Settling washing device and method for acid leaching of aluminum-silicon oxide

Abstract

The invention relates to the technical field of settling and washing, in particular to a settling and washing device and method for acid leaching of aluminum-silicon oxides, and a control device comprises a working condition data acquisition module, a settling parameter optimization module, a graded settling control module, a washing process regulation and control module and a system collaborative execution module. All the modules work cooperatively, slurry flow, solid concentration and conductivity data are collected in real time, sedimentation parameters are optimized through a sedimentation kinetic model, stirring strength and material flow direction are controlled, countercurrent washing logic is implemented, and underflow concentration is stabilized through material balance closed-loop control. Three stages or more than three stages of settling washing tanks which are connected in series are adopted, and a mixer is arranged at the top of each stage of tank so as to realize premixing of washing liquid and materials. Through cooperative operation of the devices, the separation efficiency of soluble carnallite and fine particles is effectively improved, so that the purity of aluminum-silicon oxide serving as an electrolysis raw material is improved, subsequent aluminum-silicon alloy production is facilitated, and scabbing of a roasting furnace is inhibited.

Description

Technical Field

[0001] This invention relates to the field of sedimentation and washing technology, and in particular to a sedimentation and washing apparatus and method for aluminum silicon oxide prepared by acid leaching process. Background Technology

[0002] Aluminum-silicon oxide, a crucial raw material for producing aluminum-silicon alloys, has its performance significantly affected by impurities. After acid leaching, the aluminum-silicon oxide requires thorough washing to remove dissolved salts and meet relevant quality standards. The slurry formed by the mixture of acid-leached aluminum-silicon oxide and wash water requires efficient liquid-solid separation and purification; sedimentation washing is a key unit operation for achieving this goal. The basic principle of sedimentation washing is to utilize the density difference between solid particles and the solution. Under the action of gravity or centrifugal force, the solid particles settle to form a concentrated underflow. Then, through multi-stage countercurrent washing, clean wash water fully contacts and replaces the impurity-laden mother liquor entrained in the underflow. Each stage of washing includes mixing, sedimentation, and overflow separation steps, aiming to gradually reduce the content of soluble impurities in the solid product while improving the recovery rate of useful components. Adding flocculants can promote the aggregation of fine particles, accelerate the sedimentation process, and improve the clarity of the supernatant. Ultimately, the thoroughly washed solid residue is discharged from the system, while the recovered solution is returned to the process flow or treated according to its composition. The efficiency of the entire process directly affects resource utilization and the stability of subsequent processes.

[0003] Existing sedimentation washing processes for aluminum-silicon oxides after acid leaching suffer from the following technical challenges: Firstly, the acid-leached aluminum-silicon oxide slurry contains high concentrations of soluble impurities such as sodium and calcium salts, and a large number of fine particles. Existing sedimentation washing processes may suffer from incomplete impurity separation due to insufficient washing stages and inadequate solid-liquid mixing. Secondly, inadequate sedimentation separation unit design, such as excessively short sedimentation time or improper stirring intensity, can lead to resuspension of solid particles and insufficient impurity sedimentation. Thirdly, unoptimized washing solution formulations or methods, such as a lack of chelating agents or countercurrent washing, reduce impurity removal efficiency. For instance, during the pretreatment of this raw material, incompletely separated sodium and calcium salts may enter the calcination process with the material, forming low-melting-point compounds at high temperatures. These compounds deposit on the furnace wall, causing scaling, which not only affects the purity of the aluminum-silicon oxide raw material and consequently the quality of subsequent alloys but also disrupts production continuity. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a sedimentation and washing device and method for acid leaching of aluminum silicon oxide. This invention solves the technical problem that incomplete separation of soluble impurities (such as sodium and calcium salts) and fine particles in the acid leaching solution results in low purity, high impurity content, and severe scaling in the calcining furnace of the final alumina product.

[0005] To solve the above-mentioned technical problems, the specific contents of the present invention are as follows: In a first aspect, the present invention provides a sedimentation and washing apparatus for acid leaching of aluminum silicon oxide, comprising a physical device and a control device communicatively connected to the physical device; The physical equipment includes three or more settling and washing tanks arranged in series, an overflow weir system set at the top of each tank, a variable frequency speed-regulating agitator installed in each tank, a mixer set at the top of each settling and washing tank for introducing washing liquid and flocculant and pre-mixing with the underflow material in the tank, a feed pump connecting the acid leaching slurry inlet to the first settling and washing tank, an underflow pump connecting the bottom discharge port of each tank, an overflow pump connecting the top discharge port of each tank, a washing liquid supply unit connected to the final settling and washing tank via a metering pump, and a chelating agent addition unit equipped with an EDTA storage tank and connected to the washing liquid main pipeline via an injection pump. The control device includes: The working condition data acquisition module is used to collect in real time the slurry flow rate at the outlet of the feed pump, the solid concentration in the underflow pipeline of the secondary settling tank, and the conductivity at the overflow port of the washing tank. The settling parameter optimization module is used to receive the slurry flow rate and solid concentration data collected by the working condition data acquisition module, and calculate the optimal settling time through the settling kinetic model; when the solid concentration is lower than the set threshold, the settling parameter optimization module generates a primary settling tank level adjustment command; when the conductivity fluctuates abnormally, the settling parameter optimization module generates a secondary settling tank agitator speed correction command. The staged settling control module receives the liquid level adjustment command and the rotation speed correction command from the settling parameter optimization module. The staged settling control module converts the liquid level adjustment command into a frequency adjustment signal for the underflow pump in the primary settling tank to control the residence time of the slurry in the primary settling tank. Underflow solids content is a key control point; higher underflow solids content results in less salt-containing liquid phase flowing into the subsequent settling and washing tank, leading to higher washing efficiency. The variable frequency speed-regulating agitator prevents sedimentation from clogging the underflow pump when solids content is high; the chelating agent addition unit has a similar effect during washing. The principle is to maximize the underflow solids content as much as possible while simultaneously adjusting the opening of the feed valve in the secondary settling tank. Based on the rotation speed correction command, the staged settling control module controls the variable frequency speed-regulating agitator to maintain low-speed stirring during the settling stage and appropriately increases the agitator speed based on the solids content when the underflow pump is detected to be running. The washing process control module is used to receive the conductivity data from the working condition data acquisition module; when the conductivity is continuously high, the washing process control module increases the dosage of the chelating agent addition unit according to a preset ratio, and instructs the washing liquid supply unit to increase the flow rate; the washing process control module implements countercurrent washing logic by controlling the start and stop sequence of each stage of the underflow pump, so that the flow direction of the washing liquid is opposite to the flow direction of the solid material. The system collaborative execution module receives equipment status signals from the staged sedimentation control module and the washing process control module. When the sedimentation parameter optimization module generates an instruction requiring an extension of the sedimentation time, the system collaborative execution module synchronously delays the start-up time of the washing liquid supply unit. When the washing process control module adds chelating agent, the system collaborative execution module adjusts the stirring intensity of the secondary sedimentation washing tank based on the dominant role of the mixer in the mixing process. The mixer is located at the top of the sedimentation washing tank to introduce the washing liquid and flocculant and premix them with the underflow material, while the variable frequency speed-regulating stirrer is installed at the bottom of the sedimentation washing tank to help prevent sedimentation. The system collaborative execution module stabilizes the underflow concentration within the target range through material balance closed-loop control.

