Method for sorting iron ore and method for removing phosphorus

Abstract

To provide a selection method capable of efficiently classifying and selecting iron ore into a plurality of divisions corresponding to a phosphorous content.SOLUTION: The present invention includes a threshold determination step ST1 for determining a first threshold value and a second threshold value using a threshold determination image obtained by capturing an image of a threshold determination iron ore, and a sorting step ST2 for classifying and sorting the sorting target iron ore into three sections, first to third sections, using a sorting target image obtained by capturing an image of the sorting target iron ore and the first and second threshold values. In the threshold determination step ST1, the first and second threshold values are determined so that in the threshold determination image, the intensity value of the R component in a pixel region corresponding to a yellowish brown threshold determination iron ore≥the first threshold value, the second threshold value≤the intensity value of the R component in a pixel region corresponding to a reddish brown threshold determination iron ore<the first threshold value, and the intensity value of the R component in a pixel region corresponding to a blackish threshold determination iron ore<the second threshold value.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a method for sorting iron ore and a method for dephosphorizing iron ore. In particular, the present invention relates to a sorting method that can efficiently classify and sort iron ore into multiple sections according to its phosphorus content, and to a dephosphorizing method that can efficiently perform dephosphorization treatment only on iron ore of a certain section using this sorting method. [Background technology]

[0002] In recent years, the depletion of high-quality iron ore has forced the use of high-phosphorus iron ore, which has a phosphorus content exceeding 0.1% by mass and was not previously used, as a raw material for steelmaking. While excessively high phosphorus content in iron ore negatively impacts the quality of the resulting steel products, requiring dephosphorization, uniformly dephosphorizing all iron ore used as a raw material is inefficient and prohibitively expensive. Therefore, it is desirable to classify the iron ore used according to its phosphorus content, select the iron ore with a high phosphorus content, and perform dephosphorization only on the iron ore with a high phosphorus content. However, in order to do this, it is necessary to classify and select the iron ore according to its phosphorus content.

[0003] For example, Patent Document 1 proposes separating goethite-rich ore from high-phosphorus iron ore by specific gravity separation such as JIG sorting or heavy liquid sorting, and then performing a dephosphorization treatment only on this goethite-rich ore. However, the difference in specific gravity between goethite-rich ore and other ores (such as hematite-rich ore) is not large enough to allow for efficient industrial sorting. Therefore, specific gravity sorting has the problem of not being able to efficiently classify and sort iron ore according to its phosphorus content.

[0004] Furthermore, Non-Patent Document 1 describes how iron ore particles can be classified into three types based on their appearance and color: yellow particles mainly composed of goethite, black particles mainly composed of hematite, and intermediate particles. However, Non-Patent Document 1 does not propose any methods for automatically classifying and sorting iron ore, nor does it propose any dephosphorization treatment.

[0005] Furthermore, Non-Patent Document 2 proposes a method for dephosphorizing iron ore. [Prior art documents] [Patent Documents]

[0006] [Patent Document 1] Japanese Patent Publication No. 2020-20010 [Non-patent literature]

[0007] [Non-Patent Document 1] Jun Okazaki, et al., "Classification of Iron Ore Particles and Their Mineral Properties and Sinterability," Iron and Steel, 2006, Vol. 92, No. 12, pp. 21-28. [Non-Patent Document 2] Minoru Suzumebe, et al., "Direct Dephosphorization from High-Phosphorus Iron Ore," Iron and Steel, 2014, Vol. 100, No. 2, pp. 217-222. [Overview of the project] [Problems that the invention aims to solve]

[0008] The present invention was made to solve the problems of the prior art described above, and aims to provide a sorting method that can efficiently classify and sort iron ore into multiple sections according to its phosphorus content, and a dephosphorization method that can efficiently perform dephosphorization treatment only on iron ore of a certain section using this sorting method. [Means for solving the problem]

[0009] To solve the above problems, as a result of intensive studies, the present inventors have found that the appearance colors of iron ores are, in order of decreasing phosphorus content, yellowish-brown, reddish-brown, and blackish. Further, the present inventors have found that among the RGB components of a color image obtained by imaging an iron ore, the iron ores of yellowish-brown, reddish-brown, and blackish can be classified according to the magnitude of the intensity value of the R component. Therefore, the inventors conceived that if the intensity value of the R component of the color image obtained by imaging an iron ore is extracted, the iron ore can be automatically and efficiently classified and sorted into the yellowish-brown, reddish-brown, and blackish categories having a correlation with the phosphorus content according to the magnitude thereof. The present invention has been completed based on the above findings of the present inventors.

[0010] That is, to solve the above problems, the present invention uses a threshold determination image, which is a color image obtained by imaging a threshold determination iron ore that is the same type of iron ore as the selection target iron ore to be selected, and among the RGB components of the color image, a first threshold R t1 and a second threshold R t2 for the intensity value of the R component are determined in a threshold determination step; and a selection step of classifying and selecting the selection target iron ore into three categories using the selection target image, which is a color image obtained by imaging the selection target iron ore, and the first threshold R t1 and the second threshold R t2 are provided. The threshold determination step includes an image acquisition step of imaging the threshold determination iron ore to obtain the threshold determination image, an extraction step of extracting the intensity value of the R component among the RGB components of the threshold determination image, and in the threshold determination image, among the threshold determination iron ores, the intensity value of the R component in the pixel region corresponding to the yellowish-brown threshold determination iron ore is the first threshold R t1 or more, the intensity value of the R component in the pixel region corresponding to the reddish-brown threshold determination iron ore is less than the first threshold R t1 and the second threshold R t2 or more, and the intensity value of the R component in the pixel region corresponding to the blackish threshold determination iron ore is less than the second threshold R t2 so that the first threshold R t1and the second threshold R t2 The sorting process includes a decision step to determine the first threshold R, and the sorting process includes an image acquisition step to image the iron ore to be sorted and acquire the sorting target image, an extraction step to extract the intensity value of the R component from each RGB component of the sorting target image, and the first threshold R t1 The first sorting target iron ore corresponding to the pixel region described above, and the first threshold R in the sorting target image where the intensity value of the R component is t1 Less than the previous second threshold R t2 The second category of iron ore to be sorted corresponds to the pixel region described above, and the intensity value of the R component in the sorted image corresponds to the second threshold R t2 The present invention provides a method for sorting iron ore, which includes a sorting step of classifying the iron ore into three categories: a third category of iron ore to be sorted corresponding to a pixel region that is less than a certain value, and selecting at least one category of iron ore to be sorted from among the classified three categories of iron ore to be sorted.

