JP2011141156A - Specification method of dust kind of dust fall - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a specification method of a dust kind of dust fall capable of specifying highly accurately the dust kind of the dust fall originated in an iron manufacturing plant by a blast furnace method easily, inexpensively and quickly. <P>SOLUTION: This method includes: the first process for separating collected dust fall into magnetizable dust fall and non-magnetizable dust fall; the second process for imaging the magnetizable dust fall and the non-magnetizable dust fall respectively, to thereby generate a magnetizable dust fall image and a non-magnetizable dust fall image; the third process for classifying the collected dust fall into magnetizable dark-color particles, magnetizable bright-color particles, non-magnetizable dark-color particles and non-magnetizable bright-color particles corresponding to dust characteristics specified by combination of magnetizability and brightness, by utilizing a result acquired by classifying each magnetizable dust fall and each non-magnetizable dust fall into bright color particles and dark color particles by applying image processing to the magnetizable dust fall image and the non-magnetizable dust fall image respectively; and the fourth process for specifying the dust kind of the dust fall based on a classification result in the third process and a dust characteristic of a standard sample having a known dust kind. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a method for identifying dust species of falling dust derived from a steelmaking plant by a blast furnace method.

  Dust dust generated in an iron manufacturing plant by the blast furnace method has a problem of fouling vehicles entering the steel plant premises, and measures against such a problem are required. To that end, technology is needed to identify the source of the falling dust collected at a specific point, and as a method for identifying the source of the falling dust, the dust type of the collected dust is identified. It is thought that it is effective.

  As a method for identifying the dust type of the falling dust, for example, there is chemical analysis. Chemical analysis involves chemical treatment or heating of the falling dust sample to analyze the components of the falling dust sample to determine the component composition rate, and to drop the known dust species associated with this component composition rate. This is a technique for identifying the dust sample as a dust species. While this method has the advantage that the required equipment is inexpensive, it has the disadvantage that the mass of the sample required for analysis is larger than the typical unit weight of dust. Therefore, there is a problem that it is not always possible to collect dust with a necessary mass, and it is impossible to distinguish individual dust particles.

  As a method for making up for the drawbacks of such chemical analysis, there is an analysis using an electron microscope. The analysis using an electron microscope is performed by using EPMA (Electron Probe Micro Analyzer) or the like to quantitatively determine the component composition ratio of the falling dust sample, and the known dust species associated with this component composition ratio are determined. It is a technique to identify that it is a soot species. Unlike chemical analysis, this method can distinguish individual dust particles, and has the advantage that analysis is possible even with a small amount of sample. The processing (for example, processing for polishing after embedding a sample in a resin) is complicated, and there is a disadvantage that it takes time for measurement. For this reason, there is a problem that it takes time and money to process a large number of samples.

  Further, there is visual observation as a method for compensating for the drawbacks of both chemical analysis and analysis using an electron microscope. The visual observation is a technique in which a human observes a falling dust sample using an optical microscope or the like, and a human directly specifies the dust type of each dust. While this method has the advantage that the required equipment is inexpensive and small dust samples are analyzed, the analysis results can be easily changed for different analysts. There was a drawback that the reproducibility of the analysis was low. In addition, since there are many dust types that cannot be distinguished visually, the visual observation also has a drawback of low analysis accuracy. For example, magnetite fine particles and coal fine particles of about φ30 μm or less are difficult to distinguish by microscopic observation at a low magnification of at least several tens of times. In this case, if high-magnification observation is performed, the magnetite fine particles and the coal fine particles may be distinguished from each other, but this is not realistic because the productivity of analysis is extremely reduced. Further, the visual observation has a drawback that the analysis productivity is low in a sample containing a large number of dust particles.

  There is a technique using image processing (hereinafter referred to as “image processing method”) in order to compensate for such a drawback of visual observation. This method is a method of automatically specifying the dust type of individual dust by imaging a dust falling sample using an optical microscope or the like and applying image processing to the captured image. Although this method has the advantage of higher reproducibility and productivity of analysis compared to visual observation, dust types that cannot be distinguished by visual inspection cannot be distinguished even by simply performing image processing, so at least as much as visual observation. There is a disadvantage that the analysis accuracy is low.

  As a method for discriminating particles using the image processing method as described above, for example, a method for discriminating particles based on color information of imaging sample particles (see, for example, Patent Document 1), an area of a specimen particle, and a perimeter A method of classifying and recording particle images based on characteristics such as average density (see, for example, Patent Document 2), and a method of obtaining a particle size distribution of a granular material by performing image processing of a captured image using two-dimensional Fourier transform (See, for example, Patent Document 3), a method for detecting the characteristics of particle observation light passing through a polarizing plate and discriminating the type of asbestos particles (for example, see Patent Document 4), coal doping with iodine in falling dust Methods for identifying particles (for example, see Patent Document 5), methods for performing particle image processing by adsorbing suspended dust (for example, see Patent Document 6), and the like have been proposed.

JP-A-10-332567 JP 11-132934 A JP 2006-126061 A JP 2007-108624 A JP-A-10-55060 JP 2004-301768 A

  However, even if the method described in Patent Document 1 is applied to the identification of the dust type of the falling dust generated in the steelmaking plant by the blast furnace method, the dust type cannot be specified only by the color information of the imaging sample particles. Similarly, even if the method described in Patent Document 2 is applied to the identification of the dust type of the falling dust generated in the ironmaking plant by the blast furnace method, only the particle information such as the area of the specimen particle, the perimeter length, and the average concentration is used. The dust species cannot be specified.

  Moreover, in the method described in Patent Document 3, the particle size distribution can be obtained, but the dust type of the falling dust cannot be specified.

  The method described in Patent Document 4 is intended for particles having a deflectability, and is generally applied to discriminate particles that do not have a deflectability, such as falling dust generated in a steelmaking plant by the blast furnace method. Can not.

  In addition, in the method described in Patent Document 5, particles other than coal particles cannot be identified. Therefore, it is not possible to specify one dust type from among a plurality of types of dust fallen dust generated in a steelmaking plant by the blast furnace method. Can not.

  Moreover, in the method described in Patent Document 6, it is said that the size, shape, and properties of individual fine particles, or the relative position between individual fine particles and the distance between fine particles can be measured. It is not possible to specify the type of dust that falls in the blast furnace method steel plant.

  As described above, until now, no method has been proposed that can easily and inexpensively and quickly identify the dust type of the falling dust derived from the steelmaking plant by the blast furnace method.

  Therefore, the present invention has been made in view of the above problems, and an object of the present invention is to be able to specify a dust type of falling dust derived from a steelmaking plant by a blast furnace method with high accuracy in a simple, inexpensive and rapid manner. It is to provide a method for identifying the dust species of the falling dust.

  As a result of intensive studies to solve the above-mentioned problems, the present inventors separated the collected dustfalls by the presence or absence of magnetism, and further used the image processing method to separate the separated dust particles. In order to complete the present invention based on this knowledge, it is possible to identify the dust type of the falling dust derived from the steelmaking plant by the blast furnace method with high accuracy by discriminating according to the brightness level. It came.

