Lead-zinc oxide ore flotation reagent stable adding and regulating system

Abstract

The present application relates to mineral processing and control technology field, disclose a kind of lead-zinc oxide ore flotation reagent stable addition and regulation system, including by data acquisition module obtains ore and assay data, process identification module is based on acquisition data output comprehensive disturbance index, regulation calculation module combines smooth dry ore quantity, unit reagent requirement, comprehensive disturbance index and feedback correction coefficient, operation obtains reagent solution volume flow instruction, again by reagent execution module prepared flotation reagent is according to instruction injection operating point, simultaneously, abnormal management module is used to identify abnormal condition and limit the update of feedback correction coefficient during abnormal period.The present application comprehensively ore throughput, feedforward compensation and closed-loop feedback parameter output dosing control quantity, when raw ore property and feed quantity fluctuate, realize the dynamic adjustment and closed-loop correction of reagent, prevent reagent addition imbalance, improve the stability of flotation recovery index.

Description

Technical Field

[0001] This invention relates to the field of mineral processing and control technology, specifically to a system for the stable addition and regulation of flotation reagents for oxidized lead-zinc ore. Background Technology

[0002] The flotation process relies on adding various flotation reagents to change the physicochemical properties of the mineral surface, thereby achieving the separation of useful minerals from gangue. The amount of flotation reagents added directly affects the final concentrate grade and metal recovery rate. Currently, flotation reagent control mostly relies on fixed ratio settings or manual experience adjustments. In actual production, parameters such as the throughput, grade, and phase composition of the raw ore are in a state of continuous change. Fixed ratio reagent addition methods are difficult to adapt to these dynamic disturbances, resulting in situations of excessive or insufficient reagent addition, leading to unstable production indicators.

[0003] Because flotation operations have a long time lag, relying solely on post-flotation test data for manual adjustments often lacks foresight. While existing automatic dosing systems have partially introduced feedback adjustment mechanisms, they have failed to establish multi-dimensional feedforward compensation models to offset operational disturbances in advance. Furthermore, these systems lack the ability to distinguish between the operating status of production equipment and test data. When encountering abnormal operating conditions such as feed interruptions, equipment failures, or distorted test data, erroneous feedback signals will directly participate in closed-loop control calculations, causing disordered fluctuations in dosing commands and leading to system control instability.

[0004] In addition, existing dosing systems ignore the real-time changes in solution concentration during reagent preparation at the execution level. When the actual prepared concentration of the reagent is too low, the system will passively increase the injection volume of the solution in order to achieve the set quality addition target. This method will introduce excessive water into the flotation cell, directly changing the liquid level and pH environment at the operating point, and further damaging the stability of the flotation process. Therefore, an automatic dosing control system that can comprehensively handle multi-dimensional operating condition disturbances, has a stable closed-loop feedback mechanism, and can take into account the physicochemical properties of the reagent is needed. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a stable addition and control system for flotation reagents in oxidized lead-zinc ore. This system solves the problems that existing flotation reagent addition methods cannot adapt to the dynamic fluctuations in the properties of the raw ore and the feed rate, and that the lack of a protection mechanism under abnormal operating conditions can lead to system instability.

[0006] To achieve the above objectives, the present invention provides the following technical solution: This invention provides a system for the stable addition and control of flotation reagents for oxidized lead-zinc ore, comprising: The data acquisition module is used to collect flotation production data, which includes at least the raw ore wet feed rate, raw ore moisture content, and sample test data. The process identification module, connected to the data acquisition module, is used to identify operating condition parameters based on the flotation production data collected by the data acquisition module to determine the unit reagent requirement and output a comprehensive disturbance index. An anomaly management module, connected to the data acquisition module, is used to identify whether there are any abnormal operating condition markers in the current cycle; The control calculation module is connected to the data acquisition module, process identification module, and anomaly management module, respectively. It is used to obtain the smoothed dry feed rate based on the raw ore wet feed rate and the raw ore moisture content, and to calculate and output the reagent solution volume flow rate command based on the smoothed dry feed rate, the unit reagent requirement, the comprehensive disturbance index, and the feedback correction coefficient. During the period when the abnormal condition mark is effective, the feedback correction coefficient is not updated due to the restriction of the anomaly management module. The reagent preparation module is used to prepare flotation reagents; The reagent execution module is connected to the control calculation module and the reagent preparation module respectively. It is used to receive the reagent solution volume flow rate command output by the control calculation module and inject the flotation reagent prepared by the reagent preparation module into the flotation operation point.

[0007] Furthermore, the control calculation module obtains the smoothed dry feed rate based on the collected data. Specifically, this includes: calculating the instantaneous dry feed rate for the current control cycle based on the raw ore wet feed rate and the raw ore moisture content minus the water weight obtained by the data acquisition module; calculating the absolute value of the difference between the instantaneous dry feed rate for the current control cycle and the instantaneous dry feed rate for the previous cycle, and dynamically assigning a smoothing coefficient based on the comparison result of the absolute value of the difference and the stability threshold; and substituting the instantaneous dry feed rate and the smoothing coefficient into the adaptive first-order inertial filter formula for smoothing to obtain the smoothed dry feed rate.

[0008] The above configuration eliminates transient fluctuations during the feeding process through filtering, providing stable basic data for subsequent reagent control.

[0009] Furthermore, the control calculation module obtains the unit reagent requirement for various reagents, specifically including: retrieving the baseline unit quantity of the corresponding flotation reagent based on the ore type determined by the process identification module; extracting the zinc grade offset, zinc oxidation rate offset, pulp temperature offset, and the identified gypsum content state coefficient and mixed ore state coefficient for the current cycle; performing multiplication and addition operations on the baseline unit quantity with the empirical adjustment coefficients corresponding to the above offsets and state coefficients to obtain the comprehensive state offset, and adding the baseline unit quantity and the comprehensive state offset to obtain the unit reagent requirement.

[0010] The above configuration incorporates the original mineral phase state and physicochemical conditions into the calculation of reagent demand, enabling real-time correction of the unit reagent baseline consumption.

[0011] Furthermore, the process identification module outputs a comprehensive disturbance index, which specifically includes: extracting the change amplitude of the smoothed dry feed rate, zinc grade of raw ore, zinc oxidation rate, and slurry temperature in the current control cycle compared to the previous cycle; dividing each change amplitude by the maximum fluctuation range of the corresponding parameter within the historical stable operation cycle to obtain the normalized change; and multiplying the normalized change of each parameter, the gypsum content state coefficient, and the mixed ore state coefficient by their respective set weight values ​​and then performing weighted summation to calculate the comprehensive disturbance index of a single evaluation indicator.

[0012] The above configuration transforms multi-dimensional input parameter fluctuation signals into a single evaluation index, thereby quantifying the degree of fluctuation in system operating conditions.

