China. However, the content of alkali metal oxides in its coal ash is generally ≥4%, and the content of alkaline earth metal oxides is generally ≥20%. The high content of alkali (alkaline earth) metals is the main reason for the easy occurrence of serious slagging and fouling in boilers when burning high-alkali coal. Especially when the boiler operates at variable loads, the temperature field, flow field in the furnace and the characteristics of alkali metal precipitation in coal will change violently, aggravating the slagging and fouling degree, and serious slag dropping occurs in the boiler.

[0003] In the related technology, it is difficult to accurately obtain the slagging condition in the furnace during the operation of the boiler, and it is difficult to optimize and adjust the combustion according to the slagging condition. It is impossible to weaken the slagging in the furnace and avoid large slag dropping in the boiler, which urgently needs to be improved. Summary of the Invention

[0004] This application provides a boiler combustion adjustment system and method based on slag conditions to solve the problems in the related technology that it is difficult to accurately obtain the slagging condition in the furnace during the operation of the boiler, it is difficult to optimize and adjust the combustion according to the slagging condition, it is impossible to weaken the slagging in the furnace, and it is impossible to avoid large slag dropping in the boiler.

[0005] In the first aspect of the embodiments of this application, a boiler combustion adjustment system based on slag conditions is provided, including: an image data perception system, configured to obtain image information of slag blocks, detect the contours of the slag blocks, match the three-dimensional solids of the slag blocks, and analyze the slag components of the slag blocks according to the image information, so as to generate image perception data of the slag blocks according to the contours, the three-dimensional solids, and the slag components; an edge-cloud collaborative computing architecture, configured to build a combustion big data platform based on the image perception data, and calculate the theoretical slag amount under the current combustion condition by using the combustion big data platform; a combustion optimization decision execution system, configured to determine the abnormal conditions of furnace combustion based on the difference between the theoretical slag dropping amount and the actual slag dropping amount, and adjust at least one combustion parameter among the primary air volume, the mill speed, the air distribution mode, and the soot blowing system based on the abnormal conditions, so as to generate a boiler combustion adjustment result of the slag condition.

[0006] In the embodiments of the present application, by monitoring the physical characteristics (size, mass), chemical components (combustibles, alkali metals) and combustion state parameters of the slag in real time, the optimized control of the combustion side of the boiler is realized. By constructing an "awareness - analysis - execution" integrated architecture, targeted strategy optimization is carried out for abnormal combustion conditions based on parameters such as the amount of slag falling, the position where the slag block drops, and the composition. During the operation of the boiler, the slag condition in the furnace is accurately obtained, and the combustion is optimized and adjusted according to the slagging condition, which is of great significance for weakening the slagging in the furnace and avoiding large slag dropping from the boiler.

[0007] Optionally, in an embodiment of the present application, it is characterized in that the image data perception system includes: a three - dimensional structure reconstruction system, which includes a camera array and a slag block recognition system, and is used to detect the contour of the slag block and perform three - dimensional stereo matching on the slag block; a real - time ash slag composition analysis system, which is used to non - contact scan the dropped slag block and integrate a micro near - infrared sensor to analyze the combustible content of the dropped slag block in real time; a data analysis and fusion system, which is used to bind the ash slag composition data with the position and size of the slag block by using timestamp synchronization to construct a target association database.

[0008] The embodiments of the present application can perform accurate three - dimensional reconstruction and slag block recognition, improving the accuracy of slag block recognition. The real - time ash slag composition analysis system integrates a micro near - infrared sensor, realizing non - contact scanning of the dropped slag block and real - time analysis of the combustible content. The data analysis and fusion system enhances the correlation and availability of the data, optimizes the combustion parameter settings, and reduces unnecessary energy consumption and pollutant emissions.

[0009] Optionally, in an embodiment of the present application, the three - dimensional structure reconstruction system is further used to calculate the dynamic three - dimensional coordinates of the slag block according to the binocular disparity and inter - frame motion estimation data, confirm the slag block volume according to the dynamic three - dimensional coordinates, and calculate the actual slag dropping amount of the boiler at the current moment according to the slag block volume and the empirical bulk density of the slag block.

