Intelligent water adding control system and method for sintering mixer

Abstract

The invention belongs to the technical field of sintering mixers, and particularly relates to an intelligent water adding control system and method for a sintering mixer. The system comprises a particle size online detection unit, a fuzzy control unit, a man-machine interaction display unit and a remote communication unit, the particle size online detection unit shoots an image of the mixture and performs image recognition to obtain a particle size distribution result of the mixture, and the fuzzy control unit controls the opening degree of the electric control valve according to the particle size distribution result. According to the control system and method, the water adding amount of the mixing machine can be accurately and intelligently adjusted in real time according to the target particle size range, the good mixing machine granulation effect is achieved, the air permeability of the mixture is guaranteed, the ultra-thick material layer sintering technology is achieved, the quality and strength of sintered ore are improved, and sintering energy consumption is reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of sintering mixers, and in particular relates to an intelligent water adding control system and a control method for a sintering mixer. Background Art

[0002] 80% of the clinker used in blast furnace ironmaking comes from sintered ore. Sintering plays a vital role in the steel industry. The sintering granulation process is one of the key processes in the sintering process. A good granulation effect can improve the quality and strength of the sintered ore, reduce the energy consumption of the sintering machine, achieve high efficiency, high quality, reduced consumption, and increased production of sintering, and ultimately realize the low-carbon green development concept of the steel industry. There are many factors that affect the granulation effect of the sintering mixer, among which the influence of the amount of water added to the mixer is particularly prominent. If the moisture content of the sintering mixture is too low, the granulation effect will be poor, there will be more fine materials, the air permeability of the material layer will be poor, and the phenomenon of not being burned through will occur, which will affect production efficiency and increase sintering energy consumption. If the moisture content of the sintering mixture is too high, over-dissolved and flaky sintering materials will stick to the trolley. Therefore, precise control of the amount of water added to the sintering mixture is a prerequisite for stable production of the entire sintering process.

[0003] Since most steel companies do not have advanced and intelligent detection equipment for the sintering and granulation process, they cannot automatically obtain key process parameters in real time, so they cannot form a fully closed-loop automatic control system for the water addition of the sintering mixer. At present, the traditional method of controlling the water content of the sintering mixture is to adjust it according to the manual experience value of the offline manual particle size detection results. This method is difficult to accurately and stably adjust the water content of the mixture, and the lag time is long, resulting in large fluctuations in the water content of the mixture and poor granulation effect, which seriously affects the efficiency of the sintering process and the quality of the sintered ore.

[0004] Therefore, the sintering granulation process in the metallurgical industry urgently needs an intelligent water addition control system and control method for a sintering mixer that can accurately control the opening degree of an electric regulating valve according to the particle size distribution range of the mixture. Summary of the invention

[0005] The purpose of the present invention is to provide a sintering mixer intelligent water adding control system and control method in view of the problems existing in the prior art.

[0006] To achieve the above object, the technical solution adopted by the present invention is: An intelligent water addition control system for a sintering mixer comprises an online particle size detection unit, a fuzzy control unit, a human-computer interaction display unit and a remote communication unit; the fuzzy control unit, the online particle size detection unit and the human-computer interaction display unit are wirelessly connected via the remote communication unit, and the fuzzy control unit receives a particle size distribution range set by the human interaction unit as a target value; the online particle size detection unit captures an image of a mixture and performs image recognition to obtain a particle size distribution result of the mixture; the fuzzy control unit controls the opening degree of an electric regulating valve according to the particle size distribution result of the online particle size detection unit; the human-computer interaction display unit receives the image of the mixture captured by the online particle size detection unit and the calculated particle size distribution result, and displays them in real time.

[0007] Furthermore, the fuzzy control unit includes a core controller, an electric control valve and an electromagnetic flowmeter. The fuzzy control unit communicates with the online particle size detection unit and the human-computer interaction display unit simultaneously through the remote communication unit. The fuzzy control unit receives the distribution result of the mixture particle size and the target particle size range data from the online particle size detection unit, and uses the deviation value of the mixture particle size range and the change in the deviation value as fuzzy input variables of the core controller. The core controller performs fuzzy reasoning according to a pre-established fuzzy control planning table to obtain the actual water volume adjustment requirement of the mixer, and outputs a signal to control the action of the electric control valve.

[0008] Furthermore, the online particle size detection unit includes a first industrial computer and a high-speed industrial camera. The high-speed industrial camera collects images of sintered mixtures. The first industrial computer uses deep learning-based image processing technology to identify image features of the mixture, and performs filtering, segmentation, and morphological operations on the mixture image to obtain the volume of the mixture and obtain the particle size distribution range of the mixture.

