CN115130846A - Method for analyzing maximum influence factors of lower part heat system of blast furnace based on tuyere monitoring - Google Patents
Method for analyzing maximum influence factors of lower part heat system of blast furnace based on tuyere monitoring Download PDFInfo
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Abstract
The invention particularly relates to a method for analyzing the maximum influence factor of a thermal system at the lower part of a blast furnace based on tuyere monitoring, which is used for building a blast furnace tuyere monitoring system, realizing intelligent acquisition of tuyere images based on different brightnesses and realizing automatic analysis of tuyere brightness; the method comprises the following steps of realizing automatic adjustment of the collection parameters of the tuyere monitoring system through a pre-calibration method so as to effectively collect a tuyere brightness image; and the maximum influence factors of the thermal system at the lower part of the blast furnace are automatically analyzed by adopting a partial least square method on the blast furnace blast volume, blast temperature, furnace burden descending speed, blast furnace iron output, smelting period and other relevant process parameters and the change trend of the blast furnace tuyere brightness. The invention can effectively solve the problem of over-exposure of brightness in the monitoring of the blast furnace tuyere image and realize the automatic adjustment of the tuyere image; meanwhile, the tuyere brightness monitoring result is combined with the blast furnace process parameters, so that the automatic analysis of the maximum influence factor of the thermal system at the lower part of the blast furnace is effectively carried out, the regulation at the lower part of the blast furnace is optimized, and the control level of the blast furnace is improved.
Description
Technical Field
The invention relates to the technical field of analysis methods of maximum influence factors of a lower part heat system of a blast furnace, in particular to a method for analyzing the maximum influence factors of the lower part heat system of the blast furnace based on tuyere monitoring.
Background
The iron and steel industry is the basic industry of national economy and national defense construction, and the current main flow of iron and steel in China is mainly the long flow of an iron making-steel making model. As the biggest monomer smelting equipment in the world, a blast furnace is the core of iron making, and in order to improve the energy utilization efficiency and reduce the smelting cost, the blast furnace generally adopts technologies such as pulverized coal injection in front of a tuyere, high air temperature and the like to realize optimization of the smelting efficiency of the blast furnace and regulation of the lower part of the blast furnace at present. The heat system of the blast furnace is the key point influencing the quality of pig iron of the blast furnace, smelting efficiency and operation level, and the regulation at the lower part of the blast furnace has great influence on the quality. However, at present, the blast furnace thermal system is mainly judged by manual experience or by tuyere brightness, process parameters and the like, and an effective maximum influence factor analysis method is not determined according to actual conditions.
With the development of artificial intelligence technology and CCD imaging technology, the blast furnace tuyere monitoring technology based on machine vision is widely applied, and the patent "a blast furnace tuyere on-line monitoring image pickup device" (CN201520770267.9), "a blast furnace tuyere camera device" (CN201820629808.X), "a method for monitoring and predicting abnormal conditions of the blast furnace based on deep learning of tuyere information" (CN202110187003.0) and the like propose a blast furnace tuyere imaging and tuyere state monitoring method based on machine vision, so that the automatic monitoring of the coal injection condition of the blast furnace tuyere and the judgment of the abnormal conditions of the tuyere can be realized. Has important guiding significance for improving the production efficiency of the blast furnace, reducing safety accidents and improving the quantitative operation level of the blast furnace. However, the invention only limits the blast furnace tuyere monitoring to the tuyere coal injection amount, tuyere damage and the like, so that the problems of overexposure or over-low brightness of tuyere images under partial working conditions occur, and the maximum influence factor of the blast furnace thermal system cannot be analyzed by combining with blast furnace process parameters.
Disclosure of Invention
The invention aims to provide a method for analyzing the maximum influence factor of a thermal system at the lower part of a blast furnace based on tuyere monitoring, which aims to solve the problem of brightness overexposure in the blast furnace tuyere image monitoring and realize the automatic adjustment of a tuyere image; meanwhile, the tuyere monitoring result is combined with the blast furnace process parameters, so that the automatic analysis of the maximum influence factor of the thermal system at the lower part of the blast furnace is effectively carried out, and a good foundation is laid for optimizing the regulation at the lower part of the blast furnace and improving the control level of the blast furnace.
