Flotation froth image analysis system based on pattern recognition

Abstract

The invention discloses a flotation froth image analysis system based on pattern recognition, relates to the technical field of flotation froth image analysis, and comprises an image analysis terminal used for controlling data transmission and information interaction among modules. According to the method, noise and irrelevant areas in the froth flotation image are removed firstly, density analysis and decrement analysis of follow-up froth are more convenient and accurate, then froth in the final froth flotation image is counted through a spot detection algorithm, the number of the froth is determined, then froth density information is calculated, and then the froth density information is calculated. The method comprises the steps that firstly, the position of foam is analyzed through a rectangular coordinate system, foam reduction amount information is determined, finally, the foam reduction amount information and foam density information are judged and analyzed, and whether the flotation reagent proportion needs to be changed or not is determined. And therefore, the judgment error of flotation froth can be increased, and the proportion of flotation reagents cannot be accurately regulated and controlled.

Description

Technical Field

[0001] The present invention relates to the technical field of flotation foam image analysis, and particularly to a flotation foam image analysis system based on pattern recognition. Background Art

[0002] The main process of froth flotation is that bubbles carry selectively but not tightly adhered mineral particles at the gas-liquid interface and rise in the pulp, and then the foam formed on the pulp surface is scraped off. This process has a simple concept but complex details. Its adaptability and effectiveness make froth flotation the most widely used method for separating complex and low-grade ores. More than 90% of the world's copper, lead, zinc, molybdenum, antimony, and nickel are recovered by froth flotation. Although the first froth flotation patents appeared in the 19th century, the equipment, technology, and understanding of flotation surface chemistry used are still evolving.

[0003] The flotation process is carried out in a flotation cell where foam is generated. Experienced workers usually rely on the naked eye to judge the density and reduction rate of the flotation foam. When workers stare at the flotation cell for a long time, they may get tired, which may increase the judgment error of the flotation foam and make it impossible to accurately control the proportion of flotation reagents. Summary of the Invention

[0004] To solve the above technical problems, a flotation foam image analysis system based on pattern recognition is provided. This technical solution solves the problem that in the flotation process carried out in a flotation cell where foam is generated, experienced workers usually rely on the naked eye to judge the density and reduction rate of the flotation foam. When workers stare at the flotation cell for a long time, they may get tired, which may increase the judgment error of the flotation foam and make it impossible to accurately control the proportion of flotation reagents.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows: A flotation foam image analysis system based on pattern recognition, comprising: An image analysis terminal, which is used to control each module to perform image preprocessing, foam density analysis, foam reduction amount analysis, foam density judgment, and foam reduction amount judgment on the flotation foam image, determine whether it is necessary to change the proportion of flotation reagents, and control data transmission and information interaction between each module; A database system, which is used to store the standard of foam existence duration; An image storage device, which is used to store the flotation foam image; An image preprocessing module, which performs image preprocessing on the flotation foam image to obtain a set of target flotation foam images; A foam density analysis module that performs density analysis on a set of target foam flotation images to obtain foam density information; It can be understood that when the proportion of flotation reagents does not meet the requirements, the number of generated foams will be small. Therefore, the number of foams is also a key parameter for whether the proportion of flotation reagents meets the standard; A foam reduction amount analysis module that performs stability analysis on a set of target foam flotation images to determine foam reduction amount information; It can be understood that when the maintenance time of the foam is short, that is, the foam breaks and reduces within a period of time, it can also reflect that the proportion of flotation reagents does not meet the standard. Because when the maintenance time of the foam is short, the metal particles attached to its surface will fall back into the water in the flotation cell again, and workers cannot collect this part of the metal, thereby reducing the metal collection efficiency; A foam density information judgment module that analyzes and processes the foam density information to determine the foam density level; A foam reduction amount information judgment module that analyzes and processes the foam reduction amount information to determine the foam reduction amount level; A foam level analysis module that analyzes and processes the foam density level and the foam reduction amount level to determine whether it is necessary to change the proportion of flotation reagents.