[0009] Furthermore, the human-machine interactive display unit includes a second industrial computer and a display, and the second industrial computer receives the mixture image taken by the online particle size detection unit and the calculated particle size distribution result, and displays them on the display in real time.

[0010] Furthermore, the remote communication unit includes a photoelectric converter and an optical module, and the online particle size detection unit sends the detection result and the control result to the display of the human-computer interaction display unit for display through the photoelectric converter; the human-computer interaction module sends the target particle size distribution range value of the mixture to the fuzzy control unit through the optical module.

[0011] A control method for an intelligent water adding control system of a sintering mixer comprises the following steps: S1: The human-computer interaction display unit sends the target particle size distribution range value of the mixture to the fuzzy control unit; S2: The particle size online detection unit obtains the particle size distribution range of the mixture; S3: The fuzzy control unit controls and adjusts the amount of water added in the mixer according to the particle size distribution result; S4: The human-computer interaction display unit receives the mixed material image taken by the online particle size detection unit and the calculated particle size distribution result, and displays them on the display in real time.

[0012] Further, in step S2, the specific steps of the online particle size detection unit obtaining the particle size distribution range of the mixture include: S21: industrial camera collects images of the mixture; S22: preprocessing the original image, converting the image captured by the industrial camera into a grayscale image and performing filtering and denoising; S23: Image segmentation, using an adaptive threshold segmentation algorithm to perform binarization processing on the pre-processed image; S24: morphological processing, performing morphological opening and closing operations on the noise generated after the image is binarized, and filtering out the image background noise and foreground noise; S25: Separation of adherent particles: using an improved watershed algorithm combining morphological reconstruction with distance transformation to separate adherent particles in the image; S26: Mixture particle size measurement, calibrate the industrial camera, determine the number of pixel values ​​corresponding to the unit area size, then calculate the number of pixels occupied by the particle projection area, calculate the actual projection area of ​​the mixture particles according to the corresponding relationship, and finally obtain the diameter of the mixture particles according to the area; S27: According to the total amount of the mixture and the diameter of each particle, the proportion of the mixture in each different particle size range is calculated.

[0013] Further, in step S3, the specific steps of the fuzzy control unit controlling and adjusting the amount of water added in the mixer according to the particle size distribution result include: S31: Variable fuzzification, determine the basic domain of the deviation e between the target particle size distribution range and the actual particle size distribution range, the change rate ec of the particle size range deviation, and the opening u of the electric control valve, and discretize the three variables according to the following formula: Among them, x∈[a,b],n is the discreteness; The three fuzzy variables particle size distribution range deviation E, deviation change rate EC, and electric control valve opening degree U are obtained; the fuzzy subsets of the three variables select the following language values: {NB (negative large), NM (negative medium), NS (negative small), ZO (zero), PS (positive small), PM (positive medium), PB (positive large}; S32: Establishing a membership function, the boundaries of the fuzzy variable particle size distribution range deviation E, the deviation change rate EC, and the electric control valve opening degree U select the bell-shaped membership function, and the middle selects the triangle membership function; S33: Establishing a fuzzy control rule table, collecting the experience and accumulated knowledge of the mixer granulation process experts at the sintering site to establish a control rule table for the mixer fuzzy control unit; S34: Fuzzy reasoning, the fuzzy relationship between input E, EC and output U is known from the fuzzy rule table, the fuzzy relationship submatrix Ri of each reasoning is calculated, and the fuzzy relationship matrix R is obtained by taking the union of all submatrices. The fuzzy quantity output U can be obtained from E, EC and R. The specific relationship is U=(ExEC)OR; S35: Defuzzification, defuzzification according to the weighted average method formula to obtain the actual opening control value u of the electric control valve; S36: The core controller outputs a signal to control the operation of the electric control valve according to the calculated opening value u of the electric control valve.

[0014] The beneficial effects of the present invention are: The control system described in the present application introduces an online particle size distribution detection unit and a fuzzy control unit with a high level of intelligence. The particle size detection unit captures an image of the mixture and performs image recognition to obtain the particle size distribution result of the mixture. The fuzzy control unit realizes precise control of the opening degree of the intelligent electric regulating water valve based on the particle size detection result.