[0006] Furthermore, in the sedimentation and washing device for acid leaching of aluminum silicon oxides according to the present invention, the operating condition data acquisition module includes: The electromagnetic flowmeter monitors the slurry flow rate at the outlet of the feed pump and outputs a first signal; A microwave concentration meter is installed in the underflow pipeline of the secondary settling tank to collect microwave signals and convert them into solid concentration data by analyzing the attenuation. A four-electrode conductivity electrode and a temperature sensor are disposed at the overflow port of the washing tank. The conductivity electrode measures the conductivity value, the temperature sensor collects temperature data and compensates for the conductivity value, and outputs the compensated conductivity data. The first signal, the solid concentration data, and the compensated conductivity data are transmitted to the central processing unit via industrial Ethernet and filtered using a moving average algorithm to obtain stable operating condition data for subsequent module processing.

[0007] Furthermore, in the sedimentation washing device for acid leaching of aluminum silicon oxide described in this invention, the sedimentation parameter optimization module is configured as follows: Receive stable operating condition data transmitted by the operating condition data acquisition module, wherein the stable operating condition data includes slurry flow rate, solid concentration and conductivity; The settling dynamics model is based on Kynch theory. The received real-time slurry flow rate and historical concentration data are substituted into the model, and the optimal settling time is obtained through iterative calculation. When the solid concentration data continues to be lower than the set threshold, a PID algorithm aimed at increasing the underflow concentration is triggered to dynamically calculate and generate a primary settling tank level adjustment command. When the conductivity data undergoes a step change, a spectrum analysis program is initiated to identify abnormal frequency components. If it is determined to be caused by an abnormal solid suspension, a preset expert library is called to match the optimal speed correction value, and a speed correction command for the secondary settling tank agitator is generated.

[0008] Furthermore, the sedimentation washing device for acid leaching of aluminum silicon oxide described in this invention receives liquid level adjustment commands and rotation speed correction commands from the sedimentation parameter optimization module. The graded settling control module compares the liquid level adjustment command with the preset liquid level value to obtain the liquid level deviation, and uses a fuzzy control algorithm to convert the liquid level deviation into a frequency adjustment signal for the bottom flow pump of the first-stage settling tank. Meanwhile, the graded settling control module uses the frequency adjustment signal to back-calculate the opening correction coefficient of the feed valve of the secondary settling tank based on the material balance equation, and adjusts the opening of the feed valve synchronously. For stirring control, the staged sedimentation control module sets the base speed of the variable frequency speed-regulating agitator according to the speed correction command; and based on the operating status signal of the underflow pump and solid content data, it appropriately increases the speed of the variable frequency speed-regulating agitator when the underflow pump is detected to be running, and switches to low speed mode after a delay after the underflow pump stops.

[0009] Furthermore, in the sedimentation washing device for acid leaching of aluminum silicon oxide described in this invention, the washing process control module is configured as follows: Continuously receive conductivity data from the operating condition data acquisition module; The washing process control module compares the received conductivity data with a preset threshold. When the conductivity reading exceeds the threshold, it queries the pre-stored conductivity-impurity concentration mapping table and uses a gradient boosting algorithm to predict the impurity removal efficiency. Based on the prediction result, it dynamically calculates the chelating agent increment ratio, and then instructs the chelating agent addition unit to increase the dosage proportionally, and instructs the washing liquid supply unit to increase the flow rate. For countercurrent washing, the washing process control module uses a built-in timing controller to program and set the start and stop sequence of each stage of the underflow pump so that the washing liquid flows in the opposite direction to the solid material. Meanwhile, the washing process control module controls the washing liquid supply unit to supply the liquid intermittently and monitors the liquid level in the washing tank. When the liquid level reaches its peak, it triggers a stop for a single wash.

[0010] Furthermore, in the sedimentation washing device for acid leaching of aluminum silicon oxides according to the present invention, the system collaborative execution module is configured as follows: Receive equipment status signals sent by the graded sedimentation control module and the washing process control module; When the instruction generated by the settling parameter optimization module requires an extension of the settling time, the system collaborative execution module retrieves the current status of the washing liquid supply unit and generates a delayed start instruction to synchronize the start time of the washing liquid supply unit with the settling completion signal. When the washing process control module increases the dosage of chelating agent, the system collaborative execution module calls the material diffusion model, calculates the required stirring intensity based on the dosage, and sends a speed increase command to the variable frequency speed-regulating stirrer of the secondary settling tank. The system's collaborative execution module also employs a model predictive control algorithm, using the underflow concentration as the target variable, to calculate and output optimized instructions for the material distribution ratio between each level of tank in real time.

[0011] Furthermore, in the sedimentation washing device for acid leaching of aluminum silicon oxides described in this invention, the sedimentation parameter optimization module receives stable operating condition data processed by the operating condition data acquisition module. The sedimentation parameter optimization module uses the stable operating condition data to calculate the optimal sedimentation time through the sedimentation dynamics model, and generates a liquid level adjustment command to send to the staged sedimentation control module. The graded sedimentation control module executes the liquid level adjustment command to adjust the pump frequency and valve position, and the adjusted operating conditions serve as the feeding conditions for the washing process control module. The washing process control module performs washing under the feeding conditions, and the conductivity data of the overflow liquid is collected by the operating condition data acquisition module and fed back to the sedimentation parameter optimization module. The sedimentation parameter optimization module uses the conductivity data to correct the rotation speed parameter, forming a closed-loop optimization.

[0012] Furthermore, in the sedimentation washing device for acid leaching of aluminum silicon oxide described in this invention, the staged sedimentation control module uses a fuzzy control algorithm to process liquid level adjustment commands and employs a dual-modal strategy to control the variable frequency speed-regulating stirrer. The graded sedimentation control module executes the liquid level adjustment command and outputs adjustment signals for pump frequency and valve position. The adjustment signal acts on the underflow state generated by the physical equipment device and serves as the input condition for the washing process control module. The washing process control module receives a signal characterizing the undercurrent state and processes the signal using a gradient boosting algorithm to calculate the chelating agent increment command. The system collaborative execution module receives the chelating agent increment command and generates a corresponding stirring intensity increase command, which is then sent to the staged sedimentation control module. The staged sedimentation control module adjusts the operating parameters of the variable frequency speed-regulating stirrer according to the stirring intensity increase command.

[0013] Furthermore, in the sedimentation washing device for acid leaching of aluminum silicon oxide described in this invention, the timing controller in the washing process control module controls the sequential operation of each stage of the underflow pump by outputting a countercurrent washing start / stop signal. The model predictive control algorithm in the system collaborative execution module receives the countercurrent washing start / stop signal generated by the timing controller and uses the signal as the input to the periodic material flow fluctuation model. The model predictive control algorithm, based on the fluctuation model, outputs material allocation optimization instructions to the graded settling control module; The graded settling control module executes the material distribution optimization command, and the resulting changes in operating conditions are fed back to the washing process control module. The intermittent supply strategy in the washing process control module generates an intermittent supply signal by monitoring the liquid level in the washing tank; the system collaborative execution module receives the intermittent supply signal and generates a pre-adjustment instruction for the preceding sedimentation process accordingly.