[0011] In the present invention, "iron ore for threshold determination, which is the same type of iron ore as the iron ore to be sorted" means iron ore of equivalent material quality mined from the same mine as the iron ore to be sorted, and includes iron ore mined or received at a different time than the iron ore to be sorted, as well as cases where a sample taken from the iron ore to be sorted is used as the iron ore for threshold determination. Furthermore, in this invention, "color image" means an image of iron ore taken under conditions in which the iron ore is irradiated with light emitted from a daylight, daylight, or white light source, or under conditions in which it is irradiated with sunlight, and which has the components of R (red), G (green), and B (blue) as its hue. Furthermore, in the present invention, "yellowish-brown iron ore for threshold determination," "reddish-brown iron ore for threshold determination," and "black iron ore for threshold determination" refer to iron ore for threshold determination whose appearance color is yellowish-brown, reddish-brown, and black, respectively, when irradiated with light emitted from a daylight, cool white, or white light source, or when irradiated with sunlight. Furthermore, in the present invention, "sorting iron ore from at least one category" means separating iron ore from iron ore from at least one category (for example, iron ore from the first category) from iron ore from other categories (for example, iron ore from the second and third categories).

[0012] According to the present invention, a threshold determination step determines a first threshold R for the intensity value of the R component among the RGB components of a color image. t1 and the second threshold R t2 (R t1 >R t2 The first threshold R is determined, and the sorting process separates the target iron ore into a color image of the target iron ore and the first threshold R. t1 and the second threshold R t2 Using this method, the iron ore to be sorted is classified into three categories (Category 1, Category 2, and Category 3), and at least one category of iron ore from the three categories is selected. Specifically, in the threshold determination process, in the threshold determination image, which is a color image of the iron ore used for threshold determination, the intensity value of the R component of the pixel region corresponding to the yellowish-brown iron ore used for threshold determination is the first threshold R t1 The above is the result, and the intensity value of the R component in the pixel region corresponding to the reddish-brown iron ore used for threshold determination is the first threshold R. t1 Less than and the second threshold R t2 The above is the result, and the intensity value of the R component in the pixel region corresponding to the iron ore used for determining the threshold for black is the second threshold R. t2 The first threshold R is set to be less than t1 and the second threshold R t2 This will be decided. Then, in the selection process, the intensity value of the R component in the image to be selected is the first threshold R. t1 The iron ore to be sorted corresponding to the above pixel region is classified as the first category of iron ore to be sorted. This first category of iron ore to be sorted is expected to be yellowish-brown in color. In the sorting process, the intensity value of the R component in the image to be sorted is the first threshold R. t1 Less than and the second threshold R t2The iron ore to be sorted corresponding to the above pixel region is classified as the second category of iron ore to be sorted. This second category of iron ore to be sorted is expected to be reddish-brown in color. Furthermore, in the sorting process, the intensity value of the R component in the image to be sorted is the second threshold R. t2 Iron ore samples corresponding to pixel regions less than a certain value are classified as iron ore samples of the third category. This third category of iron ore samples is expected to be black in color. As described above, according to the present invention, the iron ore to be sorted can be automatically and efficiently classified into first to third categories according to its phosphorus content by using only the intensity values ​​of the R component of the threshold determination image obtained by imaging the iron ore to be sorted and the selection target image obtained by imaging the iron ore to be sorted. Therefore, in the sorting process, it is possible to improve the efficiency of the dephosphorization process by selecting, for example, the iron ore to be sorted in the first category, which is considered to have a high phosphorus content, from among the classified first to third categories of iron ore to be sorted, and performing the dephosphorization process only on this selected first category of iron ore.

[0013] The first threshold R in the threshold determination process of the present invention t1 and the second threshold R t2 Various methods can be considered for determining this. For example, iron ore for threshold determination is visually classified into three categories: yellowish-brown, reddish-brown, and black. A threshold determination image is obtained separately for each of the three classified categories of iron ore. The intensity value of the R component of the pixel region corresponding to the iron ore in each threshold determination image is used to determine the first threshold R t1 and the second threshold R t2 A method for determining this (hereinafter, as appropriate, this will be referred to as the "first method of determination") is possible. In other words, in the first determination method, in the image acquisition step of the threshold determination process, the iron ore for threshold determination is visually classified into three categories: yellowish-brown iron ore for threshold determination, reddish-brown iron ore for threshold determination, and black iron ore for threshold determination. A threshold determination image is acquired for each of the three classified categories of iron ore for threshold determination. In the extraction step of the threshold determination process, the intensity value of the R component is extracted for each of the threshold determination images for each of the three categories of iron ore for threshold determination. In the determination step of the threshold determination process, the average value of the intensity value of the R component in the pixel area corresponding to the yellowish-brown iron ore in the threshold determination image acquired for the yellowish-brown iron ore is determined. yave The average value of the R component intensity in the pixel region corresponding to the reddish-brown iron ore used for threshold determination in the threshold determination image obtained for the reddish-brown iron ore used for threshold determination. rave The average value of the R component intensity of the pixel region corresponding to the black-colored iron ore used for threshold determination in the threshold determination image obtained for the black-colored iron ore used for threshold determination. bave The first threshold R is calculated using the following formula (1). t1 Determine the second threshold R using the following equation (2). t2 To decide. R t1 =(R yave +R rave ) / twenty one) R t2 =(R rave +R bave ) / twenty two)

[0014] According to the first determination method described above, the first threshold R determined by equation (1) t1 This allows for accurate distinction between pixel regions corresponding to yellowish-brown iron ore threshold determination and pixel regions corresponding to reddish-brown and black iron ore threshold determination. Furthermore, the second threshold R determined by equation (2) t2This allows for accurate distinction between pixel regions corresponding to black-colored iron ore used for threshold determination and pixel regions corresponding to yellowish-brown and reddish-brown iron ore used for threshold determination. Therefore, the first threshold R t1 and the second threshold R t2 This allows for accurate distinction of pixel regions corresponding to yellowish-brown, reddish-brown, and black iron ore for threshold determination. Therefore, in the sorting process, the first threshold R determined by the first determination method... t1 and the second threshold R t2 By using this method to classify the iron ore to be sorted into three categories (Category 1 to Category 3), the likelihood of the sorted iron ore in each of the three categories becoming yellowish-brown, reddish-brown, and black iron ore can be increased.

