Flotation detection method, apparatus, and computer program product

Abstract

The application provides a flotation detection method, device and computer program product, the method comprising: obtaining measurement data, corresponding measurement point position, corresponding detection time and corresponding quality-related data; calculating a flotation parameter according to the measurement data; calculating an image quality factor, a pressure quality factor, an electrical conductivity quality factor and a time synchronization quality factor according to the quality-related data of the measurement data; performing weighted summation on the image quality factor, the pressure quality factor, the electrical conductivity quality factor and the time synchronization quality factor to obtain a comprehensive quality factor; when the comprehensive quality factor is greater than or equal to a first quality threshold, correcting the flotation parameter corresponding to the measurement data according to the measurement point position and the detection time of the measurement data to obtain a corrected flotation parameter; and judging a flotation state according to the corrected flotation parameter, thereby solving the problems of misdiagnosis caused by image occlusion, pressure disturbance, sensor zero drift, electrode pollution, time stamp asynchronization and different measurement point positions.

Description

Technical Field

[0001] This application relates to the fields of multivariable measurement, fluid pressure and flow detection, image data recognition, and mineral processing monitoring. Specifically, it relates to a flotation detection method, apparatus, computer-readable storage medium, and computer program product. Background Technology

[0002] Flotation is an important method for separating valuable minerals from gangue minerals by utilizing the differences in the physicochemical properties of mineral particle surfaces. Bubbles are the carriers for the selective adhesion and flotation of mineral particles, and their size distribution, apparent gas velocity, gas holdup, and bubble surface flux directly reflect the gas dispersion and effective interface supply status within the flotation cell. Obtaining these parameters typically requires the simultaneous use of image measurement, fluid pressure measurement, conductivity measurement, liquid level or flow rate measurement, and data acquisition devices. Therefore, the synchronicity, spatial consistency, and measurement reliability of these multi-parameter detection devices directly affect the state identification results.

[0003] Current industrial operations typically rely on indicators such as air volume, valve opening, foam appearance, liquid level, reagent dosage, grade, and recovery rate as operational criteria. However, air volume and valve opening cannot directly characterize the actual apparent gas velocity and bubble dispersion state inside the flotation cell; foam appearance is subjective and has a time lag; and grade and recovery rate are outcome-based indicators. Existing bubble image measurement devices, pressure measurement devices, and conductivity measurement devices are usually independent, with inconsistent measurement point locations, sampling cycles, timestamps, and quality evaluation standards, making it difficult to generate multi-parameter synchronous measurement results that can be directly used for online identification.

[0004] Existing technologies include methods for bubble image measurement, apparent gas velocity measurement, gas holdup measurement, bubble surface area flux calculation, and flotation foam image recognition. For example, image measurement can obtain the Sauter average bubble diameter D. 32 And bubble size distribution BSD; apparent gas velocity J can be obtained by pressure accumulation method or liquid level drop method. g The gas holdup E can be obtained by the conductivity method or the differential pressure method. g Basic bubble surface area flux S b J g and D 32 Calculations are needed. However, existing solutions often focus on a single sensor, a single parameter, or a foam surface image, lacking a technical solution that integrates an image detection unit, a pressure accumulation measurement unit, a gas holdup conductivity measurement unit, a synchronous acquisition unit, and a data processing unit into a unified detection device. Directly combining data obtained from different devices at different times and locations can easily lead to parameter mismatches; on-site image occlusion, pressure disturbances, sensor zero drift, electrode contamination, and timestamp asynchrony can also cause misdiagnosis. Summary of the Invention

[0005] The main objective of this application is to provide a flotation detection method, apparatus, computer-readable storage medium, and computer program product to at least solve the problems of misdiagnosis caused by on-site image occlusion, pressure disturbance, sensor zero drift, electrode contamination, timestamp asynchrony, and different measurement point locations in the prior art.

[0006] To achieve the above objectives, according to one aspect of this application, a flotation detection method is provided, comprising: acquiring measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data, wherein the measurement data includes a bubble image sequence, gas pressure, and apparent conductivity of the gas-bearing slurry; calculating flotation parameters based on the measurement data, wherein the flotation parameters include bubble size parameters, apparent gas velocity, and gas holdup; calculating an image quality factor based on the quality-related data of the bubble image sequence, a pressure quality factor based on the quality-related data of the gas pressure, a conductivity quality factor based on the quality-related data of the apparent conductivity of the gas-bearing slurry, and a time synchronization quality factor based on the time deviation of the detection time of the measurement data; performing a weighted summation of the image quality factor, the pressure quality factor, the conductivity quality factor, and the time synchronization quality factor to obtain a comprehensive quality factor; if the comprehensive quality factor is greater than or equal to a first quality threshold, correcting the flotation parameters corresponding to the measurement data based on the measurement point locations and the detection time of the measurement data to obtain corrected flotation parameters; and determining the flotation state based on the corrected flotation parameters.

[0007] Optionally, acquiring measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data includes: acquiring the measurement data detected by each detection unit of the integrated detection device within a unified time window, and recording the measurement point locations, detection times, and corresponding quality-related data detected by each detection unit. The detection unit of the integrated detection device includes a bubble image detection unit, an apparent gas velocity and pressure measurement unit, and a gas holdup conductivity measurement unit.

[0008] Optionally, the bubble size parameters include average bubble diameter, bubble size distribution, small bubble ratio, and bubble size distribution width. The flotation parameters also include effective bubble surface area flux. The flotation parameters are calculated based on the measurement data, including: identifying the bubble image sequence to obtain the equivalent diameter of each effective bubble; and... The average bubble diameter was calculated, where D 32 Let d be the average bubble diameter. i Let n be the average particle size in the i-th particle size range. iThe number of bubbles in the i-th particle size interval is given; the ratio of the number of effective bubbles smaller than the diameter threshold to the total number of effective bubbles is calculated to obtain the proportion of small bubbles; the bubble size distribution is generated based on the equivalent diameter of the effective bubbles, which is a curve showing the change of the proportion of effective bubbles with different equivalent diameters as a function of the equivalent diameter; two boundary particle sizes and a median particle size are determined based on the equivalent diameter of each effective bubble, and the ratio of the difference between the two boundary particle sizes to the median particle size is calculated to obtain the bubble size distribution width; through... The apparent gas velocity was calculated, where J g Let V be the apparent gas velocity. t Let A0 be the equivalent volume of gas participating in compression within the measuring tube, and P be the bottom opening area of ​​the measuring tube. abs dP / dt is the absolute gas pressure at the measuring point, dP / dt is the pressure rise slope, and K is the absolute pressure at the measuring point. p This is a comprehensive correction factor for pressure, liquid level, slurry density, temperature, and depth of the measuring point; through... The gas holdup was calculated, wherein, E g The gas content is denoted as r, where r is the ratio of the apparent conductivity of the gas-bearing slurry to that of the non-gas-bearing slurry, and k is the gas content. aerated k is the apparent conductivity of the gas-bearing slurry. pulp The apparent conductivity of the gas-free slurry; through The basic bubble surface area flux was calculated, where S b The basic bubble surface area flux is given; the effective bubble surface area flux is obtained by correcting the basic bubble surface area flux based on the gas holdup, the proportion of small bubbles, the comprehensive quality factor, and the process section weight.

[0009] Optionally, an image quality factor is calculated based on the quality correlation data of the bubble image sequence, a pressure quality factor is calculated based on the quality correlation data of the gas pressure, a conductivity quality factor is calculated based on the quality correlation data of the apparent conductivity of the gas-bearing slurry, and a time synchronization quality factor is calculated based on the time deviation of the detection time of the measurement data, including: through... The image quality factor is calculated, where Q N Q represents the effective number of bubbles and their mass. C Q represents the image sharpness quality term. E For the exposure quality item, Q S For the adhesion and segmentation quality term, Q M Q represents the sampling window stability quality term. cal For the calibrated mass term, a1+a2+a3+a4+a5+a6=1; through The pressure quality factor is calculated, where Q R2 Q is the mass term for the linear fit of the effective pressure rise segment. T Q is the mass term for the effective pressure section length. Z Q represents the sensor's zero-point drift mass term. L For the level stability mass term, Q V For the state mass term of the exhaust valve, b1+b2+b3+b4+b5=1; through The conductivity quality factor is calculated, where Q stable Q is the reading stability quality term. std For the quality check of gas-free slurry, Q temp For the temperature-compensated mass term, Q range For the range matching quality term, Q poll For the electrode contamination state mass term, c1+c2+c3+c4+c5=1; through The time synchronization quality factor is calculated, where Δt max Δt represents the maximum time deviation between the measured data. allow This is the preset allowable time deviation.

[0010] Optionally, the flotation parameters corresponding to the measurement data are corrected based on the measurement point location of the measurement data to obtain corrected flotation parameters, including: acquiring the measurement data and the corresponding detection time within a unified time window; aligning the timestamps of different measurement data according to the detection time to obtain synchronized measurement data; and when the measurement point locations corresponding to different measurement data are in the same process section of the same flotation cell, and the vertical and horizontal distances between the measurement point locations corresponding to different measurement data are both less than a predetermined distance, by... The spatial correction coefficient is calculated, where Δz is the vertical distance between the measuring points, ΔL is the horizontal distance between the measuring points, H is the effective height of the slurry zone, and L is the horizontal distance between the measuring points. c The characteristic length within the tank is denoted by α, and both α and β are spatial attenuation coefficients. The spatial correction coefficients are used to correct the synchronized measurement data to obtain the corrected flotation parameters.

[0011] Optionally, determining the flotation state based on the corrected flotation parameters includes: determining the flotation state as coarse bubbles when the average bubble diameter is greater than a diameter threshold, the effective bubble surface area flux is less than a low surface area flux threshold, and the overall quality factor is greater than or equal to a second quality threshold; determining the flotation state as insufficient gas velocity when the apparent gas velocity is less than a low gas velocity threshold, the effective bubble surface area flux is less than the low surface area flux threshold, and the rate of change of the average bubble diameter is less than a rate threshold; and determining the flotation state as insufficient gas velocity when the effective bubble surface area flux is less than the low surface area flux threshold and the recovery rate is less than a rate threshold. When the recovery rate decreases, the flotation state is determined to be insufficient carrying capacity; when the proportion of small bubbles is less than the minimum proportion threshold, the average bubble diameter is greater than the reference diameter, and the fine particle recovery rate decreases, the flotation state is determined to be insufficient small bubbles; when the first and second conditions are met, the flotation state is determined to be a gas holdup plateau, the first condition being that the apparent gas velocity increases within at least two uniform time windows, and the second condition being that the rate of increase of the gas holdup is less than a first rate of increase threshold or the rate of increase of the effective bubble surface area flux is less than a second rate of increase threshold; when the third and fourth conditions are met... Under certain conditions, the flotation state is determined to be one of increased entrainment risk. The third condition is that the gas holdup is greater than the high gas holdup threshold or the proportion of small bubbles is greater than the optimal proportion of small bubbles. The fourth condition is that the foam layer depth is less than the depth threshold or the concentrate grade decreases. If the fifth and sixth conditions are met, the flotation state is determined to be one of abnormal gas-liquid interface. The fifth condition is that the fluctuation of the pressure quality factor is less than the first fluctuation threshold and the image quality factor continues to decrease. The sixth condition is that the fluctuation of the foam layer depth or the slurry level is greater than the second fluctuation threshold. If multiple single quality factors within a unified time window are less than their corresponding single thresholds, the flotation state is determined to be one of the detection units corresponding to the single quality factor, where the single quality factor is one of the image quality factor, the pressure quality factor, and the conductivity quality factor. If the flotation parameters are within the corresponding normal range and the comprehensive quality factor is greater than or equal to the first quality threshold, the flotation state is determined to be one of normal hydrodynamic states. If the comprehensive quality factor is less than the second quality threshold or the time deviation of the detection time of the measurement data is greater than the time deviation threshold, the flotation state is determined to be one awaiting retesting.

[0012] Optionally, after determining the flotation state based on the corrected flotation parameters, the method further includes: when the flotation state indicates that the bubbles are too coarse, outputting a first adjustment direction, wherein the first adjustment direction is to increase the frother, optimize the aeration and dispersion, check the impeller or stator wear, and adjust the stirring intensity; when the flotation state indicates that the gas velocity is insufficient, outputting a second adjustment direction, wherein the second adjustment direction is to increase the aeration volume, check the gas path, valves, and air distributor; when the flotation state indicates that the carrying capacity is insufficient, outputting a third adjustment direction, wherein the third adjustment direction is to increase the effective bubble interface supply capacity; when the flotation state indicates that the small bubbles are insufficient, outputting a fourth adjustment direction, wherein the fourth adjustment direction is to optimize the frother formulation and improve the bubble breakage and dispersion conditions; and when the flotation state indicates that the gas holdup has plateaued, outputting... The fifth adjustment direction prioritizes checking bubble coalescence, slurry viscosity, foam layer load, and in-tank circulation status. If the entrainment risk increases during flotation, a sixth adjustment direction is output, which involves reducing the frother dosage, increasing the foam layer depth, or optimizing the flushing water and foam scraping conditions. If the gas-liquid interface is abnormal during flotation, a seventh adjustment direction is output, which checks level control, foam overflow, and sampling window blockage. If the detection unit corresponding to a single quality factor is abnormal during flotation, an eighth adjustment direction is output, which involves cleaning the observation window, recalibrating the pressure sensor, checking the vent valve, and cleaning or calibrating the conductivity electrode. No adjustment direction is output during flotation when the fluid dynamics are normal or the retesting state is pending.

