JP6848940B2 - Prediction method and wet classification method of wet classification characteristics of valuable component-containing dust - Google Patents

Description

The present invention relates to a wet classification method, and particularly relates to separation / recovery of valuable components such as zinc from dust generated in a steelmaking process using a blast furnace, a converter, or the like.

Dust is generated in steelmaking processes such as blast furnaces and converters. Since these dusts contain iron and carbon, it is desirable to recycle them and use them again as a sintering raw material in the steelmaking process. However, these dusts contain zinc (Zn). In addition to zinc, these dusts also contain a small amount of lead (Pb), sodium (Na), calcium (Ca) and the like. Therefore, for example, when the content of zinc in the dust increases, zinc and its compounds adhere to the wall surface of the equipment in each steelmaking process, which causes a problem in operation. Furthermore, in recent years, the use of recycled scrap and the like has increased, and the concentration of zinc in the generated dust tends to increase, and the recycling (reuse) of dust is restricted by the concentration of zinc and the like. There is.

Therefore, it is important to remove (dezinc) zinc from these dusts. In addition, a component such as zinc contained in dust is a useful component (valuable component) having utility value if it can be separated and recovered with high purity.

Dust generated in the steelmaking process of blast furnaces and converters is usually collected by scrubbers and the like arranged as ancillary equipment such as blast furnaces and converters. The recovered dust is in the form of a slurry, and these slurry-like dusts (hereinafter, also referred to as dust slurries) are usually treated by various methods, one of which is a classification treatment by a wet classifier. ..

Taking zinc as an example, zinc volatilized during the steelmaking process, when oxidized in air to zinc oxide, generally becomes very fine particles of several μm. Therefore, zinc particles (zinc oxide particles) are often unevenly distributed and concentrated on the fine particle side in dust. Taking advantage of this, dust slurries such as blast furnace dust are classified by a wet separation device to separate slurries having a high zinc content on the fine grain side and slurries having a low zinc content on the coarse grain side.

For example, Patent Document 1 describes "a method for treating secondary ash from a blast furnace". According to the technique described in Patent Document 1, when the blast furnace secondary ash slurry is separated into high zinc-containing dust and high Fe-containing dust by using a variable classification ability type classifier and a dehydrator, the classification ability operation of the classifier is performed in advance. The correlation between the secondary ash load and the secondary ash solid content distribution rate and the secondary ash solid content distribution rate and the de-Zn rate according to the manipulated amount of the factor is obtained, and then the secondary ash load or the classifier Based on the result of detecting the secondary ash solid content distribution rate continuously or at predetermined intervals, the charged Zn amount of all the blast furnace charges when the high Fe-containing dust is charged into the blast furnace is set in advance. This is a method for treating secondary blast furnace ash, in which the classification ability of the classifier is controlled so as to be equal to or close to the Zn target value. In the technique described in Patent Document 1, a variable classification ability type classifier is used to de-Zn the minimum value necessary for maintaining the Zn target value charged into the blast furnace, and the blast furnace condition is maintained in a good state. However, it is said that the recovery rate of Fe and C can be maximized.

Further, Patent Document 2 describes "a method for treating blast furnace dust". The technique described in Patent Document 2 adds a dispersant to slurry-like blast furnace dust, and then ultrasonically irradiates the slurry to lead to a wet cyclone using negative pressure while dispersing the dust particles contained in the slurry. This is a method for treating blast furnace dust, which separates a slurry having a high zinc content and a slurry having a low zinc content. In the technique described in Patent Document 2, pseudo-granular dust particles are irradiated with ultrasonic waves to disperse the pseudo-granular dust particles in fine coke, fine ore, Zn or Zn compound particles, respectively. It is said that it will lead to wet cyclones.

Further, Patent Document 3 proposes a "dust treatment method". In the technique described in Patent Document 3, dust with Zn adhered is continuously charged into a rotary drum, fed in the direction of the central axis of the rotary drum, and dust continuously discharged from the rotary drum is discharged by a wet cyclone. This is a dust treatment method that performs continuous classification treatment. This rotating drum is a rotating drum that turns its central axis sideways, rotates around the central axis, and reciprocates in two directions that are orthogonal to the central axis and orthogonal to each other. By throwing the dust with Zn attached into this rotating drum, the dust particles collide violently with each other, and even if it is fine dust, the Zn particles are separated from the particle surface, and sufficient Zn can be removed from the dust. It is said that it can be done.

Further, Patent Document 4 proposes a "method for dezincifying blast furnace dust". The technique described in Patent Document 4 injects high-pressure water into the container from one end of the container and takes in air to generate a two-fluid injection flow of water and air in the container, and the slurry is added to the two-fluid injection flow. The blast furnace dust in the form of a blast furnace dust is added, and the portion having a high zinc content adhering to the blast furnace dust particles is peeled off from the particles by the stirring force of the two-fluid jet flow, and then introduced into a wet cyclone to obtain the zinc content. This is a dezincification method for blast furnace dust that separates a high particle group and a low zinc content particle group. This method is inexpensive because it uses simple equipment and can achieve a high dezincination rate. Therefore, blast furnace dust that has been dezincinated and has a low zinc content can be reused as a raw material for blast furnaces.

Further, Patent Document 5 proposes a "zinc-containing slurry treatment method". In the technique described in Patent Document 5, a slurry containing zinc-containing dust generated in the iron-making process is introduced into a slurry processing apparatus provided with at least two stages of wet cyclones having different classification performance in series, and the wet cyclone in the previous stage is used. Separated into pre-stage overflow and pre-stage underflow, and further separated the pre-stage underflow into post-stage overflow and post-stage underflow with a post-stage wet cyclone, and merged with pre-stage overflow and post-stage overflow to form a high-concentration zinc-containing slurry. This is a zinc-containing slurry treatment method in which the subsequent underflow is a low-concentration zinc-containing slurry. According to this method, the solid phase content on the high zinc side to be separated can be efficiently reduced, and zinc in zinc-containing dust, which was conventionally disposed of without being reused, is recovered and reused as zinc oxide. It is said that it can be used.

Further, Patent Document 6 describes "a method for treating zinc-containing dust". The technique described in Patent Document 6 is to produce a slurry by mixing zinc-containing dust generated from a reduction furnace that reduces a reducing metal oxide containing zinc with water, and zinc is produced from the slurry by a wet separation device. This is a method for treating zinc-containing dust, which separates a slurry of concentrated powder and a slurry of powder containing less zinc. Note that Patent Document 6 exemplifies a hydrocyclone as a wet separation device capable of separating powders by utilizing the difference in particle size and specific gravity of powders in a slurry.