[0015] In the first determination method described above, the iron ore for threshold determination must be visually classified into three categories: yellowish-brown, reddish-brown, and black. To avoid this effort, for example, a threshold determination image can be obtained for iron ore in a state where yellowish-brown, reddish-brown, and black iron ore are mixed together, and the maximum and minimum intensity values ​​of the R component in the pixel region corresponding to the iron ore in this threshold determination image can be used to determine the first threshold R t1 and the second threshold R t2 A method for determining this (hereinafter, as appropriate, this will be referred to as the "second method of determination") is possible. In other words, in the second determination mode, the determination step of the threshold determination process determines the maximum value R of the intensity value of the R component in the pixel region corresponding to the iron ore for threshold determination in the threshold determination image. max And the minimum value of the intensity of the R component in the pixel region corresponding to the iron ore used for threshold determination in the threshold determination image is R min The first threshold R is calculated using the following formula (3). t1 Determine the second threshold R using the following equation (4). t2 To decide. Rt1 =R max -(R max -R min ) / 3 ···(3) R t2 =R min +(R max -R min ) / 3 ···(4)

[0016] The second determination method described above determines the minimum R value of the R component intensity of the pixel region corresponding to the threshold iron ore in the threshold determination image. min From the maximum value R max Of the two thresholds that simply divide the range up to R into three equal parts, the threshold with the larger value is the first threshold R. t1 The smaller of the two threshold values ​​is set as the second threshold R t2 This is the method of determination. In other words, assuming that the intensity values ​​of the R component of the pixel regions corresponding to the yellowish-brown, reddish-brown, and black iron ore used for threshold determination are evenly distributed in this order, the first threshold R t1 and the second threshold R t2 This is a method for determining the first threshold R determined in this second determination method. t1 and the second threshold R t2 Compared to the first determination method described above, this method may have a lower accuracy in distinguishing the pixel regions corresponding to the yellowish-brown, reddish-brown, and black iron ore thresholds, but it has the advantage of being more efficient than the first determination method because it eliminates the need for visual classification.

[0017] Furthermore, in order to solve the aforementioned problems, the present invention is also provided as a method for dephosphorizing iron ore, which includes a dephosphorization step in which a dephosphorization treatment is performed only on iron ore from some of the three categories of iron ore to be sorted, as classified by the iron ore sorting method described in any of the above.

[0018] According to the present invention, since the dephosphorization treatment is performed only on iron ore from a subset of the three classified categories (Category 1 to Category 3) of the iron ore to be sorted, it is possible to increase the efficiency of the dephosphorization treatment.

[0019] Specifically, for example, in the dephosphorization process, it is conceivable to perform the dephosphorization treatment only on the iron ore to be sorted in the first category and the iron ore to be sorted in the second category. Since the iron ore to be sorted in the first category (which is expected to be yellowish-brown) and the iron ore to be sorted in the second category (which is expected to be reddish-brown) are thought to have a higher phosphorus content than the iron ore to be sorted in the third category (which is expected to be black), the efficiency of the dephosphorization treatment can be increased by performing the dephosphorization treatment only on the iron ore to be sorted in the first category and the iron ore to be sorted in the second category.

[0020] Furthermore, for example, in the dephosphorization process, it is conceivable to perform the dephosphorization treatment only on the iron ore to be sorted in the first category. Since the iron ore to be sorted in the first category is considered to have the highest phosphorus content among the iron ore to be sorted in the first to third categories, performing the dephosphorization treatment only on the iron ore to be sorted in the first category can further increase the efficiency of the dephosphorization treatment. [Effects of the Invention]

[0021] According to the present invention, iron ore can be efficiently classified and sorted into multiple categories according to its phosphorus content. Furthermore, this sorting method can be used to efficiently perform dephosphorization on only a portion of the iron ore. [Brief explanation of the drawing]

[0022] [Figure 1] This figure schematically shows the general configuration of a sorting apparatus for carrying out a sorting method according to one embodiment of the present invention. [Figure 2] This is a flowchart showing the general procedure of a sorting method and a phosphorus removal method according to one embodiment of the present invention. [Figure 3] This figure shows an example of a color image taken of a sample taken from iron ore to be sorted according to one embodiment of the present invention. [Figure 4]Figure 2 is a schematic diagram illustrating the contents of the image acquisition step ST12, extraction step ST13, and determination step ST14 shown in the diagram. [Figure 5] In an embodiment of the present invention, an example of the results obtained by calculating the intensity values ​​of each RGB component of the pixel region corresponding to the threshold-determining iron ore in each threshold-determining image is shown. [Figure 6] This figure shows the results of component analysis and specific gravity measurement performed in the embodiments of the present invention. [Figure 7] This figure shows the results of the phosphorus removal test performed in the embodiment of the present invention. [Modes for carrying out the invention]

[0023] The following describes an iron ore sorting method and dephosphorization method according to one embodiment of the present invention, using as an example the case where the target to be sorted and the target to be subjected to dephosphorization treatment are high-phosphorus iron ore with a phosphorus content exceeding 0.1% by mass. Figure 1 is a schematic diagram showing the general configuration of a sorting apparatus for carrying out the sorting method according to this embodiment. Figure 2 is a flowchart showing the general procedure of the sorting method and dephosphorization method according to this embodiment.

[0024] <Sorting device> First, let me explain the sorting device. As shown in Figure 1, the sorting device 100 of this embodiment includes a conveyor 10, an imaging means 20, a calculation and control means 30, and an air gun 40. The conveyor belt 10 is a means of transporting the iron ore to be sorted. Figure 3 shows an example of a color image taken of a sample taken from the iron ore to be sorted in this embodiment (although it is shown as a monochrome image in Figure 3, it is actually a color image). Figure 3(a) shows a black-colored iron ore to be sorted O b This is a color image taken of the iron ore O2, which is reddish-brown in color and is the target of sorting. r This is a color image taken of the iron ore O2, which is yellowish-brown in color and is the target of sorting. yis a color image taken. Note that the iron ore for threshold determination described later is the same type of iron ore as the iron ore to be sorted. Therefore, like the iron ore to be sorted shown in Fig. 3, it has an appearance color of black, reddish-brown, or yellowish-brown. In this specification, for the iron ore for threshold determination as well, depending on its appearance color, the same symbols O b , O y , O r will be used.

[0025] As shown in Fig. 1, the sorting device 100 of this embodiment includes three conveyors 10a, 10b, and 10c as the conveyor 10. On the conveyor 10a located on the most upstream side in the conveying direction of the iron ore to be sorted (the direction of the thick arrow shown in Fig. 1), yellowish-brown iron ore to be sorted O y , reddish-brown iron ore to be sorted O r and black iron ore to be sorted O b are placed and conveyed in a mixed state. At the end of the conveyor 10a (the end on the downstream side in the conveying direction), the iron ore to be sorted O y , O r , O b naturally fall toward the conveyor 10b located below the conveyor 10a. In this falling path, the imaging means 20 images the iron ore to be sorted O y , O<00000​​​​​​​​​​When it is expected that [it] passes in front of the air gun 40), a control signal is transmitted to the air gun 40 to drive and control the air gun 40. As a result, the air gun 40 discharges compressed air Air forward, and the iron ore to be sorted in the sorting section is blown toward the conveyor 10c located below the conveyor 10b and conveyed by the conveyor 10c. The timing at which the iron ore to be sorted in the sorting section passes in front of the air gun 40 can be calculated by the arithmetic control means 30 based on the separation distance between the imaging means 20 and the air gun 40 and the gravitational acceleration, ignoring the air resistance acting on the iron ore to be sorted. On the other hand, the iron ore to be sorted in other sections (in the example shown in FIG. 1, the iron ore to be sorted in the second and third sections, which are the iron ore to be sorted of the reddish-brown system and the blackish-brown system, respectively, and the iron ore to be sorted of the blackish-brown system r and the iron ore to be sorted of the blackish-brown system b which is expected to be) is conveyed by the conveyor 10b.

