WO2022105226A1 - Method and system for quantitatively presuming silicon-sulfur content of molten iron during blast furnace tapping - Google Patents
Method and system for quantitatively presuming silicon-sulfur content of molten iron during blast furnace tapping Download PDFInfo
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- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 title claims abstract description 354
- 229910052742 iron Inorganic materials 0.000 title claims abstract description 177
- 238000000034 method Methods 0.000 title claims abstract description 21
- AFYNYVFJTDCVBJ-UHFFFAOYSA-N [Si].[S] Chemical compound [Si].[S] AFYNYVFJTDCVBJ-UHFFFAOYSA-N 0.000 title claims abstract description 18
- 238000010079 rubber tapping Methods 0.000 title claims abstract description 10
- 238000001514 detection method Methods 0.000 claims abstract description 25
- 238000004364 calculation method Methods 0.000 claims abstract description 7
- 238000005259 measurement Methods 0.000 claims abstract description 4
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 claims description 49
- 229910052717 sulfur Inorganic materials 0.000 claims description 49
- 239000011593 sulfur Substances 0.000 claims description 49
- 229910052710 silicon Inorganic materials 0.000 claims description 45
- 239000010703 silicon Substances 0.000 claims description 45
- 238000005070 sampling Methods 0.000 claims description 23
- XWHPIFXRKKHEKR-UHFFFAOYSA-N iron silicon Chemical compound [Si].[Fe] XWHPIFXRKKHEKR-UHFFFAOYSA-N 0.000 claims description 6
- 238000002360 preparation method Methods 0.000 claims description 5
- 238000010183 spectrum analysis Methods 0.000 claims description 4
- IERLNRXXTLBBLK-UHFFFAOYSA-N [S].[Si].[Fe] Chemical compound [S].[Si].[Fe] IERLNRXXTLBBLK-UHFFFAOYSA-N 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 5
- 230000010354 integration Effects 0.000 abstract description 4
- 238000012544 monitoring process Methods 0.000 abstract description 4
- 238000003723 Smelting Methods 0.000 abstract description 2
- 230000015572 biosynthetic process Effects 0.000 abstract 1
- 230000000087 stabilizing effect Effects 0.000 abstract 1
- 239000000523 sample Substances 0.000 description 33
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 31
- 238000012360 testing method Methods 0.000 description 8
- 238000012545 processing Methods 0.000 description 4
- 230000003595 spectral effect Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 239000003086 colorant Substances 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000227 grinding Methods 0.000 description 1
- 238000011065 in-situ storage Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012797 qualification Methods 0.000 description 1
- 238000007711 solidification Methods 0.000 description 1
- 230000008023 solidification Effects 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B5/00—Making pig-iron in the blast furnace
- C21B5/006—Automatically controlling the process
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B7/00—Blast furnaces
- C21B7/24—Test rods or other checking devices
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B2300/00—Process aspects
- C21B2300/04—Modeling of the process, e.g. for control purposes; CII
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P10/00—Technologies related to metal processing
- Y02P10/25—Process efficiency
Abstract
The present invention relates to the field of blast furnace smelting, and discloses a method and system for quantitatively presuming silicon-sulfur content of molten iron during blast furnace tapping. The method comprises the following steps: step S1: obtaining a data set comprising molten iron feature image information and corresponding measurement data of silicon-sulfur content of molten iron, and performing fitting according to the data set to obtain a relational expression between molten iron feature image information and silicon-sulfur content of molten iron when a blast furnace taphole is formed; and step S2: obtaining molten iron feature image information during blast furnace taphole formation of a target heat, and performing calculation according to the relational expression to obtain the silicon-sulfur content of the molten iron. According to the present invention, silicon-sulfur information of the molten iron of a blast furnace can be continuously and quickly obtained in a conventional operation, and the integration of heat balance monitoring of the blast furnace is improved, such that the problem of excess or shortage of a blast furnace heat source is solved, and an important contribution is made for stabilizing blast furnace operation by a blast furnace operator. Meanwhile, detection costs are greatly saved, such that production costs are reduced.
Description
本发明涉及高炉冶炼领域，尤其涉及一种定量推定高炉出铁时铁水硅硫含量的方法和系统。The invention relates to the field of blast furnace smelting, in particular to a method and a system for quantitatively estimating the silicon-sulfur content of molten iron during blast furnace tapping.