The invention provides a method for analyzing the maximum influence factor of a thermal system at the lower part of a blast furnace based on tuyere monitoring, which sequentially comprises the following steps of:
s1, acquiring a real-time blast furnace tuyere image, judging whether the blast furnace tuyere image is in an overexposure or excessively dark state, and adjusting the exposure time and the gain of the blast furnace tuyere image in the overexposure or excessively dark state by adopting a pre-calibration method until the brightness of the blast furnace tuyere image meets the standard;
s2, taking a blast furnace tuyere image with a time length of S, taking the average brightness value of a group of blast furnace tuyere images at intervals of a fixed time S as the tuyere brightness of the group, simultaneously taking the average value of each blast furnace smelting process parameter at intervals of the same fixed time S, forming sample data by the tuyere brightness and the average value of all blast furnace smelting process parameters, wherein the number of the samples is S/S;
s3, the blast furnace smelting process parameters comprise blast furnace blast volume XB, blast temperature XBT, furnace burden descending speed XBD, blast furnace tapping amount XI, smelting period XS, coal injection amount XPCI and oxygen enrichment ratio XBOAnd when the brightness of the tuyere is recorded as L, an independent variable matrix formed by the average values of the blast furnace smelting process parameters is recorded as X ═ XB, XBT, XBD, XI, XS, XPCI and XBO } 7×S/s And the dependent variable matrix formed by the luminance of the air inlet is recorded as Y ═ L } 1×S/s Normalizing the X and Y matrixes to obtain a new data matrix E 0 、F 0 And then constructing a partial least squares regression equation, and measuring the importance of the influence of the blast furnace smelting process parameters on the tuyere brightness by adopting variable projection importance indexes, wherein the larger the variable projection importance index is, the higher the importance of the influence of the blast furnace smelting process parameters on the tuyere brightness is, namely, the blast furnace smelting process parameters with the largest influence on the blast furnace thermal system in the time period are.
Preferably, the blast furnace tuyere image is extracted by a blast furnace tuyere monitoring system, the blast furnace tuyere monitoring system comprises a high frame rate camera based on an FPGA, a telecentric lens, a power supply system, a data transmission system, an image storage and processing system and a high temperature resistant dustproof protective sleeve, the telecentric lens is connected with the high frame rate camera based on the FPGA, the high frame rate camera based on the FPGA is connected with the data transmission system, the data transmission system is connected with the image storage and processing system, the power supply system is used for supplying power to the blast furnace tuyere monitoring system, the high temperature resistant dustproof protective sleeve is used for high temperature resistant and dustproof protection of the blast furnace tuyere monitoring system, and the high frame rate camera based on the FPGA shoots the blast furnace tuyere image and uploads the blast furnace tuyere image to the image storage and processing system through the data transmission system.
Preferably, when the gray value of the acquired real-time blast furnace tuyere image is judged to be in the range of more than 200 or less than 100 by the FPGA-based high frame rate camera, the blast furnace image is considered to be in an overexposure state or an excessively dark state.
Preferably, in the step 1, the exposure time and the gain of the blast furnace tuyere image in the overexposure or the overexposure state are adjusted by a pre-calibration method until the average brightness of the blast furnace tuyere image within 5 seconds is within the range of 150 +/-50, so that the brightness of the blast furnace tuyere image meets the standard.
The invention has the following beneficial effects: the traditional blast furnace tuyere state monitoring can not realize the automatic camera parameter adjusting function based on the tuyere image brightness change, so that the quality of the shot tuyere image is not high, the problem of over-brightness or over-darkness is easy to occur, the quantitative judgment cannot be realized on the maximum influence factor influencing the blast furnace thermal system, and the adjustment of the lower part of a blast furnace and the optimization of the molten iron quality cannot be directly guided; meanwhile, the tuyere monitoring result is combined with the blast furnace smelting process parameters, so that the automatic analysis of the maximum influence factor of the thermal system at the lower part of the blast furnace is effectively carried out, the regulation at the lower part of the blast furnace is optimized, and the control level of the blast furnace is improved.
Detailed Description
The method for analyzing the maximum influence factor of the thermal system of the lower part of the blast furnace based on tuyere monitoring, which is provided by the specific embodiment, sequentially comprises the following steps of:
s1, acquiring real-time blast furnace tuyere images, judging whether the blast furnace tuyere images are in an overexposure or overtaking state, and carrying out exposure time and gain adjustment on the blast furnace tuyere images in the overexposure or overtaking state by adopting a pre-calibration method until the brightness of the blast furnace tuyere images meets the standard.