  That is, according to the present invention, there is provided a method for identifying the type of dust fallen dust derived from a steelmaking plant by a blast furnace method, wherein the collected dust fallen dust and magnetized fallen dust that is magnetized by applying a magnetic force. A first step of separating the non-magnetized non-magnetized dust and the non-magnetized dust and non-magnetized dust that has been separated in the first step is imaged, A second step of generating a magnetized dust image, which is an image, and a non-magnetized dust image, which is an image of the non-magnetized descending dust, and an image on each of the magnetized dust image and the non-magnetized dust image By performing the processing, each of the magnetic fallen dust existing in the magnetized dust image and each of the nonmagnetic fallen dust existing in the non-magnetized dust image are set to a predetermined brightness threshold value. Use for light and dark particles Using the result of the classification, the collected dust fall is classified into magnetized dark colored particles, magnetized bright colored particles, non-magnetized particles according to the dust characteristics defined by the combination of magnetism and brightness. Based on the third step of classifying the magnetized dark particles and the non-magnetized bright particles, the classification result in the third step, and the dust characteristics of the standard sample with known dust types And a fourth step of identifying the dust type of the falling dust, and a method for identifying the dust type of the falling dust.

  Here, in the method for identifying the dust type of the dust fall, it is preferable that a magnetic flux density when applying a magnetic force to the dust fall in the first step is 0.1 T or more and 0.4 T or less.

  In the method for identifying the dust type of the dust fall, the particle size of each dust fall may be measured in the third step.

  Further, in the method for identifying the dust type of the falling dust, the dust type is, for example, iron-based dust mainly derived from iron ore, coal-based dust mainly derived from coal, blast furnace slag mainly derived from blast furnace slag. It is a combination of at least two or more selected from the group consisting of system dust and steelmaking slag dust mainly derived from steelmaking slag.

  Further, in the method for specifying the dust type of the falling dust, when the dust type includes at least the iron dust and the steelmaking slag dust, each particle of the magnetic fallen dust in the second step Irradiating white light to the white light and transmitting the reflected light from the particles with respect to the white light through a blue filter, and then capturing the image using a monochrome camera to generate the magnetized dust image, and the fourth step In the above, it is possible to specify that the lightness of particles on the magnetized dust image is a predetermined value or more as the steelmaking slag dust, and specify particles other than the steelmaking slag dust as the iron dust.

  Further, in the method for specifying the dust type of the falling dust, when the dust type includes at least the iron dust and the steelmaking slag dust, each particle of the magnetic fallen dust in the second step The blue dust is emitted using a blue LED and the reflected light from the particles with respect to the blue light is imaged using a monochrome camera to generate the magnetized dust image, and in the fourth step, It is also possible to specify that the brightness of the particles on the magnetized dust image is a predetermined value or more as the steelmaking slag dust, and identify particles other than the steelmaking slag dust as the iron dust.

  According to the present invention, it is possible to easily and inexpensively and quickly determine the dust type of the dust fall from the steelmaking plant by the blast furnace method by discriminating the collected dust fall based on the presence or absence of magnetism and the brightness level. It can be specified with high accuracy.

It is explanatory drawing which shows the rough relationship between the magnetization and the brightness in each dust type of the dust fall derived from the steelmaking plant by a blast furnace method. It is a flowchart which shows the flow of operation in the identification method of the dust type of the falling dust which concerns on one Embodiment of this invention. It is a graph which shows the outline of the relationship between the magnetic flux density [T] of a typical dust type of the falling dust generated in the steelmaking plan by a blast furnace method, and a magnetization rate [mass%]. It is a graph which shows an example of the relationship between the magnetic flux density [T] of a typical dust type of the falling dust generated in the steelmaking plan by the blast furnace method which this inventor investigated, and the magnetization rate [mass%]. It is explanatory drawing which shows an example of the shape of the magnet used by the magnetic separation of the 1st process of this invention. It is explanatory drawing which shows an example of the magnetic separation method of the falling dust in the 1st process of this invention. It is explanatory drawing which shows an example of the apparatus which produces | generates a magnetized dust image and a non-magnetized dust image in the 2nd process of this invention. It is a flowchart which shows the flow of the particle image processing measurement in the 3rd process of this invention. It is explanatory drawing which shows an example of the imaging system used for discrimination | determination of the steel-making slag type | system | group dust and iron-type dust with insufficient aging.

  Exemplary embodiments of the present invention will be described below in detail with reference to the accompanying drawings. In addition, in this specification and drawing, about the component which has the substantially same function structure, duplication description is abbreviate | omitted by attaching | subjecting the same code | symbol.

[Overview]
The present invention is a method for identifying the dust species of falling dust derived from an iron manufacturing plant by the blast furnace method, and includes the following first to fourth steps.
(First Step) The collected dust fall is separated into a magnetic fallen dust that is magnetized by applying a magnetic force and a non-magnetized fallen dust that is not magnetized.
(Second Step) Each of the magnetic fallen dust and the non-magnetization fallen dust separated in the first step is imaged, and an image of a magnetic fallen dust image that is an image of the magnetic fallen dust and a non-magnetic fallen dust A non-magnetizing dust image that is an image is generated.
(Third step) By applying image processing to each of the magnetized dust image and the non-magnetized dust image, the individual magnetized dust falling image present in the magnetized dust image and the non-magnetized dust image are present. Each non-magnetized dust fall is classified into light and dark particles using a predetermined brightness threshold, and the collected dust is separated into magnetized and light using the classification result. Depending on the dust characteristics defined by the combination of the above, it is classified into any one of magnetized dark colored particles, magnetized bright colored particles, non-magnetized dark colored particles and non-magnetized bright colored particles.
(Fourth Step) Based on the classification result in the third step and the dust characteristics of a standard sample whose dust type is known, the dust type of the falling dust is specified.

  Hereinafter, definitions of terms used in the description of the present invention and details of each process will be described.

[Definition of dustfall]
Falling dust refers to particles having a relatively large diameter (approximately φ10 μm or more) that can settle on average in the atmosphere among solid particles floating in the atmosphere.

[Definition of dust species]
The “dust type” in the present invention is not particularly limited, but refers to the kind of dust classified according to the above-mentioned dust generation source, constituent components, and the like. For example, when classifying by source, soot species are: iron ore-derived soot generated from iron ore raw material yard, coal-derived soot generated from coal raw material yard, blast furnace slag derived from blast furnace slag It is classified as dust from the converter slag generated from the converter.

In the present invention, similar dust species may be collectively classified. Here, “similar” means that at least the main components are common and have the following relationship (i) or (ii).
(I) Being in a relationship between raw materials and products (ii) Being generated by a similar process

  Examples of the above (i) include those containing coal and coke whose main component is common in carbon (hereinafter referred to as “coal dust”), and iron ore whose main component is common in iron oxide and sintering. Some include minerals, iron oxide powder (for example, steelmaking dust), and the like (hereinafter referred to as “iron-based dust”). Examples of (ii) include blast furnace granulated slag, blast furnace slow-cooled slag, etc. that are common in silicon oxide and calcium oxide, and have common processes in terms of separating impurities from the molten raw material as liquid or solid (Hereinafter referred to as “blast furnace slag dust”) and the main component is common to silicon oxide, calcium oxide and iron oxide, and the process is common in that impurities are separated from the molten raw material as liquid or solid. There are those that include converter slag and hot metal pretreatment slag (hereinafter referred to as “steel slag dust”). The soot species that can be dustfall in modern steelmaking plants using the blast furnace method can be almost covered by the coal-based soot, iron-based soot, blast furnace slag-based soot and steel-making slag-based soot described above.