生产质量合格的铁水是高炉炼铁的重要目标之一。铁水中硅(Si)、硫(S)含量不仅是检验铁水合格与否的重要指标，同时也反映了高炉状态及其变化。在以往的生产过程中，高炉生产铁水硅、硫含量的检测方法如下：高炉出铁前，通知送样人到达现场并进行炉前取样，炉前工用样品勺在铁沟取出铁水，注入样模中，待冷却凝固后，由送样人送至理化检验室利用分析仪器进行成分检测，检测前还需要对样品进行处理，如打磨、制样等，检测完成后由检验室将检测结果反馈给高炉操作室。整个检测过程不仅耗费大量人力及物力，而且检测时间长，检测结果对高炉工长操作高炉、实时了解高炉运行状态意义不大。The production of qualified molten iron is one of the important goals of blast furnace ironmaking. The content of silicon (Si) and sulfur (S) in molten iron is not only an important indicator for testing the qualification of molten iron, but also reflects the state of the blast furnace and its changes. In the previous production process, the detection methods for the content of silicon and sulfur in the molten iron produced by the blast furnace are as follows: before the blast furnace taps iron, notify the sample sender to arrive at the site and take samples before the furnace, and use a sample spoon in front of the furnace to take out the molten iron in the iron ditch and inject the sample. In the mold, after cooling and solidification, the sampler will send it to the physical and chemical laboratory for component testing using analytical instruments. Before testing, the sample needs to be processed, such as grinding, sample preparation, etc. After the testing is completed, the testing laboratory will feedback the test results. To the blast furnace operating room. The entire detection process not only consumes a lot of manpower and material resources, but also takes a long time to detect, and the detection results are of little significance for the blast furnace foreman to operate the blast furnace and understand the operation status of the blast furnace in real time.
为解决取样、制样及检测时间长的问题，专利CN109975274A提出了一种高炉铁水硅含量在线快速检测装置。利用安装在铁水沟正上方的在线检测系统，对铁水进行取样，然后利用光谱对铁水硅含量进行在线检测。类似的，专利CN201732059U、专利CN104297218B提出了铁水原位、在线检测装置及方法，该方法将高温光学探头置入铁水中，高温探头采集信号传给中端光学传感器后，再将信号传给后端控制器铁水成分信息。In order to solve the problem of long sampling, sample preparation and detection time, patent CN109975274A proposes an online rapid detection device for silicon content in blast furnace molten iron. Using the online detection system installed directly above the molten iron ditch, the molten iron was sampled, and then the silicon content in the molten iron was detected online by spectrum. Similarly, patent CN201732059U and patent CN104297218B propose an in-situ and online detection device and method for molten iron. In this method, a high-temperature optical probe is placed in molten iron, and the high-temperature probe collects signals and transmits them to the mid-end optical sensor, and then transmits the signal to the back end. Controller molten iron composition information.
这些方法虽然能实现铁水成分的在线检测，但可以预见的，这些方法均需投入高昂的设备费用及维护费用。Although these methods can realize the on-line detection of molten iron composition, it is foreseeable that these methods require high equipment cost and maintenance cost.
发明内容SUMMARY OF THE INVENTION
有鉴于现有技术的上述缺陷，本发明的目的是提供一种定量推定高炉出铁时铁水硅硫含量的方法和系统，在常规操作中可以快速获得高炉铁水的硅硫信息，以提高高炉的热平衡监控的整合性，从而解决高炉热源过剩或短缺的问题，稳定高炉操作。In view of the above-mentioned defects of the prior art, the object of the present invention is to provide a method and a system for quantitatively estimating the silicon-sulfur content of molten iron during blast furnace tapping, and can quickly obtain the silicon-sulfur information of blast furnace molten iron in conventional operations, to improve the blast furnace's silicon and sulfur content. The integration of heat balance monitoring can solve the problem of excess or shortage of blast furnace heat source and stabilize blast furnace operation.
为实现上述目的，本发明提供了一种定量推定高炉出铁时铁水硅硫含量的方法，包括以下步骤：In order to achieve the above object, the present invention provides a method for quantitatively estimating the content of silicon and sulfur in molten iron during blast furnace tapping, comprising the following steps:
步骤S1：获取包括铁水特征图像信息和对应的铁水硅硫含量测量数据的数据集，根据所述数据集拟合获得高炉开铁口时的铁水特征图像信息和铁水硅硫含量的关系式；Step S1: acquiring a data set including molten iron characteristic image information and corresponding molten iron silicon-sulfur content measurement data, and obtaining a relational expression between the molten iron characteristic image information and the molten iron silicon and sulfur content when the blast furnace taphole is fitted according to the data set;
步骤S2：获取目标炉次高炉的开铁口时的铁水特征图像信息，根据所述关系式计算，获得铁水硅硫含量。Step S2: Obtain the characteristic image information of molten iron when the taphole of the target blast furnace is opened, and calculate according to the relational expression to obtain the content of silicon and sulfur in the molten iron.