[0010] The embodiments of the present application can more accurately calculate the dynamic three - dimensional coordinates and volume of the slag block by combining binocular disparity and inter - frame motion estimation data, providing a reliable basis for the accurate calculation of the actual slag dropping amount of the boiler, thereby improving the measurement accuracy, realizing real - time monitoring of the slag dropping situation of the boiler, and making a rapid response.

[0011] Optionally, in an embodiment of the present application, the formula for converting binocular disparity to depth of the slag block volume is: , where B is the camera baseline, f is the focal length, and d is the disparity value; The conversion formula for the dynamic three - dimensional coordinates is: , , Among them, ([[]] u, v ) are pixel coordinates, and ([[]] c x , c y ) is the optical center; The update formula for the dynamic three-dimensional coordinates is: , where ΔX is the three-dimensional displacement.

[0012] The embodiments of the present application can improve the calculation accuracy according to the formula, and further accurately calculate the dynamic three-dimensional coordinates and volume of the slag block, providing a reliable basis for the accurate calculation of the actual slag discharge amount of the boiler.

[0013] Optionally, in an embodiment of the present application, the edge-cloud collaborative computing architecture includes: an extraction layer for processing real-time images to generate processed data and extracting the basic features of the slag block according to the processed data; a calculation layer for constructing the combustion big data platform based on the basic features, and associating at least one distributed control system data among coal quality, load, operating oxygen content, and flue gas temperature with the combustion big data platform to calculate the theoretical slag amount under the current combustion condition according to the distributed control system data and at least one design parameter.

[0014] In the edge-cloud collaborative computing architecture 200 of the embodiments of the present application, preliminary processing and analysis can be first performed on the edge side, and then the necessary data is uploaded to the cloud for more in-depth big data analysis, improving the response speed and processing efficiency of the entire system, comprehensively monitoring and analyzing the combustion condition, and then accurately calculating the theoretical slag amount under the current condition.

[0015] The embodiments of the second aspect of the present application provide a boiler combustion adjustment method based on the slag state, including the following steps: obtaining the image information of the slag block, and detecting the contour of the slag block, matching the three-dimensional solid of the slag block, and analyzing the ash composition of the slag block according to the image information to generate the image perception data of the slag block; constructing a combustion big data platform based on the image perception data, and calculating the theoretical slag amount under the current combustion condition by using the combustion big data platform; determining the abnormal situation of the furnace combustion based on the difference between the theoretical slag discharge amount and the actual slag discharge amount, and adjusting at least one combustion parameter among the primary air volume, the mill speed, the air distribution mode, and the soot blowing system based on the abnormal situation to generate the boiler combustion adjustment result of the slag state.

[0016] Optionally, in an embodiment of the present application, the detecting the contour of the slag block, matching the three-dimensional solid of the slag block, and analyzing the ash composition of the slag block according to the image information include: detecting the contour of the slag block and performing three-dimensional solid matching on the slag block; non-contact scanning of the dropped slag block and integrating a micro near-infrared sensor to analyze the combustible content of the dropped slag block in real time; using timestamp synchronization to bind the ash composition data to the position and size of the slag block to construct a target association database.

[0017] Optionally, in an embodiment of the present application, the detecting the contour of the slag block, matching the three-dimensional solid of the slag block, and analyzing the ash composition of the slag block according to the image information further include: calculating the dynamic three-dimensional coordinates of the slag block according to binocular parallax and inter-frame motion estimation data; confirming the slag block volume according to the dynamic three-dimensional coordinates, and calculating the actual slag discharge amount of the boiler at the current moment according to the slag block volume and the empirical bulk density of the slag block.

[0018] Optionally, in an embodiment of the present application, the binocular parallax to depth calculation formula for the slag block volume is: , where B is the camera baseline, f is the focal length, and d is the parallax value; The conversion formula for the dynamic three-dimensional coordinates is: , , where ( u, v ) is the pixel coordinate, and ( c x , c y ) is the optical center; The update formula for the dynamic three-dimensional coordinates is: , where ΔX is the three-dimensional displacement.

[0019] Optionally, in an embodiment of the present application, the constructing a combustion big data platform based on the image perception data and using the combustion big data platform to calculate the theoretical slag amount under the current combustion condition include: processing real-time images to generate processed data, and extracting the basic features of the slag block according to the processed data; constructing the combustion big data platform based on the basic features, and associating at least one distributed control system data among coal quality, load, operating oxygen content, and flue gas temperature based on the combustion big data platform, so as to calculate the theoretical slag amount under the current combustion condition according to the distributed control system data and at least one design parameter.

