Method for measuring composition of flotation slurry suitable for lead-antimony-silver flotation process

Abstract

The application relates to the technical field of intelligent sensing systems, in particular to a flotation slurry composition measuring method suitable for a lead-antimony-silver flotation process, which comprises the following steps: in the pH regulator adding process in the lead-antimony-silver flotation process, constructing the pH sensitivity of each metal ion according to the change rule between the metal ion activity and the pH value; after all the flotation reagents are added, constructing the constraint limiting coefficient of each metal ion according to the difference of the metal ion activity values at different monitoring positions, the time change trend of each metal ion at each monitoring position and the pH sensitivity; and outputting the composition measurement results of each metal ion in the form of a range according to the constraint limiting coefficient; the method solves the problem of insufficient single-point measurement representation caused by neglecting the non-uniformity of the local flow field under the bypass tank measurement environment in the existing composition measurement mode.

Description

Technical Field

[0001] This application relates to the field of intelligent sensing system technology, specifically to a method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation processes. Background Technology

[0002] Natural metal ions exist on the surface of the raw ore. During the flotation process, these metal ions are present in the flotation pulp. After adding reagents for different purposes, the flotation machine will stir the flotation pulp in the flotation cell, and the metal ions will be randomly distributed in the flotation pulp due to the stirring.

[0003] Therefore, existing composition measurement methods typically measure the composition of flotation slurry in the bypass tank of the flotation cell by single-point measurement or sampling measurement. This ignores the non-uniformity of the local flow field in the bypass tank measurement environment, which leads to a lack of representativeness in the measurement results. The single composition measurement result may have unpredictable deviations from the actual metal composition inside the slurry, thus failing to provide reliable composition information for the control of flotation slurry process and negatively impacting the recovery rate of important metals. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides a method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation processes, thereby resolving the existing issues.

[0005] The flotation pulp composition measurement method applicable to the lead-antimony-silver flotation process of this application adopts the following technical solution:

[0006] One embodiment of this application provides a method for measuring the composition of flotation pulp suitable for lead-antimony-silver flotation processes. The method includes the following steps:

[0007] The lead-antimony-silver flotation process includes: adding a pH adjuster, a collector, and a depressant sequentially to the flotation cell; continuously stirring during the addition of the pH adjuster, and collecting data on the initial slurry in the flotation cell bypass tank during this period; and continuing stirring for a preset time after the depressant addition is completed, and collecting data on the flotation slurry in the flotation cell bypass tank during the preset time.

[0008] The collected data includes the pH value of the slurry and the activity of each metal ion at each monitoring location;

[0009] Based on the data collected during the addition of pH adjuster, the change response between pH value and the activity of each metal ion was analyzed to construct the pH sensitivity of each metal ion.

[0010] Based on the data collected after the inhibitor addition was completed, the uneven distribution of metal ions in the pulp in the time and spatial dimensions was analyzed. Combined with the range of pH values ​​of the flotation pulp and the pH sensitivity, the constraint coefficients of each metal ion were constructed.

[0011] The range of composition measurement results for each metal ion is determined based on the aforementioned constraint limiting coefficient.

[0012] In one embodiment, the step of analyzing the change response between pH value and the activity of each metal ion based on data collected during the addition of the pH adjuster, in order to construct the pH sensitivity of each metal ion, includes:

[0013] The pH adjustment agent addition process is divided into time intervals; at each monitoring location within each time interval, the activity values ​​of each metal ion are linearly fitted to the pH value of the flotation pulp; for each data point on the fitted line, a corresponding weight is set according to its collection time to calculate the weighted goodness of fit of the fitted line; the mean of the weighted goodness of fit of all monitoring locations in the latest time interval of each metal ion is used as the fitting reliability of each metal ion.

[0014] The number of times the activity value of each metal ion and the number of times the pH value changed at each monitoring location within each time interval were counted. Combined with the range of the activity value of each metal ion at each monitoring location within each time interval, the comprehensive response of each metal ion was calculated.

[0015] The pH sensitivity of each metal ion is determined based on the overall response and the fitting reliability.

[0016] In one embodiment, the weighted goodness of fit is specifically:

[0017] Sort all data points on the fitted line by time, normalize the sorted values ​​of all data points using the maximum value normalization method, and use the normalized values ​​of each sorted value as the weights of each data point; when calculating the goodness of fit of the fitted line, multiply the squared differences of each data point in the numerator and denominator of the goodness of fit calculation expression by the weights, and then sum them up to obtain the weighted goodness of fit of the fitted line.