[0015] The online particle size detection unit uses a technology that combines deep learning and image processing to process and identify the mixture image, derive the particle size distribution range of the mixture, and increase the perception function of the sintering granulation process. At the same time, the fuzzy control unit introduces a fuzzy control algorithm, and uses the fuzzy control algorithm to realize automatic control of the amount of water added to the mixer. This method applies the control experience of experienced operators and experts to the control process, organizes the control decision table according to the manual control rules, and then determines the water adjustment value of the mixer in combination with the particle size distribution range parameters of the mixture and the control decision table, and finally realizes intelligent water addition control of the mixer.

[0016] This system and method can reduce manual intervention, eliminate the impact of water volume regulation lag in the sintering mixer, achieve high efficiency and quality, energy saving and consumption reduction in the sintering process, and help steel companies achieve digital and intelligent development.

[0017] The control system and method can accurately, real-timely and intelligently adjust the amount of water added to the mixer according to the target particle size range, obtain a good mixer granulation effect, ensure the air permeability of the mixture, meet the realization of ultra-thick material layer sintering technology, improve the quality and strength of sintered ore, reduce sintering energy consumption, and realize the good wishes of steel enterprises to save energy and increase efficiency. At the same time, advanced technology and methods are used to detect the particle size of the mixture, realizing the development of the sintering granulation process from rough open production to fine intelligent production, and practicing the green and low-carbon development concept of the steel industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a system schematic diagram of an intelligent water adding control system and control method for a sintering mixer of the present invention. DETAILED DESCRIPTION

[0019] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] In the description of the present invention, it should be noted that the directions or positional relationships indicated by terms such as "middle", "upper", "lower", "left", "right", "inside" and "outside" are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on the present invention.

[0021] like Figure 1 As shown, the specific scheme of the embodiment is as follows: This embodiment provides an intelligent water adding control system for a sintering mixer.

[0022] It includes an online particle size detection unit, a fuzzy control unit, a human-machine interactive display unit and a remote communication unit. The fuzzy control unit, the online particle size detection unit and the human-machine interactive display unit are wirelessly connected through the remote communication unit, and the fuzzy control unit receives the particle size distribution range set by the human-machine interactive unit as a target value; the online particle size detection unit takes an image of the mixture and performs image recognition to obtain the particle size distribution result of the mixture; the fuzzy control unit controls the opening degree of the electric regulating valve according to the particle size distribution result of the online particle size detection unit; the human-machine interactive display unit receives the mixture image taken by the online particle size detection unit and the calculated particle size distribution result, and displays them in real time.

[0023] The fuzzy control unit includes a core controller, an electric regulating valve and an electromagnetic flowmeter. The fuzzy control unit is installed near the mixed material conveying belt equipment, and the core controller uses a high-performance industrial controller. The fuzzy control unit communicates with the online particle size detection unit and the human-computer interaction display unit through the remote communication unit. The core controller and the human-computer interaction display unit remotely communicate to receive the target particle size distribution range issued by the host computer, and at the same time receive data feedback from the online particle size detection unit to obtain the actual particle size distribution range.

[0024] Specifically, the fuzzy control unit receives the distribution result of the mixture particle size and the target particle size range data from the online particle size detection unit, and uses the deviation value of the mixture particle size range and the variation of the deviation value as the fuzzy input variables of the core controller. The core controller performs fuzzy reasoning according to the pre-established fuzzy control planning table to obtain the water volume adjustment demand of the actual mixer, calculates the opening value of the electric regulating valve, and outputs a signal to control the action of the electric regulating valve. The fuzzy control unit sends the detection results and control results to the human-computer interaction display unit for display. The data communication between the core controller and the human-computer interaction display unit is realized through the photoelectric converter module and the optical fiber.

[0025] The particle size online detection unit includes a first industrial computer and a high-speed industrial camera, which are installed together with the fuzzy control unit near the mixed material conveyor belt equipment. The industrial camera adopts a high-speed CCD or CMOS camera, and the camera is installed above the mixed material conveyor belt or at the transfer drop. Auxiliary lighting is required at the camera installation location, and the camera lens outlet is about 50 cm away from the mixed material surface.

[0026] The high-speed industrial camera collects images of the sintered mixture. The first industrial computer runs an image processing algorithm to process and identify the images taken by the industrial camera and calculate the actual particle size distribution. The image and data of the online particle size detection unit are transmitted to the human-computer interaction display unit through a photoelectric converter to achieve long-distance, stable and fast transmission of images and data. Specifically, the first industrial computer uses deep learning-based image processing technology to identify the image features of the mixture, filters, segments, and performs morphological operations on the mixture image, obtains the volume size of the mixture, and obtains the particle size distribution range of the mixture.