[0020] A third - aspect embodiment of the present application provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement the boiler combustion adjustment method based on the slag state as described in the above - mentioned embodiment.

[0021] A fourth - aspect embodiment of the present application provides a computer - readable storage medium storing a computer program, which when executed by a processor implements the above - mentioned boiler combustion adjustment method based on the slag state.

[0022] A fifth - aspect embodiment of the present application provides a computer program product storing a computer program, which when executed by a processor implements the above - mentioned boiler combustion adjustment method based on the slag state.

[0023] An embodiment of the present application relates to a combustion optimization method integrating image recognition, spectral analysis, and multi - sensor data. By real - time monitoring of the physical characteristics (size, mass), chemical components (combustibles, alkali metals) of the slag, and combustion state parameters, it realizes the optimal control of the boiler combustion side. By constructing an "awareness - analysis - execution" integrated architecture, based on parameters such as slag discharge amount, slag block falling position, and composition, it conducts targeted strategy optimization for abnormal combustion conditions. Thus, it solves the problems in the related technology that it is difficult to accurately obtain the slag condition in the furnace during the boiler operation process, difficult to optimize and adjust the combustion according to the slagging condition, unable to weaken the slagging in the furnace, and unable to avoid large - slag dropping in the boiler.

[0024] The additional aspects and advantages of the present application will be partly given in the following description, partly become obvious from the following description, or be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above - mentioned and / or additional aspects and advantages of the present application will become obvious and easy to understand from the following description of the embodiments in conjunction with the drawings, where: Figure 1 FIG. is a schematic structural diagram of a boiler combustion adjustment system based on the slag state according to an embodiment of the present application; Figure 2 FIG. is a technical flow chart of a boiler combustion adjustment system based on the slag state according to an embodiment of the present application; Figure 3 FIG. is a schematic layout diagram of a high - speed CCD camera of a boiler combustion adjustment system based on the slag state according to an embodiment of the present application; Figure 4 FIG. is a flow chart of a boiler combustion adjustment method based on the slag state according to an embodiment of the present application; Figure 5A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0027] The following describes a boiler combustion adjustment system and method based on slag status according to an embodiment of the present application with reference to the accompanying drawings. In view of the fact that the related technologies mentioned in the above background technology are difficult to accurately obtain the slag falling status in the furnace during boiler operation, and it is difficult to optimize and adjust the combustion according to the slag falling status, it is impossible to reduce the slag falling in the furnace, and it is impossible to avoid the problem of large slag falling in the boiler, the present application provides a boiler combustion adjustment system based on slag status, in which the slag physical characteristics (size, mass), chemical composition (combustibles, alkali metals) and combustion state parameters are monitored in real time to achieve optimized control of the boiler combustion side, and by building an integrated "perception-analysis-execution" architecture, based on parameters such as the slag falling amount, slag falling location, and composition, targeted strategy optimization is carried out for abnormal combustion conditions, accurately obtaining the slag falling status in the furnace during boiler operation, and optimizing and adjusting the combustion according to the slag falling status, which is of great significance for reducing slag falling in the furnace and avoiding large slag falling in the boiler. This solves the problems of related technologies in that it is difficult to accurately obtain the slagging conditions in the furnace during boiler operation, it is difficult to optimize the combustion according to the slagging conditions, it is impossible to reduce the slagging in the furnace, and it is impossible to avoid large slag falling from the boiler.

[0028] Specifically, Figure 1 A structural schematic diagram of a boiler combustion adjustment system based on slag state provided in an embodiment of the present application.

[0029] like Figure 1 As shown, the boiler combustion adjustment system 10 based on the slag state includes: Specifically, the image data perception system 100 is used to obtain image information of the slag block, and detect the contour of the slag block based on the image information, match the stereoscopic three-dimensionality of the slag block, and analyze the ash composition of the slag block, so as to generate image perception data of the slag block based on the contour, stereoscopic three-dimensionality and ash composition.

[0030] It can be understood that, in the embodiment of the present application, the three-dimensional matching of the slag block may be three-dimensional matching of the slag block.