进一步的，所述铁水特征图像包括铁水火花图像、铁水取样颜色图像、取样冷态样图像中的一种。Further, the molten iron characteristic image includes one of a molten iron spark image, a molten iron sampling color image, and a sampling cold state image.
进一步的，所述铁水特征图像是铁水火花图像，所述铁水硅硫含量和铁水火花图像信息的关系式为：Further, the molten iron feature image is a molten iron spark image, and the relationship between the molten iron silicon and sulfur content and the molten iron spark image information is:
所述步骤S1包括：The step S1 includes:
Si＝ax
1+bx
2+cr
1
Si=ax 1 +bx 2 +cr 1
S＝dx
1+ex
2+fr
1
S=dx 1 +ex 2 +fr 1
其中，x1表示火花高度信息值，x2表示火花长度信息值，r1表示火花密度信息值，a、b、c、d、e、f表示关系式的系数，Si表示铁水中硅的含量，S表示铁水中硫的含量。Among them, x1 represents the spark height information value, x2 represents the spark length information value, r1 represents the spark density information value, a, b, c, d, e, f represent the coefficients of the relational expression, Si represents the content of silicon in the molten iron, and S represents the Sulfur content in molten iron.
进一步的，所述铁水特征图像是铁水取样颜色图像，所述铁水硅硫含量与铁水取样颜色图像信息的关系式为：Further, the molten iron characteristic image is a molten iron sampling color image, and the relationship between the molten iron silicon and sulfur content and the molten iron sampling color image information is:
Si＝ax
r+bx
b+cr
g
Si= axr + bxb + crg
S＝dx
r+ex
b+fr
g
S=dx r +ex b +fr g
其中，x
r表示铁样图像中红色的亮度信息、x
b表示铁样图像中蓝色的亮度信息，x
g表示铁样图像中绿色的亮度信息；a、b、c、d、e、f表示关系式的系数；Si表示铁水中硅的含量，S表示铁水中硫的含量。
Among them, x r represents the brightness information of red in the iron-like image, x b represents the brightness information of blue in the iron-like image, and x g represents the brightness information of green in the iron-like image; a, b, c, d, e, f Represents the coefficient of the relational expression; Si represents the content of silicon in the molten iron, and S represents the content of sulfur in the molten iron.
进一步的，所述铁水特征图像是取样冷态样图像，铁水硅硫含量与所述取样冷态样图像信息的关系式为：Further, the molten iron feature image is a sampled cold state image, and the relationship between the silicon and sulfur content of the molten iron and the information of the sampled cold state image is:
Si＝ay
1+by
2+cy
3
Si=ay 1 +by 2 +cy 3
S＝dy
1+ey
2+fy
3
S=dy 1 +ey 2 +fy 3
其中，y1、y2、y3分别为第一图像纹路信息特征值、第二图像纹路信息特征值、第三图像纹路信息特征值；a、b、c、d、e、f表示关系式的系数；Si表示铁水中硅的含量，S表示铁水中硫的含量。Wherein, y1, y2, y3 are the first image texture information feature value, the second image texture information feature value, the third image texture information feature value; a, b, c, d, e, f represent the coefficients of the relational expression; Si represents the content of silicon in the molten iron, and S represents the content of sulfur in the molten iron.
进一步的，所述步骤S1具体包括：Further, the step S1 specifically includes:
1)设置机器视觉，摄取目标炉次开铁口时的铁水特征图像信息；1) Set up machine vision to capture the characteristic image information of molten iron when the target furnace is opened;
2)制作目标炉次铁水样，并检测铁水硅硫含量；2) Make the molten iron sample of the target heat, and detect the content of silicon and sulfur in the molten iron;
3)提取铁水特征图像的图像特征并辨识，获得铁水特征图像信息；3) Extracting and identifying the image features of the molten iron feature image to obtain the molten iron feature image information;
4)根据包括铁水硅硫含量及铁水特征图像信息的数据集，拟合得到铁水特征图像信息与铁水硅硫含量的关系式。4) According to the data set including the content of silicon and sulfur in molten iron and the characteristic image information of molten iron, the relationship between the characteristic image information of molten iron and the content of silicon and sulfur in molten iron is obtained by fitting.