Further, Patent Document 7 proposes "a method for reusing wet dust in blast furnace products". In the technique described in Patent Document 7, the wet dust collected when the exhaust gas generated from the blast furnace for iron making is wet-collected is made into a slurry, and the wet dust collected in the slurry is wet magnetically sorted. After dividing into "part a that uses iron for the purpose" and "part b that uses carbon and zinc for the purpose", the first wet cyclone treatment is applied to "part b that uses carbon and zinc for the purpose". Then, the lower discharge of the first wet cyclone treatment obtained was further subjected to the second wet cyclone treatment, and the upper discharge of the first wet cyclone treatment and the second wet cyclone treatment were performed. Combined with the upper discharge of the above, it is referred to as "part c that uses zinc for the purpose", and further, the discharge under the second wet cyclone treatment is designated as "part d that uses carbon for the purpose", and the blast furnace generated wet dust is used. Wet dust in blast furnace products that is separated and reused in three parts: "part a that uses iron for the purpose", "part c that uses zinc for the purpose", and "part d that uses carbon for the purpose". It is a reuse method. As a result, the effective use of blast furnace wet dust will increase.

Further, Non-Patent Document 1, a model of four basic relational expression can be estimated accurately the performance of hydrocyclones such 50% classification particle size d ₅₀ is proposed.

Japanese Unexamined Patent Publication No. 53-81406 Japanese Unexamined Patent Publication No. 53-81479 Japanese Patent Application Laid-Open No. 05-132724 Japanese Unexamined Patent Publication No. 10-317018 Japanese Unexamined Patent Publication No. 2004-12024 Japanese Patent Application Laid-Open No. 2005-21841 Japanese Unexamined Patent Publication No. 2013-23719

Plitt, L. R .: A mathematical model of the hydrocyclone classifier, CIM Bulletin (1976), pp.114-123.

In each of the techniques described in Patent Documents 1 to 7, zinc-containing dust slurry is classified using a wet classifier (wet cyclone), and a slurry consisting of a particle group having a high zinc concentration and a zinc content is low. This is a technique for separating into a slurry consisting of a group of particles having a low zinc concentration. According to these techniques, if the dust slurry is classified to a certain particle size, zinc can be dezincinated from the dust in the form of concentrated zinc on the fine-grained side dust. However, in these techniques, the classification characteristics such as the dezincification ratio from the dust slurry are obtained only from the test results using the actual machine (wet classification device), and moreover, the processing using the actual machine requires considerable time and effort. In addition to the high cost, there is a problem that many test levels cannot be taken to confirm the classification characteristics before the introduction of the actual machine (wet classification device).

Further, in Patent Documents 1 to 7 described above, whether the wet classification device used can exhibit a predetermined classification performance, or by further optimizing the operation, the classification performance is finally improved to what extent. There is no mention of operational management of wet classification equipment, such as whether it can be expected. Further, in Patent Documents 1 to 7 described above, grasping and determining the classification status of wet classification, such as whether the wet classification method using the wet classification device is the optimum wet classification that can obtain a predetermined classification characteristic. There is no mention of.

In view of the problems of the prior art, the present invention relates to the separation rate of the valuable component from the dust slurry containing a valuable component such as zinc and the abundance ratio of the solid content on the high valuable component-containing side at that time without performing the actual machine treatment. An object of the present invention is to provide a simple method for predicting the wet classification characteristics of a dust slurry containing a valuable component.

Another object of the present invention is to provide a wet classification method for grasping and managing the operating status of the wet classification device and evaluating the wet classification state.

In order to achieve the above object, the present inventors wet-classify dust (dust slurry) containing zinc as a valuable component, separate and recover the valuable component (zinc), and perform valuable component-containing dust. When removing valuable components (zinc) from the slurry, the dezincification rate (devaluation component rate) and the high zinc-containing side solid content recovery ratio (high valuable component-containing side solid content abundance ratio) without classification by the actual machine. ) Was enthusiastically examined.

As a result, first, a certain amount of sample slurry was collected from the target valuable component (zinc) -containing dust slurry, fractionated into a plurality of fractions for each constant particle size, and particles were fractionated for each obtained fraction. I came up with the idea of analyzing the diameter distribution, solid content, and valuable component (zinc) concentration. Then, by multiplying the particle size distribution and the solid content amount for each of the obtained fractions, as shown in FIG. 2A, the distribution of the solid content abundance ratio for each fraction to the entire dust can be obtained. become. Then, by summing the distribution of the solid content abundance ratio for each fraction, the particle size and the solid content in the entire target dust slurry are shown as "total" (dotted line) in FIG. 2 (a). The relationship with the abundance ratio (solid content abundance ratio distribution) can be estimated. It has been confirmed that the relationship between the particle size and the abundance ratio of the solid content (total: dotted line) is almost the same as the particle size distribution of the original dust slurry.

Furthermore, by multiplying the particle size distribution obtained for each fraction and the concentration of the valuable component (zinc), as shown in FIG. 2 (b), the particle size of each fraction with respect to the entire zinc in the dust. It will be possible to estimate the distribution of the abundance ratio of the valuable component (zinc) to. In addition, by summing up the valuable component (zinc) abundance ratio distribution for each fraction, as shown as "total" (dotted line) in FIG. 2 (b), the particle size in the entire target dust slurry The relationship with the abundance ratio of the valuable component (zinc) can be estimated.

Then, as shown in FIGS. 3 (a) and 3 (b), the relationship between the estimated particle size and the abundance ratio of the solid content and the relationship between the particle size and the abundance ratio of the valuable component (zinc) are shown in FIGS. 3 (a) and 3 (b), respectively. In addition, rewrite to "cumulative display" (cumulative distribution) that displays the accumulation from fine particle size, and the relationship between the particle size and the accumulation of the abundance ratio of solids, and the accumulation of the abundance ratio of the particle size and the valuable component (zinc). The relationship is as follows. By superimposing FIGS. 3 (a) and 3 (b) and comparing these relationships with the classification ability of the wet classifier (vertical line in FIG. 4) as shown in FIG. 4, classification is performed on the fine grain side. The solid content abundance ratio (30% in Fig. 4) and the valuable component (zinc) abundance ratio classified on the fine grain side (65% in Fig. 4) can be estimated, and the reachable classification characteristics can be predicted to some extent. I came up with the idea that I can do it.