[0018] In one embodiment, the overall response is specifically:

[0019] At each monitoring location within each time interval, the ratio of the range of activity values ​​of each metal ion to the maximum value of the range of activity values ​​of all metal ions is calculated and denoted as the first ratio; the absolute value of the difference between the number of times the activity value of each metal ion changes and the number of times the pH value changes is calculated, and the ratio of the absolute value of the difference to the number of sampling times within each time interval is calculated, and the difference between the natural number 1 and the ratio is denoted as the first difference; the average value of the first ratio and the first difference is calculated;

[0020] The weighted sum of the average values ​​of each metal ion at each monitoring location over all time intervals is used as the activity response coefficient of each metal ion at each monitoring location.

[0021] The average activity response coefficient of each metal ion at all monitoring locations is taken as the comprehensive response of each metal ion.

[0022] In one embodiment, the pH sensitivity is:

[0023] The average of the fitting reliability of each metal ion and the overall response was used as the pH sensitivity of each metal ion.

[0024] In one embodiment, the step of analyzing the uneven distribution of metal ions in the pulp in both time and space dimensions, combined with the pH range of the flotation pulp and the pH sensitivity, to construct the constraint coefficients for each metal ion includes:

[0025] After the inhibitor addition is completed, the number of data in the flotation pulp pH data whose pH value is not equal to the preset pH value is counted and recorded as the first quantity. Based on the first quantity and the range of flotation pulp pH values, combined with the pH sensitivity of each metal ion, the degree of influence of each metal ion on pH value is constructed.

[0026] Calculate the coefficient of variation of the activity values ​​of each metal ion at each monitoring location, and construct the temporal characteristic values ​​of each metal ion at each monitoring location by combining the influence degree value and the first quantity; use the mean of the temporal characteristic values ​​of all monitoring locations of each metal ion as the temporal component suspicion of each metal ion.

[0027] Based on the correlation between the time series of activity values ​​at different monitoring locations of each metal ion, and the degree of disorder in the distribution of all the time series characteristic values ​​of each metal ion, combined with the influence degree value and the first quantity, the spatial composition suspicion of each metal ion is constructed.

[0028] The constraint coefficients for each metal ion are determined based on the temporal component suspicion and the spatial component suspicion.

[0029] In one embodiment, the degree of influence value is specifically:

[0030] Calculate the mean of the normalized values ​​of the first quantity and the normalized values ​​of the pH range of the flotation pulp, and multiply the mean by the pH sensitivity of each metal ion as the influence value of each metal ion.

[0031] In one embodiment, the time-series feature value is specifically:

[0032] Obtain the normalized coefficient of variation of the activity values ​​of each metal ion at each monitoring location;

[0033] If the first quantity is equal to zero, the normalized value of the coefficient of variation is used as the time-series characteristic value of each metal ion at each monitoring location; if the first quantity is not equal to zero, the normalized value of the coefficient of variation is weighted and adjusted based on the influence value, and the adjusted result is mapped to a preset value range as the time-series characteristic value of each metal ion at each monitoring location.

[0034] In one embodiment, the spatial component suspicion level is specifically:

[0035] Calculate the correlation coefficient between the time series of activity values ​​at different monitoring locations of each metal ion, and determine the first correlation coefficient based on the mean of all the correlation coefficients of each metal ion; obtain the normalized standard deviation of the time series characteristic values ​​of all monitoring locations of each metal ion.

[0036] If the first quantity is equal to zero, the spatial composition suspicion of each metal ion is determined based on the inverse index determined by the first correlation coefficient and the normalized value of the standard deviation.

[0037] If the first quantity is not equal to zero, the inverse index determined based on the first correlation coefficient is weighted and corrected using the influence degree value, and the spatial composition suspicion of each metal ion is determined by combining the corrected inverse index with the normalized standard deviation value.

[0038] In one embodiment, the expression for the constraint limiting coefficient is:

[0039]

[0040] In the formula, Represents the constraint limit coefficient for the x-th metal ion; This indicates the preset scaling factor; The time-series composition suspicion of the xth metal ion; The spatial composition suspicion of the xth metal ion.