[0013] According to another aspect of this application, a flotation detection device is provided, comprising: an acquisition unit for acquiring measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data, wherein the measurement data includes a bubble image sequence, gas pressure, and apparent conductivity of the gas-bearing slurry; a first calculation unit for calculating flotation parameters based on the measurement data, wherein the flotation parameters include bubble size parameters, apparent gas velocity, and gas holdup; and a second calculation unit for calculating an image quality factor based on the quality-related data of the bubble image sequence, a pressure quality factor based on the quality-related data of the gas pressure, and a pressure quality factor based on the apparent conductivity of the gas-bearing slurry. The conductivity quality factor is calculated based on the quality-related data, and the time synchronization quality factor is calculated based on the time deviation of the detection time of the measurement data; the third calculation unit is used to perform a weighted summation of the image quality factor, the pressure quality factor, the conductivity quality factor, and the time synchronization quality factor to obtain a comprehensive quality factor; the correction unit is used to correct the flotation parameters corresponding to the measurement data according to the measurement point position and the detection time of the measurement data when the comprehensive quality factor is greater than or equal to a first quality threshold, to obtain corrected flotation parameters; the judgment unit is used to judge the flotation state according to the corrected flotation parameters.

[0014] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform any of the methods described.

[0015] According to another aspect of this application, a computer program product is provided, comprising a computer program that, when executed by a processor, implements any of the methods described.

[0016] By applying the technical solution of this application, the above-mentioned flotation detection method calculates multiple individual quality factors, including image quality factor, pressure quality factor, conductivity quality factor, and time synchronization quality factor, based on the quality-related data corresponding to the measurement data. A comprehensive quality factor is obtained by weighted summation of these individual quality factors. Ensuring that the comprehensive quality factor is greater than or equal to a first quality threshold eliminates abnormal factors such as on-site image occlusion, pressure disturbance, sensor zero drift, and electrode contamination. Correcting the flotation parameters corresponding to the measurement data based on the measurement point location and detection time eliminates the influence of timestamp asynchrony and different measurement point locations. Determining the flotation state based on the corrected flotation parameters corresponding to the measurement data ensures accurate judgment, avoids misdiagnosis, and provides an accurate basis for process parameter adjustment. This solves the problems of misdiagnosis caused by on-site image occlusion, pressure disturbance, sensor zero drift, electrode contamination, timestamp asynchrony, and different measurement point locations in the prior art. Attached Figure Description

[0017] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 A hardware structure block diagram of a mobile terminal performing a flotation detection method according to an embodiment of this application is shown;

[0019] Figure 2 A block diagram of a multi-parameter detection device system provided according to an embodiment of this application is shown;

[0020] Figure 3 A schematic diagram of a unified identification time window for multi-source data is shown according to an embodiment of this application;

[0021] Figure 4 A schematic diagram illustrating a state vector and effective bubble surface flux construction according to an embodiment of this application is shown.

[0022] Figure 5 A schematic diagram of a multi-source data quality assessment and quality gating system provided according to an embodiment of this application is shown.

[0023] Figure 6 A schematic diagram illustrating a historical feedback and identification parameter update according to an embodiment of this application is shown;

[0024] Figure 7 A flowchart of an online flotation state identification method according to an embodiment of this application is shown;

[0025] Figure 8 A structural block diagram of a flotation detection apparatus provided according to an embodiment of this application is shown. Detailed Implementation

[0026] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0027] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] As described in the background section, in the prior art, on-site image occlusion, pressure disturbance, sensor zero drift, electrode contamination, timestamp asynchrony, and different measurement point locations lead to misdiagnosis. To solve this problem, embodiments of this application provide a flotation detection method, apparatus, computer-readable storage medium, and computer program product.

[0030] This embodiment provides a flotation detection method. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] Figure 1 This is a flowchart of a flotation detection method according to an embodiment of this application. For example... Figure 1 As shown, the method includes the following steps:

[0032] Step S201: Obtain measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data. The measurement data includes bubble image sequences, gas pressure, and apparent conductivity of gas-bearing slurry.

[0033] Specifically, measurement data such as bubble image sequences, gas pressure, and apparent conductivity of gas-bearing slurry are collected, and the corresponding measurement point locations and detection times are recorded for subsequent calibration. At the same time, corresponding quality-related data are recorded to facilitate data quality assessment.

[0034] Step S202: Calculate the flotation parameters based on the above measurement data. The flotation parameters include bubble size parameters, apparent gas velocity, and gas holdup.

[0035] Specifically, the corresponding flotation parameters can be calculated from the measured data, namely, the bubble size parameter is calculated from the bubble image sequence, the apparent gas velocity is calculated from the gas pressure, and the gas holdup is calculated from the apparent conductivity of the gas-bearing slurry.

[0036] Step S203: Calculate the image quality factor based on the quality correlation data of the bubble image sequence, calculate the pressure quality factor based on the quality correlation data of the gas pressure, calculate the conductivity quality factor based on the quality correlation data of the apparent conductivity of the gas-bearing slurry, and calculate the time synchronization quality factor based on the time deviation of the detection time of the measurement data.

[0037] Specifically, the image quality factor q is calculated separately. img Pressure quality factor q p Conductivity quality factor q k Time synchronization quality factor q sync Each quality factor is normalized to 0-1; a larger value indicates higher data quality.

[0038] Step S204: The image quality factor, pressure quality factor, conductivity quality factor and time synchronization quality factor are weighted and summed to obtain the comprehensive quality factor.

[0039] Specifically, the aforementioned image quality factor, pressure quality factor, conductivity quality factor, and time synchronization quality factor are all single-source data quality factors. The comprehensive quality factor Q is obtained by weighted summation of multiple single-source data quality factors. F To characterize the overall data quality of a set of measurement data, i.e., through Q F =w1 q img + w2 q p + w3 q k + w4 q sync The comprehensive quality factor Q was calculated. F All values ​​of w1+w2+w3+w4 are non-negative and w1+w2+w3+w4=1. The weights are determined based on the current operating condition diagnostic mode, the source of the dominant parameters, and the results of on-site calibration. Among these, q... img q p q k and q sync All are dimensionless quality factors between 0 and 1; w1, w2, w3, and w4 represent the weighting coefficients for image quality, pressure quality, conductivity quality, and time synchronization quality, respectively. These weighting coefficients are only used for quality evaluation and do not change D. 32 J g E g and The physical unit.

[0040] Step S205: When the comprehensive quality factor is greater than or equal to the first quality threshold, the flotation parameters corresponding to the measurement data are corrected according to the measurement point location and the detection time of the measurement data to obtain the corrected flotation parameters.

[0041] Specifically, the comprehensive quality factor is greater than or equal to the first quality threshold to ensure the quality of the measurement data, reduce the risk of misidentification caused by data asynchrony or sensor malfunction, and correct the flotation parameters corresponding to the measurement data by measuring point location and detection time to correct errors caused by time inconsistency and spatial mismatch.

[0042] Step S206: Determine the flotation status based on the above-mentioned corrected flotation parameters.

[0043] Specifically, by judging the flotation state based on the corresponding calibration flotation parameters of the measurement data, the accuracy of the judgment can be guaranteed, misdiagnosis can be avoided, and accurate basis for adjusting process parameters can be provided.

[0044] In this embodiment, the flotation detection method calculates multiple individual quality factors, including image quality factor, pressure quality factor, conductivity quality factor, and time synchronization quality factor, based on the quality-related data corresponding to the measurement data. A weighted sum of these individual quality factors yields a comprehensive quality factor. Ensuring the comprehensive quality factor is greater than or equal to a first quality threshold eliminates abnormal factors such as image occlusion, pressure disturbance, sensor zero drift, and electrode contamination. Correcting the flotation parameters corresponding to the measurement data based on the measurement point location and detection time eliminates the influence of timestamp asynchrony and different measurement point locations. Determining the flotation state based on the corrected flotation parameters corresponding to the measurement data ensures accurate judgment, avoids misdiagnosis, and provides an accurate basis for process parameter adjustment. This solves the problems of misdiagnosis caused by image occlusion, pressure disturbance, sensor zero drift, electrode contamination, timestamp asynchrony, and different measurement point locations in existing technologies.

[0045] To reduce spatial mismatch between different measuring devices, in one optional implementation, step S201 includes:

[0046] Step S2011: Obtain the measurement data detected by each detection unit of the integrated detection device within a unified time window, and record the measurement point location, detection time, and corresponding quality-related data of each detection unit. The detection unit of the integrated detection device includes a bubble image detection unit, an apparent gas velocity and pressure measurement unit, and a gas content conductivity measurement unit.

[0047] In the above embodiments, the bubble image detection unit, apparent gas velocity and pressure measurement unit, and gas holdup conductivity measurement unit are installed in the same process section of the same flotation equipment. If they cannot be installed in the same location, the measurement point positions of each point are recorded, including vertical depth, horizontal distance, and relative coordinates. The flotation equipment type, mineral type, process location, cell number, froth layer depth, liquid level, reagent formulation, feed flow rate, solids mass fraction, stirring power, altitude, and atmospheric pressure are recorded, and a unified identification time window T is set by the synchronous acquisition and time window control unit. w In the unified identification time window T w Internally, the bubble image detection unit acquires bubble image sequences, the apparent gas velocity and pressure measurement unit acquires pressure curves, and the gas holdup and conductivity measurement unit acquires conductivity signals for gaseous and nearly gas-free slurries. Data such as valve opening, reagent dosage, feed flow rate, liquid level, foam layer depth, power input, slurry density, grade, and recovery rate are acquired through the process operation data interface. The connection relationships between the three detection units and the synchronous acquisition, status identification, and communication output units are as follows: Figure 2 As shown. The time alignment of bubble images, pressure, conductivity, process variables, and hysteresis grade data is as follows. Figure 3 As shown.

[0048] To calculate the flotation parameters corresponding to the measurement data, in one optional embodiment, the bubble size parameters include the average bubble diameter, bubble size distribution, small bubble ratio, and bubble size distribution width. The flotation parameters also include the effective bubble surface area flux. Step S202 includes:

[0049] Step S2021: Identify the above bubble image sequence to obtain the equivalent diameter of each effective bubble;

[0050] Step S2022, through The average bubble diameter was calculated as described above, where D 32 Let d be the average bubble diameter mentioned above. i Let n be the average particle size in the i-th particle size range. i The number of bubbles in the i-th particle size range;

[0051] Step S2023: Calculate the ratio of the number of effective bubbles smaller than the diameter threshold to the total number of effective bubbles to obtain the small bubble ratio.

[0052] Step S2024: Generate the bubble size distribution based on the equivalent diameter of the effective bubbles. The bubble size distribution is a curve showing the change of the proportion of effective bubbles with different equivalent diameters as a function of the equivalent diameter.

[0053] Step S2025: Determine two boundary particle sizes and a median particle size based on the equivalent diameter of each effective bubble, calculate the ratio of the difference between the two boundary particle sizes to the median particle size, and obtain the bubble size distribution width.

[0054] Step S2026, through The above apparent gas velocity was calculated, where J g For the above apparent gas velocity, V t Let A0 be the equivalent volume of gas participating in compression within the measuring tube, and P be the bottom opening area of ​​the measuring tube. abs Let dP / dt be the absolute gas pressure at the above measuring point, and K be the slope of the pressure rise. p It is a comprehensive correction factor for pressure, liquid level, slurry density, temperature, and depth of the measuring point;

[0055] Step S2027, through The above gas holdup was calculated, where, E g The above refers to the gas content, where r is the ratio of the apparent conductivity of the gas-bearing slurry to that of the non-gas-bearing slurry, and k is the gas content. aerated k represents the apparent conductivity of the gas-bearing slurry mentioned above. pulp The apparent conductivity of the above-mentioned gaseous slurry;

[0056] Step S2028, through The basic bubble surface area flux was calculated, where S b The above is the basic bubble surface area flux;

[0057] Step S2029: Correct the basic bubble surface area flux based on the above gas holdup, the above small bubble ratio, the above comprehensive quality factor and the process section weight to obtain the above effective bubble surface area flux.