The "presence ratio of valuable component (zinc) classified on the fine grain side" here is the "presence ratio of valuable component (zinc) on the slurry side (fine grain side) where the valuable component is concentrated". From the viewpoint of discarding (recovering) the slurry classified on the fine-grained side, it means the "devaluation component ratio", that is, the "dezincification ratio". Further, the "solid content abundance ratio classified on the fine grain side" is the "solid content abundance ratio on the high valuable component content side", that is, the "solid content abundance ratio on the high zinc content side".

Therefore, according to the above method, the "devaluation component ratio (dezincification rate)" and the "high value component-containing side solid content abundance ratio" from the valuable component-containing dust slurry (de-zincification rate) without performing an actual machine test ( It was found that the high zinc content side solid content abundance ratio) can be predicted.

Furthermore, as described above, the present inventors have obtained the relationship between the particle size and the accumulation of the solid content abundance and the particle size and the accumulation of the valuable component (zinc) abundance for the specific valuable component-containing dust slurry. In relation to the above, the devaluation component ratio (dezincification rate) from the valuable component-containing dust slurry and the high value component-containing side solid content abundance ratio (high zinc-containing side solids) are determined according to the performance (classification point) of the wet classification device. I came up with the idea that it is possible to find the relationship with (minus size ratio). Then, this relationship can be used as a classification characteristic curve of the target valuable component-containing dust slurry, as a means for operating management of the wet classification device, and further as a means for determining the classification status of the wet classification method. It was newly discovered that.

The present invention has been completed with further studies based on such findings. That is, the gist of the present invention is as follows.
(1) A valuable component-containing dust slurry containing valuable component-containing dust is wet-classified by a wet classifier to separate a slurry in which the valuable component is concentrated and a slurry in which the valuable component is low, and the valuable component is separated from the valuable component-containing dust slurry. Before removing the
A first step of collecting a predetermined amount of sample dust slurry from the valuable component-containing dust slurry and fractionating the collected sample dust slurry into a plurality of fractions at a constant particle size.
A second step of analyzing the particle size distribution, solid content ratio, and valuable component concentration for each of the plurality of fractions.
From the analyzed particle size distribution, the analyzed solid content ratio, and the analyzed valuable component concentration, the relationship between the particle size and the abundance ratio of the valuable component and the particle size over the entire dust area. The relationship between the solid content ratio and the calculated particle size and the abundance ratio of the valuable component is calculated, and from the relationship between the calculated particle size and the solid content abundance ratio, the particle size and the valuable component The third step of calculating the relationship with the cumulative abundance ratio and the relationship between the particle size and the cumulative abundance ratio of solids, and
From the relationship between the calculated particle size and the cumulative abundance ratio of the valuable component, the relationship between the particle size and the cumulative abundance ratio of the solid content, and the classification ability of the wet classifier, the slurry side where the valuable component is concentrated The fourth step of calculating the abundance ratio of the valuable component and the abundance ratio of the solid content in
Sequentially
The abundance ratio of the valuable component and the abundance ratio of the solid content on the slurry side in which the valuable component is concentrated, the devaluation component ratio from the dust slurry containing the valuable component, and the solid content abundance ratio on the high valuable component-containing side A method for predicting the wet classification characteristic of a dust slurry containing a valuable component, which comprises predicting the wet classification characteristic of the dust slurry containing the valuable component.
(2) The method for predicting the wet classification characteristics of a valuable component-containing dust slurry according to (1), wherein the wet classification device is a wet cyclone.
(3) The method for predicting the wet classification characteristics of a valuable component-containing dust slurry according to (1) or (2), wherein the valuable component-containing dust is zinc-containing dust.
(4) The method for predicting the wet classification characteristics of a valuable component-containing dust slurry according to (3), wherein the zinc-containing dust is any one of blast furnace dust, converter dust, and electric furnace dust.
(5) A wet classification method in which a valuable component-containing dust slurry containing valuable component-containing dust is wet-classified by a wet classification device, and the slurry is separated into a slurry in which the valuable component is concentrated and a slurry in which the valuable component is low.
For each of the target valuable component-containing dust slurries, a predetermined amount of sample dust slurry is collected in advance from the valuable component-containing dust slurry, and the collected sample dust slurry is divided into a plurality of fractions for each fixed particle size. The first step of fractionation and
The second step of analyzing the particle size distribution, the solid content ratio, and the concentration of valuable components for each of the plurality of fractions.
From the analyzed particle size distribution, solid content abundance ratio, and valuable component concentration, the relationship between the particle size and the valuable component abundance ratio and the relationship between the particle size and the solid content abundance ratio over the entire dust area are calculated and calculated. From the relationship between the particle size and the abundance ratio of the valuable component and the relationship between the particle size and the abundance ratio of the solid content, the relationship between the particle size and the cumulative abundance ratio of the valuable component and the cumulative particle size and the abundance ratio of the solid content The third step to calculate the relationship and
From the above-mentioned relationship between the particle size and the accumulation of the abundance ratio of valuable components and the relationship between the particle size and the accumulation of the abundance ratio of the solid content over the entire dust, it is obtained after the classification according to the classification ability of the wet classifier. The abundance ratio of the valuable component and the abundance ratio of the solid content with respect to the entire dust slurry on the slurry side where the valuable component was concentrated were obtained.
The abundance ratio of the valuable component to the entire dust slurry on the slurry side where the obtained valuable component is concentrated is defined as the devaluation component ratio, and the solid content with respect to the entire dust slurry on the slurry side where the obtained valuable component is concentrated. The fourth step of calculating the relationship curve between the devalued component ratio and the high valuable component-containing side solid content abundance ratio, with the abundance ratio of
Was sequentially carried out to obtain the calculated relationship curve between the devalued component ratio and the high valuable component-containing side solid content abundance ratio as the wet classification characteristic curve of the target valuable component-containing dust slurry.
At any time in the wet classification, the valuable component concentration and the solid content of the wet-classified slurry in which the valuable component is concentrated and the slurry in which the valuable component is low are analyzed, and the dust slurry in the slurry in which the valuable component is concentrated is analyzed. The abundance ratio of the valuable component and the abundance ratio of the solid content are calculated, and the devaluation component ratio in the slurry in which the valuable component is concentrated and the solid content abundance ratio on the high valuable component-containing side are calculated as the target valuable component-containing dust slurry. A wet classification method, characterized in that the classification status of the wet classification is determined by comparing with the wet classification characteristic curve.
(6) The wet classification method according to (5), wherein the wet classification device is a wet cyclone.
(7) The wet classification method according to (5) or (6), wherein the valuable component-containing dust is zinc-containing dust.
(8) The wet classification method according to (7), wherein the zinc-containing dust is any one of blast furnace dust, converter dust, and electric furnace dust.
(9) In operating a wet classification device for wet-classifying a valuable component-containing dust slurry containing valuable component-containing dust and separating the slurry in which the valuable component is concentrated and the slurry in which the valuable component is low.
For each of the target valuable component-containing dust slurries, a predetermined amount of sample dust slurry is collected in advance from the valuable component-containing dust slurry, and the collected sample dust slurry is divided into a plurality of fractions for each fixed particle size. The first step of fractionation and
The second step of analyzing the particle size distribution, the solid content ratio, and the concentration of valuable components for each of the plurality of fractions.
From the analyzed particle size distribution, solid content abundance ratio, and valuable component concentration, the relationship between the particle size and the valuable component abundance ratio and the relationship between the particle size and the solid content abundance ratio over the entire dust area are calculated and calculated. From the relationship between the particle size and the abundance ratio of the valuable component and the relationship between the particle size and the abundance ratio of the solid content, the relationship between the particle size and the cumulative abundance ratio of the valuable component and the cumulative particle size and the abundance ratio of the solid content The third step to calculate the relationship and
From the above-mentioned relationship between the particle size and the accumulation of the abundance ratio of valuable components and the relationship between the particle size and the accumulation of the abundance ratio of the solid content over the entire dust, it is obtained after the classification according to the classification ability of the wet classifier. Obtain the abundance ratio of the valuable component and the abundance ratio of the solid content in the entire dust slurry on the slurry side where the valuable component is concentrated, respectively.
The abundance ratio of the valuable component to the entire dust slurry on the slurry side where the obtained valuable component is concentrated is defined as the devaluation component ratio, and the solid content with respect to the entire dust slurry on the slurry side where the obtained valuable component is concentrated. The fourth step of calculating the relationship curve between the devalued component ratio and the high valuable component-containing side solid content abundance ratio, with the abundance ratio of
Was sequentially carried out to obtain the calculated relationship curve between the devalued component ratio and the high valuable component-containing side solid content abundance ratio as the wet classification characteristic curve of the target valuable component-containing dust slurry.
During the operation of the wet classifier, the valuable component concentration and the solid content of the wet-classified slurry in which the valuable component is concentrated and the slurry in which the valuable component is low are analyzed, and the value of the slurry in which the valuable component is concentrated is relative to the entire dust slurry. The abundance ratio of the component and the abundance ratio of the solid content are calculated, and the devalued component ratio and the solid content abundance ratio on the high valuable component-containing side in the slurry in which the valuable component is concentrated are determined as the wet type of the target valuable component-containing dust slurry. A method for managing the operation of a wet classifying device, which comprises determining the operating state of the wet classifying device in comparison with a classification characteristic curve.
(10) The operation management method of the wet classification device according to (9), wherein the wet classification device is a wet cyclone.
(11) The operation management method of a wet classification device according to (9) or (10), wherein the valuable component-containing dust is zinc-containing dust.
(12) The operation management method of a wet classification apparatus according to (11), wherein the zinc-containing dust is any one of blast furnace dust, converter dust, and electric furnace dust.