[0041] This application has at least the following beneficial effects:

[0042] This application collects the metal ion activity and pH value of the slurry during the addition of pH adjuster in the lead-antimony-silver flotation process and after the addition of all flotation reagents. For the data collected during pH adjuster addition, the sensitivity of each metal ion activity to pH changes is analyzed based on the variation pattern between activity and pH value, constructing a pH sensitivity for each metal ion to reflect the regulation of the dissolution balance of each metal ion by pH value. For the data collected after the addition of all flotation reagents, constraint coefficients for each metal ion are constructed based on the differences in metal ion activity values ​​at different monitoring locations and the time variation trend of each metal ion at each monitoring location, combined with the pH sensitivity. The composition measurement results of each metal ion are output in range form based on the constraint coefficients. This achieves multi-point detection, preserves spatial variation information, and solves the problem of insufficient representativeness of single-point measurements in existing composition measurement methods due to neglecting the non-uniformity of the local flow field in the bypass tank measurement environment. It also avoids overly absolute composition measurement results, making the composition measurement results closer to the true metal ion concentration of the entire flotation slurry. Attached Figure Description

[0043] Figure 1 A flowchart of a flotation pulp composition measurement method applicable to lead-antimony-silver flotation process provided in this application;

[0044] Figure 2 This is a schematic diagram of the deployment of smart sensors.

[0045] Explanation of reference numerals in the attached diagram: 101-flotation cell, 102-bypass tank inlet, 103-bypass tank, 104-ISE sensor, 105-pH sensor, 106-bypass tank outlet. Detailed Implementation

[0046] The following, in conjunction with the accompanying drawings, details the specific scheme of the flotation pulp composition measurement method applicable to the lead-antimony-silver flotation process provided in this application.

[0047] One embodiment of this application provides a method for measuring the composition of flotation pulp suitable for lead-antimony-silver flotation processes.

[0048] Specifically, the following methods for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation processes are provided. Please refer to [link / reference]. Figure 1 The method includes the following steps:

[0049] Step 1: Collect data.

[0050] Lead-antimony-silver flotation process flow: Flow ①: Grinding to obtain raw material for flotation; Flow ②: Adding deionized water to the raw material to obtain initial slurry, which is then placed in the flotation cell; Flow ③: Adding a pH adjuster to the flotation cell and continuously stirring for a preset time; simultaneously, data is collected from the initial slurry in the bypass tank of the flotation cell during stirring; Flow ④: Adding a collector to the flotation cell and continuously stirring for a preset time; Flow ⑤: Adding a depressant to the flotation cell and continuously stirring for a preset time; after Flow ⑤, continuing stirring for a preset time, and collecting data from the flotation slurry in the bypass tank of the flotation cell during stirring; Flow ⑥: Aerating the flotation cell to obtain concentrate and tailings.

[0051] Process ① is as follows: The qualified product of the crushed raw ore is put into a high-frequency vibrating screen for grinding. The grinding fineness is -0.074mm particle size accounts for 68.00%, the vibration frequency is greater than 24Hz, and the amplitude is between 1.0-2.5mm. The filtered fine material is obtained in the dewatering zone of the filter layer. The fine material is the raw material to be floated.

[0052] Process ② is as follows: Mix the raw material to be floated with deionized water at a ratio of 1:3, that is, mix 1 kg of raw material to be floated with 3 kg of deionized water to obtain the initial slurry, and put it into the flotation cell of the flotation machine.

[0053] Step ③ is as follows: Add sodium carbonate to the flotation cell and stir continuously for 4 minutes to adjust the pH value of the initial pulp to 10.

[0054] In the process of implementing step ③, the changes in the metal elements in the initial slurry can reflect the dissolution law of natural metal ions on the surface of the raw ore. Therefore, this application collects the activity of each metal ion and the pH value of the initial slurry in this process to analyze the dissolution law of each metal ion, so as to provide an adjustment basis for subsequent measurement of flotation slurry composition.

[0055] Step 4 is as follows: Add butyl ammonium black powder and ethyl thiocyanate to the flotation cell at a ratio of 2:1, with a total dosage of 300g / t, and stir continuously for 3min.

[0056] Step 5 is as follows: Add 1300g / t of zinc sulfate, 400g / t of sodium sulfite and 100g / t of ammonium chloride as combined inhibitors to the flotation cell and stir continuously for 3 minutes.

[0057] After step ⑤ is completed, all flotation reagents have been added. At this point, the interaction between the minerals and reagents in the flotation pulp tends to be in equilibrium. Under these conditions, the composition test results of the flotation pulp are closest to the true composition of the pulp. Therefore, after step ⑤, stirring continues for 3 minutes, and during this process, the composition of the flotation pulp is tested, and the activity of each metal ion and the pH value of the flotation pulp are collected.