[0058] In the above embodiments, the bubble image sequence is identified to obtain the equivalent diameter of each effective bubble. The average bubble diameter is obtained by calculating the average of the equivalent diameters of each effective bubble. If there are too many bubbles, several particle size intervals are set, and the average bubble diameter is calculated statistically based on the average particle size of the interval and the number of bubbles in the interval. Of course, it is also possible to count each bubble individually, then n i Take 1. Small bubble ratio R <1mm It can be calculated by quantity percentage, area percentage, or volume percentage. It is preferred to output both quantity percentage and area percentage simultaneously. The formula for calculating the quantity percentage is R. <1mm ,N=N d<1mm / N total The formula for calculating the area ratio is R. <1mm A = ΣA j (d j<1mm ) / ΣA j, where N d<1mm N represents the number of effective bubbles with an equivalent diameter of less than 1 mm. total A represents the total number of effectively identified bubbles. j (d j<1mm A represents the projected area of ​​an effective bubble with an equivalent diameter of less than 1 mm. j Let R represent the projected area of ​​the j-th bubble. Since R < 1 mm, it can be expressed as the percentage of the number of bubbles. <1mm N and area ratio R <1mm A; where R <1mm N is the ratio of the number of effective bubbles smaller than 1 mm to the total number of effective bubbles, and R is the number of effective bubbles. <1mm A represents the ratio of the sum of the projected areas of bubbles smaller than 1 mm to the sum of the projected areas of all effective bubbles. The equivalent diameters of the effective bubbles are statistically analyzed, yielding curves showing the percentage of effective bubbles with different equivalent diameters as a function of the equivalent diameter, i.e., the bubble size distribution (BSD). Based on the equivalent diameter of each effective bubble, two boundary particle sizes (D5 and D) are determined. 95 ) and median particle size D 50 Calculate the difference (D) between the two boundary particle sizes mentioned above. 95 -D5) and the median particle size D mentioned above 50 The ratio of the bubble size distribution width (WBSD) is used to obtain the above-mentioned bubble size distribution width. Pressure curves are collected through a gas accumulation measurement tube that is closed at the top and open at the bottom. The bottom opening of the measurement tube is placed at a preset depth in the flotation slurry zone, and a pressure sensor and an exhaust valve are installed at the top. After the exhaust valve is closed, bubbles enter the measurement tube and form a gas accumulation zone inside the tube, causing the pressure inside the measurement tube to increase over time. The system eliminates the initial disturbance section and the plateau section, selecting the effective interval where the pressure increases approximately linearly with time, and calculates the pressure rise slope dP / dt. The apparent gas velocity J... g Calculated using the pressure accumulation method, i.e., through Calculations show that K is the value obtained during initial installation without calibration conditions. p Take 1.00; K after completing the on-site calibration p The preferred value is between 0.85 and 1.15. When K p If the value is less than 0.75 or greater than 1.25, the calibration result is considered abnormal. The sealing of the measuring tube, the status of the vent valve, the zero point of the pressure sensor, liquid level fluctuations, and the measurement point depth record must be checked. This K value should not be changed. p The data is directly written to the threshold database. Conductivity is measured simultaneously using an open conductivity unit and an approximately gas-free slurry conductivity unit. The open unit measures the apparent conductivity k of the gas-bearing slurry. aerated The siphon unit or degassing unit measures the approximately gas-free slurry conductivity k. pulp After correction for electrode constant, temperature, range resistance, and standard solution calibration curve, the gas holdup E is calculated according to Maxwell-like relationships. g That is, through Calculated, through The basic bubble surface area flux S was calculated. b The basic bubble surface area flux S b Based on this, a gas holdup correction function, a small bubble ratio correction function, a data quality correction function, and a process section correction function are introduced to obtain the effective bubble surface area flux. : =S b ·f(E g )·f(R <1mm )·f(Q F )·f(stage), where f(E) g ) is the gas holdup correction function, f(R) <1mm ) is the bubble ratio correction function, f(Q) F ) is the data quality correction function, and f(stage) is the process stage correction function. For example... Figure 4 As shown, compared to the basic S b , This further reflects the limitations of the gas holdup platform, insufficient small bubble ratio, unreliable data quality, and differences in requirements across different process stages, and can serve as an online characterization of the effective bubble interface supply capacity. Preferably, the first quality threshold Q... low Set to 0.60, the second quality threshold Q high Take 0.80, when Q F low When, f(Q) F )=0; when Q low ≤Q F high When, f(Q) F )=(Q F -Q low ) / (Q high -Q low When Q F ≥Q high When, f(Q) F )=1. When E g <E g,min When, f(E) g )=E g / E g,min ; when E g,min ≤E g ≤E g,opt When, f(E) g )=1; when E g >E g,opt When, f(E) g )=max[1-λ Eg (E g -E g,opt ),f(E g )​​min ]. Among them, E g,min E is the threshold for insufficient gas holdup. g,opt λ represents the gas holdup plateau or excessively high gas holdup threshold. Eg f(E) is the penalty coefficient. g ) min This is the minimum correction limit. When R <1mm <R min When, f(R) <1mm )=R <1mm / R min When R min ≤R <1mm ≤R opt When, f(R) <1mm )=1; when R <1mm >R opt When, f(R) <1mm )=max[1-λ R (R <1mm -R opt ),f(R <1mm ) min ]. Among them, R min If the proportion of small bubbles is insufficient to reach the threshold, R opt λ represents the upper limit threshold for the proportion of small bubbles. R f(R) is the penalty factor for excessive foaming agent or the risk of entrainment. <1mm ) min This is the minimum correction limit. f(stage) is the process stage weight, which can be set according to different process positions. For example, f(stage) is 1.00 for the roughing stage, 0.90~1.10 for the scavenging stage, 0.80~1.00 for the cleaning stage, and 1.00~1.20 for the flotation column. The above E... g,min E g,opt R min R opt ,λE g ,λR,f(E g ) min f(R) <1mm ) min Parameters such as f(stage) can be determined from field calibration experiments, historical databases, mineral characteristics, empirical values ​​of process segments, or model training results. In another data-driven implementation, f(E) g f(R) <1mm f(Q) F f(stage) and f(stage) can be obtained through training on a historical database. The historical database consists of a state vector X, subsequent time lags τ, and f(stage). lagThe recovery rate change ΔR, grade change ΔG, and reagent adjustment records within the data were used as training samples. Regression models, decision trees, random forests, gradient boosting trees, or neural networks were employed to obtain... The mapping relationship between the data-driven model and actual flotation parameters. The output of the data-driven model is still affected by Q. F Gating constraints, when Q F low Control suggestions are not output at times.

[0059] In order to evaluate the data quality of each measurement, in one optional implementation, step S203 above includes:

[0060] Step S2031, through The above image quality factor was calculated, where Q N Q represents the effective number of bubbles and their mass. C Q represents the image sharpness quality term. E For the exposure quality item, Q S For the adhesion and segmentation quality term, Q M Q represents the sampling window stability quality term. cal For the calibrated mass term, a1+a2+a3+a4+a5+a6=1;

[0061] Step S2032, through The pressure quality factor mentioned above was calculated, where Q R2 Q is the mass term for the linear fit of the effective pressure rise segment. T Q is the mass term for the effective pressure section length. Z Q represents the sensor's zero-point drift mass term. L For the level stability mass term, Q V For the state mass term of the exhaust valve, b1+b2+b3+b4+b5=1;

[0062] Step S2033, through The above conductivity quality factor was calculated, where Q stable Q is the reading stability quality term. std For the quality check of gas-free slurry, Q temp For the temperature-compensated mass term, Q range For the range matching quality term, Q poll For the state mass term of electrode contamination, c1+c2+c3+c4+c5=1;

[0063] Step S2034, through The above time synchronization quality factor was calculated, where Δt max Δt represents the maximum time deviation between the above measurement data. allow This is the preset allowable time deviation. ​

[0064] In the above embodiments, by The above image quality factor, the effective bubble quantity quality term Q, was calculated. N Through Q N =min(N valid / N set 1) Calculations show that to avoid the quality factor exceeding 1 after the number of effectively identified bubbles exceeds a threshold, N... valid N represents the number of bubbles effectively identified within the current time window. set To preset the effective bubble count threshold, a value of 3000–10000 is preferred. Exposure quality item Q E It can be accessed via Q E =1-P sat The calculation yields, where P sat This represents the percentage of overexposed or underexposed pixels. Bubble overlap quality term Q. S It can be accessed via Q S =1-R overlap The calculation yields, where R overlap The proportion of bubbles identified as overlapping, stuck, or unreliable segmentation is represented by a1-a6 in the image quality factor, which correspond to Q. N Q C Q E Q S Q M and Q cal The recommended values ​​are 0.20, 0.20, 0.15, 0.20, 0.15, and 0.10. When used for diagnosing bubble size distribution or the proportion of small bubbles, the combined weight of a1 and a4 can be increased to 0.45-0.55. The pressure quality factor Q was calculated as described above. R2 The linear fit R during the pressure rise segment can be taken. 2 Q T It can be accessed via Q T =min(T valid / T min ,1), to avoid the quality factor being greater than 1 after the effective rising segment duration exceeds the minimum threshold, where T valid T represents the duration of the effective rising segment of the pressure curve. min The minimum effective duration is preset. The initial perturbation segment and the plateau segment after full gas filling do not participate in the dP / dt fitting. b1-b5 correspond to Q respectively. R2 Q T Q Z Q L and Q V The commonly recommended values ​​are 0.30, 0.20, 0.20, 0.15, and 0.15. (This is based on...) The above conductivity quality factors were calculated, and c1-c5 respectively correspond to Q. stable Q std Q temp Q range and Q poll The commonly recommended values ​​are 0.30, 0.20, 0.15, 0.15, and 0.20. The time synchronization quality factor mentioned above was calculated.

[0065] To achieve spatial and temporal correction, in one optional implementation, step S205 includes:

[0066] Step S2051: Obtain the above measurement data and the corresponding detection time within a unified time window;

[0067] Step S2052: Timestamp alignment of different measurement data according to the above detection time to obtain synchronized measurement data;

[0068] Step S2053: When the measuring points corresponding to different measurement data are located in the same process section of the same flotation cell, and the vertical and horizontal distances between the measuring points corresponding to different measurement data are both less than a predetermined distance, by... The spatial correction coefficient is calculated, where Δz is the vertical distance between the above measuring points, ΔL is the horizontal distance between the above measuring points, H is the effective height of the slurry zone, and L is the horizontal distance between the measuring points. c α is the characteristic length within the slot, and β are both spatial attenuation coefficients.

[0069] Step S2054: The above-mentioned spatial correction coefficient is used to correct the above-mentioned synchronous measurement data to obtain the above-mentioned corrected flotation parameters.

[0070] In the above embodiments, if the bubble image measurement point, J g Measurement point and E g If the measuring points are located in the same process section of the same flotation cell, and the depth difference and horizontal distance between the measuring points are both less than preset limits, then proceed directly to state vector construction. If on-site structural constraints prevent simultaneous arrangement, record the relative coordinates of the three points and adjust them according to the spatial correction factor C. s The parameters are corrected, where the spatial correction coefficient can be obtained through... Calculations show that X corr =C s ·X raw , where X raw For the raw measurement data, X corr The corrected measurement data can be used to calculate the corresponding corrected flotation parameters. Furthermore, α and β can be determined by on-site in-situ calibration experiments, historical database fitting, or empirical values ​​from similar tank types.s It can also be obtained through on-site calibration experiments or training with a historical database. Under stable inflation and stable liquid level conditions, two detection units are arranged sequentially at the same measuring point and the target measuring point. The parameter attenuation ratios within the same unified time window are compared and fitted to obtain α and β. When there are no sufficient co-position calibration samples, α is preferably 0.30-1.20 and β is preferably 0.20-1.00, and these values ​​are updated in the subsequent historical database with calibration samples. For example, when H=1.20m, L... c =1.80m, Δz=0.12m, ΔL=0.18m, α=0.60, β=0.50, C s =exp(-0.60×0.12 / 1.20-0.50×0.18 / 1.80)=0.896; If a certain parameter X raw =40.0, then X corr =35.8. If the sampling frequencies of the multi-source data are different, then a unified time window T is used. w Resampling, timestamp alignment, and moving average processing are performed based on the baseline. For low-frequency outcome indicators such as grade and recovery rate, nearest neighbor time windows or lag times τ can be used. lag It is written into the historical database and does not directly participate in the real-time control and judgment of the current time window.

[0071] In order to accurately determine the flotation state, in one optional implementation, step S205 includes:

[0072] Step S2051: If the average bubble diameter is greater than the diameter threshold, the effective bubble surface area flux is less than the low surface area flux threshold, and the comprehensive quality factor is greater than or equal to the second quality threshold, the flotation state is determined to be that the bubbles are too coarse.

[0073] Step S2052: When the apparent gas velocity is less than the low gas velocity threshold, the effective bubble surface area flux is less than the low surface area flux threshold, and the rate of change of the average bubble diameter is less than the rate threshold, the flotation state is determined to be insufficient gas velocity.

[0074] Step S2053: When the effective bubble surface area flux is less than the low surface area flux threshold and the recovery rate decreases, the flotation state is determined to be insufficient carrying capacity.

[0075] Step S2054: When the proportion of small bubbles is less than the minimum proportion threshold, the average bubble diameter is greater than the reference diameter, and the fine particle recovery rate decreases, the flotation state is determined to be insufficient small bubbles.

