Electric separator single-machine stock bin material level control system and method

Abstract

The invention belongs to the technical field of industrial automation control, and particularly relates to a material level control system and method for a single-machine stock bin of an electric separator, according to the scheme, through dynamic monitoring and real-time closed-loop adjustment of the material level, the hysteresis quality of the system is effectively overcome, the fluctuation range of the material level can be controlled within an extremely narrow preset range, and the stability of the material level is improved. Therefore, the accuracy and the stability of control are obviously improved.

Description

Technical Field

[0001] This invention belongs to the field of industrial automation control technology, specifically relating to a single-machine material level control system and method for an electric separator. Background Technology

[0002] In the field of mineral separation such as sea sand and ore, electrostatic separation is one of the key separation processes. Its stable operation is highly dependent on the precise control of the material level in the hopper of a single unit. Ideally, the material level control should be able to respond quickly to external disturbances (such as changes in upstream feed) and stabilize the material level within the optimal range required by the process, thereby ensuring separation efficiency and product quality.

[0003] Currently, the industry mainly adopts the following two technical solutions for material level control in electrostatic precipitator hoppers: Manual experience-based control combined with simple logic-based "on / off" adjustment requires operators to continuously observe the level gauges of multiple silos and manually adjust the operating frequency of the feed motor based on the rough rule of "lower frequency at high levels and higher frequency at low levels." However, due to the large number of silos, the inherent lag in the mechanical and electrical response of the system, and the variability of material characteristics (such as flowability and moisture), this method is not only labor-intensive but also heavily reliant on personal experience. It is prone to problems such as untimely adjustment, over-adjustment, or under-adjustment, causing the material level to fluctuate significantly around the target value, making true stable control impossible and directly affecting the electrostatic separation process parameters.

[0004] The traditional fixed-parameter proportional-integral-derivative (PID) control strategy is adopted. While this approach achieves a certain degree of automation, it has significant limitations in complex operating conditions such as electrostatic precipitator production. (1) Parameter solidification and working condition contradiction: During the electrostatic separation of sea sand, the characteristics of material type, particle size, humidity and other properties are frequently switched. Different material characteristics have different requirements for the response speed and stability of the control system. A fixed set of PID parameters (especially integral time I and derivative time D) cannot achieve ideal control effect under all working conditions.

[0005] (2) Lack of adaptive capability: When the working conditions change, it is necessary to rely on manual adjustment and trial and error of parameters. This process is time-consuming and labor-intensive, and it is difficult to guarantee that the optimal parameters can be obtained every time, which leads to the interruption of production continuity and restricts the improvement of intelligent production level.

[0006] (3) Rigid sampling strategy: Traditional PID controllers usually use a fixed sampling period. When the system is stable, high-frequency sampling will consume unnecessary computing and communication resources. When the system experiences large disturbances, a fixed or low sampling frequency cannot capture rapid dynamic changes, resulting in slow response. Therefore, such schemes lack a mechanism to adaptively adjust the sampling frequency according to the real-time dynamic characteristics of the system. Summary of the Invention

[0007] This invention addresses the problems existing in the prior art by providing a single-machine material level control system and method for an electrostatic separator, which effectively solves the problems existing in the prior art.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows: The single-unit material level control system for the electrostatic precipitator includes: The material level detection device is used to collect material level data in real time and transmit it to the PLC controller; The PLC controller is used to determine the adjustment amount of the feeding motor frequency based on the received material level data and the material level difference between two adjacent samples as the rate of change; based on the rate of change and a dynamic proportional coefficient, the controller constructs a motor speed adjustment command based on the obtained adjustment amount and sends it to the feeding frequency converter; wherein, the interval between two adjacent samples is determined based on a sampling strategy adaptive mechanism, and the dynamic proportional coefficient is adaptively adjusted based on a parameter self-tuning strategy to adapt to different material conditions. A feeder frequency converter is used to adjust the speed of the feeder motor based on received motor speed adjustment commands, thereby achieving precise feed control.

[0009] Furthermore, the step of determining the adjustment amount of the feed motor frequency based on the rate of change combined with the dynamic proportional coefficient specifically involves: based on a preset material level threshold, increasing the feed motor frequency when it is higher than the preset material level threshold and decreasing the feed motor frequency when it is lower than the preset material level threshold as the basic control logic; calculating the material level difference between the latest two adjacent samples as the rate of change according to a predetermined sampling interval, and multiplying it by the dynamic proportional coefficient to determine the adjustment amount of the feed motor frequency; and determining the latest feed motor output frequency based on the adjustment amount of the feed motor frequency combined with the output frequency of the previous cycle.

