CN111079537B - Method, system, machine-readable medium and equipment for identifying smelting working conditions of converter - Google Patents
Method, system, machine-readable medium and equipment for identifying smelting working conditions of converter Download PDFInfo
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- CN111079537B CN111079537B CN201911127453.XA CN201911127453A CN111079537B CN 111079537 B CN111079537 B CN 111079537B CN 201911127453 A CN201911127453 A CN 201911127453A CN 111079537 B CN111079537 B CN 111079537B
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- C21C5/00—Manufacture of carbon-steel, e.g. plain mild steel, medium carbon steel or cast steel or stainless steel
- C21C5/28—Manufacture of steel in the converter
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- G06V10/00—Arrangements for image or video recognition or understanding
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Abstract
The application discloses a recognition system for smelting working conditions of a converter, which comprises the following components: the image acquisition module is used for acquiring a fire hole flame image; the furnace mouth flame image comprises a flame image of a converter smelting slag melting stage; the image processing module is used for obtaining the texture characteristics of the fire hole flame based on the fire hole flame image and judging whether the profile characteristics of the oxygen gun exist or not based on the fire hole flame image; and the real-time judging module is used for judging the slag melting condition according to the texture characteristics of the flame at the furnace mouth and also used for predicting the smelting end point of the converter for the first time according to whether the profile characteristics of the oxygen lance exist. According to the application, through judging soft and hard fires in the smelting slag melting process and judging the outline of the smelting end point oxygen lance and the outline of flame, the edge characteristic and the texture characteristic are extracted based on gabor filtering, whether slag melting is good or not in the smelting process can be accurately judged based on a visual principle, and the smelting end point can be accurately judged in real time.
Description
Technical Field
The application relates to the technical field of converter smelting, in particular to a method, a system, a machine-readable medium and equipment for identifying the smelting working condition of a converter.
Background
China is the largest steel producing country in the world, and the steel making amount of the converter accounts for more than 80% of the total steel yield. The converter steelmaking is a very complex process, comprises a periodic heating, carbon reduction and impurity removal process, comprises very complex multi-element, multi-phase and high-temperature reactions, and is a very key technology for identifying working conditions in the smelting process and responding in time.
The slag melting process in the smelting process is used as one of important indexes of working conditions, and is closely related to the removal of impurity elements in the smelting process. In general, slag and molten steel are in direct contact in a smelting process, and physical and chemical reactions and heat transfer processes between the slag and the molten steel are involved. By adjusting the slag composition, the properties and the quantity of the slag, the oxidation and reduction processes of various elements in the metal, such as oxidation and reduction of silicon, manganese and phosphorus, desulfurization and deoxidation, and the like, can be controlled. Slag also absorbs nonmetallic inclusions in the molten steel and prevents the molten steel from absorbing gases (hydrogen and nitrogen).
Meanwhile, the end point control at the end of smelting is also an important part of working condition indexes, and means that the carbon content and the temperature of the molten steel are controlled to meet the requirement of departure, and the quality of the final molten steel is directly related. The accurate real-time prediction and judgment of the smelting endpoint has important significance for improving the production efficiency, improving the steel quality and saving the cost. The conventional methods for controlling the endpoint of converter steelmaking mainly comprise a manual experience method, a chemical analysis method, a static endpoint control method and the like since the appearance of a converter steelmaking method.
The intensity of the carbon-oxygen reaction and the temperature of molten steel in converter steelmaking can be reflected by the flame at the furnace mouth. Therefore, the manual experience method is mainly to judge the steelmaking end point by manually observing the flame and spark at the intersection. The hit rate is low, and the labor intensity of workers is high. The chemical analysis method mainly comprises a sublance detection method and a sampling detection method, wherein the sublance detection method can accurately predict the steelmaking end point of the converter, but the used detection equipment needs to work in a high-temperature and corrosive environment for a long time, the gas calibration period is short, the sampling head is frequently replaced, the equipment use and maintenance cost is high, and the popularization and the use in the steelmaking converter industry are difficult. In addition, the method is generally used in converters with the speed of more than 120t, and the current situation of middle and small steel factories in China is difficult to be satisfied. The measuring time of the sampling detection method cannot meet the real-time requirement, and the accidents of splashing exist during sampling, and the production cost of steel is increased. Modeling methods commonly used in process control can be largely divided into three categories: white box model (mechanism model), black box model (statistics model), gray box model (model combining mechanism and statistics). Because the mechanism model of the complex process is difficult to build, the traditional optimization control technology based on the accurate mathematical model is often difficult to apply in actual production.