[0006] Preferably, the image preprocessing module performs image preprocessing on the foam flotation image to obtain a set of target foam flotation images, which specifically includes the following steps: Based on the image analysis terminal, perform image extraction processing on the image storage device to obtain the foam flotation image; Based on the image analysis terminal, perform image feature preprocessing on the foam flotation image to obtain the target foam flotation image. The image feature preprocessing includes feature denoising, feature enhancement, and cropping of irrelevant regions; It can be understood that there are irrelevant regions and irrelevant features in the image. Therefore, in order to reduce the calculation amount and reduce errors, the irrelevant regions and irrelevant features are removed; Based on the image analysis terminal, perform analysis and processing on the target foam flotation image to obtain a set of target foam flotation images.

[0007] Preferably, the step of performing analysis and processing on the target foam flotation image based on the image analysis terminal to obtain a set of target foam flotation images specifically includes the following steps: Based on the image analysis terminal, perform image splitting processing on the target foam flotation image with the time unit of seconds as the feature to obtain several groups of target foam flotation pictures; Based on the image analysis terminal, uniquely mark several groups of target foam flotation images with the continuity of time to obtain several groups of target foam flotation pictures with time information; Based on the image analysis terminal, perform sorting and collection processing on several groups of target foam flotation pictures with time information with the continuity of time as the feature to obtain the target foam flotation image set.

[0008] Preferably, the foam density analysis module performs density analysis on the target foam flotation image set to obtain foam density information, which specifically includes the following steps: Based on the image analysis terminal, perform data extraction processing on the database system to obtain relevant parameter information of the flotation cell; Based on the image analysis terminal, perform data extraction processing on the relevant parameter information of the flotation cell to obtain the size information of the flotation cell mouth, and the size information of the flotation cell mouth is specifically the length data of the flotation cell mouth and the width data of the flotation cell mouth; Based on the image analysis terminal, perform calculation processing on the size information of the flotation cell mouth to obtain the area data of the flotation cell mouth; Based on the image analysis terminal, perform analysis processing on the area data of the flotation cell mouth and the target foam flotation image set to obtain foam density information.

[0009] Preferably, the image analysis terminal performs analysis processing on the area data of the flotation cell mouth and the target foam flotation image set to obtain foam density information, which specifically includes the following steps: Based on the image analysis terminal, perform screening processing on the time information of the target foam flotation pictures to determine the final foam flotation pictures; Based on the image analysis terminal, perform feature extraction processing on the final foam flotation pictures to obtain the number of foams; Based on the image analysis terminal, perform calculation processing on the number of foams and the area data of the flotation cell mouth to obtain foam density information.

[0010] Preferably, the foam reduction amount analysis module performs stability analysis on the target foam flotation image set to determine foam reduction amount information, which specifically includes the following steps: Based on the image analysis terminal, perform data reading processing on the database system to obtain the standard of foam existence duration; Based on the image analysis terminal, perform splitting processing on the target foam flotation image set with the standard of foam existence duration as the feature to obtain multiple groups of target foam flotation picture subsets; Based on the image analysis terminal, perform image extraction processing on multiple groups of target foam flotation picture subsets with the continuity of time as the feature to obtain the initial image of the subset and the final image of the subset; Based on the image analysis terminal, analyze and process the initial subset image and the final subset image to determine the foam reduction amount information.

[0011] Preferably, the step of analyzing and processing the initial subset image and the final subset image by the image analysis terminal to determine the foam reduction amount information specifically includes the following steps: Based on the image analysis terminal, set the lower left corner of the initial subset image as the coordinate origin, the horizontal direction of the initial subset image as the X-axis, and the vertical direction of the initial subset image as the Y-axis to obtain a rectangular coordinate system. The image analysis terminal marks the foam positions in the initial subset image and the final subset image through the rectangular coordinate system to obtain the initial foam position and the final foam position. Based on the image analysis terminal, perform information matching processing on the final foam position with the initial foam position as a feature to obtain the foam reduction amount information.

[0012] Preferably, the step of analyzing and processing the foam density information by the foam density information judgment module to determine the foam density grade specifically includes the following steps: Based on the image analysis terminal, judge and process the foam density information and the set foam density threshold. If the foam density information is greater than or equal to the set first foam density threshold, the foam density grade is excellent. If the foam density information is less than the set first foam density threshold and greater than or equal to the set second foam density threshold, the foam density grade is good. If the foam density information is less than the set second foam density threshold, the foam density grade is poor.