  In addition, the method for identifying the dust type of the falling dust according to the present invention is mainly the soot type mainly derived from iron ore, the soot type mainly derived from coal, and the soot type mainly derived from blast furnace slag. And a combination of at least two or more selected from the group consisting of dust species mainly derived from steelmaking slag.

[Basic technical concept]
Next, the basic technical idea of the present invention will be described with reference to FIG. FIG. 1 is an explanatory diagram showing a schematic relationship between magnetism and lightness in each dust type of dust falling from a steelmaking plant by the blast furnace method.

  As described above, the falling dust derived from the ironmaking plant by the blast furnace method is mainly classified into four types of dust, namely coal dust, iron dust, blast furnace slag dust, and steelmaking slag dust. In general, blast furnace slag dust and steelmaking slag dust are white light particles (light colored particles), and coal dust and iron dust are black light particles (dark colored particles). Therefore, as before, by performing image processing on images taken using a low-magnification optical microscope and identifying the level of brightness of individual dust particles, it is possible to detect blast furnace slag dust and steelmaking slag dust. And soot species composed of coal-based dust and iron-based dust.

  However, it is not possible to discriminate between particles having the same level of brightness, for example, discrimination between blast furnace slag dust and steelmaking slag dust, only by classifying such bright particles and dark particles. That is, as described above, the image processing is simply performed on the photographed image, and the classification based only on the brightness level is too comprehensive, and the soot species of the falling dust derived from the steelmaking plant by the blast furnace method (and the source of the falling dust) Since it cannot be specified, the utility is low.

  Therefore, in order to identify the dust type of the dust falling from the steelmaking plant by the blast furnace method (hereinafter, sometimes referred to as “iron-making dust falling dust”), the present inventor only uses the brightness level of the dust particles. We focused on the presence or absence of magnetism. As a result, the present inventor can define the dust characteristics by the combination of the brightness level and the presence or absence of magnetism, and based on this dust characteristics, the dust type of the falling dust derived from the ironmaking plant by the blast furnace method can be determined. I found out that it can be identified.

  More specifically, as shown in FIG. 1, the present inventor classified the dust type of dust falling from iron making that cannot be identified by simply image processing a low-magnification optical microscope image. It has been found that it is possible to discriminate among four types of coal dust, iron dust, blast furnace slag dust, and steelmaking slag dust. Here, the magnetism in the present invention means the property of magnetizing (being magnetized and attracted to the magnet) by applying a magnetic force to the target dust particles, The falling dust derived from the blast furnace method steelmaking plant is classified into a magnetic falling dust that is magnetized by applying a magnetic force, and a non-magnetic falling dust that is not magnetized even when a magnetic force is applied. Soot dust and non-magnetic falling dust are classified into light particles and dark particles according to the brightness.

  Specifically, coal-based soot has low lightness (dark color) and non-magnetic non-magnetized dark particles, and iron-based dust has low lightness (in dark color) magnetized dark magnetized particles, blast furnace slag Soot dust is classified as non-magnetic non-magnetized light particles with high brightness (light color), and steelmaking slag dust is classified as magnetized magnetized light-colored particles with high brightness (light color). be able to.

[Advantages of the present invention]
Next, the superiority of the present invention having the above technical idea over the prior art will be described.

  First, iron dust-derived dustfall is classified according to the presence or absence of magnetism, but hematite, which is a typical iron ore, is not attracted to the magnet by the magnetic force of a ferrite magnet, which is a typical permanent magnet. For this reason, general steel industry engineers could not have the idea of using magnetic force to separate hematite from coal. In steel engineers, separation using magnets has been considered exclusively as a technique for separating hematite from magnetite (partially magnetized into ferrite magnets) partially blended with steel raw materials.

  Also, in steelworks, there is a case where magnetic selection is performed by using a strong electromagnet to collect used iron slag that contains a lot of iron. Some slag lumps are magnetized by strong magnets. Was known to exist. However, the target of such magnetic selection is usually limited to a coarse slag lump having a diameter of at least several tens of millimeters. This is because slag is usually obtained in large blocks, and it is expensive to make fine particles, so in actual operation, slag is often crushed to the maximum size that can be processed. . Coarse slag agglomerates often contain steel ingots or pig iron ingots (both not iron oxide) that have been physically refined and solidified, while slag particles contain steel and pig iron. Inclusion is rare. This is because when the slag lump containing steel and pig iron is refined, it is separated into slag fine particles and fine particles of steel and pig iron. From the above circumstances, it has been understood among the steel industry engineers that the above-described magnetic sorting recovers a slag lump including a steel lump and a pig iron lump. In actual operation, the steel ingot and pig iron ingot contained in the collected slag lump can be easily reused as a steel raw material (Fe source) if the entire slag lump is put into the refining furnace. On the other hand, it is generally difficult to separate iron oxide, which is a slag component, from the slag lump as a steel raw material even if it is re-entered into the refining furnace. Therefore, in general, the interest of steel industry engineers regarding whether or not iron oxide, which is a slag component, is adsorbed by magnets in magnetic separation is low, whether blast furnace slag or converter slag, slag includes steel and pig iron. Whether or not it was a major concern. For this reason, the idea of using a magnet for the selection of blast furnace slag-based fine particles (dust) and converter slag-based fine particles (dust) has never existed.

  Even if there is a need for a general magnetic separation engineer to separate the blast furnace slag and converter slag, the magnetic separation of the conventional large mass is not limited to the component, Because it also depends on the diameter (diameter) (the larger the mass, the harder it is to magnetize), so in the operation of selecting the dust type (the dust type is independent of the size and mainly corresponds to the component) by magnetization, Since the error of the slag lump size is large, it is considered that quantitative sorting cannot be performed. On the other hand, in the case of fine particles having a sufficiently small particle size with respect to the cross-sectional area of the magnet, the particle size hardly affects the magnetization, and the magnetization of the fine particles is mainly determined by the components. This is due to the following reason. In other words, there is a limit to the distance that the magnetic force of the magnet can reach (limit depth), and if the slag lump to be magnetized is larger than this limit depth, the entire slag lump is resisted by gravity with a magnetic force that works only within the limit depth range. And hold it. Therefore, the larger the mass, the harder it is to magnetize (hold). For this reason, in the above-described magnetic separation of slag, a coarse slag lump that does not include a steel lump or pig iron lump does not magnetize the magnet even if it contains a large amount of iron oxide. For this reason, an engineer who is involved in slag magnetic selection has not been able to conceive that the magnetization of slag changes according to the amount of iron oxide content. On the other hand, in the case of fine particles, since the particle diameter is much smaller than the limit depth, the magnetic force applied to the fine particles has a small change in the thickness direction of the particles, and the magnetic force acting on the whole particles is determined by the horizontal cross-sectional area of the particles and the particles. Is proportional to the product of the thickness of the particles, that is, the volume of the particles. On the other hand, the gravity applied to the particles is also proportional to the particle volume. Therefore, in the fine particles, the influence of the volume of the particles is canceled out by the magnetic force and the gravity, and therefore the influence of the volume is eliminated. The present inventor has noticed a situation peculiar to the magnetic separation of such fine particles, and has found that the particles can be quantitatively sorted even when the magnetic force is used.