According to the present invention, when separating and recovering a valuable component from a dust slurry containing a valuable component, the performance of the wet classifying device to be used can be easily adjusted without performing a complicated test using an actual machine (wet classifying device). , The ratio of valuable components that can be recovered from the dust (the ratio of valuable components that can be recovered from the dust) can be predicted, and based on this prediction, the operating state of the wet classification device and the classification status at the time of wet classification in the wet classification It has a remarkable effect in the industry that it can judge appropriately. Further, according to the present invention, when introducing an actual machine (wet classification device), it is necessary to secure a desired valuable component separation / recovery ratio (devaluation component ratio) from the valuable component-containing dust, which is necessary for the actual machine (wet classification). There is also the effect that the performance of the device) can be determined to some extent.

It is explanatory drawing which shows the flow of this invention. (A) A graph showing the relationship between the particle size and the solid content abundance ratio for each fraction and the relationship between the particle size of the entire dust and the solid content abundance ratio, which is the sum of each fraction, and (b) for each fraction. It is a graph which shows the relationship between the particle size and the zinc abundance ratio, and the relationship between the particle size of the whole zinc in dust and the zinc abundance ratio which summed each fraction. (A) A graph showing the relationship between the particle size and the solid content abundance ratio of the entire dust and the relationship between the particle size and the cumulative solid content ratio, (b) The relationship between the particle size and the zinc abundance ratio of the entire zinc in the dust. It is a graph which shows the relationship between the particle size and the accumulation of zinc abundance ratio. It is a graph which shows the relationship between the particle size and the zinc abundance ratio, the particle size and the solid content abundance ratio, and the relationship between the particle size and the solid content abundance ratio, and the zinc abundance ratio accumulation of the whole dust. It is a graph which shows the relationship (wet classification characteristic curve of a valuable component-containing dust slurry) between the dezincification rate after the wet classification of a valuable component-containing dust slurry and the abundance ratio of the solid content on the high zinc-containing side. It is explanatory drawing which explains typically the fraction in an Example. It is a graph which shows the solid content abundance ratio distribution of each fraction in an Example, and the solid content abundance ratio distribution in the whole dust. It is a graph which shows the zinc abundance ratio distribution of each fraction in an Example, and the zinc abundance ratio distribution in the whole dust. It is a graph which shows the relationship between the solid content abundance ratio distribution and zinc abundance ratio distribution with respect to the particle diameter in the whole dust in the Example, and the relationship between the solid content abundance ratio accumulation and zinc abundance ratio accumulation with respect to a particle size. It is a graph which shows the wet classification characteristic curve of the dust slurry used in an Example, and the result of the wet classification test by an actual machine.

The present invention is used to remove valuable components such as zinc by wet classification from dust discharged in the iron-making process of a blast furnace, converter, etc., that is, a slurry of dust containing valuable components (dust slurry). It is possible to easily predict the removal rate of valuable components from the dust slurry, that is, the devaluation component rate from the dust slurry, etc., without going through a complicated test using an actual machine (wet classification device) or the like. This is a method for predicting the wet classification characteristics of a dust slurry containing a valuable component.