[0076] Step S2055: Under the condition of satisfying the first condition and the second condition, the above flotation state is determined to be a gas holdup plateau. The first condition is that the above apparent gas velocity increases within at least two uniform time windows. The second condition is that the rate of increase of the above gas holdup is less than the first rate of increase threshold or the rate of increase of the above effective bubble surface area flux is less than the second rate of increase threshold.

[0077] Step S2056: Under the condition that the third and fourth conditions are met, the above flotation state is determined to be an increased risk of entrainment. The third condition is that the gas holdup is greater than the high gas holdup threshold or the small bubble ratio is greater than the optimal small bubble ratio. The fourth condition is that the foam layer depth is less than the depth threshold or the concentrate grade decreases.

[0078] Step S2057: Under the condition that the fifth condition and the sixth condition are met, the above flotation state is determined to be an abnormal gas-liquid interface. The fifth condition is that the fluctuation of the pressure quality factor is less than the first fluctuation threshold and the image quality factor continues to decrease. The sixth condition is that the fluctuation of the foam layer depth or the slurry level is greater than the second fluctuation threshold.

[0079] Step S2058: When the individual quality factors of multiple unified time windows are less than the corresponding individual thresholds, the flotation state is determined to be an abnormality of the detection unit corresponding to the individual quality factor. The individual quality factor is one of the image quality factor, the pressure quality factor, and the conductivity quality factor.

[0080] Step S2059: If the above flotation parameters are within the corresponding normal range and the above comprehensive quality factor is greater than or equal to the above first quality threshold, the above flotation state is determined to be a normal hydrodynamic state.

[0081] Step S20510: If the comprehensive quality factor is less than the second quality threshold or the time deviation of the detection time of the measurement data is greater than the time deviation threshold, the flotation state is determined to be a state to be retested.

[0082] In the above implementation, if D 32 >D 32high ,and And Q F ≥Q low If J g <J g,low ,and And D 32 If the air velocity does not increase significantly, it is determined to be insufficient. If the recovery rate decreases or the tailings grade increases within a subsequent time window, it is determined to be due to insufficient carrying capacity. If R <1mm <R min And D32 >D 32ref If the recovery rate of fine particles decreases or the loss of fine-grained minerals increases, it is determined that there are insufficient small bubbles. If J g Increased over two or more consecutive time windows, while E g Increment ΔE g Less than the preset threshold, or Increment If it is less than a preset threshold, it is determined to be a gas holdup plateau. If E g >E g,high , or R <1mm >R opt Furthermore, if the foam layer depth is low or the concentrate grade decreases, it is considered an increased risk of entrainment. If the pressure curve quality q p Normal, but image quality q img If the liquid level continues to decrease and is accompanied by abnormal fluctuations in the depth of the foam layer or the liquid level, it is determined to be an abnormal gas-liquid interface. If q img q p or q k If any quality factor falls below its corresponding threshold and fails to recover for M consecutive time windows, the corresponding sensor is deemed abnormal. If D 32 J g E g R <1mm , All are within the target range, and Q F ≥Q high If Q..., then it is determined to be a normal fluid dynamic state. F low Or, the time discrepancy of multiple source parameters exceeds Δt. allow If no process adjustment suggestions are output, only the status to be retested and the cause of the abnormality will be output.

[0083] In addition, the threshold database includes, but is not limited to, D 32high D 32ref J g,low E g,min E g,opt E g,high R min R opt , ΔE g Threshold and Threshold. The threshold is set using a combination of on-site calibration and historical samples: when there are stable production samples, D 32high The 75%-90% quantile value of the target working condition sample can be taken, J g,low A 10%-25% percentile value can be used. ​The 20%-30% quantile value can be used; if there are insufficient historical samples, the initial value should be determined using laboratory or debugging samples, and then verified and updated after accumulating no less than 30 valid time windows. Output results can be displayed on a host computer, touchscreen, or operator interface, or transmitted to a PLC, DCS, or process database via OPC, Modbus, RS-485, Ethernet, or other industrial communication methods. The system will store the current state vector X, state label, suggested adjustment direction, manual operation record, and lag time τ. lag The grade and recovery rate are then written into the historical database to update the threshold database, optimize the process stage weight f(stage), and correct... Function parameters and improved state criterion matrix.

[0084] To improve flotation performance, in one optional embodiment, after determining the flotation state based on the above-mentioned corrected flotation parameters, the method further includes:

[0085] Step S301: When the above flotation state is characterized by coarse bubbles, output a first adjustment direction. The first adjustment direction is to increase the foaming agent, optimize the aeration and dispersion, check the impeller or stator wear, and adjust the stirring intensity.

[0086] Step S302: When the above flotation state is that the gas velocity is insufficient, output a second adjustment direction, which is to increase the gas volume and check the gas path, valves and air distributor.

[0087] Step S303: When the above flotation state is insufficient in terms of carrying capacity, a third adjustment direction is output, which is to improve the effective bubble interface supply capacity.

[0088] Step S304: When the flotation state is characterized by insufficient small bubbles, a fourth adjustment direction is output. The fourth adjustment direction is to optimize the frother formulation and improve the conditions for bubble breakage and dispersion.

[0089] Step S305: When the flotation state is the gas holdup plateau, output the fifth adjustment direction. The fifth adjustment direction prioritizes checking bubble aggregation, slurry viscosity, foam layer load and in-tank circulation status.

[0090] Step S306: When the above flotation state is characterized by an increased risk of entrainment, a sixth adjustment direction is output. The sixth adjustment direction is to reduce the amount of frother added, increase the depth of the foam layer, or optimize the rinsing water and foam scraping conditions.

[0091] Step S307: When the above flotation state is abnormal at the gas-liquid interface, output the seventh adjustment direction. The seventh adjustment direction is to check the liquid level control, foam overflow and sampling window blockage.

[0092] Step S308: If the detection unit corresponding to the above-mentioned single quality factor is abnormal in the above-mentioned flotation state, the eighth adjustment direction is output. The eighth adjustment direction is to clean the observation window, recalibrate the pressure sensor, check the exhaust valve, and clean or calibrate the conductivity electrode.

[0093] In step S309, when the flotation state is either the normal fluid dynamic state or the state to be retested, no adjustment direction is output.

[0094] In the above embodiments, when the flotation state is characterized by coarse bubbles, it is recommended to adjust by increasing the frother, optimizing the aeration and dispersion, checking impeller / stator wear, or adjusting the stirring intensity. When the flotation state is characterized by insufficient air velocity, it is recommended to adjust by increasing the aeration volume and checking the air path, valves, and air distributor. When the flotation state is characterized by insufficient carrying capacity, it is recommended to adjust by increasing the effective bubble interface supply capacity, and combining this with D... 32 J g and R <1mm Determine the specific adjustment method. If the flotation state is characterized by insufficient small bubbles, the recommended adjustment direction is to optimize the frother formulation and improve bubble breakage and dispersion conditions. If the flotation state is characterized by a plateau in gas holdup, the recommended adjustment direction is to avoid simply increasing the aeration rate and prioritize checking bubble coalescence, slurry viscosity, foam layer load, and in-tank circulation. If the flotation state is characterized by increased entrainment risk, the recommended adjustment direction is to reduce the frother dosage, increase the foam layer depth, or optimize flushing water / scraping conditions. If the flotation state is characterized by abnormal gas-liquid interface, the recommended adjustment direction is to check level control, foam overflow, and sampling window blockage. If the flotation state is characterized by abnormal detection units corresponding to the above-mentioned individual quality factors, the recommended adjustment direction is to clean the observation window, recalibrate the pressure sensor, check the vent valve, and clean or calibrate the conductivity electrode. When the flotation state is characterized by normal fluid dynamics or is in a state requiring retesting, no adjustment direction is output.

[0095] In addition, such as Figure 5 As shown, when Q F low When the system determines that the data quality of the current time window is insufficient, it only saves the raw data and the reason for the anomaly, does not output control suggestions, and marks the status as "to be retested" or "sensor anomaly". When Q low ≤Q F high When Q is in a certain state, the system outputs the state identification result, but lowers the confidence level and marks the result as "low confidence diagnosis". F ≥Q high When Q is within the specified range, the system outputs the state identification result with normal confidence level and suggested adjustment direction. F Once the gating condition is met, i.e., Q F ≥Q high ​​Construct a state vector X, X=[D 32 BSD, WBSD, R <1mm A, J g E g ,S b , ,q img ,q p ,q k ,q sync ,stage,H froth [Level,Reagent,Feed,Power], where stage is the process section identifier, including roughing, scavenging, cleaning, flotation columns, etc.; H froth The system defines the foam layer depth, liquid level, reagent dosage, feed flow rate, and power input. The system compares the state vector X with a threshold database or rule model, outputting state labels, confidence levels, evidence parameters, and suggested adjustment directions. The threshold database includes, but is not limited to, D. 32high D 32ref J g,low E g,min E g,opt E g,high R min R opt , ΔE g Threshold and Threshold. For example... Figure 6 As shown, the aforementioned thresholds can be determined from historical databases, on-site calibration, and empirical values ​​for different mineral types and process sections, and can be updated based on historical feedback. Output results can be displayed on a host computer, touchscreen, or operator interface, and can also be transmitted to a PLC, DCS, or process database via OPC, Modbus, RS-485, Ethernet, or other industrial communication methods. The system will store the current state vector X, state label, suggested adjustment direction, manual operation records, and lag time τ. lag The grade and recovery rate are then written into the historical database to update the threshold database, optimize the process stage weight f(stage), and correct... Function parameters and improved state criterion matrix.

[0096] To enable those skilled in the art to better understand the technical solution of this application, the implementation process of the flotation detection method of this application will be described in detail below with reference to specific embodiments.

[0097] A specific flotation detection method, such as Figure 7As shown, the bubble image detection unit, apparent gas velocity and pressure measurement unit, and gas holdup and conductivity measurement unit are integrated into a multi-parameter detection device. The positions of each measuring point are constrained by an integrated installation and spatial positioning component, ensuring that the vertical and horizontal distances between any two measuring points are less than predetermined distances, thus reducing spatial mismatch between different measuring devices. A unified time reference is established for image, pressure, conductivity, and process variables through synchronous acquisition and a time window control unit, and q... img q p q k and q sync The overall quality factor Q constitutes F Gating can reduce the risk of misidentification caused by data asynchrony or sensor malfunction. J is obtained using pressure accumulation measurement. g E is obtained by measuring conductivity. g And combined with image measurements to obtain D 32 and R <1mm Calculate S b and This expands the detection results from single-variable measurement to a multi-variable joint characterization of the effective bubble interface supply capacity. The data processing and status identification unit outputs status labels, confidence levels, evidence parameters, and suggested adjustment directions, which can be transmitted to a host computer, PLC, DCS, or process database via the output and communication unit, facilitating the formation of an online monitoring and feedback update closed loop.

[0098] Example 1:

[0099] In a copper ore roughing flotation machine, the bubble image detection unit, apparent gas velocity and pressure measurement unit, and gas holdup conductivity measurement unit are arranged in the same process section of the same flotation cell. A unified identification time window T is set. w The time window is 3 minutes. Within each time window, the system acquires 300 bubble images, pressure curves, conductivity signals, reagent dosage, valve opening, liquid level, and foam layer depth.

[0100] Image processing yields D 32 and R <1mm J was obtained by pressure accumulation method g E is obtained by conductivity method g Further calculation of S b Q F and and D 32 R <1mm J g E g S b and Perform spatial correction to obtain the spatially corrected D. 32 R <1mm J g Eg S b and As the amount of foaming agent added increases, if D [increases / decreases] within three consecutive time windows... 32 The decrease is less than 5%, E g The increase was less than 3%. The increase is less than 5%, and R <1mm If the preset target range has been reached, the system determines that the current operating condition is close to the critical range of the foaming agent.

[0101] If the foaming agent is continued to be added, it will cause R <1mm More than R opt E g Higher than E g,high If the concentrate grade decreases, the system will output a "risk of entrainment increased" status label, suggesting that the amount of foaming agent added be reduced or the depth of the foam layer be increased.

[0102] Example 2:

[0103] In a certain scavenging flotation machine, operators discovered an increase in tailings grade. Traditional methods, relying solely on air volume to determine if the gas flow is normal, are insufficient to pinpoint the cause of the anomaly. The system obtained the following status within a unified time window:

[0104] Spatially corrected D 32 J after spatial correction is above the target upper limit g Within the target interval, spatially corrected E g It is within the normal range, but the spatially corrected R <1mm Below R min Spatial correction Below Q F It is 0.86.

[0105] Based on the state criterion matrix, the system determines that the state is not simply due to insufficient gas velocity, but rather to coarse bubbles and a lack of small bubbles. The system output suggests optimizing the foaming agent formulation and checking the bubble disperser and stirring components, rather than simply increasing the aeration rate. This embodiment can utilize the spatially corrected D... 32 J g E g R <1mm and The combination of relationships distinguishes different causes of abnormality, avoiding reliance solely on J. g Or the blower volume may cause misjudgment.