[0058] Step 6 is as follows: Start the flotation machine's aeration device, aerate the flotation cell for 2 minutes to obtain concentrate and tailings.

[0059] Lead-antimony-silver flotation aims to improve the recovery rates of lead (Pb), antimony (Sb), and silver (Ag) metals, suppress the inhibition rate of arsenic (As) metal, and reduce the content of arsenopyrite. In the lead-antimony-silver flotation process, under an alkaline environment with a pH of 10, a good balance is achieved between the inhibition rates of arsenopyrite and As in the pulp and the recovery rates of Pb, Sb, and Ag. Collectors significantly improve the recovery rate of Pb, while inhibitors significantly improve the inhibition rate of As.

[0060] Data collection on the activity of various metal ions and the pH value of the slurry, such as... Figure 2 As shown, this application sets four monitoring positions at equal intervals in the middle of the bypass tank outside the flotation cell. An ISE sensor is installed at each monitoring position to collect the activity of each metal ion at each monitoring position. A pH sensor is installed at the inlet of the bypass tank to collect the pH value of the slurry. The flotation cell is stirred clockwise. Figure 2 This is a schematic diagram of the smart sensor layout, where 101 is the flotation cell (top view), 102 is the bypass tank inlet, 103 is the bypass tank, 104 is the ISE sensor, 105 is the pH sensor, and 106 is the bypass tank outlet.

[0061] In this embodiment, the data acquisition time interval for both the ISE sensor and the pH sensor is set to 5 seconds. In other embodiments of this application, the implementer can set the data acquisition time interval according to the actual situation.

[0062] Furthermore, the collected data is preprocessed: the time series of activity values ​​of each metal ion and the time series of pH values ​​of the flotation pulp collected during process ③ and after process ⑤ are filtered using the median filtering algorithm. The filtering window size is set to 5×1 to obtain the time series of activity values ​​of each metal ion and the time series of pH values ​​of the flotation pulp after noise interference is eliminated.

[0063] Considering that different reagents may accumulate in localized areas of the slurry due to insufficient stirring during the initial addition, resulting in severely uneven distribution of pH and metal ion activity, the data at this stage cannot truly reflect the overall slurry state. Therefore, this application will not consider using data collected within the first 30 seconds to ensure the reliability of subsequent analysis results.

[0064] Step 2: Based on the data collected during the addition of the pH adjuster, analyze the change response between pH value and the activity of each metal ion to construct the pH sensitivity of each metal ion.

[0065] Sodium carbonate, being an alkaline reagent, gradually increases the pH of the initial slurry until the levels of recovered and inhibited metals reach equilibrium. During this process, the activity of recovered metals gradually increases while the activity of inhibited metals gradually decreases, resulting in variations in the pH response of different metal ions. In subsequent processes, both zinc sulfate and sodium sulfite reagents cause pH fluctuations, but these undergo neutralization reactions, preventing sudden increases or decreases in pH; only minor fluctuations occur. Therefore, the closer the pH is to 10, the more significant the response between metal ion activity and pH becomes.

[0066] As process ③ proceeds, the added sodium carbonate gradually dissolves, causing the pH value of the slurry to gradually rise. The activity of metal ions also changes with the pH value. Since the changes in metal ion activity vary across different time periods in process ③, process ③ is divided into time intervals to more accurately analyze the relationship between metal ion activity and pH value. In this embodiment, a time step of 1 minute is used to divide the complete time period of process ③ into four time intervals, and the data for each time interval are analyzed separately.

[0067] (1) First, within each time interval, the pH value of the initial slurry is used as the independent variable, and the activity of each metal ion at each monitoring location is used as the dependent variable. The least squares method is used to perform linear fitting to obtain the fitting line of each metal ion at each monitoring location with respect to pH value and activity.

[0068] The weighted goodness-of-fit of each fitted line is calculated by combining time calculations. Specifically, all data points on the fitted line are sorted by time, and the sorted values ​​of all data points are normalized using the maximum value normalization method. The normalized values ​​of the sorted values ​​of each data point are used as the weights of each data point. When calculating the goodness-of-fit of the fitted line, the squared differences of the corresponding data points in the numerator and denominator of the goodness-of-fit calculation expression are multiplied by the weights, and then summed to obtain the weighted goodness-of-fit of the fitted line. The goodness-of-fit calculation is a well-known method, and the expression for goodness-of-fit is: Where m is the number of data points on the fitted line. This represents the actual measured value of the q-th data point. Let q be the value of the q-th data point on the fitted line. This is the average of the actual measured values ​​of m data points. Let q be the squared difference term corresponding to the q-th data point in the numerator. Let be the squared difference term corresponding to the q-th data point in the denominator. The expression for the weighted goodness of fit can be: ,in, Let q be the weight of the q-th data point.