[0026] As the imaging means 20, various configurations such as a CCD camera or a CMOS camera can be adopted as long as it can image the iron ore to be sorted O y , O r , O b and obtain a sorting target image which is a color image having each component of RGB as a hue.

[0027] The arithmetic control means 30 is composed of, for example, a hardware processor such as a CPU and a computer equipped with a memory such as a RAM, a ROM, and a hard disk. In the memory of the arithmetic control means 30, the first threshold value R t1 and the second threshold value R t2 are stored. Further, an image analysis program is stored in the memory of the arithmetic control means 30, and when this image analysis program is executed by the hardware processor, the arithmetic processing described later is executed. As the image analysis program, for example, general image analysis software such as "WinROOF" and "Image J" manufactured by Mitani Shosha, which can separate and extract the intensity values of each component of RGB, can be used. In this arithmetic processing, the first threshold value R t1 and the second threshold value R t2The iron ore to be sorted is O y , O r , O b The iron ore is then classified into three categories: Category 1, Category 2, and Category 3.

[0028] <Selection method and phosphorus removal method> Next, we will explain the sorting method and the phosphorus removal method. As shown in Figure 2, the sorting method according to this embodiment includes a threshold determination step ST1 and a sorting step ST2. The dephosphorization method according to this embodiment includes a dephosphorization step ST3 in addition to the sorting method according to this embodiment (in addition to the threshold determination step ST1 and the sorting step ST2). Steps ST1 to ST3 will be described below.

[0029] [Threshold determination process ST1] Threshold determination step ST1 involves preparing a threshold determination iron ore of the same type as the iron ore to be sorted, and using a threshold determination image, which is a color image of the threshold determination iron ore, a first threshold R is determined for the intensity value of the R component among the RGB components of the color image. t1 and the second threshold R t2 This is the process of determining the threshold. For example, a sample of several tens to several hundred grams taken from the iron ore to be sorted is used as the iron ore for threshold determination. In this embodiment, the threshold determination step ST1 can be selected as either a first determination mode or a second determination mode. In either case, the threshold determination step ST1 includes a washing and drying step ST11, an image acquisition step ST12, an extraction step ST13, and a determination step ST14.

[0030] (Washing and drying step ST11) In the washing and drying step ST11, the threshold determination iron ore is washed and dried so that it can be properly imaged in the subsequent image acquisition step ST12. For washing the threshold determination iron ore, for example, a tabletop ultrasonic cleaner can be used. One approach is to place the threshold determination iron ore in a beaker or tray, put it into the ultrasonic cleaner, add water until the entire threshold determination iron ore is submerged, and vibrate it for several minutes to remove any fine powder adhering to the surface of the threshold determination iron ore. After that, the threshold determination iron ore is removed from the ultrasonic cleaner and placed in a dryer, such as an oven, and dried at a temperature of about 100°C for several hours. Furthermore, when washing and drying the threshold determination iron ore in a sorting apparatus 100 as shown in Figure 1 (when removing the threshold determination iron ore from the sorting target iron ore after washing and drying), for example, while the threshold determination iron ore (sorting target iron ore) is being transported on the conveyor 10a, high-pressure water can be sprayed onto the threshold determination iron ore (sorting target iron ore) to remove fine powder adhering to the surface, and then hot air (exhaust hot air) at about 100-200°C can be blown onto the threshold determination iron ore (sorting target iron ore) to dry it.

[0031] (Image acquisition step ST12) Figure 4 is a schematic diagram illustrating the contents of the image acquisition step ST12, the extraction step ST13, and the determination step ST14. In the image acquisition step ST12, for example, an imaging means similar to the imaging means 20 shown in Figure 1 is used to image the iron ore for threshold determination after washing and drying to acquire an image for threshold determination. The imaging by the imaging means is performed in an environment in which the iron ore for threshold determination is illuminated by light emitted from a neutral white, daylight, or white light source (e.g., an LED light source), or in an environment in which it is illuminated by sunlight. In addition, to minimize the occurrence of pixel areas with high intensity values ​​other than the iron ore for threshold determination (noise areas) in the image for threshold setting, an anti-reflective sheet or the like may be placed in the background to suppress light reflection as needed.

[0032] Specifically, in the first determination method, in the image acquisition step ST12, the iron ore for threshold determination after washing and drying is visually inspected, and the yellowish-brown iron ore for threshold determination O y Reddish-brown iron ore for threshold determination O r and iron ore O for determining the threshold for black color b The iron ore is classified into three categories for threshold determination, and as shown in Figure 4(a), the iron ore O for threshold determination of the three classified categories y , O r , O b Images Img1, Img2, and Img3 for threshold determination are obtained for each step. Note that, as in the first determination method, when classifying the iron ore for threshold determination by visual inspection, if the grain size is too small, it becomes difficult to determine the appearance color. Therefore, it is preferable to classify the sample taken from the iron ore to be sorted using a sieve and use iron ore with a grain size of 1 mm or larger as the iron ore for threshold determination. On the other hand, in the second determination method, in the image acquisition step ST12, as shown in Figure 4(b), yellowish-brown iron ore O for threshold determination y Reddish-brown iron ore for threshold determination O r and iron ore O for determining the threshold for black color b For iron ore used for threshold determination, which contains a mixture of different materials, an image (Img) for threshold determination is obtained.

[0033] (Extraction step ST13) In extraction step ST13, for example, a means having the same calculation processing function as the calculation control means 30 shown in Figure 1 (or by repurposing the calculation control means 30) is used to extract the intensity value of the R component from each RGB component of the threshold determination image. If the threshold determination image is an 8-bit image, the intensity value of the R component will range from 0 for the darkest value to 255 for the brightest value, and is extracted for each pixel constituting the threshold determination image.

[0034] Specifically, in the first determination method, in extraction step ST13, three categories of iron ore for threshold determination (yellowish-brown iron ore for threshold determination O y Reddish-brown iron ore for threshold determination O r and iron ore O for determining the threshold for black colorb For each of the threshold determination images Img1, Img2, and Img3, the intensity value of the R component is extracted. On the other hand, in the second determination method, in extraction step ST13, the iron ore O for determining the threshold of the three categories y , O r , O b For the threshold determination image Img, which was acquired with a mixture of elements, the intensity value of the R component is extracted.