[0106] Example 3:

[0107] During online testing in an industrial flotation cell, the observation chamber window became contaminated with slurry, resulting in blurred images and increased bubble overlap. The system calculated q. img =0.42、qp =0.91, q k =0.87、q sync =0.94, overall quality factor Q F =0.63. Because Q F In Q low With Q high During this period, the system outputs a low-confidence diagnostic result and prompts "The image quality is low, and it is recommended to clean the observation window and retest".

[0108] In the subsequent time window, q img Further down to 0.30, Q F It dropped to 0.55, below Q. low The system stops outputting control suggestions, saves only the raw data, and marks the status as "Pending Retest / Image Sensor Abnormality." This embodiment illustrates that the present invention can prevent low-quality image data from directly entering the control suggestion process, improving the security and reliability of online identification in industrial settings.

[0109] Example 4:

[0110] In an industrial flotation machine, the spatially corrected J was measured within a uniform time window. g D is 1.20 cm / s, spatially corrected 32 E is 0.18cm after spatial correction g R = 0.18, spatially corrected <1mm 0.16, Q F =0.86, the process section is the coarse selection section. The basic bubble surface area flux after spatial correction is calculated according to S b =6J g / D 32 The calculation is 40.0 s. -1 During the calibration of the pressure measurement unit, J was obtained using a reference measurement. g,ref =1.20cm / s, and simultaneously measured (V t / A0)·(1 / P abs )·(dP / dt)=1.16cm / s, then K p =1.20 / 1.16=1.034, which is within the normal calibration range of 0.85-1.15, so the calibration parameters for this measuring point can be written. Press C. s The calculation formula for the spatial correction factor C is as follows. s For example, when H=1.20m, Lc=1.80m, Δz=0.12m, ΔL=0.18m, α=0.60, and β=0.50, C s =0.896. This example is used to illustrate the parameter calculation path. In actual submission, the reference value can be replaced with the desensitized calibration record saved by the applicant.

[0111] The on-site threshold is set to E g,min =0.10, E g,opt =0.22、R min =0.25, R opt =0.55, coarse segment f(stage)=1.00. Because E g Located within the target interval, take f(E) g )=1; Due to insufficient small bubble ratio, f(R) is taken as 1. <1mm ) = 0.16 / 0.25 = 0.64; Since Q F ≥Q high Take f(Q) F =1. Therefore, the spatially corrected value is obtained. =40.0×1×0.64×1×1.00=25.6s -1 .

[0112] If this process section For 30 seconds -1 And the spatially corrected D 32 If the value exceeds the target upper limit, the system will output a status label of "Insufficient small bubbles / Insufficient supply of effective bubble interface" and adjust the spatially corrected D value. 32 Spatial corrected R <1mm S after spatial correction b Spatial correction and Q F As an evidentiary parameter. This embodiment illustrates that even after spatial correction, S b Although it doesn't seem low, it can still be corrected by space. This reveals that insufficient microbubble ratio leads to insufficient effective interface supply.

[0113] Example 5:

[0114] At similar apparent air velocity J g Under the conditions, the laboratory flotation machine measured D 32 Approximately 1.35mm, measured by an industrial flotation machine. 32 Approximately 1.85mm. (According to...) =6J g / D 32 Calculate S under laboratory conditions b Significantly higher than industrial conditions. Meanwhile, R in laboratory flotation machines... <1mm Approximately 50% of the R in industrial flotation machines <1mm Approximately 10%, and spatial correction was applied to the measured data.

[0115] The system will spatially correct R <1mm and spatially corrected S bSimultaneously, the state vector is incorporated, and the spatially corrected vector is further calculated. The calculation results show that, although the industrial flotation machine has a spatially corrected J... g It is close to the laboratory, but due to the spatially corrected D 32 Larger bubbles and a significantly insufficient proportion of small bubbles, after spatial correction The value is below the target threshold. The system outputs a status label: "Insufficient small bubbles / Insufficient supply of effective bubble interface". This embodiment illustrates that the present invention can explain the differences between laboratory and industrial flotation indicators and provide a basis for adjusting the frother regime, bubble dispersion conditions, and stirring energy in industrial settings.

[0116] Example 6:

[0117] In a flotation column, the operator increases the aeration rate in a stepped manner. The system calculates the spatially corrected J over N consecutive uniform time windows. g E after spatial correction g and spatially corrected The robust slope. When the spatially corrected J g The relative increase is continuously greater than the threshold δ Jg And spatially corrected E g The relative increase is continuously less than the threshold δ Eg Spatial correction The relative increase is continuously less than the threshold δ Sb And Q F ≥Q high When (t), it is determined that the gas holdup response has entered a "saturated state". For example, J after spatial correction g By J g1 Increase to J g2 And spatially corrected E g Increment less than 2%, spatially corrected The increment is less than 3%, accompanied by increased foam layer fluctuations. The fusion model outputs both rule-based evidence and data-driven probabilities, suggesting that further increasing the aeration rate is unlikely to improve the supply at the effective collection interface. It is recommended to reduce the aeration rate increase and prioritize checking bubble coalescence, slurry viscosity, foam load, and in-tank circulation status.

[0118] This application also provides a flotation detection device. It should be noted that the flotation detection device of this application can be used to execute the flotation detection method provided in this application. This device is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0119] The flotation detection device provided in the embodiments of this application is described below.

[0120] Figure 8 This is a schematic diagram of a flotation detection apparatus according to an embodiment of this application. Figure 8 As shown, the device includes:

[0121] The acquisition unit 10 is used to acquire measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data. The measurement data includes bubble image sequences, gas pressure, and apparent conductivity of gas-bearing slurry.

[0122] Specifically, measurement data such as bubble image sequences, gas pressure, and apparent conductivity of gas-bearing slurry are collected, and the corresponding measurement point locations and detection times are recorded for subsequent calibration. At the same time, corresponding quality-related data are recorded to facilitate data quality assessment.

[0123] The first calculation unit 20 is used to calculate flotation parameters based on the above measurement data. The flotation parameters include bubble size parameters, apparent gas velocity, and gas holdup.

[0124] Specifically, the corresponding flotation parameters can be calculated from the measured data, namely, the bubble size parameter is calculated from the bubble image sequence, the apparent gas velocity is calculated from the gas pressure, and the gas holdup is calculated from the apparent conductivity of the gas-bearing slurry.

[0125] The second calculation unit 30 is used to calculate the image quality factor based on the quality correlation data of the bubble image sequence, the pressure quality factor based on the quality correlation data of the gas pressure, the conductivity quality factor based on the quality correlation data of the apparent conductivity of the gas-bearing slurry, and the time synchronization quality factor based on the time deviation of the detection time of the measurement data.

[0126] Specifically, the image quality factor q is calculated separately. img Pressure quality factor q p Conductivity quality factor q k Time synchronization quality factor q sync Each quality factor is normalized to 0-1; a larger value indicates higher data quality.

[0127] The third calculation unit 40 is used to perform a weighted summation of the above-mentioned image quality factor, pressure quality factor, conductivity quality factor and time synchronization quality factor to obtain a comprehensive quality factor.

[0128] Specifically, the aforementioned image quality factor, pressure quality factor, conductivity quality factor, and time synchronization quality factor are all single-source data quality factors. The comprehensive quality factor Q is obtained by weighted summation of multiple single-source data quality factors. F This is used to characterize the overall data quality of a set of measurement data.

[0129] The correction unit 50 is used to correct the flotation parameters corresponding to the measurement data based on the measurement point location and the detection time of the measurement data when the comprehensive quality factor is greater than or equal to the first quality threshold, so as to obtain the corrected flotation parameters.

[0130] Specifically, the comprehensive quality factor is greater than or equal to the first quality threshold to ensure the quality of the measurement data, reduce the risk of misidentification caused by data asynchrony or sensor malfunction, and correct the flotation parameters corresponding to the measurement data by measuring point location and detection time to correct errors caused by time inconsistency and spatial mismatch.

[0131] The judgment unit 60 is used to judge the flotation state based on the above-mentioned corrected flotation parameters.

[0132] Specifically, by judging the flotation state based on the corresponding calibration flotation parameters of the measurement data, the accuracy of the judgment can be guaranteed, misdiagnosis can be avoided, and accurate basis for process parameter adjustment can be provided.

[0133] In this embodiment, the flotation detection device calculates multiple individual quality factors, including image quality factor, pressure quality factor, conductivity quality factor, and time synchronization quality factor, based on the quality-related data corresponding to the measurement data. A weighted sum of these individual quality factors yields a comprehensive quality factor. Ensuring the comprehensive quality factor is greater than or equal to a first quality threshold eliminates abnormal factors such as image occlusion, pressure disturbance, sensor zero drift, and electrode contamination. Correcting the flotation parameters corresponding to the measurement data based on the measurement point location and detection time eliminates the influence of timestamp asynchrony and different measurement point locations. Determining the flotation state based on the corrected flotation parameters corresponding to the measurement data ensures accurate judgment, avoids misdiagnosis, and provides an accurate basis for process parameter adjustment. This solves the problems of misdiagnosis caused by image occlusion, pressure disturbance, sensor zero drift, electrode contamination, timestamp asynchrony, and different measurement point locations in the prior art.

[0134] To reduce spatial mismatch between different measuring devices, in one optional embodiment, the acquisition unit includes:

[0135] The first acquisition module is used to acquire the measurement data detected by each detection unit of the integrated detection device within a unified time window, and to record the measurement point location, detection time and corresponding quality-related data of each detection unit. The detection unit of the integrated detection device includes a bubble image detection unit, an apparent gas velocity and pressure measurement unit and a gas content conductivity measurement unit.

[0136] In the above embodiments, the bubble image detection unit, apparent gas velocity and pressure measurement unit, and gas holdup conductivity measurement unit are installed in the same process section of the same flotation equipment. If they cannot be installed in the same location, the measurement point positions of each point are recorded, including vertical depth, horizontal distance, and relative coordinates. The flotation equipment type, mineral type, process location, cell number, froth layer depth, liquid level, reagent formulation, feed flow rate, solids mass fraction, stirring power, altitude, and atmospheric pressure are recorded, and a unified identification time window T is set by the synchronous acquisition and time window control unit. w In the unified identification time window T w Inside, the bubble image detection unit acquires bubble image sequences, the apparent gas velocity and pressure measurement unit acquires pressure curves, the gas content and conductivity measurement unit acquires conductivity signals of gaseous slurry and near-gasless slurry, and the process operation data interface acquires data such as valve opening, reagent addition, feed flow rate, liquid level, foam layer depth, power input, slurry density, grade and recovery rate.

[0137] To calculate the flotation parameters corresponding to the measurement data, in one optional embodiment, the bubble size parameters include average bubble diameter, bubble size distribution, small bubble ratio, and bubble size distribution width. The flotation parameters also include effective bubble surface area flux. The first calculation unit includes:

[0138] The recognition module is used to recognize the above bubble image sequence and obtain the equivalent diameter of each effective bubble;

[0139] The first calculation module is used to... The average bubble diameter was calculated as described above, where D 32 Let d be the average bubble diameter mentioned above. i Let n be the average particle size in the i-th particle size range. i The number of bubbles in the i-th particle size range;

[0140] The second calculation module is used to calculate the ratio of the number of effective bubbles smaller than the diameter threshold to the total number of effective bubbles, and to obtain the small bubble ratio.

[0141] The generation module is used to generate the bubble size distribution based on the equivalent diameter of the effective bubbles. The bubble size distribution is a curve showing the change of the proportion of the number of effective bubbles with different equivalent diameters as a function of the equivalent diameter.

[0142] The third calculation module is used to determine two boundary particle sizes and a median particle size based on the equivalent diameter of each effective bubble, calculate the ratio of the difference between the two boundary particle sizes to the median particle size, and obtain the bubble size distribution width.

[0143] The fourth calculation module is used to... The above apparent gas velocity was calculated, where J g For the above apparent gas velocity, V t Let A0 be the equivalent volume of gas participating in compression within the measuring tube, and P be the bottom opening area of ​​the measuring tube. abs Let dP / dt be the absolute gas pressure at the above measuring point, and K be the slope of the pressure rise. p It is a comprehensive correction factor for pressure, liquid level, slurry density, temperature, and depth of the measuring point;

[0144] The fifth calculation module is used to... The above gas holdup was calculated, where, E g The above refers to the gas content, where r is the ratio of the apparent conductivity of the gas-bearing slurry to that of the non-gas-bearing slurry, and k is the gas content. aerated k represents the apparent conductivity of the gas-bearing slurry mentioned above. pulp The apparent conductivity of the above-mentioned gaseous slurry;

[0145] The sixth calculation module is used to... The basic bubble surface area flux was calculated, where S b The above is the basic bubble surface area flux;

[0146] The seventh calculation module is used to correct the basic bubble surface area flux based on the gas holdup, the small bubble ratio, the comprehensive quality factor, and the process section weight, so as to obtain the effective bubble surface area flux.