[0013] Furthermore, the control calculation module synthesizes the total calculated addition amount, specifically including: calling the feedback correction coefficient updated in the previous shift's sample statistical cycle from the storage unit; matching the corresponding anti-disturbance adjustment factor according to the functional attributes of various flotation reagents, and multiplying the anti-disturbance adjustment factor with the comprehensive disturbance index to obtain the disturbance compensation term; performing a multiplicative logic fusion operation on the smoothed dry feed amount, unit reagent demand, feedback correction coefficient, and the disturbance compensation term after superimposing a constant of 1 to obtain the total calculated addition amount.

[0014] The above configuration integrates the ore feed rate, feedforward compensation, and closed-loop feedback parameters to output the current theoretical dosing control rate.

[0015] Furthermore, the control calculation module performs boundary limit constraint processing on the total calculated addition amount, specifically including: extracting the actual total addition amount executed in the previous control cycle, constructing upper and lower limit boundaries to prevent jumps by combining the maximum allowable upward adjustment ratio and the maximum downward adjustment ratio in a single cycle, truncating the total calculated addition amount exceeding the upper and lower limit boundaries to the boundary value to obtain the transitional calculated addition amount; reading the maximum rated flow and minimum safe flow of the dosing equipment calibrated in the drug execution module to construct the limit capacity hard constraint boundary; determining whether the transitional calculated addition amount exceeds the limit capacity hard constraint boundary, performing absolute value protection processing and outputting the actual total added amount executed.

[0016] The above configuration combines anti-jump amplitude limiting and hardware extreme value constraints to avoid instability in the flotation cell or pipeline blockage caused by sudden changes in dosing commands.

[0017] Furthermore, the control calculation module converts the volumetric flow rate of the drug solution, specifically including: extracting the baseline allocation ratio of each dosing point, and performing adaptive tilt adjustment calculations in combination with the comprehensive disturbance index and allocation adjustment coefficient, and obtaining the dynamic allocation ratio of each dosing point after normalization; multiplying the actual total amount added by the corresponding dynamic allocation ratio to obtain the amount added at each dosing point; and converting the amount added at each dosing point in terms of mass dimension into the volumetric flow rate of the drug solution at the corresponding dosing point in combination with the effective concentration and density of the drug solution monitored by the drug preparation module.

[0018] The above configuration combines the operating disturbance state and the real-time physical properties of the agent to dynamically adjust the distribution ratio of each dosing point, thereby achieving accurate dosing of the agent.

[0019] Furthermore, the control calculation module implements reagent concentration protection, specifically including: calculating the storage capacity of the reagent preparation tank by combining the flow integral logic with the duration of the control cycle and the volume of the added reagent solution; monitoring the effective concentration of the reagent solution inside the reagent preparation module in real time and comparing it with the preset effective concentration safety lower limit; triggering the protection mechanism when the actual measured effective concentration of the reagent solution is lower than the effective concentration safety lower limit, forcibly blocking the upward adjustment command of the reagent solution volume flow rate at all corresponding dosing points.

[0020] The above configuration limits the increase of volumetric flow rate when the reagent concentration is low, to avoid changing the pH and liquid level environment of the flotation operation point due to the introduction of too much water.

[0021] Furthermore, the control calculation module obtains the deviation of production indicators, specifically including: at the end of the shift sample statistical period, extracting the zinc grade of raw ore, zinc grade of concentrate, and zinc grade of tailings from the shift sample test data accessed by the laboratory terminal; calling the two-product balance formula to substitute the zinc grade of raw ore, zinc grade of concentrate, and zinc grade of tailings into the solution to calculate the concentrate yield and zinc recovery rate for the current shift sample statistical period; performing difference calculations between the zinc recovery rate and the zinc grade of concentrate and the preset target recovery rate and preset target grade, respectively, to extract the zinc recovery rate deviation and concentrate zinc grade deviation with polar signs.

[0022] The above configuration calculates the deviation of actual production indicators through the balance operation of the two products, providing a correction basis for the closed-loop iteration of the control system.

[0023] Furthermore, the anomaly management module and the control calculation module work together to update the feedback correction coefficient. Specifically, this includes: quantifying six types of anomalies—feeding anomalies, ore anomalies, grinding anomalies, reagent dosing anomalies, dehydration anomalies, and sample mutations—as Boolean variables, performing a logical OR operation to determine the anomaly condition flag; when the anomaly condition flag value is 1, the closed-loop iterative formula is masked and the feedback correction coefficient of the previous cycle is forcibly locked as the output of the current cycle; when the anomaly condition flag value is 0, the zinc recovery rate deviation and the concentrate zinc grade deviation are multiplied by the corresponding integral gain coefficients, and added to the feedback correction coefficient of the previous cycle to perform a limited integral operation to obtain the feedback correction coefficient of the current cycle.

[0024] The above configuration locks the feedback correction coefficient when abnormal operating conditions are detected, preventing distorted data from participating in closed-loop iteration and ensuring the stability of the control parameter updates.

[0025] This invention provides a system for the stable addition and control of flotation reagents for oxidized lead-zinc ore. It has the following beneficial effects: 1. This invention calculates the total reagent addition by combining the smoothed dry feed rate, unit reagent requirement, and comprehensive disturbance index, transforming multi-dimensional changes in operating conditions such as raw ore feed rate, ore phase state differences, and slurry temperature into quantifiable compensation parameters. This design enables the reagent addition system to make timely feedforward compensation adjustments when faced with fluctuations in feed rate or raw ore properties, avoiding excessive or insufficient reagent addition caused by traditional fixed ratios or manual reagent addition, and improving the accuracy of basic reagent addition matching in flotation operations.

[0026] 2. Before outputting the reagent flow rate command, this invention performs dual limiting processing of anti-jump boundary and ultimate capacity hard constraint, and performs lower limit protection in combination with the effective concentration of reagent solution. The above configuration prevents the dosing equipment from being overloaded or the pipeline from being blocked due to instantaneous changes in the calculation command. At the same time, it avoids the system from continuously increasing the volume flow rate command to meet the dosing quality when the reagent concentration is too low, and prevents the introduction of excess water into the flotation slurry, thereby changing the original liquid level and pH environment of the working point and maintaining the stability of the internal state of the flotation cell.

[0027] 3. This invention updates the feedback correction coefficient by extracting sample test data to calculate production index deviations, thereby achieving closed-loop correction of the system. At the same time, an anomaly management module is set up to identify various equipment and production anomalies. When an anomaly condition flag is detected, the system restricts and locks the update calculation of the feedback correction coefficient. This mechanism can not only perform long-term calibration of the dosing model based on actual flotation recovery indicators, but also eliminate the misleading effects of peripheral equipment failures or distorted test data on closed-loop control, ensuring the long-term reliability of the automatic dosing control system. Attached Figure Description

[0028] Figure 1This is a schematic diagram of the module architecture of the present invention; Figure 2 This is a schematic diagram of the method flow of the present invention; Figure 3 This is a schematic diagram of the multidimensional state feedforward compensation and disturbance index construction process of the present invention; Figure 4 This is a schematic diagram of the total additive synthesis and multi-level safety limiting process of the present invention; Figure 5 This is a schematic diagram of the anomaly detection and long-cycle feedback iteration mechanism of the present invention; Figure 6 This is a comparison chart of the mean and standard deviation of production indicators between the experimental group and the control group of this invention; Figure 7 This is a comparison chart of the unit consumption of the collector in the experimental group and the control group of the present invention.