[0014] Secondly, the present invention provides a sedimentation washing method for acid-leached aluminum silicon oxides, applied to the aforementioned sedimentation washing apparatus for acid-leached aluminum silicon oxides, comprising: Step 1: Real-time data collection of slurry flow rate at the feed pump outlet, solid concentration in the underflow pipeline of the secondary settling tank, and conductivity at the overflow outlet of the washing tank. Step 2: Receive the slurry flow rate and solid concentration data, calculate the optimal settling time using a settling kinetics model; when the solid concentration is lower than a set threshold, generate a primary settling tank level adjustment command; when the conductivity fluctuates abnormally, generate a secondary settling tank agitator speed correction command. Step 3: Receive the liquid level adjustment command and the speed correction command; convert the liquid level adjustment command into a frequency adjustment signal for the underflow pump of the primary settling tank to control the residence time of the slurry in the primary settling tank, and simultaneously adjust the opening of the feed valve of the secondary settling tank; according to the speed correction command, control the variable frequency speed-regulating agitator to maintain low-speed stirring during the settling stage, and appropriately increase the speed of the variable frequency speed-regulating agitator based on the solid content when the underflow pump is detected to be running. Step 4: Receive the conductivity data; when the conductivity remains high, increase the dosage of the chelating agent addition unit according to a preset ratio, and instruct the washing liquid supply unit to increase the flow rate; by controlling the start-stop sequence of each underflow pump, implement the countercurrent washing logic so that the washing liquid flows in the opposite direction to the solid material flow. Step 5: Receive the equipment status signals generated in Step 3 and Step 4; when the instruction generated in Step 2 requires extending the settling time, synchronously delay the start time of the washing liquid supply unit; when the chelating agent is added in Step 4, automatically increase the stirring intensity of the secondary settling tank; through material balance closed-loop control, stabilize the underflow concentration within the target range.

[0015] Beneficial effects of this invention; This invention addresses the challenge of incomplete separation of soluble salts and fine particles in acid-leached aluminosilicate oxide slurries by integrating physical equipment and intelligent control devices. It constructs a data-driven sedimentation and washing system. A data acquisition module collects key parameters such as slurry flow rate, solids concentration, and conductivity in real time, providing accurate operational information. A sedimentation parameter optimization module calculates the optimal sedimentation time based on a sedimentation kinetic model and generates level adjustment and speed correction commands through threshold judgments to optimize the sedimentation process and prevent particle resuspension. A staged sedimentation control module translates these commands into precise adjustments to the underflow pump frequency and feed valve opening, achieving optimal slurry residence time. The system employs a multi-module collaborative intelligent control mechanism to effectively improve solid-liquid separation, significantly reduce the residue of soluble salts and fine particles in the product, thereby increasing the purity of aluminum-silicon oxide as an electrolytic raw material. This lays the foundation for producing high-quality aluminum-silicon alloys and inhibits scaling in the calcination furnace. The washing process control module dynamically adjusts the dosage of chelating agent and the flow rate of washing liquid based on conductivity data, and enhances impurity removal efficiency through countercurrent washing logic and intermittent supply. The system's collaborative execution module integrates the status signals of each module, enabling the sedimentation and washing processes to be linked through closed-loop material balance control and cross-process collaboration. By using a series arrangement of three or more sedimentation and washing tanks, and installing a mixer at the top of each tank, the system ensures the number of washing stages and mixing efficiency, allowing each tank to effectively perform its washing function. This multi-module collaborative intelligent control mechanism effectively improves solid-liquid separation, significantly reduces the residue of soluble impurities and fine particles in the product, thereby increasing the purity of aluminum-silicon oxide as an electrolytic raw material, laying the foundation for producing high-quality aluminum-silicon alloys, and inhibiting scaling in the calcination furnace. Attached Figure Description

[0016] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on the drawings without creative effort.

[0017] Figure 1 The flowchart illustrates a sedimentation and washing method for acid leaching of aluminum silicon oxides provided in an embodiment of the present invention. Detailed Implementation

[0018] To make the technical solution of the present invention clearer, the present invention will be clearly and completely described below with reference to specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. 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. The present invention provided by various embodiments will be described in detail below with reference to the accompanying drawings. To better understand the purpose of the present invention, the present invention will be described in further detail below.

[0019] In a first aspect, the present invention provides a sedimentation and washing apparatus for acid leaching of aluminum silicon oxide, comprising a physical device and a control device communicatively connected to the physical device; The physical equipment includes three or more settling and washing tanks arranged in series. Preferably, three-stage settling and washing tanks are used in series, with each stage independently completing the settling and washing functions, achieving at least three washing cycles. A mixer is added to the top of each settling and washing tank. The washing liquid and chelating agent are introduced through the mixer and fully mixed with the underflow material pumped by the bottom flow pump of the previous stage before entering the settling zone. The equipment includes an overflow weir system at the top of each tank, a variable frequency speed-regulating agitator installed in each tank, a mixer at the top of each settling and washing tank, a feed pump connecting the acid leaching slurry inlet to the first-stage settling and washing tank, a bottom flow pump connecting the bottom discharge outlet of each stage tank, a washing liquid supply unit connected to the washing tank via a metering pump, and a chelating agent addition unit equipped with an EDTA storage tank and connected to the washing liquid main pipeline via an injection pump. The physical equipment includes three or more settling and washing tanks arranged in series. Preferably, three-stage settling and washing tanks are used in series, with each stage independently completing the settling and washing functions, achieving at least three washing cycles. A mixer is added to the top of each settling and washing tank, through which the washing liquid and chelating agent are introduced and fully mixed with the underflow material pumped in by the underflow pump of the previous stage before entering the settling zone. An overflow weir system is set at the top of each tank, and a variable frequency speed-regulating agitator is installed in each tank. The control device includes: The working condition data acquisition module is used to collect in real time the slurry flow rate at the outlet of the feed pump, the solid concentration in the underflow pipeline of the secondary settling tank, and the conductivity at the overflow port of the washing tank. The settling parameter optimization module is used to receive the slurry flow rate and solid concentration data collected by the working condition data acquisition module, and calculate the optimal settling time through the settling kinetic model; when the solid concentration is lower than the set threshold, the settling parameter optimization module generates a primary settling tank level adjustment command; when the conductivity fluctuates abnormally, the settling parameter optimization module generates a secondary settling tank agitator speed correction command. The staged sedimentation control module is used to receive the liquid level adjustment command and the rotation speed correction command from the sedimentation parameter optimization module; the staged sedimentation control module converts the liquid level adjustment command into a frequency adjustment signal for the underflow pump of the primary sedimentation tank to control the residence time of the slurry in the primary sedimentation tank, and simultaneously adjusts the opening of the feed valve of the secondary sedimentation tank; according to the rotation speed correction command, the staged sedimentation control module controls the variable frequency speed-regulating agitator to maintain low-speed stirring during the sedimentation stage, and appropriately increases the rotation speed of the variable frequency speed-regulating agitator based on the solid content when the underflow pump is detected to be running; The washing process control module is used to receive the conductivity data from the working condition data acquisition module; when the conductivity is continuously high, the washing process control module increases the dosage of the chelating agent addition unit according to a preset ratio, and instructs the washing liquid supply unit to increase the flow rate; the washing process control module implements countercurrent washing logic by controlling the start and stop sequence of each stage of the underflow pump, so that the flow direction of the washing liquid is opposite to the flow direction of the solid material. The system collaborative execution module is used to receive equipment status signals from the staged sedimentation control module and the washing process control module; when the instruction generated by the sedimentation parameter optimization module requires extending the sedimentation time, the system collaborative execution module synchronously delays the start time of the washing liquid supply unit; when the washing process control module increases the addition of chelating agent, the system collaborative execution module automatically increases the stirring intensity of the secondary sedimentation tank; the system collaborative execution module stabilizes the underflow concentration within the target range through material balance closed-loop control.