  Further, as a result of the inventors' investigation, the inventors have found that dust particles cannot be separated into the above-mentioned four representative types of dust by simply using a powerful magnet that can magnetize hematite. I found it. This is because if a magnet that is too powerful is brought into contact with a dust species, even dust containing a small amount of iron (iron, steel, pig iron, iron oxide) will be magnetized. It can only be sorted into fine particles, even in trace amounts. The dust generated in a blast furnace steel production plant usually contains more or less iron (for example, coal often contains about 1% by mass of iron oxide in ash. Also, blast furnace slag In general, at least about 0.3% by mass or more of iron is contained.) The fine particles containing no iron in the dust generated in the steelmaking plant by the blast furnace method are substantially derived from the soil in the ironworks. Limited to minor dust species such as quartz-based earth and sand. Therefore, such magnetic sorting is not very useful for identifying the dust species at least in the steel plant. Therefore, in the present invention, by using a moderately strong magnet, it is possible to prevent the soot dust species (coal soot and blast furnace slag soot) containing iron but low in content from being magnetized, and so that the magnetized soot species (iron System dust and steelmaking slag dust).

  Further, by utilizing the difference in brightness of the soot particles, it can be separated into dark soot species (coal soot and iron soot) and bright soot species (blast furnace slag soot and steelmaking slag soot). As a result, if limited to the above four main types of soot generated in steelmaking plants by the blast furnace method, the soot characteristics specified by the combination of magnetism and brightness are used to make each soot practical and It can be easily categorized into four main dust types. The present inventors have found the above matters for the first time. On the other hand, general particle analysis engineers (especially analysis engineers using electron microscopes) are not limited to soot generated in steelmaking plants using the blast furnace method, but have a more versatile soot species analysis method. It was oriented. In addition, general particle analysis engineers have focused their efforts on increasing the number of elements and molecules that can be analyzed, and improving the accuracy of component composition analysis. Therefore, as in the present invention, general particles are used in analytical techniques in fields that have sufficiently high utility only by classifying individual dusts into only four types of main dust types generated in a blast furnace steel plant. There has never been an analysis engineer conceived.

[Method for Specifying Dust Type of Dust Drops According to One Embodiment of the Present Invention]
The superiority of the present invention over the prior art has been described above. Next, with reference to FIG. 2, the contents of each step included in the method for identifying the dust type of the falling dust according to the present invention will be described in detail. . FIG. 2 is a flowchart showing an operation flow in the method for identifying the dust type of the falling dust according to the embodiment of the present invention.

(First step)
The first step is a step of separating the collected falling dust into a magnetic falling dust that is magnetized by applying a magnetic force and a non-magnetic falling dust that is not magnetized (S101 to S105 in FIG. 2).

<Collecting falling dust>
In the first step, first, dust falling that is an analysis (identification) target is collected (S101). The method for collecting the falling dust in the present invention is roughly classified into a wet method and a dry method. The wet method is a method of collecting the falling dust falling in an open container in which water is stored at the bottom, and collecting the dust together with the water in the container. As an apparatus using this wet method, for example, a commercially available deposit gauge can be used. In addition, when applying a wet method, it is necessary to isolate | separate dust particles from water and dry beforehand. The dry method is a method of sucking the dust falling to a dust collection port (for example, having a funnel shape) opened upward and collecting it in a membrane filter or the like. As an apparatus used for this dry method, for example, a continuous dust / dust meter described in JP 2008-224332 A can be used. In addition, when applying a dry method, it is desirable to isolate | separate particle | grains from a membrane filter beforehand. However, this process is not necessarily required if the number of collected particles is small and individual particles can be separated and recognized on the membrane filter.

<Processing samples for analysis>
Next, the sample for analysis (specific object) is processed. Specifically, the collected dust particles are sprayed on the substrate (S103). At this time, the spraying amount is adjusted so that the particles do not contact each other. In addition, it is not always necessary to process all of the collected dustfall as an analysis sample (spread on the substrate), and a part of the collected dustfall may be extracted and used as an analysis sample. However, in order to evaluate the influence of sample variation, it is preferable to use at least 100 or more dustfall particles as an analysis sample.

  There are no particular limitations on the substrate on which the dust particles are dispersed, as long as the substrate has a flat shape and is difficult to chemically and electrically adhere to and adhere to the dust particles. A metal plate, a glass plate, etc. can be used.

  Moreover, since the falling dust is usually coarse particles having a diameter of 10 μm or more, when the falling dust particles are sprayed, free fall of the falling dust particles in the atmosphere can be used. Specifically, for example, the collected dust particles can be sprinkled with a soot and dropped onto the substrate from above, whereby the dust particles can be dispersed on the substrate.

<Magnetic separation method>
Next, by applying a magnetic force to each particle of the falling dust particles sprayed on the substrate using a magnet, the collected falling dust particles are separated into magnetic falling dust particles and non-magnetic falling dust particles. (S105). As a magnet used in this case, it is necessary to use a magnet having such a strong magnetic force that iron dust or steelmaking slag dust is magnetized and coal dust or blast furnace slag dust is not magnetized. Specifically, it is preferable to use a magnet having a magnetic flux density of 0.1 T or more and 0.4 T or less at least on the surface of the falling dust in the first step.

  Here, with reference to FIG.3 and FIG.4, the magnetism of the typical dust type of the falling dust generated in the steelmaking plan by a blast furnace method is demonstrated. FIG. 3 is a graph showing an outline of the relationship between the magnetic flux density [T] and the magnetization rate [mass%] of a typical dust type of the dust fall generated in the steelmaking plan by the blast furnace method, and FIG. It is a graph which shows an example of the relationship between the magnetic flux density [T] of a typical soot seed | species of the dust fall which generate | occur | produces with the steelmaking plan by the blast furnace method which the person investigated, and the magnetization rate [mass%]. Here, the magnetization rate in the present invention means that a magnet having a substantially constant and uniform magnetic flux density on the attracting surface is brought into contact with the sample particle group, and the magnet is attracted to the magnet (magnetized particles) and not attracted. The ratio of the total amount of magnetized particles to the total amount of sample particles before separation when separated into (non-magnetized particles). Here, “total amount” means the total amount of mass when defined by mass ratio, and means the total amount of volume when defined by volume ratio. In the following description, the total amount is defined by volume unless otherwise specified.

  According to a study by the present inventors, iron ore (magnetite (magnetite)), iron ore (hematite (hematite)), steelmaking slag, which are typical dust types of falling dust generated in the steelmaking plan by the blast furnace method, Coke and blast furnace slag were found to have a tendency as shown in FIG. That is, iron ore (magnetite) has a high magnetization rate from a small magnetic flux density of about 0.01 T and is magnetized even with a weak magnetic force such as a ferrite magnet. In addition, iron ore (hematite) and steelmaking slag are low in magnetization at a small magnetic flux density of less than 0.1 T, and are not magnetized even if they have a weak magnetic force such as a ferrite magnet. When the magnetic flux density increased to 0.1 T or more, the magnetization rate increased, and it was found that magnets having a strong magnetic force such as neodymium magnets were magnetized. Further, it was found that coke and blast furnace slag have a low magnetization rate even at a magnetic flux density of about 0.4 T, and do not magnetize a magnet having a strong magnetic force such as a neodymium magnet. Furthermore, coke increases in magnetic flux density exceeding 0.4T, but the susceptibility of blast furnace slag tends to be low even when exceeding 0.4T.