The flow of the prediction method of the present invention is shown in FIG.
First, the dust slurry (dust slurry) discharged from the steelmaking process of the steelworks is used as a raw material. The dust discharged from the steelmaking process of a steel mill is valuable component-containing dust containing a valuable component such as zinc. The dust slurry can be applied even if it is not derived from a steel mill, as long as it is a slurry containing dust containing a valuable component such as zinc.

First, as the first step, a step of fractionating the dust slurry is performed.
In this first step, an amount required for the fractionation step is collected from the target dust slurry and used as a sample dust slurry. The collected sample dust slurry is fractionated into a plurality of fractions at a constant particle size. The fractionation depends on the particle size distribution of the dust slurry as a raw material, but it is preferable to fractionate each particle size in about 3 to 10 steps. It goes without saying that the method of dividing the fractions (how to divide the particle size) becomes more complicated if it is divided too finely, and the accuracy decreases if the number of fractions is small. Sieves, filter papers, and the like can be used for fractionation, and it is preferable to combine various sieves, filter papers, and the like to fractionate a predetermined plurality of fractions.

When the dust slurry is dried to form a powder or granular material, fractionation becomes easy and it becomes possible to fractionate to a considerably fine grain side. However, when dried, many dusts are associated with each other to form large particles, which are then required to be pulverized, which is different from the state (particle size distribution) of the original slurry. Therefore, the fractionation is performed in the slurry state.

Further, it is desirable that the amount of dust (dust slurry amount) used for fractionation is a predetermined amount as small as possible within the range in which analysis is possible. When a large amount of dust (dust slurry) is processed, there is a risk that accurate sieving and filtration may not be possible due to dust remaining on the sieve or filter paper. Therefore, the treatment amount is preferably determined in consideration of the filtration area.

When hydrophobic particles such as carbon particles are contained, it is preferable to use alcohol or the like as the diluting solvent. As a result, dispersion progresses, and improvement in accuracy can be expected. Further, before the treatment with each sieve or filter paper, it is preferable to disperse the treatment with ultrasonic waves or the like. As a result, further improvement in accuracy can be expected.

Next, as a second step, analysis is performed on each fraction.
In this second step, the particle size distribution, solid content, and valuable component (zinc) concentration are analyzed for each fraction. Since the particle size distribution analysis is performed as a slurry without drying, the sample is collected as a slurry. On the other hand, in the analysis of the solid content amount and the valuable component (zinc) concentration, a dry sample is required because the measurement is performed after drying. In this case, the sample collected in the slurry state may be accurately divided, a part thereof may be used as it is as a sample for particle size distribution analysis, and a part may be dried as a sample for analysis of solid content and valuable component (zinc) concentration. .. Alternatively, the same fractionation step may be performed twice to obtain a sample for particle size distribution analysis (slurry sample) and a sample for analysis of solid content and valuable component (zinc) concentration.

Any of the usual particle size distribution measuring methods can be applied to the measurement of the particle size distribution, but among them, the laser diffraction / scattering method is preferably used.

Further, the solid content of the fraction is determined by measuring the dry weight of each fraction and calculating the ratio to the total amount of the obtained fractions to obtain the solid content abundance ratio of the fraction.

The valuable component (zinc) concentration (% by mass) of the fraction was measured from the dried sample using the usual atomic absorption spectroscopy or ICP emission spectroscopy, and the ratio to the total amount of each fraction ( The abundance ratio) is calculated and used as the valuable component abundance ratio (%) of the fraction. Needless to say, the valuable component (zinc) concentration (% by mass) is not limited to the above method.

Next, in the present invention, the third step is performed following the second step.
In the third step, a step of calculating the relationship between the particle size and the solid content abundance ratio and the relationship between the particle size and the abundance ratio of the valuable component (zinc) over the entire dust area is performed.

First, from the particle size distribution and solid content abundance ratio in each fraction obtained in the second step described above, the relationship between the particle size and solid content abundance ratio in each fraction, and the particle size in each fraction. The relationship between and the abundance ratio of the valuable component (zinc) is calculated respectively.

First, by multiplying the particle size distribution of each fraction measured in the second step by the solid content abundance ratio of each fraction measured in the second step, as shown in FIG. 2A, each The solid content abundance ratio distribution of the fraction can be obtained. In FIG. 2, the fractionation is divided into five stages, but it goes without saying that the fractionation is not limited to that. In addition, FIG. 2A also shows the total of the solid content abundance ratio distribution of each fraction. Further, by multiplying the particle size distribution of each fraction measured in the second step described by the valuable component (zinc) concentration of each fraction measured in the second step, it is shown in FIG. 2 (b). Such a valuable component abundance ratio distribution of each fraction can be obtained. Note that FIG. 2B also shows the total distribution of the abundance ratio of valuable components in each fraction.

As shown in FIG. 2A, the particles on the finest grain side have a small solid content, so the peak of the solid content abundance ratio is small, but the valuable component (zinc) particles are unevenly distributed on the fine grain side. It is concentrated and has a high concentration of valuable components (zinc) on the fine particle side. Therefore, as shown in FIG. 2B, the abundance ratio of the valuable component (zinc) has a very large peak on the finest grain side. On the other hand, in the fraction having a particle size near the center, although a large amount of solid content is present, the concentration of the valuable component (zinc) is low, so that the abundance ratio of the valuable component (zinc) is small.

Further, in the third step, the solid content abundance ratio distribution and the valuable component (zinc) abundance ratio distribution of each obtained fraction are totaled for each particle size, and the entire dust as shown in FIG. 3A is obtained. The relationship between the particle size and the solid content abundance ratio over the entire range and the relationship between the particle size over the entire valuable component in the dust and the valuable component (zinc) abundance ratio as shown in FIG. 3 (b) are calculated.

Then, in the third step, the relationship between the obtained particle size and the solid content abundance ratio is changed from the frequency distribution display to the cumulative distribution display, and is accumulated from the fine particle size as shown in FIG. 3 (a). The relationship between the particle size and the cumulative solid content ratio is calculated. Similarly, from the relationship between the particle size and the valuable component (zinc) abundance ratio, the relationship between the particle size and the cumulative value component (zinc) abundance ratio is calculated as shown in FIG. 3 (b). If a specific particle size is selected by displaying such a cumulative distribution, from this relationship, which of the solid content and the valuable component (zinc) are on the fine grain side and the coarse grain side at the specific particle size? It will be easy to calculate how it will be distributed.