为实现上述目的，本发明还提供了一种定量推定高炉出铁时铁水硅硫含量的系统，包括：机器视觉系统、取样机器人、铁水样检测装置和计算机；In order to achieve the above object, the present invention also provides a system for quantitatively estimating the silicon-sulfur content of molten iron when tapping from a blast furnace, including: a machine vision system, a sampling robot, a molten iron sample detection device and a computer;
所述机器视觉系统用于获取高炉开铁口时的铁水特征图像信息；The machine vision system is used to obtain the characteristic image information of molten iron when the blast furnace is opening the taphole;
所述取样机器人用于铁水样的样本取样和制样；The sampling robot is used for sample sampling and sample preparation of molten iron samples;
所述铁水样检测装置用于检测铁水样，获取铁水硅硫含量；The molten iron sample detection device is used to detect the molten iron sample and obtain the content of silicon and sulfur in the molten iron;
所述计算机运行有图像特征提取模块、关系式拟合模块和计算模块，所述图像特征模块用于辨识铁水特征图像的种类并根据种类提取铁水特征图像信息的信息值；所述关系式拟合模块用于根据铁水特征图像信息的信息值和铁水硅硫含量进行关系式拟合，获取铁水特征图像信息和铁水硅硫含量的关系式；所述计算模块用于输入目标炉次的铁水特征图像信息，通过对应的关系式计算获取目标炉次的铁水硅硫含量。The computer runs an image feature extraction module, a relational fitting module and a calculation module, and the image feature module is used to identify the type of the molten iron characteristic image and extract the information value of the molten iron characteristic image information according to the type; the relational expression fitting The module is used to perform relational fitting according to the information value of the characteristic image information of the molten iron and the content of silicon and sulfur in the molten iron, and obtain the relational expression between the characteristic image information of the molten iron and the content of silicon and sulfur in the molten iron; the calculation module is used to input the characteristic image of the molten iron of the target heat. information, and obtain the silicon-sulfur content of the molten iron of the target heat by calculating the corresponding relational formula.
进一步的，所述机器视觉系统包括光源、镜头、相机、采集卡和机械平台。Further, the machine vision system includes a light source, a lens, a camera, a capture card and a mechanical platform.
进一步的，所述铁水样检测装置是光谱分析检测装置。Further, the molten iron sample detection device is a spectral analysis detection device.
本发明实现了如下技术效果：The present invention achieves the following technical effects:
根据本发明，在常规操作中可以连续并快速获得高炉铁水的硅硫信息，提高了高炉的热平衡监控的整合性，从而解决高炉热源过剩或短缺的问题，对高炉操作者稳定高炉操作做出了重要贡献。同时，省去了大量检测费用，利于降低生产成本。According to the present invention, the silicon-sulfur information of the blast furnace molten iron can be continuously and rapidly obtained in the conventional operation, the integration of the heat balance monitoring of the blast furnace is improved, the problem of excess or shortage of heat sources in the blast furnace is solved, and the blast furnace operator can stabilize the blast furnace operation. important contribution. At the same time, a lot of testing costs are saved, which is beneficial to reduce production costs.
图1是本发明的实施例1的工作流程图。FIG. 1 is a flow chart of the operation of Embodiment 1 of the present invention.
为进一步说明各实施例，本发明提供有附图。这些附图为本发明揭露内容的一部分，其主要用以说明实施例，并可配合说明书的相关描述来解释实施例的运作原理。配合参考这些内容，本领域普通技术人员应能理解其他可能的实 施方式以及本发明的优点。图中的组件并未按比例绘制，而类似的组件符号通常用来表示类似的组件。To further illustrate the various embodiments, the present invention is provided with the accompanying drawings. These drawings are a part of the disclosure of the present invention, which are mainly used to illustrate the embodiments, and can be used in conjunction with the relevant description of the specification to explain the operation principles of the embodiments. Those of ordinary skill in the art will appreciate other possible embodiments and advantages of the present invention with reference to these disclosures. Components in the figures are not drawn to scale, and similar component symbols are often used to represent similar components.
现结合附图和具体实施方式对本发明进一步说明。The present invention will now be further described with reference to the accompanying drawings and specific embodiments.