[0013] Preferably, the step of analyzing and processing the foam reduction amount information by the foam reduction amount information judgment module to determine the foam reduction amount grade specifically includes the following steps: Based on the image analysis terminal, judge the foam reduction amount information and the set foam reduction amount threshold. If the foam reduction amount information is greater than or equal to the set first foam reduction amount threshold, the foam reduction amount grade is poor. If the foam reduction amount information is less than the set first foam reduction amount threshold and greater than or equal to the set second foam reduction amount threshold, the foam reduction amount grade is good. If the foam reduction amount information is less than the second foam reduction amount threshold, the foam reduction amount grade is excellent.

[0014] Preferably, for the foam grade analysis module, the step of analyzing and processing the foam density grade and the foam reduction amount grade by the foam grade analysis module to determine whether to change the proportion of flotation reagents specifically includes the following steps: If the foam density grade is excellent or good, and the foam reduction amount grade is excellent or good, the image analysis terminal records the proportion of the flotation reagent; If the foam density grade is excellent or good, and the foam reduction amount grade is poor, the image analysis terminal generates information indicating that the proportion of the flotation reagent needs to be changed, and the image analysis terminal sends the information indicating that the proportion of the flotation reagent needs to be changed to the external display terminal; If the foam density grade is poor, the image analysis terminal generates information indicating that the proportion of the flotation reagent needs to be changed, and the image analysis terminal sends the information indicating that the proportion of the flotation reagent needs to be changed to the external display terminal.

[0015] Furthermore, a flotation foam image analysis method based on pattern recognition is proposed for use in the flotation foam image analysis system based on pattern recognition as described above, including: S1. Based on the image analysis terminal, control the image preprocessing module to perform image feature denoising, feature enhancement, cropping of irrelevant regions, and image splitting on the foam flotation image to obtain a set of target foam flotation images; S2. Based on the image analysis terminal, control the foam density analysis module to perform density calculation processing on the area data and the number of foams at the mouth of the flotation cell to obtain foam density information; S3. Based on the image analysis terminal, control the foam reduction amount analysis module to match the initial foam position and the final foam position to determine the foam reduction amount information, where both the initial foam position and the final foam position are two-dimensional coordinates; S4. Based on the image analysis terminal, control the foam density information judgment module to perform judgment processing on the foam density information and the set foam density threshold to determine the foam density grade; S5. Based on the image analysis terminal, control the foam reduction amount information judgment module to perform judgment on the foam reduction amount information and the set foam reduction amount threshold to determine the foam reduction amount grade; S6. Based on the image analysis module, control the foam grade analysis module to perform analysis processing on the foam density grade and the foam reduction amount grade to determine whether the proportion of the flotation reagent needs to be changed.

[0016] Still further, a storage medium is proposed, on which a computer program is stored, and when the computer program is called and run, it executes a flotation foam image analysis method based on pattern recognition as described above.

[0017] Compared with the prior art, the present invention provides a flotation foam image analysis system based on pattern recognition, having the following beneficial effects: The present invention first preprocesses the froth flotation image to remove noise and irrelevant regions in the froth flotation image, and splits the froth flotation image into static pictures, making the subsequent density analysis and reduction analysis of the froth more convenient and accurate. Secondly, the froth in the final froth flotation picture is counted through a spot detection algorithm to determine the number of froths, and then the froth density information is calculated. Then, the position of the froth is analyzed through a rectangular coordinate system to determine the froth reduction information. Finally, the froth reduction information and the froth density information are judged and analyzed to determine whether it is necessary to change the proportion of the flotation reagent. The above method avoids the problem that workers may be fatigued when staring at the flotation cell for a long time, which may increase the judgment error of the flotation froth and make it impossible to accurately control the proportion of the flotation reagent. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 FIG. is a structural block diagram of a froth flotation image analysis system based on pattern recognition proposed by the present invention; Figure 2 FIG. is a schematic flow chart of obtaining a set of target froth flotation images proposed by the present invention; Figure 3 FIG. is a schematic flow chart of obtaining froth density information proposed by the present invention; Figure 4 FIG. is a schematic flow chart of determining froth reduction information proposed by the present invention; Figure 5 FIG. is a schematic flow chart of determining froth density level proposed by the present invention; Figure 6 FIG. is a schematic flow chart of determining froth reduction level proposed by the present invention; Figure 7 FIG. is a schematic flow chart of determining whether it is necessary to change the proportion of the flotation reagent proposed by the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0019] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations.