Then, in the present invention, the fourth step is performed.
In the fourth step, the abundance ratio of the valuable component and the abundance ratio of the solid content on the slurry side where the valuable component is concentrated, which is obtained when the target dust slurry is classified by a predetermined wet classification device, are calculated.

The relationship between the particle size and the cumulative abundance ratio of the solid content obtained in the third step, the relationship between the particle size and the cumulative abundance ratio of the valuable component (zinc), and the classification ability (classification particle size) of the predetermined wet classification device. From, and, the cumulative abundance ratio of solid content and the cumulative abundance ratio of valuable components at a particle size equal to or less than the classified particle size are calculated. The relationship between the particle size and the cumulative abundance ratio of solids and the relationship between the cumulative abundance ratio of valuable components are shown in FIG. 4 again.

Since the valuable component (zinc) is unevenly distributed on the fine grain side, if the dust slurry is classified to a certain particle size, the valuable component (zinc) can be taken out in a concentrated form on the fine grain side dust slurry. .. If the dust slurry is wet-classified with a wet classifier having a particle size shown by a vertical line in FIG. 4, that is, a classifying particle size, about 30% of the solid content is distributed to the fine grain side, and at that time, the valuable component (zinc) is released. About 65% will be distributed to the fine grain side. If the dust slurry on the fine grain side is recovered, the valuable component (zinc) can be removed to some extent (devalued component (zinc)) in the dust slurry on the coarse grain side.

Therefore, for example, with respect to the target valuable component-containing dust slurry as shown in FIG. 4, the target dust slurry is fractionated in advance as in the present invention, and detailed analysis is performed to determine the particle size. If the relationship between the cumulative abundance ratio of solids and the cumulative particle size and the cumulative abundance of valuable components is obtained, a predetermined wet classification is performed based on these relationships and the classification ability (classification particle size) of the wet classifier. The abundance ratio of the valuable component (zinc) contained in the dust slurry on the fine grain side and the solid content abundance ratio (solid content on the high zinc content side) contained in the dust slurry on the fine grain side obtained when the dust slurry is classified by the apparatus. Recovery ratio) and can be easily calculated.

By analyzing and analyzing the target valuable component (zinc) -containing dust slurry in detail in this way, the removal rate of the valuable component from the dust slurry, that is, can be easily obtained without performing a complicated test. It is possible to predict the devaluation component ratio (dezincification rate). According to the present invention, the valuable component abundance ratio concentrated on the fine-grained dust slurry side, which is obtained by wet-classifying the target valuable component-containing dust slurry, that is, the devalued component ratio (dezincification rate) and the fine-grained dust. The slurry-side solid content abundance ratio (high zinc-containing side solid content recovery ratio), that is, the wet classification characteristics can be predicted to some extent.

The classification ability (classification point) of the wet classification device is determined by the shape of the cyclone, operating conditions, etc., and the classification point is usually specified as a specification. Regarding the classification ability (classification point) of the wet cyclone, the Platt formula described in Non-Patent Document 1 and the classification particle size estimation formula described in Patent Document 7 have been proposed as relatively accurate formulas. There is.

Further, in the present invention, it is possible to grasp and judge the classification status at the time of wet classification in the wet classification method, and it is also possible to manage the operating state of the wet classification device in operation.

In the wet classification method of the present invention, the first step to the fourth step are performed in advance to obtain a wet classification characteristic curve of the target valuable component-containing dust slurry.

Similar to the above-mentioned first to fourth steps, the first to fourth steps are performed, and the abundance ratio of the valuable component in the obtained fine-grained side dust slurry is set as the devalued component ratio on the vertical axis. In addition, the solid content abundance ratio in the fine-grained side dust slurry is taken as the high valuable component-containing side solid content abundance ratio on the horizontal axis, and the devaluation component ratio and the high valuable component-containing side solid content abundance ratio are as shown in FIG. The relationship is as follows. In the present invention, this relationship is referred to as a "wet classification characteristic curve of the target valuable component-containing dust slurry".

The "wet classification characteristic curve of the target valuable component-containing dust slurry" obtained through the above-mentioned first to fourth steps can be roughly wet-classified when the target valuable component-containing dust slurry is wet-classified. It shows the limit of. It should be noted that this limit is not so high in accuracy because neither the fractionation of the dust slurry nor the wet classification can be completely separated at a certain particle size, so that the obtained particle size has some spread. Therefore, it is preferable to use it as a guideline to some extent. The "wet classification characteristic curve" shown in FIG. 5 presents a certain standard as the characteristics after classification in the wet classification of the target dust slurry, and has great industrial significance.

For example, if a "wet classification characteristic curve" as shown in FIG. 5 is obtained for the target dust, it is possible to calculate the classification point required to obtain the target post-classification characteristic (classification characteristic). It can be done, for example, when introducing a new classification device (wet cyclone), there is an advantage that it can provide a powerful clue for device selection.

Furthermore, after starting the operation of the wet classification device and starting the wet classification, the operating conditions are optimized, that is, after the classification, how fine the fine particles are concentrated in the fine-grained side (highly valuable component side) dust slurry. The issue is whether the solid content can be reduced in the grain side (highly valuable component side) dust slurry. According to the present invention, since the limit of the reachable classification characteristics (de-active ingredient ratio, solid content abundance ratio of dust on the high active ingredient side) can be predicted to some extent, there is an advantage that waste of examination time can be prevented.

Further, in the present invention, based on the above-mentioned "wet classification characteristic curve of the target valuable component-containing dust slurry", it is possible to determine the classification status at the time of actual operation in the wet classification, that is, the operating state of the wet classification device.

Fine-grained side dust slurry and coarse granules obtained by wet-classifying the target valuable component-containing dust slurry at any time during operation of the wet classification device, that is, at any time during wet classification in the wet classification method. For the side dust slurry, the concentration of valuable components and the amount of solids are analyzed, and the abundance ratio of valuable components and the abundance ratio of solids in the fine-grained side dust slurry are calculated. The abundance ratio of the valuable component in the fine-grained dust slurry is defined as the devalued component ratio, and the solid content abundance ratio in the fine-grained dust slurry is defined as the high valuable component-containing side solid content abundance ratio. In comparison with the "wet classification characteristic curve of the target valuable component-containing dust slurry", the classification status in the wet classification is judged. In addition, the operating state of the wet classification device is determined by this.