[0029] The module includes: 10. Data acquisition module; 20. Drug preparation module; 30. Drug execution module; 40. Process identification module; 50. Control calculation module; and 60. Anomaly management module. Detailed Implementation

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] See attached document Figure 1 The present invention provides a stable addition and control system for flotation reagents of oxidized lead-zinc ore, the system comprising: a data acquisition module 10, a reagent preparation module 20, a reagent execution module 30, a process identification module 40, a control calculation module 50, and an anomaly management module 60.

[0032] The data acquisition module 10 is used to collect data on raw ore wet feed rate, raw ore moisture content, raw ore zinc grade, zinc oxidation rate, ore type, gypsum content status, grinding fineness, flotation pulp temperature, concentrate grade, tailings grade, concentrate yield, flotation reflux water status, and equipment operating status. Among these, the raw ore zinc grade, zinc oxidation rate, concentrate zinc grade, and tailings zinc grade are the main indicators for closed-loop control of zinc oxide flotation reagents in this embodiment. Lead mineral-related flotation indicators are not used as closed-loop inputs for feedback correction coefficients in this embodiment. The hardware data access sources of the data acquisition module 10 include belt weighing equipment, production reporting system, sampler, laboratory terminal, and temperature sensor. The raw ore wet feed rate is accessed by the belt weighing equipment, the raw ore moisture content, zinc oxidation rate, ore type, and gypsum content status are entered and obtained by the laboratory terminal, the flotation reflux water status is obtained by the production reporting system, and the flotation pulp temperature is accessed by the temperature sensor.

[0033] The reagent preparation module 20 is located in the supporting mineral processing reagent building and is used to complete the preparation, stirring, maturation, storage and concentration management of oxidized ore flotation reagents. The reagent preparation module 20 is equipped with reagent preparation tanks and conveying pipelines. Various flotation reagents are mixed in the corresponding reagent preparation tanks to the set effective concentration. The conveying pipelines of the reagent preparation module 20 are covered with heat insulation components to maintain the conveying temperature of the reagent solution in the pipeline.

[0034] The reagent execution module 30 is used to add reagents to the corresponding flotation operation points according to the set volumetric flow rate; the corresponding flotation operation points include the slurry inlet point before roughing, the roughing operation section, the scavenging operation section, the cleaning operation section, and the middlings return position; the reagent execution module 30 consists of a dosing pump, a fluid control valve, and a flow detection device.

[0035] The process identification module 40 is connected to the data acquisition module 10 and is used to identify the current ore type, feed disturbance degree, slurry temperature change trend, gypsum content change state and flotation return water state change based on the acquired production data, and convert the identified change information into control parameters for calculation logic processing.

[0036] The control calculation module 50 is connected to the process identification module 40 and the reagent execution module 30 respectively. The control calculation module 50 is used to calculate the unit consumption, total addition, point addition and execution setting of various flotation reagents. The control calculation module 50 is also used to perform feedback correction calculation on the calculated reagent dosage according to the sample test results, and send the finally calculated execution setting to the reagent execution module 30 to execute the dosing action.

[0037] The anomaly management module 60 is connected to the data acquisition module 10 and the control calculation module 50. It is used to identify abnormal operating conditions such as shutdown maintenance, sudden changes in ore feed, sudden changes in ore properties, exceeding the capacity limit of the dosing equipment, blockage of the reagent pipeline, abnormal overflow of the concentration, and abnormal dewatering of the concentrate. During the period when the abnormal operating condition is confirmed to be effective, the anomaly management module 60 outputs instructions to restrict the control calculation module 50 from updating the long-term feedback correction parameters.

[0038] See attached document Figure 2 This invention provides a method for the stable addition and control of flotation reagents for lead-zinc oxide ore, comprising the following steps: S1, collect flotation production data and reagent system operation data for the current control cycle. The flotation production data includes the raw ore wet feed rate and raw ore moisture content. Calculate the dry feed rate based on the raw ore wet feed rate and raw ore moisture content, and perform inertial filtering and smoothing on the dry feed rate to obtain the smoothed dry feed rate. S2. Identify the ore type for the current period based on the collected flotation production data, retrieve the corresponding reagent benchmark unit quantity based on the ore type, and calculate the unit reagent requirement by combining the state offset corresponding to the zinc grade, zinc oxidation rate, pulp temperature, gypsum state and mixed ore state of the raw ore; at the same time, calculate the comprehensive disturbance index and the corresponding disturbance compensation coefficient for the current period. S3 calculates the total calculated addition of various reagents based on the smoothed dry feed rate, unit reagent demand, disturbance compensation coefficient, and feedback correction coefficient of the previous shift's statistical period; performs boundary limiting processing and equipment limit capacity constraint processing on the total calculated addition to obtain the actual total addition of each reagent. S4, based on the set spatial allocation ratio, calculates the amount of each reagent added at each dosing point, and converts the amount added at each point into the volumetric flow rate of the reagent solution in combination with the effective concentration of the reagent solution; drives the reagent execution module to continuously inject reagents into the designated flotation operation point according to the volumetric flow rate of the reagent solution; S5: Obtain the dry ore quality, concentrate quality and test grade data of the current shift sample statistical period, calculate the concentrate yield and zinc recovery rate of the current shift sample, and obtain the corresponding zinc recovery rate deviation and concentrate zinc grade deviation based on the preset indicators. S6. Determine whether there is an abnormal working condition marker in the current statistical period. If there is no abnormal working condition marker, update the feedback correction coefficients of various reagents iteratively based on the zinc recovery rate deviation and the concentrate zinc grade deviation. If there is an abnormal working condition marker, lock the feedback correction coefficients of the previous period so that they are not updated in the current period.

[0039] In specific implementations, step S1 provided by this invention may include the following steps: S101, the data acquisition module 10 acquires the raw ore wet feed rate and raw ore moisture content of the current control cycle. The data acquisition module 10 obtains the raw ore wet feed rate by receiving the weight signal through the belt weighing device installed on the belt conveyor, and obtains the raw ore moisture content through the online moisture analyzer or laboratory terminal system. The specific process of the belt weighing device acquiring the weight signal and the terminal communication network transmitting the digital signal can be configured according to the field industrial bus interface.