[0035] (Decision step ST14) In the determination step ST14, for example, using a means having the same calculation processing function as the calculation control means 30 shown in Figure 1 (or by repurposing the calculation control means 30), the threshold determination iron ore O y , O r , O b Among them, yellowish-brown iron ore for threshold determination O y The intensity value of the R component in the corresponding pixel region is the first threshold R t1 This concludes the discussion on reddish-brown iron ore for threshold determination. r The intensity value of the R component in the corresponding pixel region is the first threshold R t1 Less than and the second threshold R t2 This concludes the discussion on iron ore O for determining the threshold for black color. b The intensity value of the R component in the corresponding pixel region is the second threshold R t2 The first threshold R is set to be less than t1 and the second threshold R t2 To decide.

[0036] Specifically, in the first determination method, in determination step ST14, as shown in Figure 4(a), yellowish-brown iron ore O for threshold determination is used. y The yellowish-brown iron ore used for threshold determination in threshold determination image Img1 obtained for this purpose. y The average value of the R component intensity of the corresponding pixel region (the hatched region in the threshold determination image Img1) yave Calculate the threshold value of reddish-brown iron ore O. rThe reddish-brown iron ore used for threshold determination in threshold determination image Img2 obtained for this purpose. r The average value of the R component intensity of the corresponding pixel region (the hatched region in the threshold determination image Img2) rave Calculate the following. Furthermore, iron ore O for determining the threshold for black color b The black iron ore used for threshold determination in the threshold determination image Img3 obtained for this purpose is O b The average value of the R component intensity of the corresponding pixel region (the hatched region in the threshold determination image Img3) bave The R component intensity is calculated. The numerical values ​​shown for each pixel region in Figure 4(a) indicate the intensity value of the R component in that pixel region. Note that in Figure 4(a), for convenience, the intensity value of the R component in the same pixel region is shown as a constant value, but in reality, it is often a different value for each pixel contained in the same pixel region. In the example shown in Figure 4(a), R yave =175, R rave =137, R bave = 90 Then, in the first determination mode, in the determination step ST14, the first threshold R is determined by the following equation (1). t1 Determine the second threshold R using the following equation (2). t2 To decide. R t1 =(R yave +R rave ) / twenty one) R t2 =(R rave +R bave ) / twenty two) In the example shown in Figure 4(a), R t1 =156, R t2 = 114. According to the first determination method, the first threshold R determined by equation (1) t1 Therefore, iron ore O for determining the threshold of yellowish-brown color y Pixel regions corresponding to reddish-brown and black iron ore threshold determination regions O r , O b It can distinguish between and with high accuracy. In addition, the second threshold R determined by equation (2) t2Therefore, iron ore O for determining the threshold for black color b The corresponding pixel region and iron ore O for determining the threshold values ​​of yellowish-brown and reddish-brown colors. y , O r The corresponding pixel region can be accurately distinguished. Therefore, the first threshold R t1 and the second threshold R t2 Iron ore for determining threshold values ​​of yellowish-brown, reddish-brown, and black colors. y , O r , O b The corresponding pixel regions can be distinguished with high precision.

[0037] On the other hand, in the second determination method, in the determination step ST14, as shown in Figure 4(b), the threshold determination iron ore O in the threshold determination image Img y , O r , O b The maximum value of the R component intensity of the corresponding pixel region (the hatched region in the threshold determination image Img) R max And, the iron ore used for threshold determination in the threshold determination image Img O y , O r , O b The minimum value of the R component intensity of the corresponding pixel region is R min The R component is calculated. The numerical values ​​shown for each pixel region in Figure 4(b) indicate the intensity value of the R component in that pixel region. Note that in Figure 4(b), for convenience, the intensity value of the R component in the same pixel region is shown as a constant value, but in reality, it is often a different value for each pixel contained in the same pixel region. In the example shown in Figure 4(b), R max =181, R min = 83 Then, in the second determination mode, in the determination step ST14, the first threshold R is determined by the following equation (3). t1 Determine the second threshold R using the following equation (4). t2 To decide. R t1 =R max -(R max -R min ) / 3 ···(3) R t2 =R min+(R max -R min ) / 3 ···(4) In the example shown in Figure 4(b), R t1 =148, R t2 = 116. The second determination method involves the threshold determination iron ore O in the threshold determination image Img. y , O r , O b The minimum value of the R component intensity of the corresponding pixel region is R min From the maximum value R max Of the two thresholds that simply divide the range up to R into three equal parts, the threshold with the larger value is the first threshold R. t1 The smaller of the two threshold values ​​is set as the second threshold R t2 This is the manner in which it is determined. In other words, iron ore O for determining the threshold values ​​of yellowish-brown, reddish-brown, and black. y , O r , O b Assuming that the intensity values ​​of the R component in the pixel regions corresponding to each are evenly distributed in this order, the first threshold R t1 and the second threshold R t2 This is a method for determining the first threshold R determined in this second determination method. t1 and the second threshold R t2 Therefore, compared to the first determination method described above, the iron ore used to determine the threshold values ​​for yellowish-brown, reddish-brown, and black colors O y , O r , O b Although there is a risk of reduced accuracy in distinguishing the corresponding pixel regions, this method has the advantage of being more efficient than the first determination method because it eliminates the need for visual classification. Furthermore, since visual classification is not required, it is also possible to perform the second determination method using the sorting device 100 shown in Figure 1. In other words, it is possible to use a portion of the transported iron ore to be sorted as the iron ore to be used for threshold determination without extracting the iron ore for threshold determination from the iron ore to be sorted.

[0038] The first threshold R determined by the threshold determination process ST1 described above. t1 and the second threshold R t2This first threshold R is stored in the memory of the calculation control means 30 of the sorting device 100 and used in the sorting process ST2. t1 and the second threshold R t2 This can be a fixed value, but multiple sets can be determined and stored according to the material of the iron ore to be sorted, and a first threshold R corresponding to the material of the iron ore to be sorted is used. t1 and the second threshold R t2 It is also possible to adopt a method of selecting and using a set of these. Furthermore, even with the same type of iron ore to be sorted, the first threshold R t1 and the second threshold R t2 It is also possible to adopt a method of updating and storing the data as needed.

[0039] [Sorting process ST2] In the sorting process ST2, the iron ore to be sorted O is sorted by the sorting device 100. y , O r , O b The selection target image is a color image captured from the image, and the first threshold R t1 and the second threshold R t2 Using this, the iron ore to be sorted O y , O r , O b This process involves classifying and sorting the items into three categories (Category 1 to Category 3). The sorting step ST2 of this embodiment includes a washing and drying step ST21, an image acquisition step ST22, an extraction step ST23, and a sorting step ST24.