[0031] In the actual execution process, the embodiment of the present application can use the image data perception system 100 to capture the image information of the slag block using a high-resolution camera or other imaging devices (such as infrared cameras, X-ray imaging, etc.), and detect the contour of the slag block, match the three-dimensional stereo of the slag block, and analyze the ash composition of the slag block according to the image information, so as to generate the image perception data of the slag block based on the contour, three-dimensional stereo, and ash composition.

[0032] The embodiment of the present application can identify and extract the contour of the slag block, thereby determining the shape and size of the slag block, accurately reconstructing the three-dimensional structure of the slag block, and analyzing the spectral characteristics reflected or emitted by the slag block, thereby inferring its chemical composition, improving the detection accuracy, more intuitively understanding the physical form of the slag block, and effectively identifying various elements and compounds contained in the slag block.

[0033] Optionally, in an embodiment of the present application, it is characterized in that the image data perception system 100 includes: a three-dimensional structure reconstruction system, which includes a camera array and a slag block recognition system, and is used to detect the contour of the slag block and perform three-dimensional stereo matching on the slag block; an ash composition real-time analysis system, which is used to non-contact scan the dropped slag block and integrate a micro near-infrared sensor to real-time analyze the combustible content of the dropped slag block; a data analysis and fusion system, which is used to bind the ash composition data with the position and size of the slag block using timestamp synchronization to construct a target association database.

[0034] It can be understood that as Figure 2 shown, the image data perception system 100 in the embodiment of the present application mainly includes a high-precision three-dimensional structure reconstruction system for slag blocks, that is, a three-dimensional structure reconstruction system, an ash composition real-time analysis system, and a data analysis and fusion system; the target database can be a "space-time - composition" association database.

[0035] In the actual execution process, the three-dimensional structure reconstruction system in the embodiment of the present application is mainly composed of a camera array and its slag block recognition system, and mainly includes: arranging a circular camera array in the cold ash hopper area, with a total of 4 high-speed CCD cameras arranged by 2 horizontal + 2 vertical layers, as Figure 3 shown, the camera is built-in with an infrared supplementary light module to adapt to the high-temperature and high-dust environment inside the boiler cold ash hopper; slag block contour detection: real-time detection of furnace slag blocks based on the YOLOv7 algorithm, and through dynamic label assignment combined with a reparameterization training strategy, high-precision real-time detection of slag block contours is achieved; slag block three-dimensional stereo matching.

[0036] Furthermore, the ash residue real-time composition analysis device in the embodiment of the present application is arranged at the slag conveying device. The ash residue composition real-time online detection device adopts laser-induced breakdown spectroscopy (LIBS) technology. The ash residue composition real-time analysis system performs non-contact scanning on the fallen slag blocks, detects the content of alkali elements (such as Na, K, Fe, etc.) in the slag blocks, and integrates a micro near-infrared (NIR) sensor to analyze the combustible content of the fallen slag blocks in real time.

[0037] Furthermore, the data analysis and fusion system in the embodiment of the present application is used to bind the ash residue composition data with the position and size of the slag blocks by using timestamp synchronization to construct a "space-time - composition" correlation database.

[0038] The embodiment of the present application can perform precise three-dimensional reconstruction and slag block recognition, improving the accuracy of slag block recognition. The ash residue composition real-time analysis system integrates a micro near-infrared sensor, realizing non-contact scanning of the fallen slag blocks and real-time analysis of the combustible content. The data analysis and fusion system enhances the correlation and availability of the data, optimizes the combustion parameter settings, and reduces unnecessary energy consumption and pollutant emissions.

[0039] Optionally, in an embodiment of the present application, the three-dimensional structure reconstruction system is further used to calculate the dynamic three-dimensional coordinates of the slag blocks according to the binocular disparity and inter-frame motion estimation data, confirm the volume of the slag blocks according to the dynamic three-dimensional coordinates, and calculate the actual slag dropping amount of the boiler at that moment according to the volume of the slag blocks and the empirical bulk density of the slag blocks.

[0040] It can be understood that the inter-frame motion estimation in the embodiment of the present application is a video processing technology used to analyze the motion changes between consecutive frames to estimate the movement of an object in space.