Disclosure of Invention
In view of the above drawbacks of the prior art, an object of the present application is to provide a method, a system, a machine-readable medium and a device for identifying a smelting condition of a converter, which are used for solving the drawbacks of the prior art.
To achieve the above and other related objects, the present application provides a system for identifying a smelting condition of a converter, the system comprising:
the image acquisition module is used for acquiring a fire hole flame image; the furnace mouth flame image comprises a flame image of a converter smelting slag melting stage;
the image processing module is used for obtaining the texture characteristics of the fire hole flame based on the fire hole flame image and judging whether the profile characteristics of the oxygen gun exist or not based on the fire hole flame image;
and the real-time judging module is used for judging the slag melting condition according to the texture characteristics of the flame at the furnace mouth and also used for predicting the smelting end point of the converter for the first time according to whether the profile characteristics of the oxygen lance exist.
Optionally, the furnace mouth flame image further comprises a converter smelting end flame, and the real-time judging module predicts the converter smelting end point for the second time according to the outline characteristics of the converter smelting end flame.
Optionally, texture features and contour features of the furnace mouth flame image are obtained through a Gabor filter, and the contour features of the oxygen lance are detected through the Gabor filter.
Optionally, the identification system further comprises a preprocessing module, which is used for preprocessing the fire hole flame image, wherein the preprocessing at least comprises graying processing.
Alternatively, if the profile characteristics of the lance are present, the converter steelmaking process is near the endpoint.
Alternatively, when the shrinkage of the flame occurs at the end of the converter smelting, the converter smelting steel reaches the end.
Optionally, judging the hardness of the flame according to the texture characteristics of the flame image of the furnace mouth, and judging the slag melting condition according to the hardness of the flame; when the flame at the furnace mouth is soft, the slag melting condition is good; when the flame at the furnace mouth is hard, the slag melting condition is poor.
To achieve the above and other related objects, the present application provides a method for identifying a smelting condition of a converter, the method comprising:
acquiring a fire hole flame image; the furnace mouth flame image comprises a flame image of a converter smelting slag melting stage;
obtaining the texture characteristics of the fire hole flame based on the fire hole flame image,
judging whether profile features of an oxygen lance exist or not based on the furnace mouth flame image;
judging slag melting conditions according to the texture characteristics of the flame at the furnace mouth;
and predicting the smelting endpoint of the converter for the first time according to whether the profile features of the oxygen lance exist.
Optionally, the furnace mouth flame image further comprises a converter smelting end flame, and the converter smelting end point is predicted for the second time according to the outline characteristics of the converter smelting end flame.
Optionally, texture features and contour features of the furnace mouth flame image are obtained through a Gabor filter, and the contour features of the oxygen lance are detected through the Gabor filter.
Optionally, the identification method further comprises: and preprocessing the fire hole flame image, wherein the preprocessing at least comprises graying processing.
Alternatively, if the profile characteristics of the lance are present, the converter steelmaking process is near the endpoint.
Alternatively, when the shrinkage of the flame occurs at the end of the converter smelting, the converter smelting steel reaches the end.
Optionally, judging the hardness of the flame according to the texture characteristics of the flame image of the furnace mouth, and judging the slag melting condition according to the hardness of the flame; when the flame at the furnace mouth is soft, the slag melting condition is good; when the flame at the furnace mouth is hard, the slag melting condition is poor.
To achieve the above and other related objects, the present application provides a storage medium storing a computer program which, when executed by a processor, performs the method.