The blast furnace tuyere monitoring system comprises an FPGA-based high frame rate camera, a telecentric lens, a power supply system, a data transmission system, an image storage and processing system and a high-temperature-resistant dustproof protection sleeve piece, wherein the telecentric lens is connected with the FPGA-based high frame rate camera, the FPGA-based high frame rate camera is connected with the data transmission system, the data transmission system is connected with the image storage and processing system, the power supply system is used for supplying power to the blast furnace tuyere monitoring system, the high-temperature-resistant dustproof protection sleeve piece is used for high-temperature-resistant dustproof protection of the blast furnace tuyere monitoring system, the FPGA-based high frame rate camera can realize the functions of image edge extraction and brightness average value analysis in a camera body and carry out corresponding judgment so as to realize intelligent acquisition of tuyere images and tuyere coal injection quantity based on different brightnesses, the FPGA-based high frame rate camera shoots the blast furnace tuyere images and uploads the blast furnace tuyere images to the image storage and processing system through the data transmission system, the image storage and processing system is used for processing and analyzing the tuyere image, the detailed processing and analyzing steps are in steps S2-S3, the high-temperature-resistant dustproof protective sleeve piece covers the outside of the electronic original device of the whole blast furnace tuyere monitoring system, and therefore the internal electronic components are protected from being influenced by high temperature and coal dust of the blast furnace tuyere to cause inaccurate analysis results.
The standard for judging whether the blast furnace tuyere image is in an overexposure or an excessively dark state in the embodiment is as follows: when the high frame rate camera based on the FPGA judges that the gray value of the blast furnace tuyere image acquired in real time is greater than 200, the blast furnace tuyere image is considered to be in an overexposure state, and the gray value of the blast furnace tuyere image acquired in real time is judged to be less than 100, the blast furnace tuyere image is considered to be in an excessively dark state.
The pre-calibration method for the blast furnace tuyere brightness in the embodiment specifically comprises the following steps: in the process of blowing out of the blast furnace tuyere, blast furnace smelting process parameters such as different coal injection amount, blast temperature, furnace burden descending speed, blast furnace iron output, smelting period and oxygen enrichment rate are changed, so that the change rule of the blast furnace tuyere image brightness is obtained, and the exposure time and gain of the high frame rate camera based on the FPGA are adjusted, so that the brightness of the optimal blast furnace tuyere image effective area under different blast furnace smelting process parameters is obtained.
The method for judging whether the brightness of the blast furnace tuyere image meets the standard is that the average brightness of the blast furnace tuyere image is within the range of 150 +/-50 within continuous 5 seconds, namely the camera parameter is considered to be adjusted in place, and the brightness of the blast furnace tuyere image meets the standard.
S2, taking blast furnace tuyere images with the time length of S being 600 seconds, taking the average brightness value of a group of blast furnace tuyere images as the tuyere brightness of the group every S being 5 seconds, simultaneously taking the average value of each blast furnace smelting process parameter at the same fixed time interval of S being 5 seconds, forming sample data by the tuyere brightness and the average value of all blast furnace smelting process parameters, wherein the number of the samples is S/S being 120;
s3, the blast furnace smelting process parameters comprise blast furnace blast volume XB, blast temperature XBT, furnace burden descending speed XBD, blast furnace tapping amount XI, smelting period XS, coal injection amount XPCI and oxygen enrichment rate XB0, the tuyere brightness is recorded as L, and the average value of the blast furnace smelting process parameters isThe formed argument matrix is denoted X ═ { XB, XBT, XBD, XI, XS, XPCI, XBO } 7×120 And the dependent variable matrix formed by the luminance of the air inlet is recorded as Y ═ L } 1×120 Normalizing the X and Y matrixes to obtain a new data matrix E 0 、F 0 Then, a partial least squares regression equation is constructed, the process is as follows:
first, the basis w of the k-th new space is calculated k And c k (k-1, … 120) wherein w k Is a residual matrix E after the main component extraction in the step (k-1) k-1 T F k-1 F k-1 T E k-1 C, the maximum eigenvalue of k Is a residual matrix F after the main component extraction in the step (k-1) k-1 T E k-1 E k-1 T F k-1 The feature vector corresponding to the maximum feature value of (1). In residual matrix E k-1 Is extracted from k Residual matrix F k-1 Is extracted from k . In (w) k ) 2 1 and (c) k ) 2 Solving for covariance cov under constraint of 1 (t) k ，u k ) → max, then solving to obtain the eigenvector under the corresponding eigenvalue, and obtaining the eigenvector w corresponding to the principal axis k And c k 。
Then the first component t is solved 1 Matrix of residuals E 1 ，
t 1 ＝E 0 ·w 1 (1)
In the formula (2)
Then solving the second component t in turn 2 To the seventh component t 7 And a residual matrix E 2 To residual matrix E 7 Until the marginal contribution of the extracted principal component to the model prediction effect is insignificant.