[0069] Obtain the fourth time interval, i.e., the latest time interval, and use the mean of the weighted goodness of fit for all monitoring locations of each metal ion within this time interval as the fitting reliability for each metal ion. The higher the fitting reliability, the more reliable the linear relationship between the activity of that metal ion and the pH value.

[0070] (2) Then, when the pH value changes, the response of the activity of each metal ion will vary. Therefore, in each time interval, the number of times the activity value of each metal ion changes in the time series of the activity at each monitoring location is counted. Simultaneously, the elemental range in the activity time series is obtained and denoted as the activity value range; the number of pH changes in the initial pulp pH time series within the time interval is counted. ;

[0071] Specifically, the number of times the activity value changes in the time series is the number of elements with non-zero values ​​in the first-order difference sequence of the time series.

[0072] The activity response coefficients of each metal ion at each monitoring location are calculated, and the expression is as follows:

[0073]

[0074] In the formula, Z represents the activity response coefficient of the x-th metal ion at the y-th monitoring location; Z is the number of time intervals. The first weight for the z-th time interval; This represents the range of activity values ​​of the x-th metal ion at the y-th monitoring location within the z-th time interval; This represents the maximum value of the range of activity values ​​for all metal ions at all monitoring locations across all time intervals. Since changes in pH will inevitably cause changes in metal ion activity, therefore... It will not be 0; This represents the number of times the activity value of the x-th metal ion changes in the time series sequence of the activity at the y-th monitoring location within the z-th time interval; This represents the number of times the pH value of the initial slurry changes in the time series within the z-th time interval; This indicates the number of data collection points within each time interval. The first ratio, 1- This is the first difference.

[0075] The first weight is determined by sorting all time intervals in chronological order to obtain the sorting value of each time interval, calculating the ratio of the sorting value of each time interval to the sum of the sorting values ​​of all time intervals, and using this ratio as the first weight of each time interval.

[0076] Furthermore, the average activity response coefficient of each metal ion at all monitoring locations is taken as the comprehensive response of each metal ion.

[0077] The range of activity values ​​reflects the degree of variation in the activity of metal ions within each range. The frequency of changes in metal ion activity can be reflected. The difference between the number of pH value changes and the number of activity value changes can indicate the degree of matching between changes in metal ion activity and changes in pH value. The smaller the difference, the larger the first difference, and the higher the degree of matching between the two. All three can reflect the influence of pH changes on each metal ion.

[0078] The larger the value, the greater the change in the activity of the current metal ions when the pH value changes, and the higher the degree of matching between the change in metal ion activity and the change in pH value, indicating a greater responsiveness of the current metal ion activity.

[0079] Furthermore, the average of the fitting reliability of each metal ion and the overall response is used as the pH sensitivity of each metal ion.

[0080] The greater the pH sensitivity, the higher the response rate of each metal ion to changes in pH value, and the greater the change in the activity of each metal ion when there are slight fluctuations in pH value.

[0081] Step 3: Based on the data collected after the inhibitor addition is completed, analyze the degree of uneven distribution of metal ions in the pulp in the time and spatial dimensions. Combine the range of pH values ​​of the flotation pulp and the pH sensitivity to construct the constraint coefficients of each metal ion.

[0082] After step ⑤, the flotation process is nearing its end. The activity values ​​of each metal ion at any monitoring position should tend to stabilize. If the stability is low, it indicates that the flotation pulp at that position has not yet reached sufficient chemical equilibrium, and the state of the metal ion cannot truly reflect its composition.

[0083] If there are significant differences in the activity of metal ions at different locations in the flotation pulp, it indicates a higher degree of spatial non-uniformity in the pulp's internal distribution, and the less accurate the measurement results of the metal ion composition will be.

[0084] (1) First, for the pH time series of flotation pulp collected after process ⑤, count the number of elements with pH not equal to 10 in the series, and record it as the first quantity. Simultaneously, the elemental range in the pH time series is obtained and denoted as the pH range. For any metal ion at any monitoring location, calculate the coefficient of variation of all activity values ​​within the activity value time series.