[0041] Specifically, the three-dimensional structure reconstruction system in the embodiment of the present application further includes slag block three-dimensional stereo matching: The improved PatchMatch algorithm is used to calculate the binocular disparity (spatial information) and inter-frame motion estimation data (temporal information) respectively, and fuse the two data, that is, calculate the dynamic three-dimensional coordinates of the slag blocks according to the binocular disparity and inter-frame motion estimation data, thereby confirming the volume of the slag blocks. According to the empirical bulk density of the slag blocks, the actual volume of the slag blocks is calculated, and thus the actual slag dropping amount of the boiler at that moment is calculated.

[0042] By combining the binocular disparity and inter-frame motion estimation data, the embodiment of the present application can more accurately calculate the dynamic three-dimensional coordinates and volume of the slag blocks, providing a reliable basis for the accurate calculation of the actual slag dropping amount of the boiler, thereby improving the measurement accuracy, realizing real-time monitoring of the boiler slag dropping situation, and making a rapid response.

[0043] Among them, in an embodiment of the present application, the formula for converting binocular disparity to depth of the slag block volume is: , where B is the camera baseline, f is the focal length, and d is the disparity; The conversion formula for dynamic three-dimensional coordinates is: , , where ( u, v ) are the pixel coordinates, and ( c x , c y ) is the optical center; Assume that the slag block moves within the time Δ t . According to the three-dimensional displacement ΔX estimated by optical flow, update the coordinates. The update formula for dynamic three-dimensional coordinates is: , where ΔX is the three-dimensional displacement.

[0044] The embodiments of the present application can improve the accuracy of calculation according to the formula, and further accurately calculate the dynamic three-dimensional coordinates and volume of the slag block, providing a reliable basis for the accurate calculation of the actual slag dropping amount of the boiler.

[0045] The edge-cloud collaborative computing architecture 200 is used to construct a combustion big data platform based on image perception data, and use the combustion big data platform to calculate the theoretical slag amount under the current combustion condition.

[0046] It can be understood that the edge-cloud collaborative computing architecture 200 in the embodiments of the present application is a distributed computing architecture that combines the advantages of edge computing and cloud computing; the combustion big data platform is a platform specifically used for collecting, storing, processing, and analyzing a large amount of data related to the combustion process.

[0047] In the actual execution process, the edge-cloud collaborative computing architecture 200 in the embodiments of the present application is used to construct a combustion big data platform based on image perception data, and use the combustion big data platform to calculate the theoretical slag amount under the current combustion condition, so as to comprehensively monitor and analyze the combustion condition, and then accurately calculate the theoretical slag amount under the current condition.

[0048] Optionally, in an embodiment of the present application, the edge-cloud collaborative computing architecture 200 includes: an extraction layer, which is used to process real-time images to generate processed data, and extract the basic features of the slag block according to the processed data; a calculation layer, which is used to construct a combustion big data platform based on the basic features, and associate at least one distributed control system data among coal quality, load, operating oxygen content, and flue gas temperature with the combustion big data platform, so as to calculate the theoretical slag amount under the current combustion condition according to the distributed control system data and at least one design parameter.

[0049] It can be understood that in the embodiments of the present application, the extraction layer corresponds to the edge side, and the calculation layer corresponds to the cloud side.

[0050] In the actual execution process, in the embodiments of the present application, the edge side executes the following tasks through an embedded AI chip accelerated by local deployment of FPGA: real-time image preprocessing (denoising, distortion correction); basic feature extraction (volume, speed) of slag blocks falling from the cold hopper. In the embodiments of the present application, the cloud side is used to build a combustion big data platform based on the basic features, and correlate at least one of the coal quality, load, operating oxygen content, and flue gas temperature in the distributed control system DCS data based on the combustion big data platform, so as to calculate the theoretical slag amount under the current combustion condition according to the distributed control system data and at least one design parameter.

[0051] In the edge-cloud collaborative computing architecture 200 of the embodiments of the present application, preliminary processing and analysis can be first performed on the edge side, and then necessary data is uploaded to the cloud side for more in-depth big data analysis, which improves the response speed and processing efficiency of the entire system, further comprehensively monitors and analyzes the combustion condition, and then accurately calculates the theoretical slag amount under the current condition.