本发明了公开了一种定量推定高炉出铁时铁水硅硫含量的方法，包括以下步骤：The invention discloses a method for quantitatively estimating the silicon-sulfur content of molten iron during blast furnace tapping, comprising the following steps:
步骤S1：获取包括铁水特征图像信息和对应的铁水硅硫含量测量数据的数据集，根据所述数据集拟合获得高炉开铁口时的铁水特征图像信息和铁水硅硫含量的关系式；Step S1: acquiring a data set including molten iron characteristic image information and corresponding molten iron silicon-sulfur content measurement data, and obtaining a relational expression between the molten iron characteristic image information and the molten iron silicon and sulfur content when the blast furnace taphole is fitted according to the data set;
步骤S2：获取目标炉次高炉的开铁口时的铁水特征图像信息，根据所述关系式计算，获得铁水硅硫含量。Step S2: Obtain the characteristic image information of molten iron when the taphole of the target blast furnace is opened, and calculate according to the relational expression to obtain the content of silicon and sulfur in the molten iron.
经过技术人员的大量的数据分析，优选的，所述铁水特征图像可以铁水火花图像、铁水取样颜色图像、取样冷态样图像和铁水流动性图像等图像。以下通过多个实施例，以说明采用铁水特征图像执行步骤S1的工作流程图。After a large amount of data analysis by technicians, preferably, the molten iron characteristic images can be images such as molten iron spark images, molten iron sampling color images, sampling cold state images, and molten iron fluidity images. Several embodiments are used below to illustrate the work flow chart of performing step S1 by using the molten iron characteristic image.
实施例1Example 1
如图1所示，铁水特征图像为铁水火花图像，具体步骤如下：As shown in Figure 1, the molten iron feature image is the molten iron spark image, and the specific steps are as follows:
1、在铁口附近合适位置设置机器视觉系统，采集铁口火花图像；1. Set up a machine vision system at a suitable position near the iron mouth to collect the spark image of the iron mouth;
2、在铁口附近合适位置设置取样机器人，取铁水样，制样，并进行光谱检测；2. Set up a sampling robot at a suitable position near the iron mouth to take molten iron samples, prepare samples, and perform spectral detection;
3、由图像处理和辨识系统对铁口火花图像进行辨识和处理，提取火花高度信息特征值x1，火花长度信息特征值x2，以及火花密度信息值r1；3. Identify and process the taphole spark image by the image processing and identification system, and extract the spark height information characteristic value x1, the spark length information characteristic value x2, and the spark density information value r1;
4、根据包括铁水硅硫含量及火花图像的数据集，拟合铁水硅硫含量与火花 图像信息值之间的关系式4. According to the data set including the silicon-sulfur content of molten iron and the spark image, fit the relationship between the silicon-sulfur content of molten iron and the information value of the spark image
Si＝ax
1+bx
2+cr
1
Si=ax 1 +bx 2 +cr 1
S＝dx
1+ex
2+fr
1
S=dx 1 +ex 2 +fr 1
获得系数a、b、c、d、e、f，其中Si表示铁水中硅的含量，S表示铁水中硫的含量；Obtain coefficients a, b, c, d, e, f, where Si represents the content of silicon in the molten iron, and S represents the content of sulfur in the molten iron;
5、根据机器视觉摄取图像信息，获得火花高度信息特征值x1、火花长度信息特征值x2以及火花密度信息值r1，代入所述关系式计算获得铁水硅硫含量。5. Obtain the characteristic value x1 of spark height information, the characteristic value x2 of spark length information and the information value r1 of spark density according to the image information captured by the machine vision, and substitute them into the relational formula to calculate and obtain the content of silicon and sulfur in molten iron.
实施例2Example 2
1、在铁沟沟头合适位置设置机器视觉系统和取样机器人；1. Set up a machine vision system and a sampling robot at the appropriate position of the Tiegougou head;
2、取样机器人取样本铁水样及制样，机器视觉系统摄取铁样图像，同时样本铁样进行光谱检测；2. The sampling robot takes the molten iron sample and prepares the sample, and the machine vision system captures the image of the iron sample, and at the same time, the sample iron sample is subjected to spectral detection;
3、由图像处理和辨识系统对铁样图像进行辨识和处理，提取图像红、蓝、绿三中颜色的亮度信息x
r、x
b、x
g；
3. The iron-like image is identified and processed by the image processing and identification system, and the brightness information x r , x b , and x g of the red, blue, and green colors of the image are extracted;
4、根据包括铁水硅硫含量及铁样图像的数据集，建立铁水硅硫含量与铁样图像信息值之间的关系式4. According to the data set including the content of silicon and sulfur in molten iron and the image of iron sample, establish the relationship between the content of silicon and sulfur in molten iron and the information value of iron sample image
Si＝ax
r+bx
b+cr
g
Si= axr + bxb + crg
S＝dx
r+ex
b+fr
g
S=dx r +ex b +fr g
5、根据机器视觉摄取图像信息，进行铁水硅硫含量检测。5. According to the image information captured by machine vision, the content of silicon and sulfur in molten iron is detected.