[0085] When the value is equal to 0, it indicates that the pH value does not fluctuate. At this time, the change in the activity value of each metal ion is not related to the pH value. The temporal characteristics of each metal ion can be reflected by the change in the activity value. When not equal to 0, It can reflect the frequency of pH changes, while pH range can reflect the degree of pH change.

[0086] Based on the above analysis, the degree of influence of pH value on each metal ion is constructed, and the expression is as follows:

[0087]

[0088] In the formula, This indicates the degree to which the x-th metal ion is affected by pH value; This indicates the pH sensitivity of the xth metal ion; This represents the first quantity; This indicates the number of data collection points after process ⑤ is completed; This indicates a very poor pH value; This indicates the maximum pH value among the pH data collected after process ⑤ is completed.

[0089] (2) The coefficient of variation of the activity value can reflect the degree of fluctuation of the activity value; based on the coefficient of variation and the influence value, the time-series composition doubt of each metal ion is constructed, reflecting the unreliability of the composition measurement results of the metal ion. The expression for the time-series composition doubt is:

[0090]

[0091] In the formula, This represents the time-series characteristic value of the x-th metal ion at the y-th monitoring location; This indicates the degree to which the x-th metal ion is affected by pH value; The coefficient of variation for the x-th metal ion at the y-th monitoring location; This represents the maximum value of the coefficient of variation for all metal ions at the y-th monitoring location. Let x be the normalized value of the coefficient of variation of the x-th metal ion at the y-th monitoring location; This represents the first quantity. If... When the activity value of the metal ion is extremely stable, it indicates that the activity value of the metal ion is extremely stable. .

[0092] in, middle The function is to The range of the calculated result is mapped from the interval [0,2] to the interval [0,1].

[0093] Furthermore, the mean of the temporal characteristic values ​​of all monitoring locations for each metal ion is used as the temporal component suspicion degree T of each metal ion.

[0094] The greater the doubt about the time sequence composition, the higher the activity instability of the metal ion, and the higher the unreliability of the final composition measurement results.

[0095] (3) Obtain the time series of activity values ​​of each metal ion at each monitoring location after the completion of process ⑤, calculate the Pearson correlation coefficient between any two activity value time series of the metal ion, and calculate the mean of all the Pearson correlation coefficients of the metal ion. Further, add the natural number 1 to the mean and then divide it by 2 to change the range of the mean from [-1,1] to [0,1]. Record the transformed value as the first correlation coefficient. ;

[0096] Further calculations were performed on the standard deviation of the time-series characteristic values ​​of the metal ion at all monitoring locations. .

[0097] Based on the above analysis, the spatial composition doubt level of each metal ion is constructed, expressed as follows:

[0098]

[0099] In the formula, Indicates the degree of suspicion regarding the spatial composition of the xth metal ion; This indicates the degree to which the x-th metal ion is affected by pH value; Let be the first correlation coefficient for the x-th metal ion. It is a reverse index determined based on the first correlation coefficient; Let be the standard deviation of the temporal characteristic values ​​of all monitoring locations for the x-th metal ion; This represents the maximum value of the standard deviation for all metal ions. The normalized value of the standard deviation; This indicates the first quantity. Specifically, if... ,but It is not included in the calculation.

[0100] in, middle The function is to The range of values ​​for is mapped from the interval [0,3] to the interval [0,1]. Similarly, the specifics will not be elaborated further.

[0101] The first correlation coefficient reflects the similarity of the activity values ​​of the metal ion at different locations. Considering that the activity value is affected by changes in pH, therefore... Time utilization Adjust the first correlation coefficient; This reflects the temporal similarity of the metal ion at different positions. The larger the value, the lower the spatial uniformity of the metal ions, and the less reliable the final composition measurement results.

[0102] (4) Calculate the constraint coefficients for each metal ion based on the temporal component suspicion degree and the spatial component suspicion degree, as expressed in the following expression:

[0103]

[0104] In the formula, Represents the constraint limit coefficient for the x-th metal ion; This indicates the preset scaling factor. The value range is (0,1). If the reduction factor is too small, it may erase the true difference and cause over-adjustment; if the reduction factor is too large, the adjustment may be insufficient and may still cause over-adjustment of the component measurement result range. Therefore, in this embodiment... Take 0.7; The time-series composition suspicion of the xth metal ion; The spatial composition suspicion of the xth metal ion.

[0105] Step four: Determine the range of composition measurement results for each metal ion based on the constraint limiting coefficient.