  The above properties also appear in the results of studies conducted by the present inventors. That is, as shown in FIG. 4, the ferrous dust (steel-making dust (magnetite is the main component)) has a magnetic flux density of less than 0.1 T on the magnetized surface (for example, the lower end of the magnet magnetized with the dust particles). When the magnetic flux density is less than 0.1 T, the magnetic susceptibility is small and the magnetic flux density is 0 when the magnetic dust density is less than 0.1 T. When it became 1T or more, the magnetization rate increased rapidly. Further, the coal-based dust (coke) has a low magnetization rate until the magnetic flux density is about 0.4 T, and the magnetization rate has increased when the magnetic flux density exceeds 0.4 T. Further, the blast furnace slag dust (granulated slag, slow-cooled slag) remained low in magnetization rate within the range of 0.5 T or less, which is the examination range.

  From the above examination results, in the method for identifying the dust type of the falling dust according to the present invention, as a condition for adsorbing the iron dust and the steelmaking slag dust as one of the representative dust types to the magnet, the first A preferable range is that the magnetic flux density when applying a magnetic force to the dustfall in the process is 0.1 T or more at least on the surface of the dustfall. On the other hand, even if the magnetic force applied to the falling dust in the first step is too strong, the coal-based dust is the same as the iron-based dust due to the iron contained in a very small amount in the coal-based dust that is one of the representative dust types. As a condition for avoiding such a phenomenon, the magnetic flux density when applying the magnetic force to the falling dust in the first step is 0.4 T or less at least on the surface of the falling dust. This was made a suitable range.

  As a specific example of the magnet that can realize the above-mentioned preferable magnetic flux density range, for example, there is an electromagnet that can realize the magnetic flux density in the range of 0.1T to 0.4T. As the permanent magnet, a neodymium magnet, a samarium cobalt magnet, or the like having a magnetic force with a magnetic flux density in the range of 0.1 T to 0.4 T can be used. In addition, since the magnetic force is weak, the ferrite magnet which is a typical permanent magnet is not suitable as a magnet used by the magnetic separation of the 1st process of this invention.

  Next, the shape of the magnet used in the magnetic separation in the first step of the present invention will be described with reference to FIG. FIG. 5 is an explanatory view showing an example of the shape of a magnet used in the magnetic separation in the first step of the present invention, (a) is a vertical sectional view, and (b) is (b)-in (a). (B) It is sectional drawing cut | disconnected by the cross section, (c) is sectional drawing cut | disconnected by the (c)-(c) cross section in (a).

  As shown in FIG. 5, the magnet 11 used in the magnetic separation in the first step of the present invention is held by a magnet holder 13 and, if necessary, a spacer 15 at the tip (the side in contact with the dustfall). May be provided. Further, when the magnet 11 is brought into contact with the dustfall, the tip of the magnet 11 and the dustfall may be brought into direct contact, and the separation plate 17 is disposed between the magnet 11 (or the spacer 15) and the dustfall. Then, the magnet 11 and the dustfall may be brought into contact with each other through the separation plate 17.

The magnet 11 only needs to have a flat shape at the tip (the side in contact with the falling dust). As the magnet 11, for example, a cylinder or a prismatic type can be used. Moreover, in order to ensure the contact property with the falling dust particles sprayed on the flat substrate and the uniformity of the magnetic force applied to each dust particle, the cross-sectional area of the tip of the magnet 11 is 0.1 cm ² or more. It is preferable. Further, when a thin magnet having a small cross-sectional area at the tip is used as the magnet 11, the gradient of the magnetic flux density in the horizontal plane decreases as the distance from the tip of the magnet 11 decreases, and the magnetic force becomes uniform. A spacer 15 may be provided at the tip of the magnet 11 so that the dustfall does not approach the tip of the magnet 11 more than necessary. The material of the spacer 15 is not particularly limited as long as it is non-magnetic, and for example, a plastic plate (synthetic resin having elasticity such as rubber or vinyl chloride) can be used. Also, the shape of the spacer 15 is not particularly limited, but for example, a substantially ring-shaped shape as shown in FIG. 5 can be used. Also, the material of the separation plate 17 is not particularly limited as long as it is non-magnetic. However, as will be described later, when the separation plate 17 is placed on the particle sample of the magnetic fallen dust, a transparent material is used. By using it, the particle sample can be imaged through the placed separation plate 17, which is preferable. As such a transparent material, for example, a transparent acrylic material or the like can be used.

  Subsequently, the details of the magnetic separation method of the falling dust in the first step of the present invention will be described with reference to FIG. FIG. 6 is an explanatory view showing an example of a magnetic separation method for dustfall in the first step of the present invention. FIG. 6 shows an example in which the spacer 15 in FIG. 5 is not used.

  As shown in FIG. 6, first, the flat surface at the tip of the magnet 11 is placed on the substrate 1 on the dust fallen (consisting of the magnetism fallen dust Pm and the non-magnetism fallen dust Pn) scattered on the flat substrate 1. The tip of the magnet 11 is brought into contact with the magnet 11 directly or between the magnet 11 and the dustfall through a separation plate 17 (may be shared with a spacer) ((a) in FIG. 6). To (b)). The contact time between the magnet 11 and the dustfall at this time may be, for example, 1 second or longer.

  Thereafter, the magnet 11 is pulled up (when the separation plate 17 is used, the separation plate 17 is pulled up as it is in contact with the magnet 11). At this time, the falling dust remaining on the substrate 1 is a sample of non-magnetized falling dust Pn ((b) to (c) in FIG. 6). Further, on the substrate 2 different from the substrate 1, the magnet 11 attracted with the falling dust is lowered and brought into contact with the substrate 2 ((c) of FIG. 6).

  Further, the magnet 11 is separated from the falling dust or the separation plate 17 having the lower surface attached with the falling dust. Specifically, when the magnet 11 is an electromagnet, the current flowing through the electromagnet is turned off (in a device having a degaussing function, the current is turned off after supplying the demagnetizing current), and the magnet 11 alone is pulled up to be worn. The magnetized falling dust is left on the substrate 2. On the other hand, when the magnet 11 is a permanent magnet such as a neodymium magnet, the separation plate 17 is fixed on the substrate 2, and only the magnet 11 is pulled up, so that dust falls (being magnetized) under the separation plate 17. To remain. By doing so, the magnetized falling dust can be pressed from above by the gravity of the separation plate 17, and the magnetized falling dust can be separated from the permanent magnet. In order to fix the separation plate 17, the separation plate 17 may be simply placed on the substrate 2 using the gravity of the separation plate 17. At this time, the falling dust remaining on the substrate 2 is a sample of the magnetized falling dust Pm ((d) in FIG. 6).

(Second step)
In the second step, each of the magnetic fallen dust and the non-magnetization fallen dust separated in the first step is imaged, and a magnetized dust image that is an image of the magnetic fallen dust and a non-magnetic fallen dust This is a step of generating a non-magnetized dust image that is an image (S107 in FIG. 2).

  Here, the details of the content of the second step will be described with reference to FIG. FIG. 7 is an explanatory diagram showing an example of an apparatus for generating a magnetized dust image and a non-magnetized dust image in the second step of the present invention.