[0040] (Washing and drying step ST21) In the washing and drying step ST21, the iron ore to be sorted is selected in the subsequent image acquisition step ST22. y , O r , O b To enable proper imaging, the iron ore to be sorted O y , O r , O b After washing, the material is dried. For example, iron ore to be sorted O y , O r , O bWhile being transported by conveyor 10a, the iron ore to be sorted O is removed from the high-pressure washer (not shown). y , O r , O b After removing the fine powder adhering to the surface by spraying it with high-pressure water, hot air (exhaust air) at a temperature of approximately 100-200°C is blown from a dryer (not shown) onto the iron ore to be sorted. y , O r , O b One possible method is to spray it and let it dry.

[0041] (Image acquisition step ST22) In the image acquisition step ST22, the imaging means 20 is used to capture the iron ore to be sorted after washing and drying. y , O r , O b The image is captured to obtain an image of the target for sorting. The image captured by the imaging means 20 is of the iron ore O to be sorted. y , O r , O b The sorting is carried out in an environment where light emitted from a cool white, daylight, or white light source (e.g., an LED light source) is irradiated, or in an environment where sunlight is irradiated. In addition, the sorting target iron ore O is included in the sorting target image. y , O r , O b To minimize the occurrence of pixel regions with high intensity values ​​other than those mentioned (noise regions), an anti-reflective sheet or similar material may be installed in the background to suppress light reflection, if necessary.

[0042] (Extraction step ST23) In the extraction step ST23, the calculation control means 30 is used to extract the intensity value of the R component from each RGB component of the image to be selected. If the image to be selected is an 8-bit image, the intensity value of the R component will range from 0 for the darkest value to 255 for the brightest value, and is extracted for each pixel that makes up the image to be selected.

[0043] (Selection step ST24) In the sorting step ST24, the calculation control means 30 is used to sort the iron ore O y , O r , O b In the images to be selected, the intensity value of the R component is the first threshold R.t1 The first category of iron ore to be sorted corresponds to the pixel region described above, and the intensity value of the R component in the sorted image is the first threshold R. t1 Less than and the second threshold R t2 The second category of iron ore to be sorted corresponds to the pixel region described above, and the intensity value of the R component in the sorted image corresponds to the second threshold R. t2 The iron ore is classified into three categories: the third category of iron ore to be sorted, corresponding to the pixel region that is less than [a certain value], and the third category of iron ore to be sorted. The first category of iron ore to be sorted is yellowish-brown iron ore O y This can be expected. The iron ore to be sorted in the second category is reddish-brown iron ore O r This can be expected. The iron ore to be sorted in the third category is black-colored iron ore O b It can be expected that this will be the case.

[0044] Then, in sorting step ST24, the calculation control means 30 and the air gun 40 are used to sort at least one of the three classified categories of iron ore to be sorted. In the example shown in Figure 1, as described above, the yellowish-brown iron ore to be sorted O y The first category of iron ore, which is expected to be of a certain type, is sorted and transported by conveyor belt 10c, while the reddish-brown iron ore O r The second category of iron ore that is expected to be such, and the black-colored iron ore that is expected to be such bThe iron ore of the third category, which is expected to be of a certain quality, is not sorted (the iron ore of the second and third categories remains mixed together without being separated). However, this is not the only option. For example, even with the iron ore of the second and third categories being transported by the conveyor 10b, it is possible to separate the iron ore of the second category from the iron ore of the third category by allowing it to fall naturally towards another conveyor located below at the end of the conveyor 10b (the downstream end in the transport direction), and by arranging an imaging device and an air gun similar to the imaging device 20 and air gun 40 in the path of the fall, and performing steps similar to the image acquisition step ST22, extraction step ST23, and sorting step ST24. In other words, it is also possible to sort the iron ore of the second category after sorting the iron ore of the first category. In this embodiment, the sorting step ST24 has been described using the sorting device 100 shown in Figure 1 as an example. However, the present invention is not limited to this, and it is also possible to perform the sorting step ST24 using sorting devices with various configurations, as long as it is possible to sort at least one of the three classified categories of iron ore to be sorted.

[0045] [Phosphorus removal process ST3] The dephosphorization process ST3 is performed only on a portion of the iron ore from the three categories of iron ore to be sorted, as classified by the sorting process ST2. The dephosphorization process ST3 is not limited to this, but for example, it may be performed using a reduction furnace before the sintering process in which the iron ore to be sorted is sintered. Specifically, it is conceivable to perform the dephosphorization treatment only on the iron ore to be sorted into the first and second categories. In this case, in sorting step ST2, the iron ore to be sorted into the first category should be sorted first, and then the iron ore to be sorted into the second category should be sorted. Alternatively, in sorting step ST2, the iron ore to be sorted into the first and second categories should be sorted simultaneously (sorted with both categories of iron ore mixed together). That is, a control signal may be sent to the air gun 40 at the moment the iron ore to be sorted into the first and second categories passes in front of the air gun 40 to drive and control the air gun 40. Furthermore, in sorting step ST2, the iron ore to be sorted into the third category should be sorted, and the dephosphorization treatment may be performed on the remaining iron ore to be sorted into the first and second categories (which are transported by the conveyor 10b). The first category of iron ore to be sorted (yellowish-brown iron ore to be sorted O y (It is expected that this will be the case) and the second category of iron ore to be sorted (reddish-brown iron ore to be sorted O r (It is expected that this will be the case) is the iron ore to be sorted in the third category (black iron ore to be sorted O b Since the phosphorus content is considered to be higher compared to (which is expected to be), the efficiency of the dephosphorization process can be increased by performing the dephosphorization treatment only on the iron ore to be sorted in the first category and the iron ore to be sorted in the second category. Alternatively, it is possible to perform the dephosphorization treatment only on the iron ore of the first category. In this case, in the sorting process ST2, it is only necessary to sort the iron ore of the first category, as shown in Figure 1. Since the iron ore of the first category is considered to have the highest phosphorus content among the iron ore of the first to third categories, the efficiency of the dephosphorization treatment can be further increased by performing the dephosphorization treatment only on the iron ore of the first category.

[0046] The method for the dephosphorization treatment in the dephosphorization step ST3 is not particularly limited, but for example, it is conceivable to perform the dephosphorization treatment under the following conditions using a reductive vaporization dephosphorization method as described in Non-Patent Document 2. • Reducing gas: Hydrogen-water vapor (H2-H2O) mixed gas ·Flow rate: 800ml / min • Reduction temperature: 1000℃, 1050℃, 1100℃ • Reduction time: 30 min, 60 min, 90 min, 120 min In addition, a mixed gas containing CO-CO2-H2-H2O, which is the main reducing gas in the blast furnace process, may be used as the reducing gas. Alternatively, a dephosphorization treatment method as described in Patent Document 1 may be used.