[0040] S102, during on-site production, the raw ore contains moisture that varies with climate and mining conditions. The control calculation module 50 deducts the water weight based on the measured moisture content and converts the wet feed rate of the raw ore into the dry feed rate using the following formula: ; In the formula, This represents the current drug regulation cycle number. For the first Instantaneous dry feed rate during the cycle; For the first Periodic wet feed rate measurement; For the first The moisture content of the ore during the period is used to provide a basis for the amount of solid minerals involved in the flotation physicochemical reaction through this conversion method.

[0041] S103, In the mineral processing feeding process, the feed rate often fluctuates instantaneously due to bridging of the silo or frequency conversion of the feeder speed. The control calculation module 50 performs adaptive first-order inertial filtering on the dry feed rate of the raw ore to obtain a smooth dry feed rate. The calculation formula is as follows: ; In the formula, This refers to the control cycle number; For the first Periodic smoothing of dry feed rate; For smoothing coefficients; For the first Instantaneous dry feed rate during the cycle; This is the smoothed dry feed rate from the previous control cycle.

[0042] The control calculation module 50 dynamically assigns a smoothing coefficient based on the fluctuation range of the feed rate. When the absolute value of the difference between the current cycle dry feed rate and the previous cycle dry feed rate is within the preset stability threshold range, the control calculation module 50 assigns a smoothing coefficient between 0.6 and 0.8. When the absolute value of the difference exceeds the stability threshold range, the control calculation module 50 assigns a smoothing coefficient between 0.1 and 0.3. The stability threshold is set as the average value of the dry feed rate fluctuation range within a historical stable operating cycle plus or minus the standard deviation range. In this embodiment, the stability threshold ranges from 3% to 5%. The above control operation outputs continuous and stable feed benchmark data to support subsequent reagent calculation logic.

[0043] See attached document Figure 3 In specific implementations, step S2 provided by the present invention may include the following steps: S201, the process identification module 40 receives the raw ore source data and phase characteristic data from the data acquisition module 10 and determines the current ore type. The ore type is divided into limestone type and sandstone type according to the basic lithology. The gypsum content state and mixed ore state are not used as the basis for repeated classification of ore type, but are used as independent state parameters to participate in the subsequent unit reagent demand correction and disturbance index calculation. After determining the ore type, the process identification module 40 sends the result to the control calculation module 50. The control calculation module 50 accesses the preset reagent benchmark mapping table in the local database and retrieves the reagent benchmark unit quantity corresponding to the ore type. The specific process of database table construction and data retrieval can be designed and queryed according to the conventional database management system.

[0044] S202 In actual flotation reactions, the consumption of reagents is not only related to the amount of raw ore processed. The increase in zinc grade and oxidation rate in the raw ore will correspondingly increase the surface adsorption requirements of the collector. The decrease in pulp temperature will reduce the activity of the reagents and trigger the operation of appropriately increasing the reagent addition base. At the same time, high gypsum content and ore mixing operations will change the acid-base environment of the pulp and lead to an increase in non-selective consumption on the gangue surface. The control calculation module 50 extracts the relevant state parameters of the current cycle and calculates the state offset of the reagent base unit quantity in combination with the identified gypsum state and ore mixing state, thereby obtaining the actual unit reagent requirement.

[0045] The specific formula for calculating the unit dosage of medicine is as follows: ; In the formula, This refers to the control cycle number; Types of pharmaceutical preparations; It is an ore type; For the first Periodic drugs The unit dosage of medicine required; For medicine In ore type The baseline unit drug dosage; The zinc grade empirical adjustment coefficient is used in this embodiment. The value range is from 0.1 to 0.3; For the first The periodic zinc grade shift; This is an empirical adjustment coefficient for zinc oxidation rate, and its value ranges from 0.2 to 0.5 in this embodiment. For the first The periodic zinc oxidation rate offset; This is an empirical adjustment coefficient for slurry temperature, and in this embodiment, its value ranges from -0.05 to -0.02. For the first Periodic slurry temperature offset; The value is an empirical adjustment coefficient for gypsum content, and in this embodiment, it ranges from 0.15 to 0.25. For the first Periodic gypsum content state coefficient; It is an empirical adjustment coefficient for the mixed ore state, and its value ranges from 0.1 to 0.2 in this embodiment; For the first Periodic mixing state coefficient; Among them, the state coefficient of gypsum content With the ore mixing state coefficient The process identification module 40 assigns discrete Boolean values ​​(1 if the state exists, 0 if it does not) or actual mass percentage values ​​based on the current raw ore phase determination results. The system calculates the corresponding offset by subtracting the benchmark reference value from the real-time measured value of each parameter and outputs the prediction result. The benchmark reference value is the statistical average value of the corresponding raw ore type in the historical stable operation cycle or the manually set process target value.

[0046] S203, sudden changes in feed rate or sharp fluctuations in the properties of raw ore during production can impact the stable distribution of flotation reagents. If reagents are added according to the conventional static ratio, it will cause an imbalance in the reagent concentration in the local tank. The control calculation module 50 extracts the change amplitude of the smoothed dry feed rate and raw ore properties data of the current control cycle compared with the previous cycle and performs normalization processing. The normalized changes in feed rate, grade, oxidation rate and temperature are combined with special ore state coefficients for weighted summation. The specific normalization processing method is as follows: the change amplitude of each parameter is divided by the maximum fluctuation range of the parameter in the historical stable operation cycle, and it is mapped to the dimensionless 0 to 1 interval. The sudden fluctuation signals of multiple dimensions are fused and transformed into a single evaluation index.

[0047] The specific formula for calculating the comprehensive disturbance index is as follows: ; In the formula, This refers to the control cycle number; For the first The comprehensive disturbance index of the cycle; A weight value is set for the ore feed rate, and in this embodiment, the value ranges from 0.3 to 0.4; For the first Normalized variation in ore feed rate over a period of time; A weight value is assigned to the zinc grade, and in this embodiment, the value ranges from 0.2 to 0.3. For the first The normalized change in zinc grade over a period of time; A weight value is assigned to the zinc oxidation rate, and in this embodiment, the value ranges from 0.1 to 0.2. For the first The normalized change in zinc oxidation rate over the period; A weight value is assigned to the slurry temperature, and in this embodiment, the value ranges from 0.05 to 0.1. For the first The normalized variation of pulp temperature over a period of time; A weight value is assigned to the gypsum content state, and in this embodiment, the value ranges from 0.05 to 0.1; For the first Periodic gypsum content state coefficient; A weight value is set for the mixed ore state, and in this embodiment, the value ranges from 0.05 to 0.1; For the first Periodic mixing state coefficient, and and and and and Each parameter represents a set weight value, and the sum of the weight values ​​is 1. In this embodiment, the weights of each parameter are assigned according to their sensitivity to the flotation process, and the sum of the feed weight and the grade weight is set to be greater than 0.5.