[0020] The control device's operating condition data acquisition module achieves synchronous measurement of multiple parameters through a distributed sensor network. An electromagnetic flowmeter is installed at the feed pump outlet pipe, directly detecting the instantaneous flow rate of the slurry and outputting a standard current signal. A microwave concentration meter employs a non-contact measurement principle, emitting microwaves into the underflow pipe of the secondary settling tank and receiving the attenuated signal. A built-in calibration curve converts the signal attenuation into a solid mass percentage concentration. A four-electrode conductivity electrode and a platinum resistance temperature sensor are integrated and installed at the overflow port of the washing tank. The conductivity electrode obtains the raw conductivity value by measuring the solution's conductivity, while the temperature sensor monitors the solution temperature in real time and performs temperature compensation correction on the conductivity value. All sensor data is transmitted to a programmable logic controller via industrial Ethernet. A moving average algorithm is used to filter the data, eliminating instantaneous fluctuation interference and forming a stable and reliable operating condition dataset.

[0021] After receiving preprocessed stable operating data, the settling parameter optimization module initiates a settling dynamics model based on Kynch theory for calculation. The model compares the real-time slurry flow rate with a historical concentration database and solves for the optimal settling time parameter corresponding to the critical settling velocity through iterative calculations. When the solid concentration data is continuously below a set threshold, a proportional-integral-derivative control algorithm is triggered to dynamically calculate the liquid level setpoint of the primary settling tank and generate a liquid level adjustment command, with the goal of increasing the underflow concentration. When the conductivity data shows a step change, the module initiates a fast Fourier transform for spectrum analysis, identifies abnormal frequency characteristics, and then calls the expert knowledge base to match the corresponding agitator speed correction parameters, generating a speed correction command. This dual judgment mechanism enables the settling process parameters to adapt to fluctuations in operating conditions.

[0022] The staged settling control module compares the received liquid level adjustment command with the preset liquid level value to obtain the deviation. A fuzzy control algorithm is then used to convert the deviation into a frequency adjustment signal for the underflow pump in the primary settling tank. Simultaneously, based on the material conservation equation, the opening correction coefficient of the feed valve in the secondary settling tank is derived from the underflow pump frequency signal, achieving interstage flow matching. For agitation control, the module sets the base speed value of the variable frequency speed-regulating agitator according to the speed correction command. By monitoring the underflow pump's operating status signal and solid content data, when the underflow pump is running, the module appropriately increases the speed of the variable frequency speed-regulating agitator based on the solid content to promote material suspension. After the pump stops, a delay is applied before switching to a low-speed agitation mode to prevent solid deposition.

[0023] The washing process control module continuously monitors the conductivity data at the overflow outlet of the washing tank. When the value exceeds a set threshold, it automatically queries the mapping table between conductivity and impurity concentration, uses a gradient boosting decision tree algorithm to predict the impurity removal efficiency, dynamically calculates the chelating agent addition ratio based on the prediction results, and instructs the injection pump to adjust the dosage. The countercurrent washing logic is implemented through a programmable timing controller. By programming the start and stop sequence of each stage of the underflow pump, the flow direction of the washing liquid is made to flow in the opposite direction to the solid conveying direction. The washing liquid supply adopts an intermittent operation mode. By monitoring the changes in the washing tank liquid level, the supply is automatically cut off when the liquid level reaches the peak, forming a pulse washing effect.

[0024] The system's collaborative execution module achieves cross-process collaborative control by integrating the status signals of each subsystem. When the settling parameter optimization module issues a command to extend the settling time, the module automatically retrieves the status information of the washing liquid supply unit and delays its start time until the settling process is completed. When the washing process control module increases the dosage of chelating agent, the module adjusts the stirring intensity based on the dominant role of the mixer in the mixing process. The mixer is located at the top of the settling washing tank to introduce the washing liquid and flocculant and premix it with the underflow material, while the variable frequency speed-regulating stirrer is installed at the bottom of the tank to help prevent sedimentation. The module uses a model predictive control algorithm, with the underflow concentration as the controlled variable, to optimize the material balance between each level of equipment in real time. Through multi-variable coordinated control, the system operates stably within the optimal operating range.

[0025] Each module forms a complete control loop through data and command flows. The operating data acquisition module provides real-time operational status awareness for the system, the sedimentation parameter optimization module converts process parameters into equipment operation commands, the staged sedimentation control module and the washing process regulation module respectively execute precise control of the sedimentation and washing processes, and the system coordination execution module coordinates the timing of actions in preceding and following processes with equipment operating parameters, making the entire system an organic whole. This architecture results in a synergistic gain between sedimentation separation effect and washing purification efficiency, ultimately achieving a significant improvement in impurity removal.

[0026] Specifically, the sedimentation and washing device for acid leaching of aluminum silicon oxides according to the present invention includes a working condition data acquisition module comprising: The electromagnetic flowmeter monitors the slurry flow rate at the outlet of the feed pump and outputs a first signal; A microwave concentration meter is installed in the underflow pipeline of the secondary settling tank to collect microwave signals and convert them into solid concentration data by analyzing the attenuation. A four-electrode conductivity electrode and a temperature sensor are disposed at the overflow port of the washing tank. The conductivity electrode measures the conductivity value, the temperature sensor collects temperature data and compensates for the conductivity value, and outputs the compensated conductivity data. The first signal, the solid concentration data, and the compensated conductivity data are transmitted to the central processing unit via industrial Ethernet and filtered using a moving average algorithm to obtain stable operating condition data for subsequent module processing.

[0027] In the working condition data acquisition module of this invention, an electromagnetic flowmeter is installed in the outlet pipe of the feed pump. It detects the instantaneous flow rate by measuring the induced electromotive force generated by the slurry flow in the pipe and outputs a 4-20mA standard current signal. A microwave concentration meter emits a microwave signal of a specific frequency into the underflow pipe of the secondary settling tank. The receiving end detects the attenuation of the microwave after passing through the slurry and converts it into solid mass percentage concentration data through a pre-calibrated attenuation degree versus solid concentration curve. A four-electrode conductivity electrode uses an AC excitation method to measure the conductivity value of the overflow liquid from the washing tank. Simultaneously, an integrated platinum resistance temperature sensor collects solution temperature data in real time and performs temperature compensation correction on the conductivity measurement value to eliminate the influence of ambient temperature. The first signal, solid concentration data, and compensated conductivity data collected by all sensors are transmitted to the programmable logic controller via an industrial Ethernet network. A moving average digital filtering algorithm is used to process the continuously sampled data to eliminate random fluctuation interference and generate a stable and reliable working condition dataset for use by subsequent modules.

[0028] Specifically, in the sedimentation washing apparatus for acid leaching of aluminum silicon oxides according to the present invention, the sedimentation parameter optimization module is configured as follows: Receive stable operating condition data transmitted by the operating condition data acquisition module, wherein the stable operating condition data includes slurry flow rate, solid concentration and conductivity; The settling dynamics model is based on Kynch theory. The received real-time slurry flow rate and historical concentration data are substituted into the model, and the optimal settling time is obtained through iterative calculation. When the solid concentration data continues to be lower than the set threshold, a PID algorithm aimed at increasing the underflow concentration is triggered to dynamically calculate and generate a primary settling tank level adjustment command. When the conductivity data undergoes a step change, a spectrum analysis program is initiated to identify abnormal frequency components. If it is determined to be caused by an abnormal solid suspension, a preset expert library is called to match the optimal speed correction value, and a speed correction command for the secondary settling tank agitator is generated.