实施例3：Example 3:
1、在铁沟沟头合适位置设置机器视觉系统和取样机器人；1. Set up a machine vision system and a sampling robot at the appropriate position of the Tiegougou head;
2、取样机器人取样本铁水样及制样，机器视觉系统摄取铁样图像，同时样 本铁样进行光谱检测；2. The sampling robot takes the molten iron sample and prepares the sample, the machine vision system captures the image of the iron sample, and at the same time, the sample iron sample is subjected to spectral detection;
3、由图像处理和辨识系统对铁样图像进行辨识和处理，提取图像纹路信息特征值y1、y2、y3；3. Identify and process the iron-like image by the image processing and identification system, and extract the characteristic values y1, y2, y3 of the image texture information;
4、根据包括铁水硅硫含量及铁样图像的数据集，建立铁水硅硫含量与铁样图像信息值之间的关系式4. According to the data set including the content of silicon and sulfur in molten iron and the image of iron sample, establish the relationship between the content of silicon and sulfur in molten iron and the information value of iron sample image
Si＝ay
1+by
2+cy
3
Si=ay 1 +by 2 +cy 3
S＝dy
1+ey
2+fy
3
S=dy 1 +ey 2 +fy 3
5、根据机器视觉摄取图像信息，进行铁水硅硫含量检测。5. According to the image information captured by machine vision, the content of silicon and sulfur in molten iron is detected.
根据本发明的上述实施例，均可在常规操作中连续并快速获得高炉铁水的硅硫信息，提高高炉的热平衡监控的整合性，从而解决高炉热源过剩或短缺的问题，对高炉操作者稳定高炉操作做出了重要贡献。同时，省去了大量检测费用，利于降低生产成本。According to the above-mentioned embodiments of the present invention, the silicon-sulfur information of the blast furnace molten iron can be obtained continuously and rapidly in the conventional operation, and the integration of the heat balance monitoring of the blast furnace can be improved, so as to solve the problem of excess or shortage of the blast furnace heat source, and stabilize the blast furnace for the blast furnace operator. Operations made an important contribution. At the same time, a lot of testing costs are saved, which is beneficial to reduce production costs.
本发明还提供了一种定量推定高炉出铁时铁水硅硫含量的系统，包括：机器视觉系统、取样机器人、铁水样检测装置和计算机(即图像处理和辨识系统)；所述机器视觉系统用于获取高炉开铁口时的铁水特征图像信息；所述取样机器人用于铁水样的样本取样和制样；所述铁水样检测装置用于检测铁水样，获取铁水硅硫含量；所述计算机运行有图像特征提取模块、关系式拟合模块和计算模块，所述图像特征模块用于辨识铁水特征图像的种类并根据种类提取铁水特征图像信息的信息值；所述关系式拟合模块用于根据铁水特征图像信息的信息值和铁水硅硫含量进行关系式拟合，获取铁水特征图像信息和铁水硅硫含量的关系式；所述计算模块用于输入目标炉次的铁水特征图像信息，通过对应的关系式计算获取目标炉次的铁水硅硫含量。The invention also provides a system for quantitatively estimating the content of silicon and sulfur in molten iron during blast furnace tapping, including: a machine vision system, a sampling robot, a molten iron sample detection device and a computer (ie, an image processing and identification system); the machine vision system It is used to obtain the characteristic image information of molten iron when the blast furnace is opening the taphole; the sampling robot is used for sample sampling and preparation of molten iron samples; the molten iron sample detection device is used to detect the molten iron samples and obtain the content of silicon and sulfur in the molten iron; The computer runs an image feature extraction module, a relational fitting module and a calculation module, and the image feature module is used to identify the type of the molten iron characteristic image and extract the information value of the molten iron characteristic image information according to the type; the relational expression fitting The module is used to perform relational fitting according to the information value of the characteristic image information of the molten iron and the content of silicon and sulfur in the molten iron, and obtain the relational expression between the characteristic image information of the molten iron and the content of silicon and sulfur in the molten iron; the calculation module is used to input the characteristic image of the molten iron of the target heat. information, and obtain the silicon-sulfur content of the molten iron of the target heat by calculating the corresponding relational formula.