To achieve the above and other related objects, the present application provides an apparatus comprising: a processor and a memory;
the memory is used for storing a computer program, and the processor is used for executing the computer program stored in the memory so as to enable the terminal to execute the method.
As described above, the identification method, system, machine-readable medium and equipment for converter smelting conditions have the following beneficial effects:
according to the application, through judging soft and hard fires in the smelting slag melting process and judging the outline of the smelting end point oxygen lance and the outline of flame, the edge characteristic and the texture characteristic are extracted based on gabor filtering, whether slag melting is good or not in the smelting process can be accurately judged based on a visual principle, and the smelting end point can be accurately judged in real time.
Drawings
FIG. 1 is a schematic block diagram of a system for identifying converter smelting conditions in accordance with an embodiment of the present application;
FIG. 2 is a flow chart of a method for identifying smelting conditions of a converter in accordance with an embodiment of the present application.
Detailed Description
Other advantages and effects of the present application will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present application with reference to specific examples. The application may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present application by way of illustration, and only the components related to the present application are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
As shown in fig. 1, a system for identifying a smelting working condition of a converter comprises an image acquisition module 11, an image processing module 12 and a real-time discrimination module 13;
an image acquisition module 11 for acquiring a fire hole flame image; wherein the furnace mouth flame image comprises a flame image of a converter smelting slag melting stage. Specifically, the fire flame image is acquired frame by frame in a video manner. The flame image can be directly obtained through an industrial camera, the industrial camera is fixed and supported through a tripod, and a better visual orientation is obtained through adjusting the height and rotation degree of the tripod.
The image processing module 12 is used for obtaining the texture characteristics of the fire hole flame based on the fire hole flame image and judging whether the profile characteristics of the oxygen gun exist or not based on the fire hole flame image;
the texture features of the flame are features of the flame that differ in color space distribution and composition, i.e., the texture, from the background color analog.
Specifically, the texture characteristics of the fire hole flame image can be obtained through a Gabor filter, and the frequency and the direction of the Gabor filter are similar to those of a human visual system, so that the Gabor filter is suitable for texture representation and discrimination. Gabor features mainly rely on Gabor kernels to window the signal in the frequency domain so that local frequency information of the signal can be described.
Whether the oxygen lance contour exists or not is judged, contour detection is carried out firstly, namely, in a digital image containing a target and a background, the influence of textures and noise interference in the background and the target is ignored, and a certain technology and method are adopted to realize the process of extracting the target contour. In this embodiment, the contour detection may be performed by a Gabor filter to determine whether the Gu Yangqiang contour exists in the flame image.
And the real-time judging module 13 is used for judging the slag melting condition according to the texture characteristics of the flame at the furnace mouth and also used for predicting the smelting end point of the converter for the first time according to whether the profile characteristics of the oxygen lance exist.
In general, whether the slag melting condition is good or not in the smelting process can be judged by the hardness of flame: the slag is well melted, and can be uniformly covered on the steel surface, and gas is discharged with resistance, so that the flame is soft; if the slag is well formed or is agglomerated, the slag cannot well cover the liquid level of molten steel, the resistance is small when the gas is discharged, and the flame is powerful, namely the flame is hard. When the slag amount is large, the resistance is large when the gas is discharged, and the flame is soft.
Therefore, the application judges the condition of the flame according to the texture characteristics of the flame at the furnace mouth, and judges the specific standard of the slag melting condition according to the condition of the flame: when the flame at the furnace mouth is soft, the slag melting condition is good; when the flame at the furnace mouth is hard, the slag melting condition is poor.
Judging the hardness of the flame through the texture characteristics of the flame:
and acquiring a plurality of flame texture features, and then carrying out parameter optimization modeling based on the flame texture features to obtain a model, wherein the hardness of the flame can be distinguished through the model.
When a new flame texture feature slice is acquired, the hardness of the flame can be judged based on the model. Generally, the flame texture changes in disorder and the turbulence is big, and is soft; otherwise hard.
In the embodiment, the converter smelting endpoint is predicted for the first time through the profile features of the oxygen lance, namely, when the profile of the oxygen lance appears in the flame image, the converter steelmaking is judged to be approaching the endpoint preliminarily.