[0027] The human-machine interactive display unit includes a second industrial computer and a display. The human-machine interactive display unit has multiple functions of displaying data, querying data, sending instructions, parameter setting and remote login. The human-machine interactive display unit receives the mixed material image taken by the online particle size detection unit and the calculated particle size distribution result, and displays them on the display in real time, and can also send the target particle size distribution range value of the mixed material to the fuzzy control unit.

[0028] The remote communication unit includes a photoelectric converter and an optical module. The fuzzy control unit sends the detection results and control results to the display of the human-computer interaction display unit for display through the photoelectric converter; the human-computer interaction module sends the target particle size distribution range value of the mixture to the fuzzy control unit through the optical module.

[0029] This embodiment also provides a control method for an intelligent water adding control system of a sintering mixer, comprising the following steps.

[0030] S1: The human-computer interaction display unit sends the target particle size distribution range value of the mixture to the fuzzy control unit.

[0031] S2: The particle size online detection unit obtains the particle size distribution range of the mixture. The particle size online detection unit first uses the technology of deep learning and image processing to preprocess the mixture image, perform threshold segmentation, morphological processing, and use the improved watershed algorithm to separate the adhesion particles, then calculate the size of the mixture particles, and finally perform particle size distribution statistics. The specific steps are as follows.

[0032] S21: An industrial camera captures images of the mixture.

[0033] S22: Preprocess the original image, convert the image captured by the industrial camera into a grayscale image and perform filtering and denoising. First, the image captured by the industrial camera is converted into a grayscale image. In view of the situation where the grayscale value of the mixed material particles is similar to that of the background, the grayscale image is contrast enhanced. During the shooting process of the industrial camera, the image will have a certain degree of noise due to reasons such as complex background, lighting, and on-site dust. In order to reduce the impact of noise on image segmentation, filtering and denoising is an indispensable part. The present invention uses a median filtering algorithm to process the image and smooth the image noise.

[0034] S23: Image segmentation, using the adaptive threshold segmentation algorithm to binarize the pre-processed image. The pre-processed image is binarized and the adaptive threshold segmentation algorithm is used. This algorithm uses the integral image to avoid the problem that the local threshold algorithm needs to traverse the same pixel multiple times, effectively improving the efficiency of the algorithm. The image after binarization successfully separates the mixture particles from the background.

[0035] S24: Morphological processing, morphological opening and closing operations are performed on the noise generated after the image is binarized to filter out the image background noise and foreground noise. It can be seen from the mixed material image after threshold segmentation that some particles contain holes. This is because the metal ore particles reflect light, forming highlights. These highlights are similar to the background and are mistakenly identified as the background during segmentation, thus forming holes. The hole filling operation is used to solve this problem. Morphological opening and closing operations are performed on the noise generated after the image is binarized to filter out the image background noise and foreground noise.

[0036] S25: Separating the adhered particles. To solve the problem of overlapping particles in the mixed material image, the traditional watershed algorithm is prone to over-segmentation when segmenting the image. The present invention uses an improved watershed algorithm that combines morphological reconstruction with distance transformation to separate the adhered particles in the image.

[0037] S26: Mixture particle size measurement, calibrate the industrial camera, determine the number of pixel values ​​corresponding to the unit area size, then calculate the number of pixels occupied by the particle projection area, calculate the actual projection area of ​​the mixture particles according to the corresponding relationship, and finally obtain the diameter of the mixture particles according to the area; S27: According to the total amount of the mixture and the diameter of each particle, the proportion of the mixture in each different particle size range is calculated.

[0038] S3: The fuzzy control unit controls and adjusts the amount of water added in the mixer according to the particle size distribution results. The fuzzy control unit constructs the control relationship between the particle size distribution range of the mixture and the electric control valve of the mixer, U=(ExEC)OR, where R is the fuzzy relationship matrix R. The fuzzy control unit first fuzzifies the variables particle size distribution range deviation e, deviation change rate ec, and obtains three fuzzy variables: particle size distribution range deviation E, deviation change rate EC, and electric valve opening degree U. Then, a fuzzy control rule table is established. According to the fuzzy control rule table, the fuzzy relationship matrix R is obtained. According to the fuzzy control relationship U=(ExEC)OR, the opening value U of the electric control valve is determined, and finally, the precise opening degree u of the electric control valve is obtained by defuzzification.