[0029] After receiving stable operating condition data transmitted by the operating condition data acquisition module, the sedimentation parameter optimization module of this invention starts a sedimentation dynamics model based on Kynch theory for calculation. This model compares real-time slurry flow data with a historical concentration database, and iteratively calculates the relationship between the settling velocity of solid particles and the change in the clarification interface height to obtain the optimal settling time parameters. When the solid concentration data is below a set threshold for multiple consecutive sampling periods, a proportional-integral-derivative (PID) control algorithm is triggered to dynamically calculate the liquid level setpoint of the primary sedimentation tank and generate a liquid level adjustment command, with the goal of increasing the underflow concentration. When the conductivity data undergoes a step change, the module starts a fast Fourier transform algorithm for spectrum analysis to identify abnormal frequency characteristics. If the spectrum characteristics match an abnormal solid suspension pattern, a preset expert knowledge base is called to match the corresponding agitator speed correction parameters, generating an agitator speed correction command for the secondary sedimentation tank.

[0030] Specifically, the sedimentation washing device for acid leaching of aluminum silicon oxide according to the present invention receives liquid level adjustment instructions and rotation speed correction instructions from the sedimentation parameter optimization module; The graded settling control module compares the liquid level adjustment command with the preset liquid level value to obtain the liquid level deviation, and uses a fuzzy control algorithm to convert the liquid level deviation into a frequency adjustment signal for the bottom flow pump of the first-stage settling tank. Meanwhile, the graded settling control module uses the frequency adjustment signal to back-calculate the opening correction coefficient of the feed valve of the secondary settling tank based on the material balance equation, and adjusts the opening of the feed valve synchronously. For stirring control, the staged sedimentation control module sets the base speed of the variable frequency speed-regulating agitator according to the speed correction command; and based on the operating status signal of the underflow pump and solid content data, it appropriately increases the speed of the variable frequency speed-regulating agitator when the underflow pump is detected to be running, and switches to low speed mode after a delay after the underflow pump stops.

[0031] The staged settling control module of this invention receives the liquid level adjustment command and speed correction command sent by the settling parameter optimization module. It compares the liquid level adjustment command with the preset liquid level value to obtain the deviation. A fuzzy control algorithm is then used to convert the liquid level deviation into a frequency adjustment signal for the underflow pump in the primary settling tank. Simultaneously, based on the material balance equation, the frequency adjustment signal of the underflow pump is used to deduce the opening correction coefficient of the feed valve in the secondary settling tank, and the feed valve opening is adjusted synchronously to achieve interstage flow balance. For stirring control, the module sets the base speed value of the variable frequency speed-regulating stirrer according to the speed correction command, and automatically switches the stirring mode by monitoring the underflow pump's operating status signal: when the underflow pump is running, it switches to a high-speed stirring mode to promote the suspension of solid materials; after the underflow pump stops, it switches to a low-speed stirring mode after a delay to prevent solid deposition in the tank.

[0032] Specifically, in the sedimentation washing apparatus for acid leaching of aluminum silicon oxides according to the present invention, the washing process control module is configured as follows: Continuously receive conductivity data from the operating condition data acquisition module; The washing process control module compares the received conductivity data with a preset threshold. When the conductivity reading exceeds the threshold, it queries the pre-stored conductivity-impurity concentration mapping table and uses a gradient boosting algorithm to predict the impurity removal efficiency. Based on the prediction result, it dynamically calculates the chelating agent increment ratio, and then instructs the chelating agent addition unit to increase the dosage proportionally, and instructs the washing liquid supply unit to increase the flow rate. For countercurrent washing, the washing process control module uses a built-in timing controller to program and set the start and stop sequence of each stage of the underflow pump so that the washing liquid flows in the opposite direction to the solid material. Meanwhile, the washing process control module controls the washing liquid supply unit to supply the liquid intermittently and monitors the liquid level in the washing tank. When the liquid level reaches its peak, it triggers a stop for a single wash.

[0033] The washing process control module of this invention continuously receives conductivity data from the operating condition data acquisition module, compares the conductivity reading with a preset threshold, and automatically queries a pre-stored conductivity-impurity concentration mapping table when the value exceeds the threshold. It then uses a gradient boosting decision tree algorithm to predict impurity removal efficiency, dynamically calculates the chelating agent increment ratio based on the prediction result, and instructs the chelating agent addition unit to adjust the dosage proportionally. Simultaneously, it instructs the washing liquid supply unit to increase the flow rate. The counter-current washing logic is implemented through a programmable timing controller, which programs the start-stop sequence of each stage of the underflow pump, ensuring that the washing liquid flow direction is opposite to the solid material conveying direction. The washing liquid supply operates intermittently, automatically cutting off the supply when the washing tank level reaches its peak, creating a pulsed washing effect to enhance mass transfer efficiency.

[0034] Specifically, in the sedimentation and washing apparatus for acid leaching of aluminum silicon oxides according to the present invention, the system collaborative execution module is configured as follows: Receive equipment status signals sent by the graded sedimentation control module and the washing process control module; When the instruction generated by the settling parameter optimization module requires an extension of the settling time, the system collaborative execution module retrieves the current status of the washing liquid supply unit and generates a delayed start instruction to synchronize the start time of the washing liquid supply unit with the settling completion signal. When the washing process control module increases the dosage of chelating agent, the system collaborative execution module calls the material diffusion model, calculates the required stirring intensity based on the dosage, and sends a speed increase command to the variable frequency speed-regulating stirrer of the secondary settling tank. The system's collaborative execution module also employs a model predictive control algorithm, using the underflow concentration as the target variable, to calculate and output optimized instructions for the material distribution ratio between each level of tank in real time.

[0035] The system collaborative execution module of this invention receives equipment status signals from the staged sedimentation control module and the washing process control module. When the sedimentation parameter optimization module issues a command to extend the sedimentation time, the module automatically retrieves the status information of the washing liquid supply unit and generates a delayed start command, ensuring that the start time of the washing liquid supply unit is synchronized with the sedimentation completion signal. When the washing process control module increases the dosage of chelating agent, the system collaborative execution module calls the material diffusion kinetics model, calculates the required stirring intensity based on the dosage, and sends a speed increase command to the variable frequency speed-regulating stirrer in the secondary sedimentation tank. The module employs a model predictive control algorithm, using the underflow concentration as the controlled variable, to optimize the material distribution ratio between each stage of the tank in real time, maintaining stable system operation through multivariate coordinated control.

[0036] Specifically, in the sedimentation washing device for acid leaching of aluminum silicon oxides according to the present invention, the sedimentation parameter optimization module receives stable operating condition data processed by the operating condition data acquisition module. The sedimentation parameter optimization module uses the stable operating condition data to calculate the optimal sedimentation time through the sedimentation dynamics model, and generates a liquid level adjustment command to send to the staged sedimentation control module. The graded sedimentation control module executes the liquid level adjustment command to adjust the pump frequency and valve position, and the adjusted operating conditions serve as the feeding conditions for the washing process control module. The washing process control module performs washing under the feeding conditions, and the conductivity data of the overflow liquid is collected by the operating condition data acquisition module and fed back to the sedimentation parameter optimization module. The sedimentation parameter optimization module uses the conductivity data to correct the rotation speed parameter, forming a closed-loop optimization.