[0047] <Examples> The following describes examples of threshold determination step ST1 and dephosphorization step ST3, etc. In this example, samples taken from Australian iron ore A and B, which were the iron ore to be sorted, were used as threshold determination iron ore. Each iron ore A and B was classified using a sieve, and for each iron ore A and B, threshold determination iron ore with a particle size of 4.75 mm or more and less than 9.5 mm was prepared, and threshold determination iron ore with a particle size of 2.0 mm or more and less than 2.8 mm was prepared (i.e., four sets of threshold determination iron ore). Approximately 150-200 g of each classified threshold determination iron ore was placed in beakers or trays and put into a tabletop ultrasonic cleaner. Water was added until the entire threshold determination iron ore was submerged, and the cleaner was vibrated for several minutes to remove fine powder adhering to the surface of the threshold determination iron ore. After that, the threshold determination iron ore was removed from the ultrasonic cleaner and placed in a dryer and dried at a temperature of 105°C for more than two hours.

[0048] Next, visually inspect each iron ore used for threshold determination after washing and drying, and select the yellowish-brown iron ore used for threshold determination. y Reddish-brown iron ore for threshold determination O r and iron ore O for determining the threshold for black color b The iron ore was classified into three categories for threshold determination. y , O r , O b For each step, a threshold determination image was obtained (4 sets of threshold determination iron ore × 3 divisions = 12 threshold determination images). Figure 3, mentioned above, is a threshold determination image obtained by imaging iron ore A with a grain size of 4.75 mm or more and less than 9.5 mm in an environment illuminated by light emitted from a daylight-white LED light source.

[0049] Next, the calculation control means 30 was repurposed to calculate the intensity values ​​of each RGB component in the pixel region corresponding to the threshold-determining iron ore in each threshold-determining image. Figure 5 shows an example of the results of calculating the intensity values ​​of each RGB component in the pixel region corresponding to the thresholding iron ore in each thresholding image. Figure 5(a) shows the intensity values ​​of each RGB component obtained for the thresholding image obtained for thresholding iron ore with a grain size of 4.75 mm or more and less than 9.5 mm using iron ore A. Figure 5(b) shows the intensity values ​​of each RGB component obtained for the thresholding image obtained for thresholding iron ore with a grain size of 4.75 mm or more and less than 9.5 mm using iron ore B. In Figure 5, the points plotted with "○", "△", and "□" represent the average value of the intensity, and the bars extending above and below each plotted point represent the variability (standard deviation σ). As can be seen from Figure 5, the intensity value of the R component differs from the intensity values ​​of the G component and the B component, and is determined by the iron ore O used for threshold determination. y , O r , O b A significant difference is observed between them, and the intensity values ​​increase in this order. Therefore, in the threshold determination step ST1, the first threshold R is determined by the aforementioned equations (1) and (2), or by the aforementioned equations (3) and (4). t1 and the second threshold R t2 Once determined, the iron ore used to determine the threshold values ​​for yellowish-brown, reddish-brown, and black colors is O y , O r , O b It can be said that the pixel regions corresponding to each can be distinguished with high accuracy. Furthermore, in the sorting process ST2, the first threshold R determined in the threshold determination process ST1 t1 and the second threshold R t2By using this method to classify the iron ore to be sorted into three categories, the iron ore to be sorted in the classified categories 1 to 3 is divided into yellowish-brown, reddish-brown, and black types, respectively. y , O r , O b This can raise expectations that it will happen.

[0050] In this embodiment, the iron ore used to determine each threshold value was determined based on "JIS M 8202" (Iron ore - General rules for analytical methods), "JIS M 8206" (Iron ore - ICP emission spectrometry method), "JIS M 8211" (Iron ore - Method for determining compound water), and "JIS M 8212" (Iron ore - Method for determining total iron). y , O r , O b Component analysis was also performed. In addition, in this example, based on "JIS M 8717" (Iron ore - Density testing method), each threshold determination iron ore O y , O r , O b We also measured its specific gravity. Figure 6 shows the results of the above-mentioned component analysis and specific gravity measurement. Figure 6(a) shows the results obtained for threshold determination iron ore with a particle size of 4.75 mm or more and less than 9.5 mm using iron ore A. Figure 6(b) shows the results obtained for threshold determination iron ore with a particle size of 2.0 mm or more and less than 2.8 mm using iron ore A. Figure 6(c) shows the results obtained for threshold determination iron ore with a particle size of 4.75 mm or more and less than 9.5 mm using iron ore B. Figure 6(d) shows the results obtained for threshold determination iron ore with a particle size of 2.0 mm or more and less than 2.8 mm using iron ore B. As can be seen from Figure 6, yellowish-brown iron ore O for threshold determination y Reddish-brown iron ore for threshold determination O r Iron ore for determining the threshold for black color b In this order, it was confirmed that the phosphorus (P) content was highest. Also, iron ore O for determining the threshold for black color b It tends to have a high iron content (T.Fe) and low water of crystallization (CW), indicating that it is mainly hematite, and is a yellowish-brown iron ore used for threshold determination. yBased on its low iron (T.Fe) content and high water of crystallization (CW) content, it was confirmed that the material is primarily composed of goethite.

[0051] Furthermore, as can be seen from Figure 6, the black iron ore O used for threshold determination b and reddish-brown iron ore for threshold determination O r It tends to be dense, and the yellowish-brown iron ore used for threshold determination is O y However, the density tended to be low. For this reason, in specific gravity sorting as described in Patent Document 1, black iron ore O b and reddish-brown iron ore for threshold determination O r And, yellowish-brown iron ore for threshold determination O y It is possible to classify them in this way, but black iron ore for threshold determination O b And, reddish-brown iron ore for threshold determination O r Classifying them in this way is considered difficult.

[0052] Next, in this embodiment, the iron ore to be sorted into the first to third categories, which are classified in the sorting process ST2, are correctly classified as yellowish-brown, reddish-brown, and black iron ore O, respectively. y , O r , O b Assuming this was the case, a phosphorus removal test was conducted that simulated the phosphorus removal process ST3. Specifically, the threshold determination iron ore was classified into three categories by visual inspection: iron ore O with a grain size of 4.75 mm or more and less than 9.5 mm using ore A, and iron ore with a grain size of 4.75 mm or more and less than 9.5 mm using ore B. y , O r , O b Approximately 10g each of six sets of iron ore for threshold determination was placed in a Ni crucible, and each crucible was simultaneously placed in an electric furnace with an inner diameter of 73mm. Next, the electric furnace was heated to a predetermined temperature under an N2 gas atmosphere, and then the atmosphere was switched to a reducing gas atmosphere for a 120-minute reduction vaporization dephosphorization treatment. The amount of phosphorus removed was calculated as the change in phosphorus content before and after the dephosphorization treatment (change per ton of each iron ore for threshold determination). Two reduction temperatures were used: 500°C and 700°C, and hydrogen (H2) gas was used as the reducing gas.