  In the second step, for example, using a commercially available microscope equipped with illumination means, imaging means, and the like as shown in FIG. Specifically, the illumination unit 25 is used to irradiate light uniformly to the falling dust particles P (magnetic falling dust or non-magnetic falling dust) dispersed on the substrate 1. In the present invention, in order to measure the brightness of the particle image, it is preferable to set the illumination condition at the time of capturing the dustfall so that the illuminance is always constant on the imaging surface. As the illumination means 25, a commercially available ring illumination for a microscope can be used.

  Next, each of the sample of the magnetized dust fall and the sample of the non-magnetized dust fall is imaged using the imaging means 21, and a magnetized dust image and a non-magnetized dust image are generated. As an imaging method by the imaging unit 21, for example, illumination is emitted from the illumination unit 25 toward the falling dust particles P, and reflected light from the surface of the falling dust particles P is received by the imaging unit 21 (or the lens 23). The imaging means 21 generates a captured image (a magnetized dust image and a non-magnetized dust image). As the imaging means 21, a CCD type or CMOS type digital camera can be used.

  In addition, the brightness (representative brightness) of each dust particle is averaged within the size of the corresponding CCD element corresponding to each particle image, so that it is desirable for the measurement accuracy of the brightness of the particle that the number of pixels of the camera is large. Specifically, it is preferable to use the imaging means 21 having pixels with a density that enables imaging of target particles with at least 9 pixels (monochrome camera). From the viewpoint of accurately recording the brightness of the particles, a monochrome camera is preferable. When a single-plate color camera (usually, a different color filter is applied to adjacent CCD elements) is used as the image pickup means 21, lightness values (CCD is interpolated using lightness for at least four pixels). In the case of a Bayer array), it is necessary to perform measurement accuracy processing such as using the brightness to be measured. Therefore, the imaging means 21 having pixels with a density capable of imaging the target particle with at least 54 pixels or more is used. It is preferable. Further, in order to secure the pixel density necessary for imaging the target particles, the particles may be enlarged and imaged through a lens 23 such as a microscope, if necessary.

(Third step)
In the third step, image processing is performed on each of the magnetized dust image and the non-magnetized dust image, so that each magnetic fallen dust particle existing in the magnetized dust image and non-magnetized dust image exists. Each non-magnetized dust fall is classified into light and dark particles using a predetermined brightness threshold, and the collected dust is separated into magnetized and light using the classification result. In accordance with the dust characteristics defined by the combination of the above, it is a step of classifying into any one of the magnetized dark colored particles, the magnetized bright colored particles, the non-magnetized dark colored particles, and the non-magnetized bright colored particles (Fig. 2 S109, S111 and FIG. 8).

  Here, the details of the content of the third step will be described with reference to FIGS. 2 and 8. FIG. 8 is a flowchart showing the flow of particle image processing measurement in the third step of the present invention.

  In the third step, generally performed particle image processing measurement is performed on each of the magnetized dust image and the non-magnetized dust image captured in the second step (original image). This particle image processing measurement can be performed using, for example, a particle image processing measurement function that is normally installed in commercially available image processing software such as “ImageProPlus”.

  Specifically, as shown in FIG. 8, first, the imaging data (original image) is binarized using a predetermined brightness threshold value T1 (S151). An example of a method for setting the lightness threshold value T1 in this case is as follows. That is, a certain lightness threshold value t1 is provisionally determined for a sample with a known dust type (for example, a mixture of coal-based dust and blast furnace slag-based dust whose mixing ratio is known), and this lightness threshold value t1. Using the method described below, light particles (which should be blast furnace slag dust in the above example) and dark particles (in the above example should be coal dust) Is determined). At this time, if the determination result is significantly different from the predetermined blending ratio, another lightness threshold value t2 is provisionally determined, and binarization is performed using this lightness threshold value t2. Distinguish between color particles and dark particles. By repeating the above-described operation, the lightness threshold value T1 can be set as the lightness threshold value T1 that provides the best separation (the determination result and the predetermined blending ratio substantially coincide). However, the setting method of the lightness threshold value T1 is not limited to the above method, and any method can be used as long as the lightness threshold value with the best separation can be obtained. Good.

  Since it is actually difficult to obtain completely uniform illuminance over the entire area of the field of view of the imaging means (camera), before the binarization, the brightness of the recorded pixel is set to the two-dimensional pixel The variation in illuminance in the image may be corrected by increasing or decreasing the correction value that is a function of the position. As a correction value calculation method in this case, for example, a gray test piece whose scattering light reflectance value is known in advance is photographed with the imaging system used in the present invention, and all of the images recorded at this time are recorded. A value obtained by subtracting the brightness of each pixel from the average brightness value of the pixel can be used as a brightness correction value for each pixel. If the correction value is sufficiently smaller than the dynamic range of the pixel, the error in this correction method is reduced. Further, it is desirable to make the illuminance on the photographing surface as uniform as possible so that the correction value becomes small.

  Next, from the connection relationship of the binarized brightness of adjacent pixels, an area where the same binarized brightness is continuous and independent of other areas is specified as an area where particles exist (S153). Further, if necessary, the area of each particle whose presence is specified in step S153 is calculated, and the center position of the particle and the diameter converted into an equivalent circle are calculated (S155). Note that data such as the area, center position, and diameter of each particle calculated in step S155 is recorded in a storage unit (not shown) provided in the imaging system.

  Next, the imaged data (original image) is binarized using a lightness threshold value T2 (> T1) higher than the lightness threshold value T1 in step S151 (S157), and the same as in step S153. A region where the binarized brightness is continuous and independent of other regions is specified as a region where particles exist (S159). Further, similarly to step S155, the area of each particle specified in step S159 is calculated as necessary, and the center position of the particle and the diameter converted into an equivalent circle are calculated (S161). The particles specified in steps S159 and S161 are specified as light-colored particles.

  Next, the particles whose shape is specified in step S155 are compared with the particles whose shape is specified in step S161 (light color particles), and particles whose center positions are within a predetermined threshold value are compared. The same particle (light color particle) is specified, the particle specified as the light color particle is excluded from the set of particles whose shape is specified in step S155, and the remaining particles are specified as dark color particles (S163).

  According to the dust characteristics determined from the classification result of the bright color particles and the dark color particles classified as described above and the separation result performed in step S105 of the first step, the imaged dust particles are captured. The particles are classified into any one of magnetized dark particles, magnetized light colored particles, non-magnetized dark particles, and non-magnetized light colored particles (S165).

  The above steps S151 to S165 were collected by carrying out each of the sample particles of magnetic falling dust and the sample particles of non-magnetic falling dust separated in step S105 (step S167). The falling dust particles can be classified into magnetized dark particles, magnetized light colored particles, non-magnetized dark particles, and non-magnetized light colored particles (S111 in FIG. 2).

  In the image processing of the present invention, the brightness of each particle is discriminated using the brightness of each particle. Therefore, if the background of the particle has a brightness with which it is easy to ensure contrast according to the average brightness of the sample particle, it is appropriate. Good.

(Fourth process)
The fourth step is a step of identifying the dust type of the falling dust based on the classification result in the third step and the dust characteristic of the standard sample whose dust type is known (S113 to S117 in FIG. 2). .