[0037] The sedimentation parameter optimization module of this invention utilizes stable operating condition data processed by the operating condition data acquisition module to calculate the optimal sedimentation time through a sedimentation kinetic model and generates a liquid level adjustment command, which is sent to the staged sedimentation control module. The staged sedimentation control module executes the liquid level adjustment command, adjusting the pump frequency and valve position. The adjusted operating condition parameters serve as the feeding conditions for the washing process control module. Under these feeding conditions, the washing process control module performs the washing operation. The resulting overflow liquid conductivity data is collected by the operating condition data acquisition module and fed back to the sedimentation parameter optimization module. The sedimentation parameter optimization module uses this data to correct the agitator speed parameters, forming a data-driven closed-loop optimization mechanism.

[0038] Specifically, in the sedimentation and washing device for acid leaching of aluminum silicon oxides described in this invention, the staged sedimentation control module uses a fuzzy control algorithm to process liquid level adjustment commands and employs a dual-modal strategy to control the variable frequency speed-regulating stirrer. The graded sedimentation control module executes the liquid level adjustment command and outputs adjustment signals for pump frequency and valve position. The adjustment signal acts on the underflow state generated by the physical equipment device and serves as the input condition for the washing process control module. The washing process control module receives a signal characterizing the undercurrent state and processes the signal using a gradient boosting algorithm to calculate the chelating agent increment command. The system collaborative execution module receives the chelating agent increment command and generates a corresponding stirring intensity increase command, which is then sent to the staged sedimentation control module. The staged sedimentation control module adjusts the operating parameters of the variable frequency speed-regulating stirrer according to the stirring intensity increase command.

[0039] The staged sedimentation control module of this invention uses a fuzzy control algorithm to process liquid level adjustment commands, converting liquid level deviations into frequency adjustment signals for the underflow pump in the primary sedimentation tank. Simultaneously, it employs a dual-modal strategy to control the variable frequency speed-regulating agitator. The pump frequency and valve position adjustment signals output by the module, after acting on the physical equipment, generate underflow state parameters, which serve as input signals for the washing process control module. The washing process control module receives the underflow state signals and uses a gradient boosting algorithm to calculate the chelating agent increment command. The system coordination execution module receives the chelating agent increment command, generates an agitation intensity increase command, and sends it to the staged sedimentation control module. The staged sedimentation control module adjusts the agitator operating parameters according to the command, achieving coordinated control of the sedimentation and washing processes.

[0040] Specifically, in the sedimentation washing device for acid leaching of aluminum silicon oxides described in this invention, the timing controller in the washing process control module controls the sequential operation of each stage of the underflow pump by outputting a countercurrent washing start / stop signal. The model predictive control algorithm in the system collaborative execution module receives the countercurrent washing start / stop signal generated by the timing controller and uses the signal as the input to the periodic material flow fluctuation model. The model predictive control algorithm, based on the fluctuation model, outputs material allocation optimization instructions to the graded settling control module; The graded settling control module executes the material distribution optimization command, and the resulting changes in operating conditions are fed back to the washing process control module. The intermittent supply strategy in the washing process control module generates an intermittent supply signal by monitoring the liquid level in the washing tank; the system collaborative execution module receives the intermittent supply signal and generates a pre-adjustment instruction for the preceding sedimentation process accordingly.

[0041] The timing controller in the washing process control module of this invention controls the sequential operation of each stage of underflow pumps by outputting countercurrent washing start / stop signals. The model predictive control algorithm in the system collaborative execution module receives these start / stop signals as input to a periodic material flow fluctuation model. Based on the fluctuation model, the model predictive control algorithm outputs material allocation optimization instructions to the staged settling control module. The changes in operating conditions generated after the staged settling control module executes the instructions are fed back to the washing process control module. The intermittent supply strategy in the washing process control module generates intermittent supply signals by monitoring the washing tank level. The system collaborative execution module receives the intermittent supply signals and generates pre-adjustment instructions for the preceding settling process. Through timing coordination and predictive control, the overall system efficiency is improved.

[0042] Secondly, please refer to Figure 1 This invention provides a sedimentation washing method for acid-leached aluminum silicon oxides, applied to the aforementioned sedimentation washing apparatus for acid-leached aluminum silicon oxides, comprising: Step 1: Real-time data collection of slurry flow rate at the feed pump outlet, solid concentration in the underflow pipeline of the secondary settling tank, and conductivity at the overflow outlet of the washing tank. Step 2: Receive the slurry flow rate and solid concentration data, calculate the optimal settling time using a settling kinetics model; when the solid concentration is lower than a set threshold, generate a primary settling tank level adjustment command; when the conductivity fluctuates abnormally, generate a secondary settling tank agitator speed correction command. Step 3: Receive the liquid level adjustment command and the speed correction command; convert the liquid level adjustment command into a frequency adjustment signal for the underflow pump of the primary settling tank to control the residence time of the slurry in the primary settling tank, and simultaneously adjust the opening of the feed valve of the secondary settling tank; according to the speed correction command, control the variable frequency speed-regulating agitator to maintain low-speed stirring during the settling stage, and appropriately increase the speed of the variable frequency speed-regulating agitator based on the solid content when the underflow pump is detected to be running. Step 4: Receive the conductivity data; when the conductivity remains high, increase the dosage of the chelating agent addition unit according to a preset ratio, and instruct the washing liquid supply unit to increase the flow rate; by controlling the start-stop sequence of each underflow pump, implement the countercurrent washing logic so that the washing liquid flows in the opposite direction to the solid material flow. Step 5: Receive the equipment status signals generated in Step 3 and Step 4; when the instruction generated in Step 2 requires extending the settling time, synchronously delay the start time of the washing liquid supply unit; when the chelating agent is added in Step 4, automatically increase the stirring intensity of the secondary settling tank; through material balance closed-loop control, stabilize the underflow concentration within the target range.

[0043] This invention addresses the challenge of incomplete separation of soluble salts and fine particles in acid-leached aluminosilicate oxide slurries by integrating physical equipment and intelligent control devices. It constructs a data-driven sedimentation and washing system. The physical equipment comprises multi-stage sedimentation and washing tanks arranged in series, combined with an overflow weir system, a variable frequency speed-regulating agitator, and precise pump and valve units, providing the basic structure for solid-liquid separation. The control device's operational data acquisition module collects key parameters such as slurry flow rate, solid concentration, and conductivity in real time, providing accurate operational status awareness for the system. The sedimentation parameter optimization module calculates the optimal sedimentation time based on a sedimentation kinetic model and generates liquid level adjustment and speed correction commands through threshold judgment, optimizing the sedimentation process to prevent particle resuspension. The staged sedimentation control module converts these commands into adjustment signals for the underflow pump frequency and feed valve opening, achieving precise control of slurry residence time and step-by-step separation. Simultaneously, a stirring strategy based on solid content adaptively adjusts the stirring intensity during sedimentation and transfer stages to maintain stable solid particle sedimentation. The washing process control module dynamically adjusts the chelating agent dosage and washing liquid flow rate based on conductivity data, and employs countercurrent washing logic and intermittent supply to enhance impurity removal efficiency. The system collaborative execution module integrates the status signals of each module, and through material balance closed-loop control and cross-process collaboration, links the sedimentation and washing processes, ultimately stabilizing the underflow concentration within the target range. This effectively reduces the residue of soluble impurities and fine particles in the product, improves the purity of aluminum-silicon oxide raw materials, ensures the quality of subsequent aluminum-silicon alloy production, and inhibits scaling in the calcining furnace.