[0048] S204, the control calculation module 50 matches the corresponding disturbance compensation coefficients for flotation reagents with different functions based on the calculated comprehensive disturbance index. The control calculation module 50 sets the anti-disturbance adjustment factor of the collector and frother to a positive value in the range of 0.1 to 0.2 and triggers a positive compensation command when the feed or ore properties change abruptly. The control calculation module 50 sets the anti-disturbance adjustment factor of the modifier to 0 and keeps the modifier's baseline dosage ratio locked during disturbances. The control calculation module 50 sets the anti-disturbance adjustment factor of the inhibitor to a negative value in the range of -0.1 to -0.05 and reduces the dosage of the inhibitor when the operating conditions fluctuate. Thus, the actual control parameters of various reagents corresponding to sudden operating conditions are output.

[0049] See attached document Figure 4 In specific implementations, step S3 provided by the present invention may include the following steps: S301, the control calculation module 50 extracts the smoothed dry feed rate and the unit reagent demand and comprehensive disturbance index of various reagents output from the previous steps. Simultaneously, it retrieves the feedback correction coefficient updated in the previous shift's statistical cycle from the local storage unit. Through multiplication logic, it fuses the above multidimensional control parameters. At the same time, it introduces the disturbance compensation term, which is formed by multiplying the anti-disturbance adjustment factor and the comprehensive disturbance index, into the synthesis calculation structure. The specific formula for the total calculated reagent addition amount couples feedforward prediction with long-cycle closed-loop feedback and front-end anti-disturbance compensation to form a preliminary theoretical reagent addition control amount. The formula for the total calculated addition amount is as follows: ; In the formula, This refers to the control cycle number; Types of pharmaceutical preparations; For the first Periodic drugs Total calculated additions; For the first Periodic smoothing of dry feed rate; For the first Periodic drugs The unit dosage of medicine required; The reagents locked for the previous shift's statistical cycle Feedback correction coefficient; For medicine The corresponding disturbance rejection adjustment factor; For the first The comprehensive disturbance index of the cycle, the above synthesis logic comprehensively considers the basic dry ore processing capacity and the fluctuation of reagent consumption caused by instantaneous phase changes, and uses the feedback index of the previous shift to perform closed-loop correction of the benchmark parameters, and in conjunction with the anti-disturbance compensation item, improves the robustness of the system under sudden working conditions.

[0050] S302, the mineral flotation system has the physical characteristics of large volume and long hysteresis. A step change in the reagent injection command will cause instability in the fluid dynamics and bubble mineralization equilibrium state established inside the flotation cell. The control calculation module 50 performs anti-jump boundary limit control on the total calculated addition amount. The system extracts the actual total addition amount of the previous control cycle as the benchmark reference base, and sets the allowable upward increase threshold and downward decrease threshold for a single cycle. When the calculated change rate of the total added amount exceeds the above-set threshold, the system performs truncation processing according to the preset boundary. The specific anti-jump limit control formula is as follows: ; In the formula, This represents the amount added during the transition calculation after amplitude limiting processing; Represents the drugs of the previous regulatory cycle The actual total amount added during execution; This represents the maximum allowable upward adjustment percentage per cycle, and in this embodiment, the value range is set to 5% to 8%; The function is for finding the minimum value; This is a function to find the maximum value. This represents the maximum allowable reduction ratio in a single cycle, and in this embodiment, the value range is set to 3% to 5%. The flotation system has asymmetric characteristics when responding to changes in reagents, and excessively rapid reduction of reagents can lead to a serious deterioration in mineral de-removal and recovery rates. The aforementioned asymmetric limiting structure imposes nonlinear constraints on the dosing command based on the process characteristics, reducing the risk of instantaneous shocks in reagent concentration inside the flotation cell caused by abnormal extreme values ​​in the model output.

[0051] S303, the diaphragm metering pump or variable frequency peristaltic pump performing the dosing action on-site is limited by the mechanical stroke and motor frequency, resulting in a physical limit boundary for its conveying capacity. When the flow rate of the chemical solution is lower than the minimum range of the equipment, crystallization blockage will occur inside the fluid pipeline. After obtaining the transition calculation dosage, the control calculation module 50 superimposes the hard constraint calculation logic of the dosing equipment's limit capacity. The system reads the hardware parameters of the dosing pump fed back by the chemical execution module 30 and extracts the calibrated maximum rated flow rate and minimum safe flow rate of the equipment. Absolute value protection processing is performed on the transition data after the limit is applied. The specific hard constraint formula for the limit capacity is as follows: ; In the formula, This refers to the control cycle number; Types of pharmaceutical preparations; The agent after hard constraint treatment The actual total amount added during execution; The function is for finding the minimum value; For medicine The corresponding maximum allowable output flow rate limit of the dosing equipment; This is a function to find the maximum value. This is the amount added for the transition calculation after amplitude limiting processing; To maintain the medication The minimum safe flow limit value corresponding to the laminar flow in the pipeline, and the data after passing through the absolute boundary constraint of this layer, are output as the final executable control command at the physical level to the subsequent spatial allocation stage. The calibration of equipment flow parameters and the configuration of operating constraints can be implemented according to the actual equipment manual on site.

[0052] In specific implementations, step S4 provided by this invention may include the following steps: S401. When the flotation conditions are dynamically changing and the feed grade or ore properties are disturbed, there may be insufficient reagents in the roughing stage and excessive reagents in the scavenging stage. The control calculation module 50 extracts the baseline allocation ratio of each dosing point based on historical balance data and performs dynamic calculations in conjunction with the comprehensive disturbance index of the current cycle. Based on different disturbance states, the system performs adaptive tilt adjustment calculations of the dosing ratio for different flotation stages. The system adds up the adjusted ratios of each point and performs normalization to maintain the sum of the total allocation ratios constant at 1. The specific dynamic allocation ratio calculation formula is as follows: ; In the formula, This refers to the control cycle number; Types of pharmaceutical preparations; Number the dosing point; For the first Periodic drugs At the medication dispensing point The dynamic allocation ratio; For medicine At the medication dispensing point The baseline allocation ratio; For the first The comprehensive disturbance index of the cycle. The system allocates adjustment coefficients based on the dosing point. Different allocation adjustment coefficients are assigned to the different operating sections. For the slurry inlet point before roughing and the roughing operating section, the allocation adjustment coefficient is set to a positive number in the range of 0.05 to 0.1. For the scavenging operating section and the cleaning operating section, it is set to a negative number or zero value in the range of -0.05 to 0. The system outputs a reagent pre-dosing command during the operating condition disturbance stage and restores to the baseline distribution state when the operating condition is stable.