In order to further determine the converter steelmaking end point, accurate determination is also required. The specific method comprises the following steps: when the flame profile of the converter is contracted at the final stage of converter smelting, the steel smelted by the converter reaches the final stage. Specifically, a Gabor filter may be employed to extract the profile of the flame.
In an embodiment, the method further comprises preprocessing the fire hole flame image, wherein the preprocessing at least comprises graying processing. The graying image obtained by the graying processing is input to a Gabor filter.
In an embodiment, the method further provides a step of guiding the image processed by the image processing module into the real-time judging module to judge the current working condition.
Specifically, the hard fire texture judgment result is 0, the soft fire texture judgment result is 1, and when the output result is 0, the current converter internal slag melting condition is bad; when the output result is 1, the current converter internal slagging condition is good.
Specifically, when the smelting end point is judged for the first time, the profile of the oxygen lance which does not appear is 0, the profile of the oxygen lance which appears is 1, and when the output result is 0, the smelting end point is not approached; when the output is 1, this means that the smelting endpoint is currently approached.
Specifically, the second discrimination of the smelting end point is carried out, the flame contour is not shrunk to 0, the flame contour starts to shrink to 1, and when the output result is 0, the current smelting end point is not reached; when the output result is 1, this means that the smelting end point is about to be reached.
Table 1 real-time judging module smelting condition judging condition
In summary, an output of 0 in the slagging process represents poor slagging conditions; output 1 represents good slagging. When judging the smelting end point, outputting 0 and 0 to represent that the smelting end point is not reached or is not close to the smelting end point; outputs 1, 0 represent that the smelting endpoint has been approached but not reached; outputs 1, 1 represent the current point of the converter smelting endpoint being reached.
The application provides a recognition system of converter smelting working conditions based on vision, which judges whether the current slagging is good or not by judging the flame hardness of a converter smelting slagging stage; and the smelting end point is primarily judged through the appearance of the profile of the oxygen lance, and the smelting end point of the converter is accurately predicted through the shrinkage and rarefaction of flame at the smelting end point of the converter. And meanwhile, the edge characteristic and the texture characteristic are extracted through gabor filtering to replace manual judgment of real-time smelting working conditions. The method avoids subjective errors caused by artificial observation, realizes accurate judgment of the smelting working condition of the converter, improves the production efficiency and reduces the smelting production cost.
As shown in fig. 2, a method for identifying smelting conditions of a converter includes:
s1, acquiring a fire hole flame image; the furnace mouth flame image comprises a flame image of a converter smelting slag melting stage;
s2, obtaining the texture characteristics of the fire hole flame based on the fire hole flame image,
s3, judging whether profile features of the oxygen lance exist or not based on the furnace mouth flame image;
s4, judging slag melting conditions according to the texture characteristics of the fire hole flame;
s5, predicting the smelting end point of the converter for the first time according to whether the profile features of the oxygen lance exist.
In one embodiment, the furnace mouth flame image further comprises a converter smelting end flame, and the converter smelting end point is predicted for the second time according to the outline characteristics of the converter smelting end flame.
In one embodiment, the texture features and the contour features of the burner flame image are obtained by a Gabor filter, and the contour features of the oxygen lance are detected by the Gabor filter.
In an embodiment, the identification method further comprises: and preprocessing the fire hole flame image, wherein the preprocessing at least comprises graying processing.
In one embodiment, if the profile characteristics of the lance are present, the converter steelmaking process is near the endpoint.
In one embodiment, the converter smelts steel to the end point when shrinkage of the flame occurs at the end of the converter smelt.
In one embodiment, judging the hardness of the flame according to the texture characteristics of the flame image of the furnace mouth, and judging the slag melting condition according to the hardness of the flame; when the flame at the furnace mouth is soft, the slag melting condition is good; when the flame at the furnace mouth is hard, the slag melting condition is poor.
Since the embodiments of the method portion and the embodiments of the apparatus portion correspond to each other, the content of the embodiments of the method portion is referred to the description of the embodiments of the apparatus portion, which is not repeated herein.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/terminal device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory ((RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, etc.