[0020] Referring to Figure 1 as shown, a froth flotation image analysis system based on pattern recognition includes: An image analysis terminal, which is used to control each module to perform image preprocessing, froth density analysis, froth reduction analysis, froth density judgment, and froth reduction judgment on the froth flotation image, determine whether it is necessary to change the proportion of the flotation reagent, and control data transmission and information interaction between each module; A database system, which is used to store the froth existence duration standard; An image storage device for storing froth flotation images; An image preprocessing module for preprocessing the froth flotation images to obtain a set of target froth flotation images; A foam density analysis module for performing density analysis on the set of target froth flotation images to obtain foam density information; A foam reduction amount analysis module for performing stability analysis on the set of target froth flotation images to determine foam reduction amount information; A foam density information judgment module for analyzing and processing the foam density information to determine the foam density grade; A foam reduction amount information judgment module for analyzing and processing the foam reduction amount information to determine the foam reduction amount grade; A foam grade analysis module for analyzing and processing the foam density grade and the foam reduction amount grade to determine whether to change the proportion of flotation reagents; In this embodiment, after the metal is broken, the metal particles are attached to the foam generated in the flotation cell through reagents, thereby realizing the separation of the metal. However, the density of the foam and the dissipation time of the foam affect the efficiency of metal classification. The existing judgment of flotation foam is carried out by the naked eye of experienced workers. When workers stare at the flotation cell for a long time, it may cause visual fatigue, and thus may increase the judgment error of flotation foam, and it is impossible to accurately control the proportion of flotation reagents. Therefore, by performing foam density analysis, foam reduction amount analysis, foam density judgment, and foam reduction amount judgment on the froth flotation images, it is determined whether to adjust the proportion of flotation reagents, which reduces the working intensity of workers while improving the accuracy of froth flotation. In addition, the proportion of flotation reagents can be accurately controlled through the state of the foam.

[0021] Refer to Figure 2 As shown, the steps for the image preprocessing module to preprocess the froth flotation images to obtain a set of target froth flotation images are as follows: Based on the image analysis terminal, perform image extraction processing on the image storage device to obtain froth flotation images; Based on the image analysis terminal, perform image feature preprocessing on the froth flotation images to obtain target froth flotation images, and the image feature preprocessing includes feature denoising, feature enhancement, and cropping of irrelevant regions; Based on the image analysis terminal, perform analysis and processing on the target froth flotation images to obtain a set of target froth flotation images; Among them, based on the image analysis terminal, analyzing and processing the target froth flotation image to obtain the target froth flotation image set specifically includes the following steps: Based on the image analysis terminal, perform image splitting processing on the target froth flotation image with seconds as the time unit to obtain several groups of target froth flotation pictures; Based on the image analysis terminal, perform unique marking on several groups of target froth flotation images with the continuity of time as the feature to obtain several groups of target froth flotation pictures with time information; Based on the image analysis terminal, perform sorting and collection processing on several groups of target froth flotation pictures with time information with the continuity of time as the feature to obtain the target froth flotation image set; In this embodiment, there are not only foam features but also other features in the froth flotation image, such as environmental features, flotation cell features, etc. In order to reduce the computational complexity of subsequent analysis, the froth flotation image is cropped to remove irrelevant features and retain foam features. At the same time, in order to make the subsequent counting of foam quantity more accurate, the foam features are enhanced. In the subsequent steps, it is necessary to determine the foam reduction amount information. Therefore, the target froth flotation image is split into individual images, and the number of foams is determined by analyzing each image. However, the change in the number of foams occurs within a time range. Therefore, the split pictures are marked with time information, and the marking is unique, making the subsequent analysis orderly.