进一步的，所述机器视觉系统包括光源、镜头、相机、采集卡和机械平台。Further, the machine vision system includes a light source, a lens, a camera, a capture card and a mechanical platform.
进一步的，所述铁水样检测装置是光谱分析检测装置，可以通过光谱分析检测装置进行硅含量和硫含量的测定。Further, the molten iron sample detection device is a spectral analysis and detection device, and the silicon content and the sulfur content can be measured by the spectral analysis and detection device.
尽管结合优选实施方案具体展示和介绍了本发明，但所属领域的技术人员应该明白，在不脱离所附权利要求书所限定的本发明的精神和范围内，在形式上和细节上可以对本发明做出各种变化，均为本发明的保护范围。Although the present invention has been particularly shown and described in connection with preferred embodiments, it will be understood by those skilled in the art that changes in form and detail may be made to the present invention without departing from the spirit and scope of the invention as defined by the appended claims. Various changes are made within the protection scope of the present invention.
Claims (9)
- 一种定量推定高炉出铁时铁水硅硫含量的方法，其特征在于，包括以下步骤：A method for quantitatively estimating the content of silicon and sulfur in molten iron during blast furnace tapping, comprising the following steps:步骤S1：获取包括铁水特征图像信息和对应的铁水硅硫含量测量数据的数据集，根据所述数据集拟合获得高炉开铁口时的铁水特征图像信息和铁水硅硫含量的关系式；Step S1: acquiring a data set including molten iron characteristic image information and corresponding molten iron silicon-sulfur content measurement data, and obtaining a relational expression between the molten iron characteristic image information and the molten iron silicon and sulfur content when the blast furnace taphole is fitted according to the data set;步骤S2：获取目标炉次高炉的开铁口时的铁水特征图像信息，根据所述关系式计算，获得铁水硅硫含量。Step S2: Obtain the characteristic image information of molten iron when the taphole of the target blast furnace is opened, and calculate according to the relational expression to obtain the content of silicon and sulfur in the molten iron.
- 如权利要求1所述的方法，其特征在于，所述铁水特征图像包括铁水火花图像、铁水取样颜色图像、取样冷态样图像中的一种。The method of claim 1, wherein the molten iron characteristic image comprises one of a molten iron spark image, a molten iron sampled color image, and a sampled cold state image.
- 如权利要求1所述的方法，其特征在于，所述铁水特征图像是铁水火花图像，所述铁水硅硫含量和铁水火花图像信息的关系式为：The method according to claim 1, wherein the characteristic image of molten iron is an image of molten iron sparks, and the relationship between the content of silicon and sulfur in molten iron and the information of the molten iron spark image is:所述步骤S1包括：The step S1 includes:Si＝ax 1+bx 2+cr 1 Si=ax 1 +bx 2 +cr 1S＝dx 1+ex 2+fr 1 S=dx 1 +ex 2 +fr 1其中，x1表示火花高度信息值，x2表示火花长度信息值，r1表示火花密度信息值，a、b、c、d、e、f表示关系式的系数，Si表示铁水中硅的含量，S表示铁水中硫的含量。Among them, x1 represents the spark height information value, x2 represents the spark length information value, r1 represents the spark density information value, a, b, c, d, e, f represent the coefficients of the relational expression, Si represents the content of silicon in the molten iron, and S represents the Sulfur content in molten iron.
- 如权利要求1所述的方法，其特征在于，所述铁水特征图像是铁水取样颜色图像，所述铁水硅硫含量与铁水取样颜色图像信息的关系式为：The method of claim 1, wherein the molten iron characteristic image is a molten iron sampling color image, and the relationship between the molten iron silicon and sulfur content and the molten iron sampling color image information is:Si＝ax r+bx b+cr g Si= axr + bxb + crgS＝dx r+ex b+fr g S=dx r +ex b +fr g其中，x r表示铁样图像中红色的亮度信息、x b表示铁样图像中蓝色的亮度信 息，x g表示铁样图像中绿色的亮度信息；a、b、c、d、e、f表示关系式的系数；Si表示铁水中硅的含量，S表示铁水中硫的含量。 Among them, x r represents the brightness information of red in the iron-like image, x b represents the brightness information of blue in the iron-like image, and x g represents the brightness information of green in the iron-like image; a, b, c, d, e, f Represents the coefficient of the relational expression; Si represents the content of silicon in the molten iron, and S represents the content of sulfur in the molten iron.