[0053] S402, after the mineral processing reagent is diluted and prepared to a specific concentration by the preparation system, it is fed into the flotation operation. The control calculation module 50 multiplies the calculated total amount of reagent added by the dynamic distribution ratio of each addition point to obtain the amount of reagent added at each point. Combined with the effective concentration and density of the reagent solution fed back by the reagent preparation module 20, the amount of reagent added at each point in terms of mass dimension is converted into a volumetric flow rate execution command. The specific conversion formula for volumetric flow rate is as follows: ; In the formula, This refers to the control cycle number; Types of pharmaceutical preparations; Number the dosing point; For the first Periodic drugs At the medication dispensing point The corresponding volumetric flow rate of the reagent solution at the location; For the first Periodic drugs The actual total amount added during execution; For the first Periodic drugs At the medication dispensing point The dynamic allocation ratio; For the first Periodic drugs The effective concentration of the solution; For medicine The solution density is calculated; the control calculation module 50 converts the calculated volumetric flow rate into a standard analog quantity or digital communication command and sends it to drive the dosing pump and fluid control valve in the reagent execution module 30 to continuously inject reagents into the designated flotation operation point according to the above command. The dosing command communication conversion and pump valve closed-loop control process can be implemented according to the conventional automated control system configuration.

[0054] S403, the reagent preparation module 20 is equipped with a level transmitter and a temperature sensor to monitor the status of the reagent solution. The system calculates the storage capacity of each reagent preparation tank according to a predetermined time step using flow integral logic. The specific formula for calculating the storage capacity is as follows: ; In the formula, This refers to the control cycle number; Types of pharmaceutical preparations; Number the dosing point; End of current cycle drug The inventory level of the storage tanks; The last dose of the previous cycle The inventory level of the storage tanks; For newly prepared and added medicines during this cycle Solution volume; For the first Periodic drugs At the medication dispensing point The corresponding volumetric flow rate of the reagent solution at the location; To control the duration of the control cycle, the control calculation module 50 sets 10°C as the heat preservation trigger threshold and activates the heat tracing operation of the heat preservation component outside the delivery pipeline when the pipeline temperature is detected to be lower than this threshold. At the same time, it sets 8% as the safe lower limit of the effective concentration of the reagent solution and triggers a temporary suspension protection mechanism when the actual concentration is lower than this lower limit. During the period when this mechanism is in effect, the control calculation module 50 forcibly blocks the upward adjustment command of the reagent solution volume flow rate and outputs an abnormal alarm signal to avoid additional increase in the moisture load inside the flotation cell.

[0055] In specific implementations, step S5 provided by the present invention may include the following steps: S501, the actual operating status of the flotation process is reflected in the concentrate yield and zinc recovery rate corresponding to the balance of the two products. At the end of each shift's statistical cycle, the data acquisition module 10 accesses the test data of the zinc grade of the raw ore, the zinc grade of the concentrate, and the zinc grade of the tailings through the laboratory terminal system. The control calculation module 50 extracts the above-mentioned shift's test data and performs the calculation of the balance of the two products and the production indicators. The specific concentrate yield and zinc recovery rate are solved using the following two-product balance formula: ; ; In the formula, For the statistical period number of the class sample; For the first Concentrate yield per class sample period; For the first Zinc grade of raw ore for each shift's statistical period; For the first Zinc grade of tailings in each shift's statistical period; For the first Zinc grade of concentrate in each class sample statistical period; For the first The zinc recovery rate for each shift's statistical cycle; the specific process of data entry and database retrieval for the laboratory terminal system can be achieved through standard interface calls based on the on-site laboratory information management system.

[0056] S502, the control calculation module 50 sets preset target recovery rate and preset target grade based on the annual production task book of the concentrator and the process control indicators issued in the previous concentrator test report. The control calculation module 50 extracts the calculated value of zinc recovery rate and the test value of zinc grade of concentrate of the current shift sample and performs the reagent control target deviation measurement calculation. The system obtains the deviation degree of key production indicators by subtracting the actual operating indicators from the preset control targets. The specific reagent control target deviation measurement formula is as follows: ; ; In the formula, For the statistical period number of the class sample; Representing the Deviation in zinc recovery rate for each class sample over a statistical period; Representing the Deviation of zinc grade in concentrate for each shift's statistical period; This represents a preset target recovery rate, which in this embodiment is set to a constant between 85% and 88%. This represents a preset target grade, which in this embodiment is set to a constant between 40% and 45%. For the first Zinc recovery rate for each class sample over a statistical period; For the first The zinc grade of concentrate for each shift's statistical period; the above deviation values ​​have positive and negative polarity signs and map whether the current system is in a production state of exceeding or failing to meet the target, and the deviation data serves as the basic input source for subsequent long-term feedback correction coefficient iterative updates.

[0057] See attached document Figure 5 In specific implementations, step S6 provided by the present invention may include the following steps: S601, the deterioration of production indicators caused by equipment failures or unsteady events such as process water interruption during flotation production is independent of reagent dosing operations. The control calculation module 50 constructs a multi-dimensional abnormal operating condition marking and judgment model based on the operation log and extracts six categories of engineering abnormal signals: ore abnormality, grinding abnormality, reagent dosing abnormality, dewatering abnormality, and sample mutation. The system quantifies the abnormal states of each dimension into discrete variables of Boolean type and performs a logical OR operation. The comprehensive anomaly judgment adopts the following Boolean logic calculation formula: ; In the formula, For the statistical period number of the class sample; For the first Comprehensive abnormal working condition marking for each shift / sample cycle; For the first Boolean variables representing abnormal ore feeding during each shift cycle; For the first Boolean variables representing ore anomalies in each shift's sample period; For the first Abnormal Boolean variables of grinding in each shift cycle; For the first Abnormal Boolean variables for drug administration in each shift cycle; For the first Abnormal Boolean variables for dehydration in each class sample cycle; For the first The Boolean variable for each shift sample cycle is set to 1 when the feed interruption time exceeds 15 minutes or the dosing pump fault alarm signal lasts for 10 minutes. The system outputs the overall working condition health status label of the current shift sample cycle through logical OR operation.

[0058] S602, the control calculation module 50 receives the comprehensive abnormal working condition flag and executes the data locking and anti-pollution protection mechanism based on the flag value. When the value of the comprehensive abnormal working condition flag in the current period is determined to be 1, the system directly blocks the subsequent feedback iteration formula. The control calculation module 50 forcibly controls the feedback correction coefficient of all reagents in the storage unit to maintain the same value as the previous shift sample statistical period. This interlocking control means blocks the abnormal data caused by peripheral equipment level faults from propagating to the core parameter area of ​​the control algorithm. The communication access of equipment fault alarm signals can be configured using industrial Ethernet.