[0053] Figure 7 shows the results of the dephosphorization test described above. Figure 7(a) shows the results obtained for the iron ore used for threshold determination using iron ore A. Figure 7(b) shows the results obtained for the iron ore used for threshold determination using iron ore B. As can be seen from Figure 7, although the amount of dephosphorization varies depending on the reduction temperature, under both the 500°C reduction and 700°C reduction conditions, the yellowish-brown iron ore used for threshold determination O y The amount of phosphorus removal was highest for the reddish-brown iron ore used for threshold determination. r However, the amount of phosphorus removal is large, and iron ore used for determining the threshold for black-colored materials O b It showed a tendency to have the smallest amount of dephosphorylation. Therefore, among high-phosphorus iron ores, the yellowish-brown type with a high proportion of goethite and phosphorus content is the target for sorting. y (Iron ore subject to sorting in Category 1), or yellowish-brown iron ore subject to sorting O y In addition, reddish-brown iron ore is also a target for sorting. r By selectively performing dephosphorization on the iron ore (targeted for sorting in the second category), it is possible to reduce the processing volume in the dephosphorization process ST3, which requires high-temperature heating and a large amount of reducing gas, and thus the energy required, thereby improving the efficiency of the dephosphorization process. [Explanation of Symbols]

[0054] 10... Conveyor 20. Imaging means 30. Calculation control means 40... Air gun 100... sorting device ST1...Threshold determination process ST2... Sorting process ST3... Phosphate removal process ST11... Washing and drying step ST12...Image acquisition step ST13... Extraction Step ST14...Decision Step ST21... Washing and drying step ST22...Image acquisition step ST23... Extraction Step ST24... Sorting step

Claims

1. Using a threshold determination image, which is a color image of the iron ore to be sorted and iron ore of the same type as the iron ore to be sorted, a first threshold R is determined for the intensity value of the R component among the RGB components of the color image. ｔ１ and the second threshold R ｔ２ A threshold determination process to determine the threshold, The sorting target image is a color image of the iron ore to be sorted, and the first threshold R ｔ１ and the second threshold R ｔ２ The sorting process includes a method for classifying the iron ore to be sorted into three categories and sorting them using the method described above. The threshold determination step described above is: Image acquisition step: Image the iron ore for threshold determination and obtain the threshold determination image. An extraction step of extracting the intensity value of the R component from among the RGB components of the threshold determination image, In the threshold determination image, among the threshold determination iron ores, the intensity value of the R component of the pixel region corresponding to the yellowish-brown threshold determination iron ore is the first threshold R ｔ１ or more, and the intensity value of the R component of the pixel region corresponding to the reddish-brown threshold determination iron ore is less than the first threshold R ｔ１ and is greater than or equal to the second threshold R ｔ２ and the intensity value of the R component of the pixel region corresponding to the black threshold determination iron ore is less than the second threshold R ｔ２ so as to be less than, the first threshold R ｔ１ and the second threshold R ｔ２ including a determination step of determining, The aforementioned sorting process is, An image acquisition step is to capture an image of the iron ore to be sorted and obtain an image of the sorting target, The extraction step involves extracting the intensity value of the R component from among the RGB components of the selected image, The iron ore to be sorted is defined as having an R component intensity value in the sorting target image, which is the first threshold R. ｔ１ The first sorting target iron ore corresponding to the pixel region described above, and the first threshold R, where the intensity value of the R component in the sorting target image is described above. ｔ１ Less than the second threshold R ｔ２ The second category of iron ore to be sorted corresponds to the pixel region described above, and the intensity value of the R component in the sorted image is the second threshold R. ｔ２ The sorting step includes classifying the iron ore into three categories: a third category of iron ore to be sorted corresponding to a pixel region that is less than [a certain value], and selecting at least one category of iron ore from the classified three categories of iron ore to be sorted, Methods for sorting iron ore.

2. In the image acquisition step of the threshold determination process, the iron ore for threshold determination is visually classified into three categories: yellowish-brown iron ore for threshold determination, reddish-brown iron ore for threshold determination, and black iron ore for threshold determination. An image for threshold determination is then acquired for each of the three classified categories of iron ore for threshold determination. In the extraction step of the threshold determination process, the intensity value of the R component is extracted for each of the threshold determination images for each of the three categories of iron ore used for threshold determination. In the determination step of the threshold determination process, the average value R of the intensity value of the R component in the pixel region corresponding to the yellowish-brown iron ore used for threshold determination in the threshold determination image obtained for the yellowish-brown iron ore used for threshold determination. ｙａｖｅ The average value of the R component intensity in the pixel region corresponding to the reddish-brown iron ore used for threshold determination in the threshold determination image obtained for the reddish-brown iron ore used for threshold determination is R ｒａｖｅ The average value of the R component intensity in the pixel region corresponding to the black-colored iron ore used for threshold determination in the threshold determination image obtained for the black-colored iron ore used for threshold determination is R ｂａｖｅ The first threshold R is calculated using the following formula (1). ｔ１ Determine the second threshold R using the following formula (2). ｔ２ to decide The method for sorting iron ore according to claim 1. R ｔ１ =(R ｙａｖｅ +R ｒａｖｅ ) / 2 ・・・(1) R ｔ２ =(R ｒａｖｅ +R ｂａｖｅ ) / 2 ・・・(2)

3. In the determination step of the threshold determination process, the maximum value R of the intensity value of the R component in the pixel region corresponding to the iron ore for threshold determination in the threshold determination image is determined. ｍａｘ And the minimum value of the intensity of the R component in the pixel region corresponding to the iron ore used for threshold determination in the threshold determination image is R ｍｉｎ The first threshold R is calculated using the following formula (3). ｔ１ Determine the second threshold R using the following formula (4). ｔ２ to decide The method for sorting iron ore according to claim 1. R ｔ１ =R ｍａｘ -(R ｍａｘ -R ｍｉｎ ) / 3 ・・・(3) R ｔ２ =R ｍｉｎ +(R ｍａｘ -R ｍｉｎ ) / 3 ・・・(4)

4. The method comprises a dephosphorization step in which a dephosphorization treatment is performed only on some of the iron ore to be sorted from among the three categories of iron ore to be sorted, which are classified according to any one of claims 1 to 3. A method for removing phosphorus from iron ore.

5. In the dephosphorization process, the dephosphorization treatment is performed only on the iron ore to be sorted in the first category and the iron ore to be sorted in the second category. The method for dephosphorizing iron ore according to claim 4.

6. In the dephosphorization process, the dephosphorization treatment is performed only on the iron ore of the first category to be sorted. The method for dephosphorizing iron ore according to claim 4.

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