  In the fourth step, first, a standard sample with a known dust type (representative sample: a pure sample containing only one kind of dust type) is prepared, and the above-described figures are shown for the standard samples of each dust type. Eight steps S151 to S165 are performed. Then, from the dust characteristics of each particle (the presence or absence of magnetism and the brightness level), the composition ratio of the particles corresponding to the difference in the dust characteristics is obtained for each dust type. As a result, the dust characteristics of the particles having the highest composition ratio in each dust species are specified as the dust characteristics of the dust species, and the dust species and dust characteristics are associated (S113). For example, in a standard sample of a certain dust type, when the composition ratio of the magnetized dark color particles is the highest, the dust type is associated with the dust characteristic of magnetism and dark color.

According to the knowledge of the present inventor, typical dust types of dust falling from a blast furnace method steel plant can be classified into particles having the following dust characteristics and can be distinguished from each other.
(A) Coal-based soot (coal and coke): Soot characteristics are non-magnetic and dark (b) Iron-based soot (iron oxide powder such as iron ore, sintered ore, steelmaking dust): Soot characteristics are magnetized・ Dark color (c) Blast furnace slag dust (Blast furnace granulated slag, blast furnace slow-cooled slag): Dust characteristics are non-magnetic. (D) Steelmaking slag dust (converter slag, hot metal pretreatment slag): Dust Characteristics are magnetism and light color

  The association (S113) between the soot species and the soot characteristics using the standard sample with the known soot species identifies the soot species of the collected falling dust as long as the validity of the standard sample is not lost. In this case, it is sufficient to carry out only once, and in the second and subsequent analysis, the result of the first time can be used as it is.

  Next, for the collected dustfall, the dust characteristics classified in step S111 of the third step described above are compared with the dust characteristics associated with the dust species in step S113, and the standard having the same dust characteristics It is specified as the dust type of the sample (S115). For example, if the dust characteristics of the particles used as the analysis sample in the collected dust fall are “magnetization / dark color”, the dust fall is identified as iron dust. Moreover, if the dust characteristics of the particles used as the analysis sample in the collected dust fall are “non-magnetized / light color”, it is identified as blast furnace slag dust.

  Further, the dust type and particle size distribution of the sample used as the analysis sample are obtained using the diameter of each dust particle obtained in the third step and the information on the collected dust type of the fallen dust collected in step S115. Next, the information on the soot type and particle size distribution of the obtained sample is compared with the information on the soot type and particle size distribution at each dust source in the steelmaking plant, and dust sources with high similarity between these information are obtained. It can be specified as a dust generation source of the collected dustfall (S117).

  The determination of whether or not they have the same dust characteristics in step S115 and the determination of similarity in step S117 may be performed by a human or a computer. When each of the above determinations is made using a computer, for example, an algorithm of an expert system that makes a human determination method into a rule and makes a determination based on this rule can be used.

(Identification of steelmaking slag dust with insufficient aging)
As described above, both the iron dust and the steelmaking slag dust can be magnetized by using a magnet having a predetermined magnetic flux density. On the other hand, ferrous dust and steelmaking slag dust are completely different in dust generation source. Therefore, both should be able to clearly distinguish each other.

  Here, converter slag (steel slag) dust that has been sufficiently aged by being exposed to wind and rain outdoors for a long time generally has a light gray calcium carbonate layer formed on its surface. It can be distinguished from dark iron-based dust.

  However, a small amount of steelmaking slag that has not yet been sufficiently aged. Such a steelmaking slag dust is a little dark because a light gray calcium carbonate layer is not sufficiently formed on the surface. Therefore, steelmaking slag-based dust with insufficient aging may not be distinguished from particles with relatively high brightness among iron-based dusts depending only on magnetism and brightness.

  Therefore, as a result of analyzing the spectrum of the reflected light when the iron dust and the steelmaking slag dust are irradiated with white light, the present inventor cannot visually distinguish, but in the iron dust, the particles with relatively high brightness It was found to have a sharp peak from yellow to red (wavelength 600 μm to 780 μm). On the other hand, in steelmaking slag dust (steel slag), the peak of spectrum in the yellow to red range as seen in iron dust is not remarkable. Therefore, when all the reflected light with respect to white light is detected by an imaging means such as a camera, even iron-based dust particles and steel-making slag dust particles that are determined to have the same average brightness are less than 650 μm. If the reflected light is detected only for the light of the wavelength, the iron dust particles can be detected as relatively dark particles, and the steelmaking slag dust particles can be detected as relatively light particles. Can be determined. Hereinafter, a specific method for performing such determination will be described.

<Method using blue filter>
As a first example, as shown in FIG. 9, a blue filter 27 is arranged between the particles P as the analysis sample dispersed on the substrate 1 and the imaging system, and white light (for example, as the illumination unit 25). There is a method in which the reflected light from the particles P irradiated with the halogen lamp is imaged by the imaging means 21 such as a monochrome CCD camera after passing through the blue filter 27. At this time, as the blue filter 27, for example, a glass filter that almost completely blocks light having a wavelength of 550 μm or more is commercially available. Such a filter may be used.

<Method using blue LED>
As a second example, in the imaging system as shown in FIG. 7, a blue LED lamp is used as the illumination unit 25, and the particles P are directly irradiated with blue light, and the blue light is reflected from the particles P. There is a method of imaging light with imaging means 21 such as a monochrome CCD camera. At this time, what is necessary is just to use what is marketed as a blue LED lamp.

<Method using color CCD camera>
In principle, there may be a method of analyzing only the blue component using a color CCD camera. However, in commercially available color CCD cameras, different color filters are coated for each adjacent CCD element, and these filters are generally used for the purpose of discriminating between iron dust and steelmaking slag dust. It does not correspond to the wavelength range of the range to do. For this reason, even if it analyzes using the image of only B (blue) signal among the RGB outputs of a camera, it is difficult to discriminate between iron dust particles and steelmaking slag dust particles only by lightness There are many. In addition, in a color CCD camera, elements coated with the same filter are rarely adjacent to each other. Therefore, when performing an analysis focusing on only blue light, the spatial resolution during imaging of each particle is significantly reduced. It will be disadvantageous.

  The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to such examples. It is obvious that a person having ordinary knowledge in the technical field to which the present invention pertains can come up with various changes or modifications within the scope of the technical idea described in the claims. Of course, it is understood that these also belong to the technical scope of the present invention.

  Next, the present invention will be described more specifically with reference to examples.

(Creation of analysis sample)
First, iron ore, coal, blast furnace granulated slag and converter slag are prepared as standard samples with known soot species. It was spread on an aluminum plate using a stainless steel spatula so that the particles did not overlap each other. The expanded particle group was present in the range of about 10 mm in diameter.

  Next, a commercially available cylindrical electromagnet having a diameter of 10 mm is installed so that the central axis is in the vertical direction, and is supplied to the electromagnet so that the average magnetic flux density at the front end surface (lower end surface) of the magnet is 0.3T. The current was adjusted. In this state, the operator held the electromagnet by hand and lowered it vertically from above the particles dispersed on the aluminum substrate to bring the electromagnet into contact with the particles. After standing still in this state for 1 second, the electromagnet is lifted upward, the magnetized particles are moved together with the electromagnet, and the electromagnet is vertically aligned from above on a second aluminum plate treated with white anodized. Was lowered to place the electromagnet on the second aluminum plate. Next, after applying a degaussing current to the electromagnet, the supply of current to the electromagnet was stopped, and the electromagnet was lifted upward and separated from the second aluminum plate.