[0039] In step S3, the specific steps of the fuzzy control unit controlling and adjusting the amount of water added in the mixer according to the particle size distribution result include: S31: Variable fuzzification, determine the basic domain of the deviation e between the target particle size distribution range and the actual particle size distribution range, the change rate ec of the particle size range deviation, and the opening u of the electric control valve, and discretize the three variables according to the following formula: Among them, x∈[a,b],n is the discreteness; The three fuzzy variables particle size distribution range deviation E, deviation change rate EC, and electric control valve opening degree U are obtained. The fuzzy subsets of the three variables select the following language values: {NB (negative large), NM (negative medium), NS (negative small), ZO (zero), PS (positive small), PM (positive medium), PB (positive large}; S32: Establish a membership function. Membership is the degree to which a certain quantity belongs to a certain fuzzy language variable. There are three common continuous membership functions in fuzzy control: bell-shaped, triangle, and trapezoid. In the present invention, the boundary part of the fuzzy variable particle size distribution range deviation E, deviation change rate EC, and electric control valve opening degree U selects the bell-shaped membership function, and the middle part selects the triangle membership function.

[0040] In a fuzzy control unit, the value of the particle size detection may have a certain range of fluctuations. For boundary values, such as the minimum or maximum acceptable range of the particle size, the bell-shaped membership function can handle these boundary conditions more delicately. If the particle size is close to the minimum acceptable value or the maximum acceptable value, the bell-shaped function can better reflect this fuzzy state close to the boundary, that is, it is neither completely unacceptable (the membership is not 0) nor completely acceptable (the membership is not 1). For the intermediate particle size values, these values ​​are often normal working or relatively ideal particle size ranges. The triangle membership function can simply and effectively represent the degree of membership of these intermediate values ​​in different fuzzy sets. For example, for the fuzzy concept of "moderate" particle size, the triangle membership function can accurately describe the membership of different particle size values ​​under this concept by adjusting the vertex position and base range of the triangle.

[0041] S33: Establishing a fuzzy control rule table. The control rule is the core of the fuzzy controller, and its correctness directly affects the performance of the controller. The present invention collects many years of valuable experience and accumulated knowledge of sintering site mixer granulation process experts to establish a control rule table for the mixer fuzzy control unit.

[0042] S34: Fuzzy reasoning, the fuzzy relationship between input E, EC and output U is known from the fuzzy rule table, the fuzzy relationship submatrix Ri of each reasoning is calculated, and the fuzzy relationship matrix R is obtained by taking the union of all submatrices. The fuzzy quantity output U can be obtained from E, EC and R. The specific relationship is U=(ExEC)OR; S35: Defuzzification, defuzzification according to the weighted average method formula to obtain the actual opening control value u of the electric control valve; S36: The core controller outputs a signal to control the operation of the electric control valve according to the calculated opening value u of the electric control valve.

[0043] S4: The human-computer interaction display unit receives the mixed material image taken by the online particle size detection unit and the calculated particle size distribution result, and displays them on the display in real time.

[0044] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent water adding control system for a sintering mixer, characterized in that: It includes an online particle size detection unit, a fuzzy control unit, a human-computer interaction display unit and a remote communication unit; the fuzzy control unit, the online particle size detection unit and the human-computer interaction display unit are wirelessly connected via the remote communication unit, and the fuzzy control unit receives the particle size distribution range set by the human interaction unit as a target value; the online particle size detection unit takes an image of the mixture and performs image recognition to obtain a particle size distribution result of the mixture; The fuzzy control unit controls the opening degree of the electric regulating valve according to the particle size distribution result of the online particle size detection unit; the human-computer interaction display unit receives the mixture image taken by the online particle size detection unit and the calculated particle size distribution result, and displays them in real time.

2. According to the intelligent water adding control system of a sintering mixer according to claim 1, it is characterized in that: The fuzzy control unit includes a core controller, an electric control valve and an electromagnetic flowmeter. The fuzzy control unit communicates with the online particle size detection unit and the human-computer interaction display unit simultaneously through the remote communication unit. The fuzzy control unit receives the distribution result of the mixture particle size and the target particle size range data from the online particle size detection unit, and uses the deviation value of the mixture particle size range and the change in the deviation value as fuzzy input variables of the core controller. The core controller performs fuzzy reasoning according to a pre-established fuzzy control planning table to obtain the actual water volume adjustment demand of the mixer, and outputs a signal to control the action of the electric control valve.