[0044] The sedimentation kinetic model is based on Kynch theory, a mathematical model describing particle sedimentation behavior. It determines sedimentation characteristics by analyzing the relationship between particle sedimentation velocity and concentration in a suspension. In this invention, the model uses real-time collected slurry flow rate data and historical concentration data as input. Utilizing the interfacial sedimentation principle in Kynch theory, it calculates the critical sedimentation velocity of the particle group and then uses an iterative algorithm to solve for the optimal sedimentation time, ensuring sedimentation efficiency. The PID algorithm is a proportional-integral-derivative control algorithm used to dynamically adjust the liquid level deviation. When the solid concentration remains below a set threshold, the PID algorithm calculates the adjustment amount based on the real-time deviation value and generates a liquid level adjustment command to stabilize the underflow concentration. The fuzzy control algorithm is a control method based on fuzzy logic used to handle the fuzziness of the liquid level deviation. This algorithm converts the liquid level deviation into a fuzzy set and derives the frequency adjustment signal for the underflow pump through a preset fuzzy rule base, achieving precise control. The gradient boosting algorithm is a machine learning algorithm used to predict impurity removal efficiency. This algorithm combines multiple weak prediction models to progressively optimize prediction accuracy and dynamically calculates the chelating agent dosage based on the mapping relationship between conductivity data and impurity concentration. The model predictive control algorithm is a multivariate control strategy that uses undercurrent concentration as the control target. It predicts future states by establishing a dynamic system model and optimizes material distribution instructions to ensure stable system operation. The spectrum analysis program uses a fast Fourier transform algorithm to convert the time-domain signal of conductivity data into a frequency-domain signal, identifying abnormal frequency components to determine solid suspension anomalies. The expert database is a pre-set knowledge base containing speed correction value matching rules under various operating conditions. It is built based on historical data and expert experience and is used for rapid response to abnormal situations. The material diffusion model describes the diffusion process of the chelating agent in the slurry. By calculating the relationship between dosage and stirring intensity, the required stirring parameters are determined. The moving average algorithm is a data filtering method that smooths the collected sensor data, eliminates random fluctuations, and generates stable operating condition data. The timing controller uses programmable logic to set the start-stop sequence of each stage of the underflow pumps, realizing countercurrent washing logic and ensuring that the washing liquid and materials flow in opposite directions. The material balance equation, based on the principle of mass conservation, is used to calculate inter-stage flow matching and maintains system balance through a correction coefficient for the opening of the reverse feed valve. The dual-modal strategy refers to the agitator using different speed modes during the settling and transfer stages, automatically switching according to the underflow pump's operating status to avoid solid deposition. The intermittent supply strategy monitors changes in the washing tank level and controls the pulsed supply of the washing liquid, enhancing mass transfer efficiency.

Claims

1. A settling and washing device for acid leaching of aluminum silicon oxide, characterized in that, Includes physical equipment and a control device communicatively connected to the physical equipment; The physical equipment includes three or more settling and washing tanks arranged in series, an overflow weir system set at the top of each tank, a variable frequency speed-regulating agitator installed in each tank, a mixer set at the top of each settling and washing tank, a feed pump connecting the acid leaching slurry inlet to the first settling and washing tank, an underflow pump connecting the discharge port at the bottom of each tank, a washing liquid supply unit connected to the washing tank via a metering pump, and a chelating agent addition unit equipped with an EDTA storage tank and connected to the washing liquid main pipeline via an injection pump. The control device includes: The working condition data acquisition module is used to collect in real time the slurry flow rate at the outlet of the feed pump, the solid concentration in the underflow pipeline of the secondary settling tank, and the conductivity at the overflow port of the washing tank. The settling parameter optimization module is used to receive the slurry flow rate and solid concentration data collected by the working condition data acquisition module, and calculate the optimal settling time through the settling kinetic model; when the solid concentration is lower than the set threshold, the settling parameter optimization module generates a primary settling tank level adjustment command; when the conductivity fluctuates abnormally, the settling parameter optimization module generates a secondary settling tank agitator speed correction command. The staged sedimentation control module is used to receive the liquid level adjustment command and the rotation speed correction command from the sedimentation parameter optimization module; the staged sedimentation control module converts the liquid level adjustment command into a frequency adjustment signal for the underflow pump of the primary sedimentation tank to control the residence time of the slurry in the primary sedimentation tank, and simultaneously adjusts the opening of the feed valve of the secondary sedimentation tank; according to the rotation speed correction command, the staged sedimentation control module controls the variable frequency speed-regulating agitator to maintain low-speed stirring during the sedimentation stage, and appropriately increases the rotation speed of the variable frequency speed-regulating agitator based on the solid content when the underflow pump is detected to be running; The washing process control module is used to receive the conductivity data from the working condition data acquisition module; when the conductivity is continuously high, the washing process control module increases the dosage of the chelating agent addition unit according to a preset ratio, and instructs the washing liquid supply unit to increase the flow rate; the washing process control module implements countercurrent washing logic by controlling the start and stop sequence of each stage of the underflow pump, so that the flow direction of the washing liquid is opposite to the flow direction of the solid material. The system collaborative execution module is used to receive equipment status signals from the staged sedimentation control module and the washing process control module; when the instruction generated by the sedimentation parameter optimization module requires extending the sedimentation time, the system collaborative execution module synchronously delays the start time of the washing liquid supply unit; when the washing process control module increases the addition of chelating agent, the system collaborative execution module automatically increases the stirring intensity of the secondary sedimentation tank; the system collaborative execution module stabilizes the underflow concentration within the target range through material balance closed-loop control.

2. The settling and washing apparatus for acid leaching of aluminum silicon oxide according to claim 1, characterized in that, The operating condition data acquisition module includes: The electromagnetic flowmeter monitors the slurry flow rate at the outlet of the feed pump and outputs a first signal; A microwave concentration meter is installed in the underflow pipeline of the secondary settling tank to collect microwave signals and convert them into solid concentration data by analyzing the attenuation. A four-electrode conductivity electrode and a temperature sensor are disposed at the overflow port of the washing tank. The conductivity electrode measures the conductivity value, the temperature sensor collects temperature data and compensates for the conductivity value, and outputs the compensated conductivity data. The first signal, the solid concentration data, and the compensated conductivity data are transmitted to the central processing unit via industrial Ethernet and filtered using a moving average algorithm to obtain stable operating condition data for subsequent module processing.

3. The settling and washing apparatus for acid leaching of aluminum silicon oxide according to claim 2, characterized in that, The settlement parameter optimization module is configured as follows: Receive stable operating condition data transmitted by the operating condition data acquisition module, wherein the stable operating condition data includes slurry flow rate, solid concentration and conductivity; The settling dynamics model is based on Kynch theory. The received real-time slurry flow rate and historical concentration data are substituted into the model, and the optimal settling time is obtained through iterative calculation. When the solid concentration data continues to be lower than the set threshold, a PID algorithm aimed at increasing the underflow concentration is triggered to dynamically calculate and generate a primary settling tank level adjustment command. When the conductivity data undergoes a step change, a spectrum analysis program is initiated to identify abnormal frequency components. If it is determined to be caused by an abnormal solid suspension, a preset expert library is called to match the optimal speed correction value, and a speed correction command for the secondary settling tank agitator is generated.