[0106] The activity of a metal ion is equal to the product of its activity coefficient and its concentration; that is, the activity of a metal ion is related to its concentration and activity coefficient. By reading the activity values ​​of each metal ion, the composition of the flotation pulp can be measured. Therefore, after process ⑤ and before process ⑥, ionic-level composition measurement is performed on the flotation pulp, using the activity of metal ions for composition determination.

[0107] Considering the spatial inhomogeneity of each metal ion, this application sets a range for the composition measurement results of each metal ion based on the constraint limiting coefficient, and expresses the composition measurement results of each metal ion in the form of a range.

[0108] Specifically, taking the xth metal ion as an example, the average activity value of all monitoring locations for that metal ion collected after step ⑤ is calculated. As the composition measurement result of the metal ion, and based on the constraint limiting coefficient, the range of the composition measurement result of the metal ion is determined as [ ]. ].

[0109] The range of composition measurement results for each metal ion was obtained using the above method.

[0110] After obtaining concentrate and tailings through process ⑥, the first lead-antimony-silver flotation process ends. The tailings obtained from the first flotation are then subjected to further "scavenging" treatment, which continues for three times before the process ends.

[0111] In summary, this application embodiment collects the metal ion activity and pH value of the slurry during the addition of pH adjuster in the lead-antimony-silver flotation process and after the addition of all flotation reagents. For the data collected during the addition of pH adjuster, the sensitivity of each metal ion activity to pH value changes is analyzed based on the variation law between each metal ion activity and pH value, and a pH sensitivity of each metal ion is constructed to reflect the regulation of the dissolution balance of each metal ion by pH value. For the data collected after the addition of all flotation reagents, constraint coefficients of each metal ion are constructed based on the differences in metal ion activity values ​​at different monitoring locations and the time variation trend of each metal ion at each monitoring location, combined with the pH sensitivity. The composition measurement results of each metal ion are output in the form of range based on the constraint coefficients. This achieves multi-point detection, preserves spatial variation information, and solves the problem of insufficient representativeness of single-point measurement in existing composition measurement methods due to neglecting the non-uniformity of the local flow field in the bypass tank measurement environment. It also avoids the composition measurement results from being too absolute, making the composition measurement results closer to the true metal ion concentration of the entire flotation slurry.

Claims

1. A method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation processes, characterized in that, The method includes the following steps: The lead-antimony-silver flotation process includes: adding a pH adjuster, a collector, and a depressant sequentially to the flotation cell; continuously stirring during the addition of the pH adjuster, and collecting data on the initial slurry in the flotation cell bypass tank during this period; and continuing stirring for a preset time after the depressant addition is completed, and collecting data on the flotation slurry in the flotation cell bypass tank during the preset time. The collected data includes the pH value of the slurry and the activity of each metal ion at each monitoring location; Based on the data collected during the addition of pH adjuster, the change response between pH value and the activity of each metal ion was analyzed to construct the pH sensitivity of each metal ion. Based on the data collected after the inhibitor addition was completed, the uneven distribution of metal ions in the pulp in the time and spatial dimensions was analyzed. Combined with the range of pH values ​​of the flotation pulp and the pH sensitivity, the constraint coefficients of each metal ion were constructed. The range of composition measurement results for each metal ion is determined based on the aforementioned constraint limiting coefficient.

2. The method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation process as described in claim 1, characterized in that, The step of analyzing the change response between pH value and the activity of each metal ion based on data collected during the addition of the pH adjuster, in order to construct the pH sensitivity of each metal ion, includes: The pH adjustment agent addition process is divided into time intervals; at each monitoring location within each time interval, the activity values ​​of each metal ion are linearly fitted to the pH value of the flotation pulp; for each data point on the fitted line, a corresponding weight is set according to its collection time to calculate the weighted goodness of fit of the fitted line; the mean of the weighted goodness of fit of all monitoring locations in the latest time interval of each metal ion is used as the fitting reliability of each metal ion. The number of times the activity value of each metal ion and the number of times the pH value changed at each monitoring location within each time interval were counted. Combined with the range of the activity value of each metal ion at each monitoring location within each time interval, the comprehensive response of each metal ion was calculated. The pH sensitivity of each metal ion is determined based on the overall response and the fitting reliability.