In the present invention, the devalued component ratio and the high valuable component-containing side solid content abundance ratio obtained at any time during operation of the wet classification device, that is, at any time during wet classification in the wet classification method. If the relationship is within a certain range from the "wet classification characteristic curve" obtained in advance, it is determined that the wet classification device is operating normally and the wet classification is normally performed (for example, in FIG. 5). Measurement points 1 and 2). On the other hand, if it is out of a certain range from the wet classification characteristic curve (for example, measurement point 3 in FIG. 5), it is determined that the wet classification is in a defective state, and whether the operation of the wet classification device is abnormal or not. It can be determined whether the device is out of order or the properties of the target dust slurry have changed. Therefore, it is possible to provide effective information regarding the narrowing down of abnormal parts. For example, in order to determine the change in the properties of the dust slurry, it is preferable to take samples regularly, carry out the present invention, and confirm the fluctuation of the sample.

Further, according to the present invention, the characteristics after classification (devaluation component ratio, high valuable component content side (fine grain side slurry) solid content abundance ratio) can be predicted in advance. It is possible to provide useful information when considering the scale and specifications of the dehydrator, etc. Once the amount of solids after classification is known, the scale (processing amount) of the sedimentation basin, dehydrator, etc. corresponding to the fine-grain side slurry and coarse-grain side slurry can be determined to some extent according to the amount of solids to be concentrated and the amount of solids to be dehydrated. can do.

Hereinafter, the present invention will be further described based on Examples.

As a dust slurry containing a valuable component (zinc), a dust (blast furnace dust) slurry (concentrated dust slurry) from a steel mill is targeted, and the concentrated dust slurry is diluted with ethanol to have a dust concentration of 5 g / L. Of which, 100 mL was collected as a sample dust slurry.

Next, as shown in FIG. 6, the sample dust slurry was combined with various sieves (opening: 106 μm, 53 μm, 25 μm) and filter paper (pore diameter: 20 μm) in series, and the particle size range exceeded 106 μm (pore size: 20 μm). Five stages consisting of fraction 1), 106 to 53 over μm (fraction 2), 53 to 25 over μm (fraction 3), 25 to 20 over μm (fraction 4), and 20 μm or less (fraction 5). It was fractionated into the fractions of.

Then, each fraction on the sieve was backwashed with ethanol, collected, filtered through a filter (pore size: 0.2 μm), and dried at 105 ° C. to obtain a solid content sample of each fraction. The obtained solid content sample was weighed (dry weight) together with the filter. The dry weight of the filter was measured in advance and subtracted from the obtained weight to obtain the solid content weight of each fraction. Further, the fraction (fraction 5) on the filter paper was dried, and then the weight (dry weight) was measured together with the filter paper. The dry weight of the filter paper before filtration was measured in advance and subtracted from the obtained weight to obtain the solid content weight of the fraction. Then, from the weight of the solid content of each of the obtained fractions, a ratio to the total amount of solid content was calculated and used as the solid content abundance ratio of the fraction. In addition, the solid content weight of each fraction was totaled, and the ratio to the treated amount (total treated amount) was calculated and used as the recovery rate. After that, the solid content sample was acid-dissolved as it was, and then the zinc concentration was determined by ICP emission spectroscopic analysis. Table 1 shows the solid content abundance ratio and zinc concentration of each fraction.

The loss of solids due to fractionation was small, and the recovery rate was 93.7%. From Table 1, it can be seen that the abundance ratio of the solid content is small in the fraction having a fine particle size and large in the fraction having an intermediate particle size. In addition, the abundance ratio of zinc is higher in the fine-grained side fraction, and it can be seen that zinc is concentrated in the fine-grained side fraction.

Further, the sample dust slurry was fractionated again as shown in FIG. However, this time, after backwashing the fraction on the sieve, the slurry was recovered as it was without filtering with a filter, and the particle size distribution was measured by using a laser diffraction / scattering method. Regarding the fraction (fraction 5) captured on the filter paper, the filter paper is cut into small pieces, put into an ethanol solution together with the filter paper, and stirred in the ethanol solution with ultrasonic waves for about 10 minutes to separate the fractions. The filter paper was dispersed in an ethanol solution to prepare a slurry sample. The particle size distribution of the obtained slurry sample was measured in the same manner.

By multiplying the particle size distribution for each of the obtained fractions by the solid content abundance ratio of each fraction, the solid content abundance ratio distribution (relationship between the particle size and the solid content abundance ratio) for each fraction is obtained. Furthermore, the solid content abundance ratio distribution of each fraction was summed to obtain the solid content abundance ratio distribution (relationship between the particle size and the solid content abundance ratio) with respect to the entire dust. The relationship between the particle size and the solid content abundance ratio with respect to the entire dust was almost the same as the particle size distribution of the target dust. The obtained results are shown in FIG. Note that FIG. 7 also shows the cumulative solid content ratio accumulated from the side with the smaller particle size.

Further, by multiplying the obtained particle size distribution for each fraction and the valuable component (zinc) concentration, the zinc abundance ratio distribution for each fraction (the particle size and the zinc abundance ratio) with respect to the entire zinc in the dust. (Relationship) was obtained, and the zinc abundance ratio distribution of each fraction was summed to obtain the zinc abundance ratio distribution (relationship between particle size and zinc abundance ratio) with respect to the entire dust. The obtained results are shown in FIG. Note that FIG. 8 also shows the cumulative zinc abundance ratio, which is the cumulative zinc abundance ratio from the side with the smaller particle size.

FIG. 7 and FIG. 8 are superimposed and shown in FIG.
From the relationship between the particle size and the cumulative solid content ratio and the relationship between the particle size and the cumulative zinc abundance ratio shown in FIG. 9, if the dust slurry is classified using a wet classification device with a classification point of about 7 μm, the target dust slurry will be fine. It can be inferred that the solid content (high zinc content side solid content abundance ratio) is 50% and zinc (zinc abundance ratio) is 73% on the grain side (zinc-concentrated slurry side). That is, the fine-grained side dust slurry (zinc-concentrated slurry side) is discharged to the outside of the system as high zinc dust and is not recycled. Therefore, the wet classification characteristics (dezincination rate, solid content present) of the target dust slurry. The ratio) can be predicted to be a dezincification rate of 73% and a solid content abundance ratio of 50%.

Next, using the relationship between the particle size and the cumulative solid content ratio and the relationship between the particle size and the cumulative zinc abundance ratio shown in FIG. 9, the fine-grained dust slurry (fine-grained side dust slurry) obtained when the classification points are variously changed. Dezincination rate and high zinc content side solid content are calculated based on the cumulative solid content ratio (high zinc content side solid content abundance ratio) and zinc abundance ratio cumulative (dezincification rate) classified into the zinc-concentrated slurry side). The relationship with the abundance ratio, that is, the wet classification characteristic curve of the target valuable component-containing dust slurry, is shown by dotted line in FIG.