- 如权利要求1所述的方法，其特征在于，所述铁水特征图像是取样冷态样图像，铁水硅硫含量与所述取样冷态样图像信息的关系式为：The method according to claim 1, wherein the characteristic image of molten iron is a sampled cold state image, and the relationship between the content of silicon and sulfur in molten iron and the information of the sampled cold state image is:Si＝ay 1+by 2+cy 3 Si=ay 1 +by 2 +cy 3S＝dy 1+ey 2+fy 3 S=dy 1 +ey 2 +fy 3其中，y1、y2、y3分别为第一图像纹路信息特征值、第二图像纹路信息特征值、第三图像纹路信息特征值；a、b、c、d、e、f表示关系式的系数；Si表示铁水中硅的含量，S表示铁水中硫的含量。Wherein, y1, y2, y3 are the first image texture information feature value, the second image texture information feature value, the third image texture information feature value; a, b, c, d, e, f represent the coefficients of the relational expression; Si represents the content of silicon in the molten iron, and S represents the content of sulfur in the molten iron.
- 如权利要求1所述的方法，其特征在于，所述步骤S1具体包括：The method of claim 1, wherein the step S1 specifically comprises:1)设置机器视觉，摄取目标炉次开铁口时的铁水特征图像信息；1) Set up machine vision to capture the characteristic image information of molten iron when the target furnace is opened;2)制作目标炉次铁水样，并检测铁水硅硫含量；2) Make the molten iron sample of the target heat, and detect the content of silicon and sulfur in the molten iron;3)提取铁水特征图像的图像特征并辨识，获得铁水特征图像信息；3) Extracting and identifying the image features of the molten iron feature image to obtain the molten iron feature image information;4)根据包括铁水硅硫含量及铁水特征图像信息的数据集，拟合得到铁水特征图像信息与铁水硅硫含量的关系式。4) According to the data set including the content of silicon and sulfur in molten iron and the characteristic image information of molten iron, the relationship between the characteristic image information of molten iron and the content of silicon and sulfur in molten iron is obtained by fitting.
- 一种定量推定高炉出铁时铁水硅硫含量的系统，其特征在于，包括：机器视觉系统、取样机器人、铁水样检测装置和计算机；A system for quantitatively estimating the content of silicon and sulfur in molten iron during blast furnace tapping, characterized in that it comprises: a machine vision system, a sampling robot, a molten iron sample detection device and a computer;所述机器视觉系统用于获取高炉开铁口时的铁水特征图像信息；The machine vision system is used to obtain the characteristic image information of molten iron when the blast furnace is opening the taphole;所述取样机器人用于铁水样的样本取样和制样；The sampling robot is used for sample sampling and sample preparation of molten iron samples;所述铁水样检测装置用于检测铁水样，获取铁水硅硫含量；The molten iron sample detection device is used to detect the molten iron sample and obtain the content of silicon and sulfur in the molten iron;所述计算机运行有图像特征提取模块、关系式拟合模块和计算模块，所述图像特征模块用于辨识铁水特征图像的种类并根据种类提取铁水特征图像信息 的信息值；所述关系式拟合模块用于根据铁水特征图像信息的信息值和铁水硅硫含量进行关系式拟合，获取铁水特征图像信息和铁水硅硫含量的关系式；所述计算模块用于输入目标炉次的铁水特征图像信息，通过对应的关系式计算获取目标炉次的铁水硅硫含量。The computer runs an image feature extraction module, a relational fitting module and a calculation module, and the image feature module is used to identify the type of the molten iron characteristic image and extract the information value of the molten iron characteristic image information according to the type; the relational expression fitting The module is used to perform relational fitting according to the information value of the characteristic image information of the molten iron and the content of silicon and sulfur in the molten iron, and obtain the relational expression between the characteristic image information of the molten iron and the content of silicon and sulfur in the molten iron; the calculation module is used to input the characteristic image of the molten iron of the target heat. information, and obtain the silicon-sulfur content of the molten iron of the target heat by calculating the corresponding relational formula.
- 如权利要求7所述的系统，其特征在于，所述机器视觉系统包括光源、镜头、相机、采集卡和机械平台。The system of claim 7, wherein the machine vision system includes a light source, a lens, a camera, a capture card, and a mechanical platform.
- 如权利要求7所述的系统，其特征在于，所述铁水样检测装置是光谱分析检测装置。The system of claim 7, wherein the molten iron sample detection device is a spectral analysis detection device.
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