The above embodiments are merely illustrative of the principles of the present application and its effectiveness, and are not intended to limit the application. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the application. Accordingly, it is intended that all equivalent modifications and variations of the application be covered by the claims, which are within the ordinary skill of the art, be within the spirit and scope of the present disclosure.
Claims (10)
1. A system for identifying smelting conditions of a converter, the system comprising:
the image acquisition module is used for acquiring a fire hole flame image; the furnace mouth flame image comprises a flame image of a converter smelting slag melting stage;
the image processing module is used for obtaining the texture characteristics of the fire hole flame based on the fire hole flame image and judging whether the profile characteristics of the oxygen gun exist or not based on the fire hole flame image;
the real-time judging module is used for judging slag melting conditions according to the texture characteristics of the flame at the furnace mouth and predicting the smelting end point of the converter for the first time according to whether the profile characteristics of the oxygen lance exist;
the furnace mouth flame image also comprises converter smelting final flame, and the real-time judging module predicts the converter smelting end point for the second time according to the outline characteristics of the converter smelting final flame;
if the profile of the oxygen lance appears, the converter smelting steel is close to the end point;
when the flame profile shrinks at the end of converter smelting, the converter smelting steel reaches the end point.
2. The identification system of converter smelting conditions according to claim 1, wherein the texture features and the contour features of the furnace mouth flame are obtained through a Gabor filter; the profile features of the lance were detected by a Gabor filter.
3. The system for identifying smelting conditions of a converter according to claim 1, further comprising a preprocessing module, wherein the preprocessing module is configured to perform preprocessing on the flame image of the furnace mouth, and the preprocessing includes at least graying processing.
4. The identification system for the smelting working condition of the converter according to claim 1, wherein the hardness of the flame is judged according to the texture characteristics of the flame at the furnace mouth, and the slag melting condition is judged according to the hardness of the flame; when the flame at the furnace mouth is soft, the slag melting condition is good; when the flame at the furnace mouth is hard, the slag melting condition is poor.
5. The identification method for the smelting working condition of the converter is characterized by comprising the following steps:
acquiring a fire hole flame image; the furnace mouth flame image comprises a flame image of a converter smelting slag melting stage;
obtaining texture characteristics of the fire hole flame based on the fire hole flame image;
judging whether profile features of an oxygen lance exist or not based on the furnace mouth flame image;
judging slag melting conditions according to the texture characteristics of the flame at the furnace mouth;
predicting the smelting end point of the converter for the first time according to whether the profile features of the oxygen lance exist or not;
the furnace mouth flame image also comprises converter smelting final flame, and the converter smelting end point is predicted for the second time according to the outline characteristics of the converter smelting final flame;
if the profile of the oxygen lance appears, the converter smelting steel is close to the end point;
when the flame shrinks at the final stage of converter smelting, the steel smelting of the converter reaches the final stage.
6. The method for identifying the smelting working condition of the converter according to claim 5, wherein the texture features and the contour features of the flame image of the furnace mouth are obtained through a Gabor filter, and the contour features of the oxygen lance are detected through the Gabor filter.
7. The method for identifying the smelting condition of the converter according to claim 5, wherein the identifying method further comprises: and preprocessing the fire hole flame image, wherein the preprocessing at least comprises graying processing.
8. The method for identifying the smelting working condition of the converter according to claim 5, wherein the method is characterized in that the hardness of the flame is judged according to the texture characteristics of the flame image of the furnace mouth, and the slag melting condition is judged according to the hardness of the flame; when the flame at the furnace mouth is soft, the slag melting condition is good; when the flame at the furnace mouth is hard, the slag melting condition is poor.
9. A storage medium storing a computer program which, when executed by a processor, performs the method of any one of claims 5 to 8.
10. An apparatus, comprising: a processor and a memory;
the memory is configured to store a computer program, and the processor is configured to execute the computer program stored in the memory, so as to cause the terminal to perform the method according to any one of claims 5 to 8.
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