3. According to the intelligent water adding control system of a sintering mixer as claimed in claim 2, it is characterized in that: The online particle size detection unit includes a first industrial computer and a high-speed industrial camera. The high-speed industrial camera collects images of sintered mixtures. The first industrial computer uses deep learning-based image processing technology to identify image features of the mixture, and performs filtering, segmentation, and morphological operations on the mixture image to obtain the volume size of the mixture and obtain the particle size distribution range of the mixture.

4. According to the intelligent water adding control system of a sintering mixer as claimed in claim 3, it is characterized in that: The human-machine interactive display unit includes a second industrial computer and a display. The second industrial computer receives the mixed material image photographed by the online particle size detection unit and the calculated particle size distribution result, and displays them on the display in real time.

5. According to the intelligent water adding control system of a sintering mixer as claimed in claim 4, it is characterized in that: The remote communication unit includes a photoelectric converter and an optical module. The online particle size detection unit sends the detection result and the control result to the display of the human-computer interaction display unit for display through the photoelectric converter; the human-computer interaction module sends the target particle size distribution range value of the mixture to the fuzzy control unit through the optical module.

6. A control method for an intelligent water adding control system for a sintering mixer, characterized in that: The following steps are involved: S1: The human-computer interaction display unit sends the target particle size distribution range value of the mixture to the fuzzy control unit; S2: The particle size online detection unit obtains the particle size distribution range of the mixture; S3: The fuzzy control unit controls and adjusts the amount of water added in the mixer according to the particle size distribution result; S4: The human-computer interaction display unit receives the mixed material image taken by the online particle size detection unit and the calculated particle size distribution result, and displays them on the display in real time.

7. A control method for an intelligent water adding control system for a sintering mixer according to claim 6, characterized in that: In step S2, the specific steps of the online particle size detection unit obtaining the particle size distribution range of the mixture include: S21: industrial camera collects images of the mixture; S22: preprocessing the original image, converting the image captured by the industrial camera into a grayscale image and performing filtering and denoising; S23: Image segmentation, using an adaptive threshold segmentation algorithm to perform binarization processing on the pre-processed image; S24: morphological processing, performing morphological opening and closing operations on the noise generated after the image is binarized, and filtering out the image background noise and foreground noise; S25: Separation of adherent particles: using an improved watershed algorithm combining morphological reconstruction with distance transformation to separate adherent particles in the image; S26: Mixture particle size measurement, calibrate the industrial camera, determine the number of pixel values ​​corresponding to the unit area size, then calculate the number of pixels occupied by the particle projection area, calculate the actual projection area of ​​the mixture particles according to the corresponding relationship, and finally obtain the diameter of the mixture particles according to the area; S27: According to the total amount of the mixture and the diameter of each particle, the proportion of the mixture in each different particle size range is calculated.

8. A control method for an intelligent water adding control system for a sintering mixer according to claim 7, characterized in that: In step S3, the specific steps of the fuzzy control unit controlling and adjusting the amount of water added in the mixer according to the particle size distribution result include: S31: Variable fuzzification, determine the basic domain of the deviation e between the target particle size distribution range and the actual particle size distribution range, the change rate ec of the particle size range deviation, and the opening u of the electric control valve, and discretize the three variables according to the following formula: Among them, x∈[a,b],n is the discreteness; The three fuzzy variables particle size distribution range deviation E, deviation change rate EC, and electric control valve opening degree U are obtained; the fuzzy subsets of the three variables select the following language values: {NB (negative large), NM (negative medium), NS (negative small), ZO (zero), PS (positive small), PM (positive medium), PB (positive large}; S32: Establishing a membership function, the boundaries of the fuzzy variable particle size distribution range deviation E, the deviation change rate EC, and the electric control valve opening degree U select the bell-shaped membership function, and the middle selects the triangle membership function; S33: Establishing a fuzzy control rule table, collecting the experience and accumulated knowledge of the mixer granulation process experts at the sintering site to establish a control rule table for the mixer fuzzy control unit; S34: Fuzzy reasoning, the fuzzy relationship between input E, EC and output U is known from the fuzzy rule table, the fuzzy relationship submatrix Ri of each reasoning is calculated, and the fuzzy relationship matrix R is obtained by taking the union of all submatrices. The fuzzy quantity output U can be obtained from E, EC and R. The specific relationship is U=(ExEC)OR; S35: Defuzzification, defuzzification according to the weighted average method formula to obtain the actual opening control value u of the electric control valve; S36: The core controller outputs a signal to control the operation of the electric control valve according to the calculated opening value u of the electric control valve.

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