4. The settling and washing apparatus for acid leaching of aluminum silicon oxide according to claim 3, characterized in that, Receive liquid level adjustment command and rotation speed correction command from the sedimentation parameter optimization module; The graded settling control module compares the liquid level adjustment command with the preset liquid level value to obtain the liquid level deviation, and uses a fuzzy control algorithm to convert the liquid level deviation into a frequency adjustment signal for the bottom flow pump of the first-stage settling tank. Meanwhile, the graded settling control module uses the frequency adjustment signal to back-calculate the opening correction coefficient of the feed valve of the secondary settling tank based on the material balance equation, and adjusts the opening of the feed valve synchronously. For stirring control, the staged sedimentation control module sets the base speed of the variable frequency speed-regulating agitator according to the speed correction command; and based on the operating status signal of the underflow pump and solid content data, it appropriately increases the speed of the variable frequency speed-regulating agitator when the underflow pump is detected to be running, and switches to low speed mode after a delay after the underflow pump stops.

5. The settling and washing apparatus for acid leaching of aluminum silicon oxide according to claim 4, characterized in that, The washing process control module is configured as follows: Continuously receive conductivity data from the operating condition data acquisition module; The washing process control module compares the received conductivity data with a preset threshold. When the conductivity reading exceeds the threshold, it queries the pre-stored conductivity-impurity concentration mapping table and uses a gradient boosting algorithm to predict the impurity removal efficiency. Based on the prediction result, it dynamically calculates the chelating agent increment ratio, and then instructs the chelating agent addition unit to increase the dosage proportionally, and instructs the washing liquid supply unit to increase the flow rate. For countercurrent washing, the washing process control module uses a built-in timing controller to program and set the start and stop sequence of each stage of the underflow pump so that the washing liquid flows in the opposite direction to the solid material. Meanwhile, the washing process control module controls the washing liquid supply unit to supply the liquid intermittently and monitors the liquid level in the washing tank. When the liquid level reaches its peak, it triggers a stop for a single wash.

6. The settling and washing apparatus for acid leaching of aluminum silicon oxide according to claim 5, characterized in that, The system collaborative execution module is configured as follows: Receive equipment status signals sent by the graded sedimentation control module and the washing process control module; When the instruction generated by the settling parameter optimization module requires an extension of the settling time, the system collaborative execution module retrieves the current status of the washing liquid supply unit and generates a delayed start instruction to synchronize the start time of the washing liquid supply unit with the settling completion signal. When the washing process control module increases the dosage of chelating agent, the system collaborative execution module calls the material diffusion model, calculates the required stirring intensity based on the dosage, and sends a speed increase command to the variable frequency speed-regulating stirrer of the secondary settling tank. The system's collaborative execution module also employs a model predictive control algorithm, using the underflow concentration as the target variable, to calculate and output optimized instructions for the material distribution ratio between each level of tank in real time.

7. The settling and washing apparatus for acid leaching of aluminum silicon oxide according to claim 6, characterized in that, The settlement parameter optimization module receives stable operating condition data processed by the operating condition data acquisition module. The sedimentation parameter optimization module uses the stable operating condition data to calculate the optimal sedimentation time through the sedimentation dynamics model, and generates a liquid level adjustment command to send to the staged sedimentation control module. The graded sedimentation control module executes the liquid level adjustment command to adjust the pump frequency and valve position, and the adjusted operating conditions serve as the feeding conditions for the washing process control module. The washing process control module performs washing under the feeding conditions, and the conductivity data of the generated overflow liquid is collected by the working condition data acquisition module and fed back to the sedimentation parameter optimization module. The sedimentation parameter optimization module uses the conductivity data to correct the rotation speed parameter, forming a closed-loop optimization.

8. The settling and washing apparatus for acid leaching of aluminum silicon oxide according to claim 7, characterized in that, The graded sedimentation control module uses a fuzzy control algorithm to process liquid level adjustment commands and a dual-modal strategy to control the variable frequency speed-regulating agitator. The graded sedimentation control module executes the liquid level adjustment command and outputs adjustment signals for pump frequency and valve position. The adjustment signal acts on the underflow state generated by the physical equipment device and serves as the input condition for the washing process control module. The washing process control module receives a signal characterizing the undercurrent state and processes the signal using a gradient boosting algorithm to calculate the chelating agent increment command. The system collaborative execution module receives the chelating agent increment command and generates a corresponding stirring intensity increase command, which is then sent to the staged sedimentation control module. The staged sedimentation control module adjusts the operating parameters of the variable frequency speed-regulating stirrer according to the stirring intensity increase command.

9. The settling and washing apparatus for acid leaching of aluminum silicon oxide according to claim 8, characterized in that, The timing controller in the washing process control module controls the sequential operation of each stage of the underflow pump by outputting a countercurrent washing start / stop signal; The model predictive control algorithm in the system collaborative execution module receives the countercurrent washing start / stop signal generated by the timing controller and uses the signal as the input to the periodic material flow fluctuation model. The model predictive control algorithm, based on the fluctuation model, outputs material allocation optimization instructions to the graded settling control module; The graded settling control module executes the material distribution optimization command, and the resulting changes in operating conditions are fed back to the washing process control module. The intermittent supply strategy in the washing process control module generates an intermittent supply signal by monitoring the liquid level in the washing tank; the system collaborative execution module receives the intermittent supply signal and generates a pre-adjustment instruction for the preceding sedimentation process accordingly.

10. A sedimentation washing method for acid-leached aluminum silicon oxide, applied to the sedimentation washing apparatus for acid-leached aluminum silicon oxide as described in any one of claims 1 to 9, characterized in that, include: Step 1: Real-time data collection of slurry flow rate at the feed pump outlet, solid concentration in the underflow pipeline of the secondary settling tank, and conductivity at the overflow outlet of the washing tank. Step 2: Receive the slurry flow rate and solid concentration data, and calculate the optimal settling time using a settling kinetics model; When the solid concentration is lower than the set threshold, a liquid level adjustment command for the primary settling tank is generated; when the conductivity fluctuates abnormally, a stirrer speed correction command for the secondary settling tank is generated. Step 3: Receive the liquid level adjustment command and the speed correction command; convert the liquid level adjustment command into a frequency adjustment signal for the underflow pump of the primary settling tank to control the residence time of the slurry in the primary settling tank, and simultaneously adjust the opening of the feed valve of the secondary settling tank; according to the speed correction command, control the variable frequency speed-regulating agitator to maintain low-speed stirring during the settling stage, and appropriately increase the speed of the variable frequency speed-regulating agitator based on the solid content when the underflow pump is detected to be running. Step 4: Receive the conductivity data; when the conductivity remains high, increase the dosage of the chelating agent addition unit according to a preset ratio, and instruct the washing liquid supply unit to increase the flow rate; by controlling the start-stop sequence of each underflow pump, implement the countercurrent washing logic so that the washing liquid flows in the opposite direction to the solid material flow. Step 5: Receive the equipment status signals generated in Step 3 and Step 4; when the instruction generated in Step 2 requires extending the settling time, synchronously delay the start time of the washing liquid supply unit; when the chelating agent is added in Step 4, automatically increase the stirring intensity of the secondary settling tank; through material balance closed-loop control, stabilize the underflow concentration within the target range.

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