3. The method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation process as described in claim 2, characterized in that, The weighted goodness of fit is specifically: Sort all data points on the fitted line by time, normalize the sorted values ​​of all data points using the maximum value normalization method, and use the normalized values ​​of each sorted value as the weight of each data point. When calculating the goodness of fit of the fitted line, the squared differences of the corresponding data points in the numerator and denominator of the goodness of fit calculation expression are multiplied by the weights, and then summed to obtain the weighted goodness of fit of the fitted line.

4. The method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation process as described in claim 2, characterized in that, The comprehensive responsiveness is specifically as follows: At each monitoring location within each time interval, the ratio of the range of activity values ​​of each metal ion to the maximum value of the range of activity values ​​of all metal ions is calculated and recorded as the first ratio; the absolute value of the difference between the number of times the activity value of each metal ion changes and the number of times the pH value changes is calculated, and the ratio of the absolute value of the difference to the number of collection times within each time interval is calculated, and the difference between the natural number 1 and the ratio is recorded as the first difference. Calculate the average of the first ratio and the first difference; The weighted sum of the average values ​​of each metal ion at each monitoring location over all time intervals is used as the activity response coefficient of each metal ion at each monitoring location. The average activity response coefficient of each metal ion at all monitoring locations is taken as the comprehensive response of each metal ion.

5. The method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation process as described in claim 2, characterized in that, The pH sensitivity is: The average of the fitting reliability of each metal ion and the overall response was used as the pH sensitivity of each metal ion.

6. The method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation process as described in claim 1, characterized in that, The analysis of the uneven distribution of metal ions in the pulp in both time and space, combined with the pH range of the flotation pulp and the pH sensitivity, to construct the constraint coefficients for each metal ion includes: After the inhibitor addition is completed, the number of data in the flotation pulp pH data whose pH value is not equal to the preset pH value is counted and recorded as the first quantity. Based on the first quantity and the range of flotation pulp pH values, combined with the pH sensitivity of each metal ion, the degree of influence of each metal ion on pH value is constructed. Calculate the coefficient of variation of the activity values ​​of each metal ion at each monitoring location, and construct the temporal characteristic values ​​of each metal ion at each monitoring location by combining the influence degree value and the first quantity; use the mean of the temporal characteristic values ​​of all monitoring locations of each metal ion as the temporal component suspicion of each metal ion. Based on the correlation between the time series of activity values ​​at different monitoring locations of each metal ion, and the degree of disorder in the distribution of all the time series characteristic values ​​of each metal ion, combined with the influence degree value and the first quantity, the spatial composition suspicion of each metal ion is constructed. The constraint coefficients for each metal ion are determined based on the temporal component suspicion and the spatial component suspicion.

7. The method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation process as described in claim 6, characterized in that, The specific value of the degree of influence is as follows: Calculate the mean of the normalized values ​​of the first quantity and the normalized values ​​of the pH range of the flotation pulp, and multiply the mean by the pH sensitivity of each metal ion as the influence value of each metal ion.

8. The method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation process as described in claim 6, characterized in that, The time-series feature values ​​are specifically: Obtain the normalized coefficient of variation of the activity values ​​of each metal ion at each monitoring location; If the first quantity is equal to zero, then the normalized value of the coefficient of variation is used as the time-series characteristic value of each metal ion at each monitoring position. If the first quantity is not equal to zero, the normalized value of the coefficient of variation is weighted and adjusted based on the influence value, and the adjusted result is mapped to a preset numerical range as the time-series characteristic value of each metal ion at each monitoring location.

9. The method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation process as described in claim 8, characterized in that, The spatial component suspiciousness is specifically as follows: Calculate the correlation coefficient between the time series of activity values ​​at different monitoring locations of each metal ion, and determine the first correlation coefficient based on the mean of all the correlation coefficients of each metal ion; Obtain the normalized standard deviation of the time-series characteristic values ​​of all monitoring locations for each metal ion; If the first quantity is equal to zero, the spatial composition suspicion of each metal ion is determined based on the inverse index determined by the first correlation coefficient and the normalized value of the standard deviation. If the first quantity is not equal to zero, the inverse index determined based on the first correlation coefficient is weighted and corrected using the influence degree value, and the spatial composition suspicion of each metal ion is determined by combining the corrected inverse index with the normalized standard deviation value.

10. The method for measuring the composition of flotation pulp applicable to lead-antimony-silver flotation process as described in claim 6, characterized in that, The expression for the constraint limiting coefficient is: In the formula, Represents the constraint limit coefficient for the x-th metal ion; This indicates the preset scaling factor; The time-series composition suspicion of the xth metal ion; The spatial composition suspicion of the xth metal ion.

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