Constructing a partial least squares regression equation: such as formula (3)
Projection importance index I using variables j To measure the importance of the influence of blast furnace smelting process parameters on the tuyere brightness, a variable projection importance index I j The larger the value is, the higher the influence of the blast furnace smelting process parameters on the tuyere brightness is, namely, the blast furnace smelting process parameters with the largest influence on the blast furnace thermal schedule in the time period are.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (4)
1. A method for analyzing the maximum influence factor of a thermal system at the lower part of a blast furnace based on tuyere monitoring is characterized by sequentially comprising the following steps of:
s1, acquiring a real-time blast furnace tuyere image, judging whether the blast furnace tuyere image is in an overexposure or excessively dark state, and adjusting the exposure time and the gain of the blast furnace tuyere image in the overexposure or excessively dark state by adopting a pre-calibration method until the brightness of the blast furnace tuyere image meets the standard;
s2, taking a blast furnace tuyere image with a time length of S, taking the average brightness value of a group of blast furnace tuyere images at intervals of a fixed time S as the tuyere brightness of the group, simultaneously taking the average value of each blast furnace smelting process parameter at intervals of the same fixed time S, forming sample data by the tuyere brightness and the average value of all blast furnace smelting process parameters, wherein the number of the samples is S/S;
s3, the blast furnace smelting process parameters comprise blast furnace blast volume XB, blast temperature XBT, furnace burden descending speed XBD, blast furnace tapping quantity XI, smelting period XS, coal injection quantity XPCI and oxygen enrichment ratio XBO, the tuyere brightness is L, and an independent variable matrix formed by the average values of the blast furnace smelting process parameters is X ═ { XB, XBT, XBD, XI, XS, XPCI, XBO } 7×S/s And the dependent variable matrix formed by the luminance of the air inlet is recorded as Y ═ L } 1×S/s Normalizing the X and Y matrixes to obtain a new data matrix E 0 、F 0 And then constructing a partial least squares regression equation, measuring the importance of the influence of the blast furnace smelting process parameters on the tuyere brightness by adopting a variable projection importance index, wherein the larger the variable projection importance index is, the higher the influence importance of the blast furnace smelting process parameters on the tuyere brightness is, namely, the blast furnace smelting process parameters with the largest influence on the blast furnace heat system in the time period are.
2. The method for analyzing the maximum influence factors of the lower heat system of the blast furnace based on tuyere monitoring as recited in claim 1, wherein: the blast furnace tuyere image is extracted by a blast furnace tuyere monitoring system, the blast furnace tuyere monitoring system comprises a high frame rate camera based on an FPGA, a telecentric lens, a power supply system, a data transmission system, an image storage and processing system and a high-temperature-resistant dustproof protective sleeve, the telecentric lens is connected with the high frame rate camera based on the FPGA, the high frame rate camera based on the FPGA is connected with the data transmission system, the data transmission system is connected with the image storage and processing system, the power supply system is used for supplying power to the blast furnace tuyere monitoring system, the high-temperature-resistant dustproof protective sleeve is used for high-temperature-resistant dustproof protection of the blast furnace tuyere monitoring system, and the high-furnace tuyere image is shot by the high-temperature-resistant camera based on the FPGA and is uploaded to the image storage and processing system through the data transmission system.
3. The method for analyzing the maximum influence factor of the thermal regulation of the lower part of the blast furnace based on tuyere monitoring as claimed in claim 2, wherein: and when the FPGA-based high frame rate camera judges that the gray value of the acquired real-time blast furnace tuyere image is in the range of more than 200 or less than 100, the blast furnace image is considered to be in an overexposure state or an excessively dark state.
4. The method for analyzing the maximum influence factor of the thermal system of the lower part of the blast furnace based on tuyere monitoring as claimed in claim 3, wherein: step 1, carrying out exposure time and gain adjustment on the blast furnace tuyere image in an overexposure or excessively dark state by adopting a pre-calibration method until the average brightness of the blast furnace tuyere image is within the range of 150 +/-50 within 5 seconds continuously, so that the brightness of the blast furnace tuyere image meets the standard.
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| CN115326657A (en) * | 2022-10-14 | 2022-11-11 | 北京科技大学 | Non-blowing-out blast furnace coke granularity degradation online monitoring and evaluation method and system |
| CN115326657B (en) * | 2022-10-14 | 2023-01-17 | 北京科技大学 | Non-blowing-out blast furnace coke granularity degradation online monitoring and evaluation method and system |
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