[0022] Refer to Figure 3 As shown, the foam density analysis module performs density analysis on the target froth flotation image set to obtain the foam density information, which specifically includes the following steps: Based on the image analysis terminal, perform data extraction processing on the database system to obtain the relevant parameter information of the flotation cell; Based on the image analysis terminal, perform data extraction processing on the relevant parameter information of the flotation cell to obtain the size information of the flotation cell orifice, and the size information of the flotation cell orifice is specifically the length data of the flotation cell orifice and the width data of the flotation cell orifice; Based on the image analysis terminal, perform calculation processing on the size information of the flotation cell orifice to obtain the area data of the flotation cell orifice; Based on the image analysis terminal, perform analysis processing on the area data of the flotation cell orifice and the target froth flotation image set to obtain the foam density information; Among them, based on the image analysis terminal, performing analysis processing on the area data of the flotation cell orifice and the target froth flotation image set to obtain the foam density information specifically includes the following steps: Based on the image analysis terminal, perform screening processing on the time information of the target froth flotation pictures to determine the final froth flotation pictures; Based on the image analysis terminal, perform feature extraction processing on the final foam flotation pictures to obtain the foam quantity; Based on the image analysis terminal, perform calculation processing on the foam quantity and the area data of the flotation cell notch to obtain the foam density information; In this embodiment, workers can collect metals by collecting the foam, and the last picture in the foam flotation image is the finally determined quantity of the foam. Therefore, by comparing the time information of the target foam pictures, the pictures with the last time information are screened out, and feature extraction is performed on them through the spot detection algorithm to obtain the foam quantity. The foam quantity here is the quantity of the foam finally collected by the workers. Therefore, by screening the final foam flotation pictures, the foam density information is obtained.

[0023] Refer to Figure 4 As shown, the foam reduction amount analysis module performs stability analysis on the target foam flotation image set to determine the foam reduction amount information, which specifically includes the following steps: Based on the image analysis terminal, perform data reading processing on the database system to obtain the foam existence duration standard; Based on the image analysis terminal, perform splitting processing on the target foam flotation image set with the foam existence duration standard as a feature to obtain multiple groups of target foam flotation picture subsets; Based on the image analysis terminal, perform image extraction processing on multiple groups of target foam flotation picture subsets with the continuity of time as a feature to obtain the initial image and the final image of the subset; Based on the image analysis terminal, perform analysis processing on the initial image and the final image of the subset to determine the foam reduction amount information; Among them, based on the image analysis terminal, performing analysis processing on the initial image and the final image of the subset to determine the foam reduction amount information specifically includes the following steps: Based on the image analysis terminal, set the lower left corner of the initial image of the subset as the coordinate origin, the horizontal direction of the initial image of the subset as the X-axis, and the vertical direction of the initial image of the subset as the Y-axis to obtain a rectangular coordinate system; The image analysis terminal performs marking processing on the foam positions in the initial image and the final image of the subset through the rectangular coordinate system to obtain the initial foam position and the final foam position; Based on the image analysis terminal, perform information matching processing on the final foam position with the initial foam position as a feature to obtain the foam reduction amount information; In this embodiment, in order to accurately obtain the reduction amount of foam, a rectangular coordinate system is constructed to locate the foam in the image, and it is determined whether the foam has decreased based on the coordinate information of each foam in two pictures. Because when the proportion of flotation reagents is inappropriate, the maintenance time of the foam will become shorter. After the foam breaks, the metal particles attached to the foam will also sink and float in the flotation cell, and workers will not be able to collect this part of the metal, thereby reducing the metal collection efficiency. It should be noted that the longer the maintenance time of the foam, the lower the reduction amount of the foam.

[0024] Referring to Figure 5 As shown, the foam density information judgment module analyzes and processes the foam density information to determine the foam density level, which specifically includes the following steps: Based on the image analysis terminal, the foam density information is judged and processed with the set foam density threshold; If the foam density information is greater than or equal to the set first foam density threshold, the foam density level is excellent; If the foam density information is less than the set first foam density threshold and greater than or equal to the set second foam density threshold, the foam density level is good; If the foam density information is less than the set second foam density threshold, the foam density level is poor; In this embodiment, the proportion of flotation reagents not only affects the foam density but also affects the maintenance time of the foam. Therefore, analyzing the foam density can determine whether the proportion of flotation reagents meets the requirements and whether it is necessary to change the proportion of flotation reagents.

[0025] Referring to Figure 6 As shown, the foam reduction amount information judgment module analyzes and processes the foam reduction amount information to determine the foam reduction amount level, which specifically includes the following steps: Based on the image analysis terminal, the foam reduction amount information is judged with the set foam reduction amount threshold; If the foam reduction amount information is greater than or equal to the set first foam reduction amount threshold, the foam reduction amount level is poor; If the foam reduction amount information is less than the set first foam reduction amount threshold and greater than or equal to the set second foam reduction amount threshold, the foam reduction amount level is good; If the foam reduction amount information is less than the second foam reduction amount threshold, the foam reduction amount level is excellent.