[0147] In the above embodiments, the bubble image sequence is identified to obtain the equivalent diameter of each effective bubble. The average bubble diameter is obtained by calculating the average of the equivalent diameters of each effective bubble. If there are too many bubbles, several particle size intervals are set, and the average bubble diameter is calculated statistically based on the average particle size of the interval and the number of bubbles in the interval. Of course, it is also possible to count each bubble individually, then n i Take 1. Small bubble ratio R <1mm It can be calculated by quantity percentage, area percentage, or volume percentage. It is preferred to output both quantity percentage and area percentage simultaneously. The formula for calculating the quantity percentage is R. <1mm,N=N d<1mm / N total The formula for calculating the area ratio is R. <1mm A=ΣA j (d j<1mm ) / ΣA j , where N d<1mm N represents the number of effective bubbles with an equivalent diameter of less than 1 mm. total A represents the total number of effectively identified bubbles. j (d j<1mm A represents the projected area of ​​an effective bubble with an equivalent diameter of less than 1 mm. j Let R represent the projected area of ​​the j-th bubble. Since R < 1 mm, it can be expressed as the percentage of the number of bubbles. <1mm N and area ratio R <1mm A; where R <1mm N is the ratio of the number of effective bubbles smaller than 1 mm to the total number of effective bubbles, and R is the number of effective bubbles. <1mm A represents the ratio of the sum of the projected areas of bubbles smaller than 1 mm to the sum of the projected areas of all effective bubbles. The equivalent diameters of the effective bubbles are statistically analyzed, yielding curves showing the percentage of effective bubbles with different equivalent diameters as a function of the equivalent diameter, i.e., the bubble size distribution (BSD). Based on the equivalent diameter of each effective bubble, two boundary particle sizes (D5 and D) are determined. 95 ) and median particle size D 50 Calculate the difference (D) between the two boundary particle sizes mentioned above. 95 -D5) and the median particle size D mentioned above 50 The ratio of the bubble size distribution width (WBSD) is used to obtain the above-mentioned bubble size distribution width. Pressure curves are collected through a gas accumulation measurement tube that is closed at the top and open at the bottom. The bottom opening of the measurement tube is placed at a preset depth in the flotation slurry zone, and a pressure sensor and an exhaust valve are installed at the top. After the exhaust valve is closed, bubbles enter the measurement tube and form a gas accumulation zone inside the tube, causing the pressure inside the measurement tube to increase over time. The system eliminates the initial disturbance section and the plateau section, selecting the effective interval where the pressure increases approximately linearly with time, and calculates the pressure rise slope dP / dt. The apparent gas velocity J... g Calculated using the pressure accumulation method, i.e., through The conductivity was calculated. Simultaneous measurement of conductivity was performed using an open conductivity unit and an approximately gas-free slurry conductivity unit. The open unit measured the apparent conductivity k of the gas-bearing slurry. aerated The siphon unit or degassing unit measures the approximately gas-free slurry conductivity k. pulp After correction for electrode constant, temperature, range resistance, and standard solution calibration curve, the gas holdup E is calculated according to Maxwell-like relationships. g That is, through Calculated, through The basic bubble surface area flux S was calculated. b The basic bubble surface area flux Sb Based on this, a gas holdup correction function, a small bubble ratio correction function, a data quality correction function, and a process section correction function are introduced to obtain the effective bubble surface area flux. : =S b ·f(E g )·f(R <1mm )·f(Q F )·f(stage), where f(E) g ) is the gas holdup correction function, f(R) <1mm ) is the bubble ratio correction function, f(Q) F ) is the data quality correction function, and f(stage) is the process stage correction function. For example... Figure 4 As shown, compared to the basic S b , This further reflects the insufficient gas holdup platform, small bubble ratio, unreliable data quality, and differences in requirements across different process stages, and can serve as an online characterization of the effective bubble interface supply capacity. When Q... F low When, f(Q) F )=0; when Q low ≤Q F high When, f(Q) F )=(Q F -Q low ) / (Q high -Q low When Q F ≥Q high When, f(Q) F )=1. When E g <E g,min When, f(E) g )=E g / E g,min ; when E g,min ≤E g ≤E g,opt When, f(E) g )=1; when E g >E g,opt When, f(E) g )=max[1-λ Eg (E g -E g,opt ),f(E g ) min ]. Among them, E g,min E is the threshold for insufficient gas holdup. g,opt λ represents the gas holdup plateau or excessively high gas holdup threshold. Eg f(E) is the penalty coefficient. g ) min ​​This is the minimum correction limit. When R <1mm <R min When, f(R) <1mm )=R <1mm / R min When R min ≤R <1mm ≤R opt When, f(R) <1mm )=1; when R <1mm >R opt When, f(R) <1mm )=max[1-λ R (R <1mm -R opt ),f(R <1mm ) min ]. Among them, R min If the proportion of small bubbles is insufficient to reach the threshold, R opt λ represents the upper limit threshold for the proportion of small bubbles. R f(R) is the penalty factor for excessive foaming agent or the risk of entrainment. <1mm ) min This is the minimum correction limit. f(stage) is the process stage weight, which can be set according to different process positions. For example, f(stage) is 1.00 for the roughing stage, 0.90~1.10 for the scavenging stage, 0.80~1.00 for the cleaning stage, and 1.00~1.20 for the flotation column. The above E... g,min E g,opt R min R opt ,λE g ,λR,f(E g ) min f(R) <1mm ) min Parameters such as f(stage) can be determined from field calibration experiments, historical databases, mineral characteristics, empirical values ​​of process segments, or model training results. In another data-driven implementation, f(E) g f(R) <1mm f(Q) F f(stage) and f(stage) can be obtained through training on a historical database. The historical database consists of a state vector X, subsequent time lags τ, and f(stage). lag The recovery rate change ΔR, grade change ΔG, and reagent adjustment records within the data were used as training samples. Regression models, decision trees, random forests, gradient boosting trees, or neural networks were employed to obtain... The mapping relationship between the data-driven model and actual flotation parameters. The output of the data-driven model is still affected by Q. F Gating constraints, when Q F low Control suggestions are not output at times. ​

[0148] To evaluate the data quality of each measurement, in one optional implementation, the second calculation unit includes:

[0149] The eighth calculation module is used to... The above image quality factor was calculated, where Q N Q represents the effective number of bubbles and their mass. C Q represents the image sharpness quality term. E For the exposure quality item, Q S For the adhesion and segmentation quality term, Q M Q represents the sampling window stability quality term. cal For the calibrated mass term, a1+a2+a3+a4+a5+a6=1;

[0150] The ninth calculation module is used to... The pressure quality factor above was calculated, where Q R2 Q is the mass term for the linear fit of the effective pressure rise segment. T Q is the mass term for the effective pressure section length. Z Q represents the sensor's zero-point drift mass term. L For the level stability mass term, Q V For the state mass term of the exhaust valve, b1+b2+b3+b4+b5=1;

[0151] The tenth calculation module is used to... The above conductivity quality factor was calculated, where Q stable Q is the reading stability quality term. std For the quality check of gas-free slurry, Q temp For the temperature-compensated mass term, Q range For the range matching quality term, Q poll For the state mass term of electrode contamination, c1+c2+c3+c4+c5=1;

[0152] The eleventh calculation module is used to... The above time synchronization quality factor was calculated, where Δt max Δt represents the maximum time deviation between the above measurement data. allow This is the preset allowable time deviation.

[0153] In the above embodiments, by The above image quality factor, the effective bubble quantity quality term Q, was calculated. N Through Q N =min(N valid / N set ,1) Calculations show that to avoid the quality factor exceeding 1 after the number of effectively identified bubbles exceeds a threshold, where Nvalid N represents the number of bubbles effectively identified within the current time window. set To preset the effective bubble count threshold, a value of 3000–10000 is preferred. Exposure quality item Q E It can be accessed via Q E =1-P sat The calculation yields, where P sat This represents the percentage of overexposed or underexposed pixels. Bubble overlap quality term Q. S It can be accessed via Q S =1-R overlap The calculation yields, where R overlap The proportion of bubbles deemed to be overlapping, stuck together, or unreliably segmented. The pressure quality factor Q was calculated as described above. R2 The linear fit R during the pressure rise segment can be taken. 2 Q T It can be accessed via Q T =min(T valid / T min ,1), to avoid the quality factor being greater than 1 after the effective rising segment duration exceeds the minimum threshold, where T valid T represents the duration of the effective rising segment of the pressure curve. min The minimum effective duration is preset. The initial disturbance segment and the plateau segment after complete gas filling are not included in the dP / dt fitting. The above conductivity quality factor was calculated, and then... The time synchronization quality factor mentioned above was calculated.

[0154] To achieve spatial and temporal correction, in one optional implementation, the correction unit includes:

[0155] The second acquisition module is used to acquire the above-mentioned measurement data and the corresponding above-mentioned detection time within a unified time window;

[0156] The adjustment module is used to align the timestamps of different measurement data according to the above detection time to obtain synchronized measurement data.

[0157] The twelfth calculation module is used to calculate the following when the measuring points corresponding to different measurement data are located in the same process section of the same flotation cell, and when the vertical and horizontal distances between the measuring points corresponding to different measurement data are both less than a predetermined distance: The spatial correction coefficient is calculated, where Δz is the vertical distance between the above measuring points, ΔL is the horizontal distance between the above measuring points, H is the effective height of the slurry zone, and L is the horizontal distance between the measuring points. c α is the characteristic length within the slot, and β are both spatial attenuation coefficients.

[0158] The calibration module is used to correct the synchronized measurement data using the aforementioned spatial correction coefficient to obtain the aforementioned corrected flotation parameters.

[0159] In the above embodiments, if the bubble image measurement point, J g Measurement point and E g If the measuring points are located in the same process section of the same flotation cell, and the depth difference and horizontal distance between the measuring points are both less than preset limits, then proceed directly to state vector construction. If on-site structural constraints prevent simultaneous arrangement, record the relative coordinates of the three points and adjust them according to the spatial correction factor C. s The parameters are corrected, where the spatial correction coefficient can be obtained through... Calculations show that X corr =C s ·X raw , where X raw For the raw measurement data, X corr The corrected measurement data can be used to calculate the corresponding corrected flotation parameters. Furthermore, α and β can be determined by on-site in-situ calibration experiments, historical database fitting, or empirical values ​​from similar tank types. s It can also be obtained through on-site calibration experiments or training with historical databases. If the sampling frequencies of multiple data sources are different, a unified time window T should be used. w Resampling, timestamp alignment, and moving average processing are performed based on the baseline. For low-frequency outcome indicators such as grade and recovery rate, nearest neighbor time windows or lag times τ can be used. lag It is written into the historical database and does not directly participate in the real-time control and judgment of the current time window.

[0160] To accurately determine the flotation state, in one optional implementation, the determination unit includes:

[0161] The first determining module is used to determine that the flotation state is that the bubbles are too coarse when the average bubble diameter is greater than the diameter threshold, the effective bubble surface area flux is less than the low surface area flux threshold, and the comprehensive quality factor is greater than or equal to the second quality threshold.

[0162] The second determining module is used to determine that the flotation state is insufficient gas velocity when the apparent gas velocity is less than the low gas velocity threshold, the effective bubble surface area flux is less than the low surface area flux threshold, and the rate of change of the average bubble diameter is less than the rate threshold.

[0163] The third determining module is used to determine that the flotation state is insufficient carrying capacity when the effective bubble surface area flux is less than the low surface area flux threshold and the recovery rate decreases.

[0164] The fourth determining module is used to determine the flotation state as insufficient small bubbles when the proportion of small bubbles is less than the minimum proportion threshold, the average bubble diameter is greater than the reference diameter, and the fine particle recovery rate decreases.

[0165] The fifth determining module is used to determine the above flotation state as a gas holdup plateau when the first condition and the second condition are met. The first condition is that the apparent gas velocity increases within at least two uniform time windows. The second condition is that the rate of increase of the gas holdup is less than a first rate of increase threshold or the rate of increase of the effective bubble surface area flux is less than a second rate of increase threshold.

[0166] The sixth determining module is used to determine that the above flotation state is an increased risk of entrainment when the third and fourth conditions are met. The third condition is that the gas holdup is greater than the high gas holdup threshold or the small bubble ratio is greater than the optimal small bubble ratio. The fourth condition is that the froth layer depth is less than the depth threshold or the concentrate grade decreases.

[0167] The seventh determination module is used to determine that the above flotation state is an abnormal gas-liquid interface when the fifth and sixth conditions are met. The fifth condition is that the fluctuation of the pressure quality factor is less than the first fluctuation threshold and the image quality factor continues to decrease. The sixth condition is that the fluctuation of the foam layer depth or the slurry level is greater than the second fluctuation threshold.

[0168] The eighth determining module is used to determine that the flotation state is an abnormality of the detection unit corresponding to the single quality factor when the single quality factor of multiple unified time windows is less than the corresponding single threshold. The single quality factor is one of the image quality factor, the pressure quality factor and the conductivity quality factor.