[0059] S603, when the comprehensive abnormal operating condition flag value of the current cycle is determined to be 0, the control calculation module 50 executes the feedback correction coefficient iterative update logic under normal operating conditions. The system extracts the feedback correction coefficient of the previous cycle and performs a limited integral calculation by combining the zinc recovery rate deviation and concentrate zinc grade deviation of the current cycle. The specific feedback correction coefficient iterative update formula is as follows: ; In the formula, For the statistical period number of the class sample; Types of pharmaceutical preparations; For the first Statistical analysis of each class's periodic drug dosage Updated feedback correction coefficients; The function is for finding the minimum value; This is a function to find the maximum value. For the previous shift's sample statistical cycle of reagents Feedback correction coefficient; For the first Deviation in zinc recovery rate for each class sample over a statistical period; For the first Deviation of zinc grade in concentrate for each shift's statistical period; The integral gain coefficient representing the recovery rate has a positive or negative polarity depending on the reagent. The types and metallurgical mechanisms of action are set, for example, the values ​​for collectors and activators are set to -0.05 to -0.01, and the values ​​for inhibitors are set to 0.01 to 0.05; The integral gain coefficient representing the grade is set according to the type of reagent k and the metallurgical mechanism. For example, the value is set to 0.01 to 0.05 for collectors and activators, and to -0.05 to -0.01 for inhibitors. The amplitude-limited integral operation limits the feedback correction coefficient to the range of 0.8 to 1.2 and drives the system to complete long-cycle closed-loop iterative updates.

[0060] Application Examples: To aid in understanding the technical solution of this invention, the following is an application embodiment of a system for the stable addition and control of flotation reagents for lead-zinc oxide ore.

[0061] The data acquisition module 10 obtains the current control cycle's raw ore wet feed rate as 100 tons per hour and the raw ore moisture content as 5%. The control calculation module 50 converts the raw ore wet feed rate into a raw ore dry feed rate of 95 tons per hour based on the measured moisture content. The control calculation module 50 extracts the smoothed dry feed rate of the previous control cycle as 90 tons per hour and calculates that the absolute value of the difference between the current cycle's dry feed rate and the previous cycle's dry feed rate is 5 tons per hour. It determines that this difference is within the stable threshold range of 3% to 5%, and the control calculation module 50 assigns a smoothing coefficient of 0.6. Through the smoothing processing formula, it calculates that the current cycle's smoothed dry feed rate is 93 tons per hour.

[0062] The process identification module 40 determines that the current ore type is sandstone and the gypsum content status is high. The control calculation module 50 calls the database to obtain the collector's benchmark unit quantity as 100 grams per ton. The control calculation module 50 extracts the current cycle zinc grade offset as 0.5% and the corresponding zinc grade empirical adjustment coefficient as 0.2, the zinc oxidation rate offset as 2% and the corresponding empirical adjustment coefficient as 0.3, the slurry temperature offset as -1℃ and the corresponding empirical adjustment coefficient as -0.02, the gypsum content status coefficient as 1 and the corresponding empirical adjustment coefficient as 0.2, and the mixed ore status coefficient as 0. The control calculation module 50 substitutes the above values ​​into the formula to obtain the unit reagent requirement as 192 grams per ton. The process identification module 40 simultaneously outputs the current cycle comprehensive disturbance index calculation value as 0.1 and sets the anti-disturbance adjustment factor allocated to the collector to 0.1.

[0063] The control calculation module 50 extracts the collector feedback correction coefficient locked in the previous shift's sample statistical period as 1.05. Multiplying the smoothed dry feed rate, the unit reagent demand, the feedback correction coefficient, and the disturbance compensation term corresponding to the comprehensive disturbance index, the total calculated addition amount is 18936 grams per hour. After performing boundary limit and equipment limit constraint processing, the control calculation module 50 outputs the actual total addition amount as 18.94 kilograms per hour. The control calculation module 50 extracts the baseline allocation ratio of the reagent addition point in the roughing operation as 0.6 and sets the allocation adjustment coefficient to 0.05. Based on the comprehensive disturbance index, the dynamic allocation ratio of the addition point is calculated to be 0.605. Combining the effective concentration of the reagent solution of 10% and the solution density of 1.0 kilograms per liter, the control calculation module 50 converts the addition amount at the sub-point into a reagent solution volume flow rate of 114.58 liters per hour. Finally, the reagent execution module 30 is driven to inject the collector into the roughing operation point according to this volume flow rate.

[0064] This invention selects the flotation industrial production line of a large-scale lead-zinc oxide ore beneficiation plant as the experimental platform. The original fixed-ratio manual reagent addition mode is set as the control group, and the lead-zinc oxide ore flotation reagent stable addition and control system 100 provided by this invention is set as the experimental group. The continuous operation cycle is set to 30 days, and production data is statistically analyzed in 3 shifts per day. The system records the dynamic tracking data of collector addition flow rate and raw ore processing volume in real time and generates a dynamic tracking curve of system comprehensive control. The system synchronously collects the zinc recovery rate and concentrate zinc grade data output by the laboratory terminal of each shift and generates a scatter plot of production index distribution.

[0065] Experimental data show that the experimental group can adjust the reagent injection amount in advance based on multidimensional feedforward parameters when facing drastic fluctuations in raw ore grade and sudden changes in feed rate. The unit consumption of collector in the experimental group is reduced by 8.5% compared with the control group. Under the effect of closed-loop feedback correction mechanism, the zinc recovery rate of the experimental group shows a higher degree of convergence. The average zinc recovery rate of the experimental group increases by 1.22 percentage points and the average zinc grade of concentrate increases by 0.85 percentage points. The standard deviation of the core indicators of the experimental group is lower than that of the control group.

[0066] Table 1: Comparison of Experimental Data on Flotation Production Parameters

[0067] According to Table 1 and Figure 6 and Figure 7 Thus, the control system provided by the present invention eliminates the subjective arbitrariness of manual operation through a control architecture that couples multi-dimensional state feedforward compensation and long-cycle feedback correction, reduces the fluctuation range of core indicators of flotation operation, and improves the metal recovery level of concentrate products while reducing reagent consumption.

[0068] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A system for the stable addition and control of flotation reagents for lead-zinc oxide ore, characterized in that, include: The data acquisition module is used to collect flotation production data, which includes at least the raw ore wet feed rate, raw ore moisture content, and sample test data. The process identification module, connected to the data acquisition module, is used to identify operating condition parameters based on the flotation production data collected by the data acquisition module to determine the unit reagent requirement and output a comprehensive disturbance index. An anomaly management module, connected to the data acquisition module, is used to identify whether there are any abnormal operating condition markers in the current cycle; The control calculation module is connected to the data acquisition module, process identification module and anomaly management module respectively. It is used to obtain the smoothed dry feed rate based on the raw ore wet feed rate and the raw ore moisture content, and to calculate and output the reagent solution volume flow rate command based on the smoothed dry feed rate, the unit reagent requirement, the comprehensive disturbance index and the feedback correction coefficient. And during the period in which the abnormal operating condition flag is effective, the feedback correction coefficient is not updated due to the restriction of the abnormal management module; The reagent preparation module is used to prepare flotation reagents; The reagent execution module is connected to the control calculation module and the reagent preparation module respectively. It is used to receive the reagent solution volume flow rate command output by the control calculation module and inject the flotation reagent prepared by the reagent preparation module into the flotation operation point.