  The dimensions of the first aluminum plate and the second aluminum plate used were 30 mm × 30 mm in size and 3 mm in thickness. Moreover, as a demagnetizing method of the electromagnet, a commercially available electromagnet demagnetization controller was used.

  As a result of the above operation, the particles remaining on the first aluminum plate were used as samples of non-magnetizing dustfall, and the particles remaining on the second aluminum plate were used as samples of magnetism falling dust.

(Particle imaging)
Next, a commercially available trinocular stereomicroscope (objective lens magnification: 0.5 times), a commercially available ring light source (white light) in a lens barrel, a commercially available monochrome digital camera (CCD 6 million pixels, pixel dimensions are 3 [mu] m square) was mounted on the camera mounting opening. Next, a sample of magnetized fallen dust and a sample of non-magnetized fallen dust are placed on the stage of the microscope, and the illumination conditions are the same, and the camera aperture and exposure are taken in order under the same conditions. A dust image and a non-magnetized dust image were obtained.

  At this time, the magnification of the microscope was adjusted so that the actual size of the particle to be measured was imaged to the same size on the CCD element of the camera. In addition, the particles to be recognized with a microscope are particles with a size of φ10 μm or more because they are dust falling and the particles are coarse. In the present embodiment, the size of the particles corresponds to 9 pixels or more of the CCD.

(Image processing)
For the magnetized dust image and the non-magnetized dust image obtained as described above, commercially available particle image processing software IMAGRPRO PLUS VER. 5 was used for particle image processing measurement. At this time, the measurement target was the center position of each particle, the circle equivalent diameter of each particle, and the average brightness of each particle (the average value of the brightness of each pixel existing in the pixel region recognized as a particle).

  Specifically, using a predetermined lightness threshold value T1, a pixel region having a lightness less than the lightness threshold value T1 is specified as a region where particles are present, and each pixel existing in the pixel region is specified. Based on the position and brightness, the center position, average brightness, and circle equivalent diameter of each particle present in each of the magnetized dust image and the non-magnetized dust image were calculated, and the calculation results were recorded.

  Next, the average brightness of each particle calculated as described above is compared with a predetermined brightness threshold value T2 (> T1), and each particle in the image is classified into a dark color particle and a light color particle. did.

  Furthermore, using the circle equivalent diameter of each particle calculated as described above, each particle is classified according to a particle size category for which boundary values have been defined in advance, and the particle composition ratio for each particle size category is represented by a lightness category (dark color and light color). For each particle).

  The dust characteristics of the standard sample obtained by the above operation are as shown in Table 1 below.

Moreover, the example which calculated | required the particle | grain composition rate for every particle size division is shown below regarding the iron ore (magnetic dark particle) among the standard samples described in Table 1.
Iron ore: <φ30 μm: 20% <φ100 μm: 70% ≧ φ100 μm: 10%

(Analysis of collected dustfall)
Next, the dustfall was collected for one week with a commercially available deposit gauge in the blast furnace method steel plant site to obtain 100 mg of dustfall. After this dustfall was naturally dried indoors for 3 days, 500 µg of the total amount of dustfall was treated in the same manner as the standard sample described above to obtain dust characteristics of the dustfall particles. The results are shown in Table 2 below.

  Comparing the dust characteristics of the collected dust fall sample thus obtained with the dust characteristics of the standard sample shown in Table 1 above, the dust fall sample is mainly composed of magnetized dark particles. Therefore, the collected dustfall was identified as iron ore composed mainly of magnetized dark particles.

In addition, the particle composition rate for each particle size classification of the collected dust falling sample was as follows.
Falling dust: <φ30 μm: 50% <φ100 μm: 45% ≧ φ100 μm: 5%

  Looking at this result, the particle size distribution of the iron ore shown above is different, but from this result, the location where the falling dust sample, which is the sample in this example, was collected is Because it was far away from the storage yard, etc., it can be inferred that the large-diameter particles dropped halfway before reaching the collection site, and the composition ratio of the large-diameter particles decreased. .

DESCRIPTION OF SYMBOLS 1 (1st) board | substrate 2 2nd board | substrate 11 Magnet 13 Magnet holder 15 Spacer 17 Separation plate 21 Imaging means 23 Lens 25 Illumination means 27 Blue filter Pm Magnetization fallen dust Pn Non-magnetism fallen dust

Claims (6)

A method for identifying dust species of falling dust derived from a steelmaking plant by the blast furnace method,
A first step of separating the collected dust fallen into a magnetic fallen dust that is magnetized by applying a magnetic force and a non-magnetized fallen dust that is not magnetized;
Each of the magnetic fallen dust and the non-magnetic fallen dust separated in the first step is imaged, and a magnetized dust image that is an image of the magnetic fallen dust and an image of the non-magnetic fallen dust A second step of generating a non-magnetizing dust image,
By performing image processing on each of the magnetized dust image and the non-magnetized dust image, the individual magnetized dust particles present in the magnetized dust image and the individual particles present in the non-magnetized dust image The non-magnetizing dustfall is classified into light particles and dark particles using a predetermined brightness threshold, and the collected dust dust is separated into magnetism and brightness using the classification result. A third step of classifying the magnetic dark particles, the magnetic bright particles, the non-magnetic dark particles, and the non-magnetic bright particles according to the dust characteristics defined by the combination of: ,
A fourth step of identifying the dust type of the falling dust based on the classification result in the third step and the dust characteristic of the standard sample whose dust type is known;
A method for identifying a dust species of falling dust, characterized by comprising:   2. The method for identifying the dust type of the falling dust according to claim 1, wherein a magnetic flux density when applying a magnetic force to the falling dust in the first step is 0.1 T or more and 0.4 T or less. .   3. The method for identifying the dust type of the falling dust according to claim 1, wherein a particle size of each of the falling dust is measured in the third step.   The soot species are mainly iron-based soot derived from iron ore, coal-based soot mainly derived from coal, blast-furnace slag-based dust mainly derived from blast furnace slag, and steel-making slag-based dust mainly derived from steelmaking slag. The method for identifying a dust species of falling dust according to any one of claims 1 to 3, wherein the method is a combination of at least two selected from the group consisting of: When the dust type includes at least the iron dust and the steelmaking slag dust,
In the second step, by irradiating each particle of the magnetic fallen dust with white light and transmitting reflected light from the particle with respect to the white light through a blue filter, and then imaging with a monochrome camera Generate the magnetized dust image,
In the fourth step, particles whose brightness on the magnetized dust image is a predetermined value or more are identified as the steelmaking slag dust, and particles other than the steelmaking slag dust are identified as the iron dust. The method for identifying a dust type of falling dust according to claim 4, wherein: When the dust type includes at least the iron dust and the steelmaking slag dust,
In the second step, each particle of the magnetism falling dust is irradiated with blue light using a blue LED, and reflected light from the particle with respect to the blue light is imaged using a monochrome camera, whereby the attachment is performed. Generate magnetic dust image,
In the fourth step, particles whose brightness on the magnetized dust image is a predetermined value or more are identified as the steelmaking slag dust, and particles other than the steelmaking slag dust are identified as the iron dust. The method for identifying a dust type of falling dust according to claim 4, wherein:

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