[0169] The ninth determining module is used to determine that the flotation state is a normal hydrodynamic state when the flotation parameters are within the corresponding normal range and the comprehensive quality factor is greater than or equal to the first quality threshold.

[0170] The tenth determining module is used to determine the flotation state as a state to be retested when the comprehensive quality factor is less than the second quality threshold or the time deviation of the detection time of the measurement data is greater than the time deviation threshold.

[0171] In the above implementation, if D 32 >D 32high ,and And Q F ≥Q low If J g <J g,low ,and And D 32If the air velocity does not increase significantly, it is determined to be insufficient. If the recovery rate decreases or the tailings grade increases within a subsequent time window, it is determined to be due to insufficient carrying capacity. If R <1mm <R min And D 32 >D 32ref If the recovery rate of fine particles decreases or the loss of fine-grained minerals increases, it is determined that there are insufficient small bubbles. If J g Increased over two or more consecutive time windows, while E g Increment ΔE g Less than the preset threshold, or Increment If it is less than a preset threshold, it is determined to be a gas holdup plateau. If E g >E g,high , or R <1mm >R opt Furthermore, if the foam layer depth is low or the concentrate grade decreases, it is considered an increased risk of entrainment. If the pressure curve quality q p Normal, but image quality q img If the liquid level continues to decrease and is accompanied by abnormal fluctuations in the depth of the foam layer or the liquid level, it is determined to be an abnormal gas-liquid interface. If q img q p or q k If any quality factor falls below its corresponding threshold and fails to recover for M consecutive time windows, the corresponding sensor is deemed abnormal. If D 32 J g E g R <1mm , All are within the target range, and Q F ≥Q high If Q..., then it is determined to be a normal fluid dynamic state. F low Or, the time discrepancy of multiple source parameters exceeds Δt. allow If no process adjustment suggestions are output, only the status to be retested and the cause of the abnormality will be output.

[0172] To improve flotation performance, in one optional embodiment, the above-mentioned apparatus further includes:

[0173] The first output unit is used to output a first adjustment direction after judging the flotation state according to the above-mentioned corrected flotation parameters, when the flotation state is that the bubbles are too coarse. The first adjustment direction is to increase the foaming agent, optimize the aeration and dispersion, check the impeller or stator wear, and adjust the stirring intensity.

[0174] The second output unit is used to output a second adjustment direction when the above-mentioned flotation state is insufficient gas velocity. The second adjustment direction is to increase the gas volume, check the gas path, valves and air distributor.​

[0175] The third output unit is used to output a third adjustment direction when the above flotation state is insufficient in terms of carrying capacity. The third adjustment direction is to improve the supply capacity of the effective bubble interface.

[0176] The fourth output unit is used to output a fourth adjustment direction when the flotation state is insufficient for small bubbles. The fourth adjustment direction is to optimize the frother regime and improve the conditions for bubble breakage and dispersion.

[0177] The fifth output unit is used to output a fifth adjustment direction when the flotation state is the gas holdup plateau. The fifth adjustment direction prioritizes checking bubble aggregation, slurry viscosity, foam layer load and in-tank circulation status.

[0178] The sixth output unit is used to output a sixth adjustment direction when the above flotation state is characterized by an increased risk of entrainment. The sixth adjustment direction is to reduce the amount of frother added, increase the depth of the foam layer, or optimize the rinsing water and foam scraping conditions.

[0179] The seventh output unit is used to output a seventh adjustment direction when the above flotation state is an abnormal gas-liquid interface. The seventh adjustment direction is to check the liquid level control, foam overflow and sampling window blockage.

[0180] The eighth output unit is used to output an eighth adjustment direction when the detection unit corresponding to the above-mentioned single quality factor is abnormal in the above-mentioned flotation state. The eighth adjustment direction is to clean the observation window, recalibrate the pressure sensor, check the exhaust valve, and clean or calibrate the conductivity electrode.

[0181] The ninth output unit is used to not output the adjustment direction when the above flotation state is the above-mentioned normal hydrodynamic state and the above-mentioned state to be retested.

[0182] In the above embodiments, when the flotation state is characterized by coarse bubbles, it is recommended to adjust by increasing the frother, optimizing the aeration and dispersion, checking impeller / stator wear, or adjusting the stirring intensity. When the flotation state is characterized by insufficient air velocity, it is recommended to adjust by increasing the aeration volume and checking the air path, valves, and air distributor. When the flotation state is characterized by insufficient carrying capacity, it is recommended to adjust by increasing the effective bubble interface supply capacity, and combining this with D... 32 J g and R <1mmDetermine the specific adjustment method. If the flotation state is characterized by insufficient small bubbles, the recommended adjustment direction is to optimize the frother formulation and improve bubble breakage and dispersion conditions. If the flotation state is characterized by a plateau in gas holdup, the recommended adjustment direction is to avoid simply increasing the aeration rate and prioritize checking bubble coalescence, slurry viscosity, foam layer load, and in-tank circulation. If the flotation state is characterized by increased entrainment risk, the recommended adjustment direction is to reduce the frother dosage, increase the foam layer depth, or optimize flushing water / scraping conditions. If the flotation state is characterized by abnormal gas-liquid interface, the recommended adjustment direction is to check level control, foam overflow, and sampling window blockage. If the flotation state is characterized by abnormal detection units corresponding to the above-mentioned individual quality factors, the recommended adjustment direction is to clean the observation window, recalibrate the pressure sensor, check the vent valve, and clean or calibrate the conductivity electrode. When the flotation state is characterized by normal fluid dynamics or is in a state requiring retesting, no adjustment direction is output.

[0183] In addition, such as Figure 5 As shown, when Q F low When the system determines that the data quality of the current time window is insufficient, it only saves the raw data and the reason for the anomaly, does not output control suggestions, and marks the status as "to be retested" or "sensor anomaly". When Q low ≤Q F high When Q is in a certain state, the system outputs the state identification result, but lowers the confidence level and marks the result as "low confidence diagnosis". F ≥Q high When Q is within the specified range, the system outputs the state identification result with normal confidence level and suggested adjustment direction. F Once the gating condition is met, i.e., Q F ≥Q high Construct a state vector X, X=[D 32 BSD, WBSD, R <1mm A, J g E g ,S b , ,q img ,q p ,q k ,q sync ,stage,H froth [Level,Reagent,Feed,Power], where stage is the process section identifier, including roughing, scavenging, cleaning, flotation columns, etc.; H froth The system defines the foam layer depth, liquid level, reagent dosage, feed flow rate, and power input. The system compares the state vector X with a threshold database or rule model, outputting state labels, confidence levels, evidence parameters, and suggested adjustment directions. The threshold database includes, but is not limited to, D.​​32high D 32ref J g,low E g,min E g,opt E g,high R min R opt , ΔE g Threshold and Threshold. For example... Figure 6 As shown, the aforementioned thresholds can be determined from historical databases, on-site calibration, and empirical values ​​for different mineral types and process sections, and can be updated based on historical feedback. Output results can be displayed on a host computer, touchscreen, or operator interface, and can also be transmitted to a PLC, DCS, or process database via OPC, Modbus, RS-485, Ethernet, or other industrial communication methods. The system will store the current state vector X, state label, suggested adjustment direction, manual operation records, and lag time τ. lag The grade and recovery rate are then written into the historical database to update the threshold database, optimize the process stage weight f(stage), and correct... Function parameters and improved state criterion matrix.

[0184] The aforementioned flotation detection device includes a processor and a memory. The acquisition unit, first calculation unit, second calculation unit, third calculation unit, correction unit, and judgment unit are all stored as program units in the memory. The processor executes these program units stored in the memory to achieve the corresponding functions. All of the above modules reside in the same processor; alternatively, the modules may be located in different processors in any combination. The processor contains a kernel, which retrieves the corresponding program units from the memory. One or more kernels can be configured, and adjusting kernel parameters can address problems in the prior art such as image occlusion, pressure disturbance, sensor zero drift, electrode contamination, timestamp asynchrony, and misdiagnosis caused by different measurement point locations. The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. The memory includes at least one memory chip.

[0185] This invention provides a computer-readable storage medium including a stored program, wherein the program, when running, controls the device containing the computer-readable storage medium to perform the flotation detection method.

[0186] Specifically, flotation detection methods include:

[0187] Step S201: Acquire measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data. The measurement data includes bubble image sequences, gas pressure, and apparent conductivity of the gas-bearing slurry. Step S202: Calculate flotation parameters based on the measurement data. The flotation parameters include bubble size parameters, apparent gas velocity, and gas holdup. Step S203: Calculate the image quality factor based on the quality-related data of the bubble image sequences, the pressure quality factor based on the quality-related data of the gas pressure, and the conductivity based on the quality-related data of the apparent conductivity of the gas-bearing slurry. The quality factor is calculated based on the time deviation of the detection time of the above measurement data to obtain the time synchronization quality factor; step S204, the image quality factor, pressure quality factor, conductivity quality factor and time synchronization quality factor are weighted and summed to obtain the comprehensive quality factor; step S205, if the comprehensive quality factor is greater than or equal to the first quality threshold, the flotation parameters corresponding to the above measurement data are corrected according to the measurement point position and the detection time of the above measurement data to obtain the corrected flotation parameters; step S206, the flotation state is determined according to the corrected flotation parameters.

[0188] This invention provides a processor for running a program, wherein the program executes the flotation detection method described above.

[0189] Specifically, flotation detection methods include:

[0190] Step S201: Acquire measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data. The measurement data includes bubble image sequences, gas pressure, and apparent conductivity of the gas-bearing slurry. Step S202: Calculate flotation parameters based on the measurement data. The flotation parameters include bubble size parameters, apparent gas velocity, and gas holdup. Step S203: Calculate the image quality factor based on the quality-related data of the bubble image sequences, the pressure quality factor based on the quality-related data of the gas pressure, and the conductivity based on the quality-related data of the apparent conductivity of the gas-bearing slurry. The quality factor is calculated based on the time deviation of the detection time of the above measurement data to obtain the time synchronization quality factor; step S204, the image quality factor, pressure quality factor, conductivity quality factor and time synchronization quality factor are weighted and summed to obtain the comprehensive quality factor; step S205, if the comprehensive quality factor is greater than or equal to the first quality threshold, the flotation parameters corresponding to the above measurement data are corrected according to the measurement point position and the detection time of the above measurement data to obtain the corrected flotation parameters; step S206, the flotation state is determined according to the corrected flotation parameters.

[0191] This invention provides a device including a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs at least the following steps:

[0192] Step S201: Acquire measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data. The measurement data includes bubble image sequences, gas pressure, and apparent conductivity of the gas-bearing slurry. Step S202: Calculate flotation parameters based on the measurement data. The flotation parameters include bubble size parameters, apparent gas velocity, and gas holdup. Step S203: Calculate the image quality factor based on the quality-related data of the bubble image sequences, the pressure quality factor based on the quality-related data of the gas pressure, and the conductivity based on the quality-related data of the apparent conductivity of the gas-bearing slurry. The quality factor is calculated based on the time deviation of the detection time of the above measurement data to obtain the time synchronization quality factor; step S204, the image quality factor, pressure quality factor, conductivity quality factor and time synchronization quality factor are weighted and summed to obtain the comprehensive quality factor; step S205, if the comprehensive quality factor is greater than or equal to the first quality threshold, the flotation parameters corresponding to the above measurement data are corrected according to the measurement point position and the detection time of the above measurement data to obtain the corrected flotation parameters; step S206, the flotation state is determined according to the corrected flotation parameters.

[0193] The devices mentioned in this article can be servers, PCs, tablets, mobile phones, etc.

[0194] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having at least the following method steps:

[0195] Step S201: Acquire measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data. The measurement data includes bubble image sequences, gas pressure, and apparent conductivity of the gas-bearing slurry. Step S202: Calculate flotation parameters based on the measurement data. The flotation parameters include bubble size parameters, apparent gas velocity, and gas holdup. Step S203: Calculate the image quality factor based on the quality-related data of the bubble image sequences, the pressure quality factor based on the quality-related data of the gas pressure, and the conductivity based on the quality-related data of the apparent conductivity of the gas-bearing slurry. The quality factor is calculated based on the time deviation of the detection time of the above measurement data to obtain the time synchronization quality factor; step S204, the image quality factor, pressure quality factor, conductivity quality factor and time synchronization quality factor are weighted and summed to obtain the comprehensive quality factor; step S205, if the comprehensive quality factor is greater than or equal to the first quality threshold, the flotation parameters corresponding to the above measurement data are corrected according to the measurement point position and the detection time of the above measurement data to obtain the corrected flotation parameters; step S206, the flotation state is determined according to the corrected flotation parameters.