2. The system for stable addition and regulation of flotation reagents for lead-zinc oxide ore according to claim 1, characterized in that, The control calculation module obtains the smoothed dry feed rate based on the collected data, specifically including: Based on the raw ore wet feed rate obtained by the data acquisition module and the raw ore moisture content minus water weight, the instantaneous dry feed rate for the current control cycle is calculated. Calculate the absolute value of the difference between the instantaneous dry feed rate in the current control cycle and the instantaneous dry feed rate in the previous cycle, and dynamically assign a smoothing coefficient based on the comparison result of the absolute value of the difference and the stability threshold. The instantaneous dry feed rate and the smoothing coefficient are substituted into the adaptive first-order inertial filter formula for smoothing to obtain the smoothed dry feed rate.

3. The system for stable addition and control of flotation reagents for lead-zinc oxide ore according to claim 1, characterized in that, The regulation calculation module obtains the unit dosage requirement of various drugs, specifically including: The reference unit quantity of the corresponding flotation reagent is retrieved based on the ore type determined by the process identification module. Extract the zinc grade offset, zinc oxidation rate offset, slurry temperature offset, and the identified gypsum content state coefficient and mixed ore state coefficient for the current period; The baseline unit quantity is multiplied and added with the empirical adjustment coefficients corresponding to the above offsets and state coefficients to obtain the comprehensive state offset. The baseline unit quantity is then added to the comprehensive state offset to obtain the unit drug requirement.

4. The system for stable addition and regulation of flotation reagents for lead-zinc oxide ore according to claim 1, characterized in that, The process identification module outputs the comprehensive disturbance index, specifically including: Extract the changes in smoothed dry feed rate, zinc grade of raw ore, zinc oxidation rate, and slurry temperature compared to the previous cycle in the current control cycle; Divide the magnitude of each change by the maximum fluctuation range of the corresponding parameter within the historical stable operating period to obtain the normalized change. The normalized change of each parameter, the gypsum content state coefficient, and the mixed ore state coefficient are multiplied by their respective set weight values ​​and then weighted and summed to calculate the comprehensive disturbance index of a single evaluation index.

5. The system for stable addition and control of flotation reagents for lead-zinc oxide ore according to claim 1, characterized in that, The total calculated addition amount synthesized by the regulation calculation module specifically includes: Retrieve the feedback correction coefficient updated in the previous sample statistical cycle from the storage unit; Based on the functional properties of various flotation reagents, a corresponding anti-disturbance adjustment factor is matched, and the anti-disturbance adjustment factor is multiplied by the comprehensive disturbance index to obtain the disturbance compensation term; The total calculated addition amount is obtained by performing a multiplicative logic fusion operation on the smoothed dry feed amount, the unit reagent requirement, the feedback correction coefficient, and the disturbance compensation term after superposition constant 1.

6. The system for stable addition and regulation of flotation reagents for lead-zinc oxide ore according to claim 5, characterized in that, The regulation calculation module performs boundary limit constraint processing on the total calculated addition amount, specifically including: Extract the actual total amount added in the previous adjustment cycle, and construct the upper and lower limits of the anti-jump range by combining the maximum upward adjustment ratio and the maximum downward adjustment ratio allowed in a single cycle. Cut off the total calculated amount added beyond the upper and lower limits to the boundary value to obtain the transitional calculated amount added. Read the maximum rated flow and minimum safe flow of the dosing equipment calibrated in the drug execution module, and construct the limit capacity hard constraint boundary; Determine whether the amount of the transition calculation exceeds the limit capability hard constraint boundary, perform absolute value protection processing, and output the actual total amount of addition.

7. The stable addition and control system for lead-zinc oxide ore flotation reagents according to claim 6, characterized in that, The control calculation module converts the volumetric flow rate of the pharmaceutical solution, specifically including: Extract the baseline allocation ratio of each dosing point, and perform adaptive tilt adjustment calculation by combining the comprehensive disturbance index and allocation adjustment coefficient. After normalization, obtain the dynamic allocation ratio of each dosing point. Multiply the actual total amount added by the corresponding dynamic allocation ratio to obtain the amount added at each dosing point; Combining the effective concentration and density of the drug solution monitored by the drug preparation module, the amount added at each point in terms of mass is converted into the volumetric flow rate of the drug solution at the corresponding dosing point.

8. The system for stable addition and regulation of flotation reagents for lead-zinc oxide ore according to claim 1, characterized in that, The regulation calculation module performs drug concentration protection, specifically including: The storage capacity of the reagent preparation tank is calculated by combining the flow integral logic with the duration of the control cycle and the volume of the replenished reagent solution. The effective concentration of the drug solution inside the drug preparation module is monitored in real time and compared with the preset safe lower limit of the effective concentration. When the actual measured effective concentration of the reagent solution is lower than the effective concentration safety lower limit, the protection mechanism is triggered, and the upward adjustment command of the reagent solution volume flow rate at all corresponding dosing points is forcibly blocked.

9. The system for stable addition and regulation of flotation reagents for lead-zinc oxide ore according to claim 1, characterized in that, The control calculation module obtains the deviation in production indicator calculation, specifically including: At the end of the shift sample statistical cycle, the zinc grade of the raw ore, the zinc grade of the concentrate, and the zinc grade of the tailings are extracted from the shift sample test data accessed by the laboratory terminal. The zinc grade of the raw ore, the zinc grade of the concentrate, and the zinc grade of the tailings are substituted into the two-product balance formula to solve the problem, and the concentrate yield and zinc recovery rate of the current shift sample statistical period are calculated. The zinc recovery rate and the zinc grade of the concentrate are respectively subtracted from the preset target recovery rate and the preset target grade to extract the zinc recovery rate deviation and the zinc grade deviation with polar signs.

10. The system for stable addition and regulation of flotation reagents for lead-zinc oxide ore according to claim 1, characterized in that, The anomaly management module and the regulation calculation module work together to update the feedback correction coefficient, specifically including: The six abnormal states—feeding anomaly, ore anomaly, grinding anomaly, reagent addition anomaly, dewatering anomaly, and sample mutation—are quantified as Boolean variables, and a logical OR operation is performed to determine the abnormal condition flag. When the abnormal operating condition flag value is 1, the closed-loop iterative formula is shielded and the feedback correction coefficient of the previous cycle is forcibly locked as the output of the current cycle. When the abnormal operating condition flag value is 0, the zinc recovery rate deviation and the concentrate zinc grade deviation are multiplied by the corresponding integral gain coefficients, and then added to the feedback correction coefficient of the previous cycle to perform a limited integral operation to obtain the feedback correction coefficient of the current cycle.

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