[0052] The combustion optimization decision execution system 300 is used to determine the abnormal situation of furnace combustion based on the difference between the theoretical slag discharge amount and the actual slag discharge amount, and based on the abnormal situation, adjust at least one combustion parameter among the primary air volume, coal mill speed, air distribution mode, and soot blowing system to generate a boiler combustion adjustment result for the slag state.

[0053] It can be understood that the difference in the embodiments of the present application can be 20% or more.

[0054] As a possible implementation manner, the combustion optimization decision execution system 300 in the embodiments of the present application can perform a judgment on the threshold of the combustion abnormal state: by comparing the actual slag discharge amount with the theoretical slag discharge amount, when the actual slag discharge amount is 20% or more higher than the theoretical slag discharge amount, it indicates that there is an abnormal situation in furnace combustion. The embodiments of the present application can perform combustion strategy optimization: based on the abnormal situation, adjust at least one combustion parameter among the primary air volume, coal mill speed, air distribution mode, and soot blowing system according to the current slag discharge amount from the cold hopper, slag block position and composition to generate a boiler combustion adjustment result for the slag state.

[0055] The embodiments of the present application can carry out targeted strategy optimization for abnormal combustion conditions based on parameters such as the slag discharge amount, slag block falling position, and composition by constructing a "perception - analysis - execution" integrated architecture.

[0056] The boiler combustion adjustment system based on slag state proposed according to the embodiments of the present application realizes the optimal control of the combustion side of the boiler by real-time monitoring of the physical characteristics (size, mass), chemical composition (combustibles, alkali metals) and combustion state parameters of the slag, and through constructing an "awareness - analysis - execution" integrated architecture, based on parameters such as slag drop amount, slag block drop position, composition, etc., carries out targeted strategy optimization for abnormal combustion conditions. Thereby, it solves the problems in the related technology that it is difficult to accurately obtain the slag condition in the furnace during the operation of the boiler, and it is difficult to optimize the combustion according to the slagging condition, unable to weaken the slagging in the furnace, and unable to avoid the problem of large slag dropping in the boiler.

[0057] Next, the boiler combustion adjustment method based on slag state proposed according to the embodiments of the present application is described with reference to the accompanying drawings.

[0058] Figure 4 It is a flowchart of the boiler combustion adjustment method based on slag state according to the embodiments of the present application.

[0059] As Figure 4 shown, the boiler combustion adjustment method based on slag state includes the following steps: In step S401, obtain the image information of the slag block, and detect the contour of the slag block, match the three-dimensional solid of the slag block and analyze the ash composition of the slag block according to the image information, so as to generate the image perception data of the slag block based on the contour, three-dimensional solid and ash composition.

[0060] In step S402, based on the image perception data, construct a combustion big data platform, and use the combustion big data platform to calculate the theoretical slag amount under the current combustion condition.

[0061] In step S403, based on the difference between the theoretical slag drop amount and the actual slag drop amount, determine the abnormal situation of the furnace combustion, and based on the abnormal situation, adjust at least one combustion parameter among the primary air volume, mill speed, air distribution mode and soot blowing system, so as to generate the boiler combustion adjustment result of the slag state.

[0062] Optionally, in an embodiment of the present application, detecting the contour of the slag block, matching the three-dimensional solid of the slag block and analyzing the ash composition of the slag block according to the image information includes: detecting the contour of the slag block and performing three-dimensional solid matching on the slag block; non-contact scanning of the dropped slag block, and integrating a micro near-infrared sensor to analyze the combustible content of the dropped slag block in real time; using timestamp synchronization to bind the ash composition data with the position and size of the slag block to construct a target association database.

[0063] Optionally, in an embodiment of the present application, detecting the contour of the slag block, matching the three-dimensional solid of the slag block, and analyzing the ash composition of the slag block based on the image information further includes: calculating the dynamic three-dimensional coordinates of the slag block according to the binocular parallax and the inter-frame motion estimation data; confirming the volume of the slag block according to the dynamic three-dimensional coordinates, and calculating the actual slag drop amount of the boiler at the current moment according to the volume of the slag block and the empirical stacking density of the slag block.