[0196] As can be seen from the above description, the embodiments of this application achieve the following technical effects:

[0197] In the flotation detection method of this application, multiple individual quality factors are calculated from the quality-related data corresponding to the measurement data, including image quality factor, pressure quality factor, conductivity quality factor, and time synchronization quality factor. The weighted sum of the multiple individual quality factors is used to obtain a comprehensive quality factor. Ensuring that the comprehensive quality factor is greater than or equal to a first quality threshold eliminates abnormal factors such as on-site image occlusion, pressure disturbance, sensor zero drift, and electrode contamination. The flotation parameters corresponding to the measurement data are corrected according to the measurement point location and detection time to eliminate the influence of timestamp asynchrony and different measurement point locations. The flotation state is judged according to the corrected flotation parameters corresponding to the measurement data, which ensures the accuracy of the judgment, avoids misdiagnosis, and provides an accurate basis for process parameter adjustment. This solves the problem of misdiagnosis caused by on-site image occlusion, pressure disturbance, sensor zero drift, electrode contamination, timestamp asynchrony, and different measurement point locations in the prior art.

[0198] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A flotation detection method, characterized in that, include: Acquire measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data. The measurement data includes bubble image sequences, gas pressure, and apparent conductivity of gas-bearing slurry. Flotation parameters are calculated based on the measurement data, including bubble size parameters, apparent gas velocity, and gas holdup. An image quality factor is calculated based on the quality correlation data of the bubble image sequence, a pressure quality factor is calculated based on the quality correlation data of the gas pressure, a conductivity quality factor is calculated based on the quality correlation data of the apparent conductivity of the gas-bearing slurry, and a time synchronization quality factor is calculated based on the time deviation of the detection time of the measurement data. The image quality factor, the pressure quality factor, the conductivity quality factor, and the time synchronization quality factor are weighted and summed to obtain the comprehensive quality factor. When the comprehensive quality factor is greater than or equal to the first quality threshold, the flotation parameters corresponding to the measurement data are corrected according to the measurement point location and the detection time of the measurement data to obtain the corrected flotation parameters. The flotation state is determined based on the corrected flotation parameters; An image quality factor is calculated based on the quality correlation data of the bubble image sequence; a pressure quality factor is calculated based on the quality correlation data of the gas pressure; a conductivity quality factor is calculated based on the quality correlation data of the apparent conductivity of the gas-bearing slurry; and a time synchronization quality factor is calculated based on the time deviation of the detection time of the measurement data, including: through... The image quality factor is calculated, where Q N Q represents the effective number of bubbles and their mass. C Q represents the image sharpness quality term. E For the exposure quality item, Q S For the adhesion and segmentation quality term, Q M Q represents the sampling window stability quality term. cal For the calibrated mass term, a1+a2+a3+a4+a5+a6=1; through The pressure quality factor is calculated, where Q R2 Q is the mass term for the linear fit of the effective pressure rise segment. T Q is the mass term for the effective pressure section length. Z Q represents the sensor's zero-point drift mass term. L For the level stability mass term, Q V For the state mass term of the exhaust valve, b1+b2+b3+b4+b5=1; through The conductivity quality factor is calculated, where Q stable Q is the reading stability quality term. std For the quality check of gas-free slurry, Q temp For the temperature-compensated mass term, Q range For the range matching quality term, Q poll For the electrode contamination state mass term, c1+c2+c3+c4+c5=1; through The time synchronization quality factor is calculated, where Δt max Δt represents the maximum time deviation between the measured data. allow This is the preset allowable time deviation.

2. The method according to claim 1, characterized in that, Acquire measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data, including: The measurement data detected by each detection unit of the integrated detection device within a unified time window are acquired, and the measurement point location, detection time, and corresponding quality-related data of each detection unit are recorded. The detection unit of the integrated detection device includes a bubble image detection unit, an apparent gas velocity and pressure measurement unit, and a gas holdup conductivity measurement unit.

3. The method according to claim 1, characterized in that, The bubble size parameters include average bubble diameter, bubble size distribution, proportion of small bubbles, and bubble size distribution width. The flotation parameters also include effective bubble surface area flux. The flotation parameters are calculated based on the measurement data, including: The bubble image sequence is identified to obtain the equivalent diameter of each effective bubble; pass The average bubble diameter was calculated, where D 32 Let d be the average bubble diameter. i Let n be the average particle size in the i-th particle size range. i The number of bubbles in the i-th particle size range; The ratio of the number of effective bubbles smaller than the diameter threshold to the total number of effective bubbles is calculated to obtain the small bubble ratio; The bubble size distribution is generated based on the equivalent diameter of the effective bubbles, and the bubble size distribution is a curve showing the change of the proportion of the number of effective bubbles with different equivalent diameters as a function of the equivalent diameter; Two boundary particle sizes and a median particle size are determined based on the equivalent diameter of each effective bubble. The ratio of the difference between the two boundary particle sizes to the median particle size is calculated to obtain the bubble size distribution width. pass The apparent gas velocity was calculated, where J g V is the apparent gas velocity. t Let A0 be the equivalent volume of gas participating in compression within the measuring tube, and P be the bottom opening area of ​​the measuring tube. abs dP / dt is the absolute gas pressure at the measuring point, dP / dt is the pressure rise slope, and K is the absolute pressure at the measuring point. p It is a comprehensive correction factor for pressure, liquid level, slurry density, temperature, and depth of the measuring point; pass The gas holdup was calculated, wherein, E g The gas content is denoted as r, where r is the ratio of the apparent conductivity of the gas-bearing slurry to that of the non-gas-bearing slurry, and k is the gas content. aerated k is the apparent conductivity of the gas-bearing slurry. pulp The apparent conductivity of the gas-free slurry; pass The basic bubble surface area flux was calculated, where S b The basic bubble surface area flux; The effective bubble surface area flux is obtained by correcting the basic bubble surface area flux based on the gas holdup, the proportion of small bubbles, the comprehensive quality factor, and the process section weight.

4. The method according to claim 1, characterized in that, The flotation parameters corresponding to the measurement data are corrected based on the measurement point location of the measurement data to obtain corrected flotation parameters, including: Obtain the measurement data and the corresponding detection time within a unified time window; The different measurement data are timestamped according to the detection time to obtain synchronized measurement data; When the measuring points corresponding to different measurement data are located in the same process section of the same flotation cell, and the vertical and horizontal distances between the measuring points corresponding to different measurement data are both less than a predetermined distance, by... The spatial correction coefficient is calculated, where Δz is the vertical distance between the measuring points, ΔL is the horizontal distance between the measuring points, H is the effective height of the slurry zone, and L is the horizontal distance between the measuring points. c α is the characteristic length within the slot, and β are both spatial attenuation coefficients. The spatial correction coefficient is used to correct the synchronized measurement data to obtain the corrected flotation parameters.

5. The method according to claim 3, characterized in that, Determining the flotation state based on the corrected flotation parameters includes: If the average bubble diameter is greater than the diameter threshold, the effective bubble surface area flux is less than the low surface area flux threshold, and the comprehensive quality factor is greater than or equal to the second quality threshold, the flotation state is determined to be that the bubbles are too coarse. If the apparent gas velocity is less than the low gas velocity threshold, the effective bubble surface area flux is less than the low surface area flux threshold, and the rate of change of the average bubble diameter is less than the rate threshold, the flotation state is determined to be insufficient gas velocity. If the effective bubble surface area flux is less than the low surface area flux threshold and the recovery rate decreases, the flotation state is determined to be insufficient carrying capacity. If the proportion of small bubbles is less than the minimum proportion threshold, the average bubble diameter is greater than the reference diameter, and the fine particle recovery rate decreases, the flotation state is determined to be insufficient small bubbles. Under the condition that the first condition and the second condition are met, the flotation state is determined to be a gas holdup plateau. The first condition is that the apparent gas velocity increases within at least two uniform time windows. The second condition is that the rate of increase of the gas holdup is less than a first rate of increase threshold or the rate of increase of the effective bubble surface area flux is less than a second rate of increase threshold. Under the condition that the third and fourth conditions are met, the flotation state is determined to be an increased risk of entrainment. The third condition is that the gas holdup is greater than the high gas holdup threshold or the proportion of small bubbles is greater than the optimal proportion of small bubbles. The fourth condition is that the depth of the froth layer is less than the depth threshold or the concentrate grade decreases. Under the condition that the fifth and sixth conditions are met, the flotation state is determined to be an abnormal gas-liquid interface. The fifth condition is that the fluctuation of the pressure quality factor is less than the first fluctuation threshold and the image quality factor continues to decrease. The sixth condition is that the fluctuation of the foam layer depth or the slurry level is greater than the second fluctuation threshold. If the individual quality factor of multiple unified time windows is less than the corresponding individual threshold, the flotation state is determined to be an abnormal detection unit corresponding to the individual quality factor, wherein the individual quality factor is one of the image quality factor, the pressure quality factor and the conductivity quality factor; If the flotation parameters are within the corresponding normal range and the comprehensive quality factor is greater than or equal to the first quality threshold, the flotation state is determined to be a normal hydrodynamic state. If the overall quality factor is less than the second quality threshold or the time deviation of the detection time of the measurement data is greater than the time deviation threshold, the flotation state is determined to be a state to be retested.

6. The method according to claim 5, characterized in that, After determining the flotation state based on the corrected flotation parameters, the method further includes: When the flotation state is characterized by coarse bubbles, a first adjustment direction is output. The first adjustment direction is to increase the foaming agent, optimize the aeration and dispersion, check the impeller or stator wear, and adjust the stirring intensity. When the flotation state is characterized by insufficient gas velocity, a second adjustment direction is output, which is to increase the gas volume, check the gas path, valves, and air distributor. When the flotation state is characterized by insufficient carrying capacity, a third adjustment direction is output, which is to improve the effective bubble interface supply capacity. When the flotation state is characterized by insufficient small bubbles, a fourth adjustment direction is output, which is to optimize the frother regime and improve the conditions for bubble breakage and dispersion. When the flotation state is the gas holdup plateau, a fifth adjustment direction is output, which prioritizes checking bubble aggregation, slurry viscosity, foam layer load and in-tank circulation status. When the flotation state is such that the risk of entrainment increases, a sixth adjustment direction is output. The sixth adjustment direction is to reduce the amount of foaming agent added, increase the depth of the foam layer, or optimize the rinsing water and foam scraping conditions. When the flotation state is abnormal at the gas-liquid interface, a seventh adjustment direction is output, which is to check the liquid level control, foam overflow and sampling window blockage. When the flotation state is abnormal in the detection unit corresponding to the single quality factor, the eighth adjustment direction is output. The eighth adjustment direction is to clean the observation window, recalibrate the pressure sensor, check the exhaust valve, and clean or calibrate the conductivity electrode. When the flotation state is either the normal fluid dynamic state or the state to be retested, no adjustment direction is output.

7. A flotation detection device, characterized in that, include: The acquisition unit is used to acquire measurement data, corresponding measurement point locations, corresponding detection times, and corresponding quality-related data. The measurement data includes bubble image sequences, gas pressure, and apparent conductivity of gas-bearing slurry. The first calculation unit is used to calculate flotation parameters based on the measurement data, the flotation parameters including bubble size parameters, apparent gas velocity and gas holdup; The second calculation unit is used to calculate an image quality factor based on the quality correlation data of the bubble image sequence, a pressure quality factor based on the quality correlation data of the gas pressure, a conductivity quality factor based on the quality correlation data of the apparent conductivity of the gas-bearing slurry, and a time synchronization quality factor based on the time deviation of the detection time of the measurement data. The third calculation unit is used to perform a weighted summation of the image quality factor, the pressure quality factor, the conductivity quality factor, and the time synchronization quality factor to obtain a comprehensive quality factor; The calibration unit is used to calibrate the flotation parameters corresponding to the measurement data according to the measurement point location and the detection time when the comprehensive quality factor is greater than or equal to the first quality threshold, so as to obtain the calibrated flotation parameters. The judgment unit is used to determine the flotation state based on the corrected flotation parameters; The second computing unit includes: an eighth computing module, used for... The image quality factor is calculated, where Q N Q represents the effective number of bubbles and their mass. C Q represents the image sharpness quality term. E For the exposure quality item, Q S For the adhesion and segmentation quality term, Q M Q represents the sampling window stability quality term. cal For the scale calibration mass term, a1+a2+a3+a4+a5+a6=1; the ninth calculation module is used to... The pressure quality factor is calculated, where Q R2 Q is the mass term for the linear fit of the effective pressure rise segment. T Q is the mass term for the effective pressure section length. Z Q represents the sensor's zero-point drift mass term. L For the level stability mass term, Q V For the state mass term of the exhaust valve, b1+b2+b3+b4+b5=1; the tenth calculation module is used to... The conductivity quality factor is calculated, where Q stable Q is the reading stability quality term. std For the quality check of gas-free slurry, Q temp For the temperature-compensated mass term, Q range For the range matching quality term, Q poll For the electrode contamination state mass term, c1+c2+c3+c4+c5=1; the eleventh calculation module is used to... The time synchronization quality factor is calculated, where Δt max Δt represents the maximum time deviation between the measured data. allow This is the preset allowable time deviation.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 6.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1 to 6.

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