Then, the dust (blast furnace dust) slurry from the above-mentioned steel mill was put into a wet cyclone having a classification point of 7 μm, and a wet classification test was carried out on an actual machine. The wet classification test was performed 20 times in total. After wet classification, the solid content and zinc concentration of the fine-grained dust slurry and the coarse-grained dust slurry were analyzed. The analysis method was the same as the above method. The input dust slurry was also analyzed in the same manner.

From the obtained results, the solid content abundance ratio in the fine-grained side (high zinc-containing side) dust slurry (high zinc-containing side solid content abundance ratio) and the zinc abundance ratio in the fine-grained side (high zinc-containing side) dust slurry ( Dezincification rate) was calculated and plotted in FIG. 10 with a + mark. In the figure, the above-mentioned prediction points are marked with a circle.

The results of the actual wet classification test show that there are some variations due to variations in the solid content concentration of the charged slurry and fluctuations in the flow rate, but all of them are distributed in the vicinity of the wet classification characteristic curve and the prediction point. It can be said that the prediction method of the present invention can predict the wet classification characteristics by an actual machine with sufficient accuracy without performing an actual machine test.

Claims (8)

The valuable component-containing dust slurry containing the valuable component-containing dust is wet-classified by a wet classifier to separate the slurry in which the valuable component is concentrated and the slurry in which the valuable component is low, and the valuable component is removed from the valuable component-containing dust slurry. In advance,
A first step of collecting a predetermined amount of sample dust slurry from the valuable component-containing dust slurry and fractionating the collected sample dust slurry into a plurality of fractions at a constant particle size.
A second step of analyzing the particle size distribution, solid content ratio, and valuable component concentration for each of the plurality of fractions.
From the analyzed particle size distribution, the analyzed solid content ratio, and the analyzed valuable component concentration, the relationship between the particle size and the abundance ratio of the valuable component and the particle size over the entire dust area. The relationship between the solid content ratio and the calculated particle size and the abundance ratio of the valuable component is calculated, and from the relationship between the calculated particle size and the solid content abundance ratio, the particle size and the valuable component The third step of calculating the relationship with the cumulative abundance ratio and the relationship between the particle size and the cumulative abundance ratio of solids, and
From the relationship between the calculated particle size and the cumulative abundance ratio of the valuable component, the relationship between the particle size and the cumulative abundance ratio of the solid content, and the classification ability of the wet classifier, the slurry side where the valuable component is concentrated The fourth step of calculating the abundance ratio of the valuable component and the abundance ratio of the solid content in
Sequentially
The abundance ratio of the valuable component and the abundance ratio of the solid content on the slurry side in which the valuable component is concentrated, the devaluation component ratio from the dust slurry containing the valuable component, and the solid content abundance ratio on the high valuable component-containing side A method for predicting the wet classification characteristic of a dust slurry containing a valuable component, which comprises predicting the wet classification characteristic of the dust slurry containing the valuable component. The method for predicting the wet classification characteristics of a valuable component-containing dust slurry according to claim 1, wherein the wet classification device is a wet cyclone. The method for predicting the wet classification characteristics of a valuable component-containing dust slurry according to claim 1 or 2, wherein the valuable component-containing dust is zinc-containing dust. The method for predicting the wet classification characteristics of a valuable component-containing dust slurry according to claim 3, wherein the zinc-containing dust is any one of blast furnace dust, converter dust, and electric furnace dust. A wet classification method in which a valuable component-containing dust slurry containing valuable component-containing dust is wet-classified by a wet classifier and separated into a slurry in which the valuable component is concentrated and a slurry in which the valuable component is low.
For each of the target valuable component-containing dust slurries, a predetermined amount of sample dust slurry is collected in advance from the valuable component-containing dust slurry, and the collected sample dust slurry is divided into a plurality of fractions for each fixed particle size. The first step of fractionation and
The second step of analyzing the particle size distribution, the solid content ratio, and the concentration of valuable components for each of the plurality of fractions.
From the analyzed particle size distribution, solid content abundance ratio, and valuable component concentration, the relationship between the particle size and the valuable component abundance ratio and the relationship between the particle size and the solid content abundance ratio over the entire dust area are calculated and calculated. From the relationship between the particle size and the abundance ratio of the valuable component and the relationship between the particle size and the abundance ratio of the solid content, the relationship between the particle size and the cumulative abundance ratio of the valuable component and the cumulative particle size and the abundance ratio of the solid content The third step to calculate the relationship and
From the above-mentioned relationship between the particle size and the accumulation of the abundance ratio of valuable components and the relationship between the particle size and the accumulation of the abundance ratio of the solid content over the entire dust, it is obtained after the classification according to the classification ability of the wet classifier. The abundance ratio of the valuable component and the abundance ratio of the solid content with respect to the entire dust slurry on the slurry side where the valuable component was concentrated were obtained.
The abundance ratio of the valuable component to the entire dust slurry on the slurry side where the obtained valuable component is concentrated is defined as the devaluation component ratio, and the solid content with respect to the entire dust slurry on the slurry side where the obtained valuable component is concentrated. The fourth step of calculating the relationship curve between the devalued component ratio and the high valuable component-containing side solid content abundance ratio, with the abundance ratio of
Was sequentially carried out to obtain the calculated relationship curve between the devalued component ratio and the high valuable component-containing side solid content abundance ratio as the wet classification characteristic curve of the target valuable component-containing dust slurry.
At any time in the wet classification, the valuable component concentration and the solid content of the wet-classified slurry in which the valuable component is concentrated and the slurry in which the valuable component is low are analyzed, and the dust slurry in the slurry in which the valuable component is concentrated is analyzed. The abundance ratio of the valuable component and the abundance ratio of the solid content are calculated, and the devaluation component ratio in the slurry in which the valuable component is concentrated and the solid content abundance ratio on the high valuable component-containing side are calculated as the target valuable component-containing dust slurry. A wet classification method, characterized in that the classification status of the wet classification is determined by comparing with the wet classification characteristic curve. The wet classification method according to claim 5, wherein the wet classification device is a wet cyclone. The wet classification method according to claim 5 or 6, wherein the valuable component-containing dust is zinc-containing dust. The wet classification method according to claim 7, wherein the zinc-containing dust is any one of blast furnace dust, converter dust, and electric furnace dust.

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