[0064] Optionally, in an embodiment of the present application, the formula for converting binocular parallax to depth of the slag block volume is: , where B is the camera baseline, f is the focal length, and d is the parallax value; The conversion formula for the dynamic three-dimensional coordinates is: , , where ( u, v ) are the pixel coordinates, and ( c x , c y ) is the optical center; The update formula for the dynamic three-dimensional coordinates is: , where ΔX is the three-dimensional displacement.

[0065] Optionally, in an embodiment of the present application, based on the image perception data, a combustion big data platform is constructed, and the theoretical slag amount under the current combustion condition is calculated by using the combustion big data platform, including: processing the real-time image to generate processed data, and extracting the basic features of the slag block according to the processed data; constructing a combustion big data platform based on the basic features, and associating at least one distributed control system data of coal quality, load, operating oxygen content, and flue gas temperature based on the big data platform, so as to calculate the theoretical slag amount under the current combustion condition according to the distributed control system data and at least one design parameter.

[0066] It should be noted that the foregoing explanation of the embodiment of the boiler combustion adjustment system based on the slag state also applies to the boiler combustion adjustment method based on the slag state of this embodiment, and will not be elaborated here.

[0067] The boiler combustion adjustment method based on slag state proposed in the embodiments of the present application relates to a combustion optimization method integrating image recognition, spectral analysis, and multi-sensor data. By real-time monitoring of the physical characteristics (size, mass), chemical components (combustibles, alkali metals), and combustion state parameters of the slag, the optimization control of the boiler combustion side is realized. By constructing an "awareness - analysis - execution" integrated architecture, targeted strategy optimization is carried out for abnormal combustion conditions based on parameters such as slag discharge amount, slag block falling position, and composition. Thus, the problems in the related technology during the boiler operation process are solved, including the difficulty in accurately obtaining the slag condition in the furnace, the difficulty in optimizing the combustion according to the slagging condition, the inability to weaken the slagging in the furnace, and the inability to avoid large slag dropping in the boiler.

[0068] Figure 5 The structural schematic diagram of the electronic device provided by the embodiments of the present application. The electronic device may include: A memory 501, a processor 502, and a computer program stored on the memory 501 and executable on the processor 502.

[0069] When the processor 502 executes the program, it implements the boiler combustion adjustment method based on slag state provided in the above embodiments.

[0070] Furthermore, the electronic device further includes: A communication interface 503 for communication between the memory 501 and the processor 502.

[0071] The memory 501 is used to store the computer program executable on the processor 502.

[0072] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0073] If the memory 501, the processor 502, and the communication interface 503 are independently implemented, the communication interface 503, the memory 501, and the processor 502 can be interconnected through a bus and complete the communication between each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 5 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0074] Optionally, in a specific implementation, if the memory 501, the processor 502, and the communication interface 503 are integrated on a single chip, the memory 501, the processor 502, and the communication interface 503 can communicate with each other through an internal interface.

[0075] The processor 502 may be a central processing unit (CPU for short), or an application specific integrated circuit (ASIC for short), or one or more integrated circuits configured to implement the embodiments of the present application.

[0076] This embodiment also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the above-described method for adjusting boiler combustion based on slag state is implemented.

[0077] The embodiments of the present application also provide a computer program product, on which a computer program is stored, and when the program is executed by a processor, the above-described method for adjusting boiler combustion based on slag state is implemented.

[0078] In the description of this specification, the descriptions with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc., mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, without conflict, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0079] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0080] Any process or method description represented in a flowchart or otherwise described herein can be understood to represent a module, segment, or portion of code including one or N executable instructions for implementing a customized logical function or process. The scope of the preferred embodiments of the present application includes additional implementations, where functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0081] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing a logical function, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion with one or N wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically by optically scanning the paper or other media, followed by editing, interpretation, or other appropriate processing as necessary, and then stored in a computer memory.

[0082] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0083] Those of ordinary skill in the art can understand that all or part of the steps carried out in implementing the above-described embodiment methods can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0084] In addition, in each of the embodiments of the present application, the functional units can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. When the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0085] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A boiler combustion adjustment system based on the slag state, characterized in that, Including: An image data perception system, which is used to obtain the image information of slag blocks, detect the contours of the slag blocks according to the image information, match the three-dimensional stereo of the slag blocks, and analyze the ash composition of the slag blocks, so as to generate image perception data of the slag blocks according to the contours, the three-dimensional stereo and the ash composition; An edge-cloud collaborative computing architecture, which is used to build a combustion big data platform based on the image perception data, and calculate the theoretical slag amount under the current combustion condition by using the combustion big data platform; A combustion optimization decision execution system, which is used to determine the abnormal situation of furnace combustion based on the difference between the theoretical slag falling amount and the actual slag falling amount, and adjust at least one combustion parameter among the primary air volume, the coal mill speed, the air distribution mode and the soot blowing system based on the abnormal situation, so as to generate a boiler combustion adjustment result of the slag state.