[0026] Referring to Figure 7 As shown, the foam level analysis module analyzes and processes the foam density level and the foam reduction amount level to determine whether it is necessary to change the proportion of flotation reagents, which specifically includes the following steps: If the foam density grade is excellent or good, and the foam reduction grade is excellent or good, the imaging analysis terminal records the proportion of the flotation reagent; If the foam density grade is excellent or good, and the foam reduction grade is poor, the imaging analysis terminal generates information indicating that the proportion of the flotation reagent needs to be changed, and the imaging analysis terminal sends the information indicating that the proportion of the flotation reagent needs to be changed to the external display terminal; If the foam density grade is poor, the imaging analysis terminal generates information indicating that the proportion of the flotation reagent needs to be changed, and the imaging analysis terminal sends the information indicating that the proportion of the flotation reagent needs to be changed to the external display terminal; In this embodiment, by performing grade analysis on the foam density grade and the foam reduction grade, it is possible to determine whether the proportion of the flotation reagent meets the standard. Therefore, by determining the foam density information and the foam reduction information through the above method, it is possible to directly obtain whether the proportion of the flotation reagent meets the requirements.

[0027] The foregoing has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and the principles described in the specification are only the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A flotation foam image analysis system based on pattern recognition, characterized in that: include: An image analysis terminal, which is used to control each module to perform image preprocessing, foam density analysis, foam reduction analysis, foam density judgment and foam reduction judgment on the foam flotation image, determine whether the flotation reagent ratio needs to be changed, and control data transmission and information interaction between each module; A database system, the database system being used to store a standard of foam existence duration; An image storage device, the image storage device being used to store froth flotation images; An image preprocessing module, which performs image preprocessing on the froth flotation image to obtain a target froth flotation image set; A foam density analysis module, which performs density analysis on a target foam flotation image set to obtain foam density information; A foam reduction analysis module, which performs stability analysis on a target foam flotation image set to determine foam reduction information; A foam density information determination module, which analyzes and processes the foam density information to determine the foam density level; A foam reduction amount information determination module, which analyzes and processes the foam reduction amount information to determine the foam reduction amount level; A foam level analysis module analyzes and processes the foam density level and the foam reduction level to determine whether the flotation reagent ratio needs to be changed.

2. A flotation foam image analysis system based on pattern recognition according to claim 1, characterized in that: The image preprocessing module performs image preprocessing on the froth flotation image to obtain a target froth flotation image set, specifically comprising the following steps: Based on the image analysis terminal, the image storage device is processed for image extraction to obtain the froth flotation image; Based on the image analysis terminal, the foam flotation image is preprocessed with image features to obtain the target foam flotation image, wherein the image feature preprocessing includes feature denoising, feature enhancement and irrelevant area cropping; Based on the image analysis terminal, the target foam flotation image is analyzed and processed to obtain a target foam flotation image set.

3. A flotation foam image analysis system based on pattern recognition according to claim 2, characterized in that: The method of analyzing and processing the target foam flotation image based on the image analysis terminal to obtain the target foam flotation image set specifically includes the following steps: Based on the image analysis terminal, the target foam flotation image is split and processed with the time unit second as the feature to obtain several groups of target foam flotation images; Based on the image analysis terminal, several groups of target foam flotation images are uniquely marked with the time continuity as a feature, and several groups of target foam flotation images with time information are obtained; Based on the image analysis terminal, several groups of target foam flotation pictures with time information are sorted and collected based on the time continuity feature to obtain a target foam flotation image set.

4. The flotation foam image analysis system based on pattern recognition according to claim 1, characterized in that: The foam density analysis module performs density analysis on the target foam flotation image set to obtain foam density information, specifically including the following steps: Based on the image analysis terminal, the database system is processed for data extraction to obtain relevant parameter information of the flotation cell; Based on the image analysis terminal, data extraction and processing are performed on the relevant parameter information of the flotation cell to obtain the size information of the flotation cell slot, wherein the size information of the flotation cell slot is specifically the length data of the flotation cell slot and the width data of the flotation cell slot; Based on the image analysis terminal, the size information of the flotation tank slot is calculated and processed to obtain the area data of the flotation tank slot; Based on the image analysis terminal, the area data of the flotation tank notch and the target froth flotation image set are analyzed and processed to obtain the froth density information.