2. The boiler combustion adjustment system based on the slag state according to claim 1, wherein, The image data perception system includes: A three-dimensional structure reconstruction system, which includes a camera array and a slag block recognition system, and is used to detect the contours of the slag blocks and perform three-dimensional stereo matching on the slag blocks; An ash composition real-time analysis system, which is used to non-contact scan the falling slag blocks and integrate a micro near-infrared sensor to real-time analyze the combustible content of the falling slag blocks; A data analysis and fusion system, which is used to bind the ash composition data with the position and size of the slag blocks by using timestamp synchronization to build a target association database.

3. The boiler combustion adjustment system based on the slag state according to claim 2, characterized in that The three-dimensional structure reconstruction system is further used to calculate the dynamic three-dimensional coordinates of the slag blocks according to the binocular parallax and the inter-frame motion estimation data, confirm the slag block volume according to the dynamic three-dimensional coordinates, and calculate the actual slag falling amount of the boiler at the current moment according to the slag block volume and the slag block empirical bulk density.

4. The boiler combustion adjustment system based on the slag state according to claim 3, characterized in that The binocular parallax to depth calculation formula of the slag block volume is: ， where B is the camera baseline, f is the focal length, and d is the disparity value; The conversion formula of the dynamic three-dimensional coordinates is: ， ， Among them, ( u, v ) is the pixel coordinate, and ( c x , c y ) is the optical center; The update formula of the dynamic three-dimensional coordinates is: ， Where, ΔX is the three-dimensional displacement.

5. The boiler combustion adjustment system based on the slag state according to claim 1, wherein The edge-cloud collaborative computing architecture includes: An extraction layer, which is used to process real-time images to generate processed data, and extract the basic features of the slag blocks according to the processed data; A calculation layer, which is used to build the combustion big data platform based on the basic features, and associate at least one distributed control system data among coal quality, load, operating oxygen content and flue gas temperature based on the combustion big data platform, so as to calculate the theoretical slag amount under the current combustion condition according to the distributed control system data and at least one design parameter.

6. A boiler combustion adjustment method based on the slag state, characterized in that, Including the following steps: Obtain the image information of the slag blocks, detect the contours of the slag blocks according to the image information, match the three-dimensional stereo of the slag blocks, and analyze the ash composition of the slag blocks, so as to generate image perception data of the slag blocks according to the contours, the three-dimensional stereo and the ash composition; Build a combustion big data platform based on the image perception data, and calculate the theoretical slag amount under the current combustion condition by using the combustion big data platform; Based on the difference between the theoretical slag loss and the actual slag loss, determine the abnormal situation of furnace combustion, and based on the abnormal situation, adjust at least one combustion parameter among the primary air volume, the mill speed, the air distribution mode, and the soot blowing system, so as to generate a boiler combustion adjustment result for the slag state.

7. The method for adjusting boiler combustion based on slag condition according to claim 6, characterized in that, The detecting the contour of the slag block, matching the three-dimensional solid of the slag block, and analyzing the ash composition of the slag block according to the image information includes: Detect the contour of the slag block and perform three-dimensional solid matching on the slag block; Non-contact scan the dropped slag block and integrate a micro near-infrared sensor to analyze the combustible content of the dropped slag block in real time; Use timestamp synchronization to bind the ash composition data to the position and size of the slag block to construct a target association database.

8. An electronic device, characterized in that, Including: A memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the program to implement the boiler combustion adjustment method based on the slag state according to any one of claims 6-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to be used for implementing the boiler combustion adjustment method based on the slag state according to any one of claims 6-7.

10. A computer program product, comprising a computer program, characterized in that, The computer program is executed to be used for implementing the boiler combustion adjustment method based on the slag state according to any one of claims 6-7.

Images