5. The flotation foam image analysis system based on pattern recognition according to claim 4, characterized in that: The image analysis terminal is used to analyze and process the area data of the flotation tank notch and the target froth flotation image set to obtain the froth density information, which specifically includes the following steps: Based on the image analysis terminal, the time information of the target foam flotation picture is screened and processed to determine the final foam flotation picture; Based on the image analysis terminal, feature extraction and processing are performed on the final foam flotation image to obtain the foam quantity; Based on the image analysis terminal, the foam quantity and the area data of the flotation tank notch are calculated and processed to obtain the foam density information.

6. The flotation foam image analysis system based on pattern recognition according to claim 1, characterized in that: The foam reduction analysis module performs stability analysis on the target foam flotation image set to determine the foam reduction information, specifically including the following steps: Based on the image analysis terminal, the database system is read and processed to obtain the standard of foam existence time; Based on the image analysis terminal, the target foam flotation image set is split and processed based on the foam existence time standard to obtain multiple groups of target foam flotation image subsets; Based on the image analysis terminal, image extraction and processing are performed on multiple target foam flotation image subsets with time continuity as the feature, and the initial image and final image of the subset are obtained; Based on the image analysis terminal, the subset initial image and the subset final image are analyzed and processed to determine the foam reduction amount information.

7. A flotation foam image analysis system based on pattern recognition according to claim 6, characterized in that: The method of analyzing and processing the subset initial image and the subset final image based on the image analysis terminal to determine the foam reduction amount information specifically includes the following steps: Based on the image analysis terminal, the lower left corner of the initial image of the subset is set as the coordinate origin, the horizontal direction of the initial image of the subset is set as the X axis, and the vertical direction of the initial image of the subset is set as the Y axis to obtain a rectangular coordinate system; The image analysis terminal marks the foam positions in the initial image of the subset and the final image of the subset through a rectangular coordinate system to obtain the initial foam position and the final foam position; Based on the image analysis terminal, the final foam position is matched with the initial foam position as a feature to obtain the foam reduction information.

8. The flotation foam image analysis system based on pattern recognition according to claim 1, characterized in that: The foam density information determination module analyzes and processes the foam density information to determine the foam density level, specifically including the following steps: Based on the image analysis terminal, the foam density information and the set foam density threshold are judged and processed; If the foam density information is greater than or equal to the set first foam density threshold, the foam density level is excellent; If the foam density information is less than the set first foam density threshold, and the foam density information is greater than or equal to the set second foam density threshold, the foam density level is good; If the foam density information is less than the set second foam density threshold, the foam density level is poor.

9. The flotation foam image analysis system based on pattern recognition according to claim 1, characterized in that: The foam reduction amount information determination module analyzes and processes the foam reduction amount information to determine the foam reduction amount level, specifically including the following steps: Based on the image analysis terminal, the foam reduction information and the set foam reduction threshold are judged; If the foam reduction amount information is greater than or equal to the set first foam reduction amount threshold, the foam reduction amount level is poor; If the foam reduction amount information is less than the set first foam reduction amount threshold, and the foam reduction amount information is greater than or equal to the set second foam reduction amount threshold, the foam reduction amount level is good; If the foam reduction amount information is less than the second foam reduction amount threshold, the foam reduction amount level is excellent.

10. The flotation foam image analysis system based on pattern recognition according to claim 1, characterized in that: The foam level analysis module analyzes and processes the foam density level and the foam reduction level to determine whether the flotation reagent ratio needs to be changed, and specifically includes the following steps: If the foam density grade is excellent or good, and the foam reduction grade is excellent or good, the image analysis terminal records the proportion of flotation reagent; If the foam density level is excellent or good, and the foam reduction level is poor, the image analysis terminal generates information that the flotation reagent ratio needs to be changed, and the image analysis terminal sends the information that the flotation reagent ratio needs to be changed to the external display terminal; If the foam density level is poor, the image analysis terminal generates information that the flotation agent ratio needs to be changed, and the image analysis terminal sends the information that the flotation agent ratio needs to be changed to the external display terminal.

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