[0010] Furthermore, the output frequency of the feed motor is specifically expressed as follows: in, This is the latest feed motor output frequency. This is the output frequency of the previous cycle. This refers to the adjustment amount of the feed motor frequency. The dynamic proportional coefficient determined in the previous cycle. for The rate of change is calculated based on the difference between the current sampled material level and the previous sampled material level. for The material level is sampled at all times. for The material level is sampled at all times.

[0011] Furthermore, the adaptive sampling strategy mechanism is specifically as follows: Based on the material level data sequence sampled within the preset evaluation window, the mean absolute deviation and mean absolute rate of change are calculated respectively. Based on the obtained mean absolute deviation and mean absolute rate of change, combined with a preset threshold, the system operating state is determined; wherein, the system operating state includes quasi-steady state, large disturbance or response hysteresis, and dynamic steady state. Based on the obtained system operating status, the sampling interval between two adjacent samplings is dynamically adjusted.

[0012] Furthermore, the dynamic adjustment of the interval between two adjacent samplings is specifically expressed as follows: When the system is in a quasi-steady state, the following adjustments are performed: If and only if the mean absolute deviation is less than the lower limit of deviation and the mean absolute rate of change is less than the lower limit of rate of change and the stable duration is greater than the stable duration threshold. When the system is experiencing a large disturbance or slow response, the following adjustments should be made: If and only if the absolute rate of change at the current moment is greater than the preset disturbance threshold, or if the absolute deviation at the current moment is greater than the upper limit of the deviation and the absolute rate of change at the current moment is less than the lower limit of the rate of change and the stable duration is greater than the hysteresis judgment time threshold. When the system is in a dynamically stable state, that is, when it does not meet the requirements of quasi-steady state and response hysteresis state, the current sampling interval remains unchanged; in, The latest sampling interval after adjustment. This is the upper limit of the sampling interval. This is the lower limit of the sampling interval. For the current sampling interval, To extend the sampling period, To shorten the sampling period.

[0013] Furthermore, the dynamic proportional coefficient is adaptively adjusted for gain based on a parameter self-tuning strategy, specifically as follows: Based on the material level data sequence sampled within the preset evaluation window, the mean absolute deviation, mean absolute rate of change, and oscillation index are calculated respectively. Based on the obtained mean absolute deviation, mean absolute rate of change, and oscillation index, combined with a preset threshold, the control performance status is determined; wherein, the control performance status includes under-regulation, over-regulation, and acceptable performance. Based on the obtained control performance status, the dynamic proportional coefficient is adaptively adjusted for gain.

[0014] Furthermore, the dynamic scaling factor is specifically expressed as follows: When the control performance status is under-adjusted, the following adjustments are performed: If and only if the mean absolute deviation is greater than the upper limit of deviation and the mean absolute rate of change is less than the lower limit of rate of change; When the control performance status is over-adjusted, the following adjustments are performed: If and only if the mean absolute deviation is less than the lower limit of deviation and the mean absolute rate of change is greater than the upper limit of rate of change, or the oscillation index is greater than the oscillation index threshold; When the control performance is in an acceptable state, i.e., when it does not meet the conditions of under-regulation or over-regulation, the current dynamic proportional coefficient remains unchanged. Finally, regarding the states of under-regulation and over-regulation, As the latest dynamic scaling factor; in, This is the upper limit of the dynamic scaling factor. This is the lower limit of the dynamic proportional coefficient. To increase the amplitude of the dynamic scaling factor, To reduce the amplitude of the dynamic scaling factor.

[0015] A method for controlling the material level in a single hopper of an electrostatic precipitator, based on the aforementioned control system for the material level in a single hopper of an electrostatic precipitator, includes: Real-time material level data collection; Based on the obtained material level data sequence, the material level difference between the latest two adjacent samples is used as the rate of change; the adjustment amount of the feeding motor frequency is determined based on the rate of change and the dynamic proportional coefficient; the motor speed adjustment command is constructed based on the obtained adjustment amount; wherein, the interval between the two adjacent samples is determined based on the sampling strategy adaptive mechanism, and the dynamic proportional coefficient is adaptively adjusted based on the parameter self-tuning strategy to adapt to different material working conditions. Based on the obtained motor speed adjustment command, the speed of the feeding motor is adjusted to achieve precise feeding control.

[0016] An electronic device includes a memory, a processor, and a computer program stored in the memory and running on it. When the processor executes the program, it implements the above-described method for controlling the material level of a single hopper in an electric separator.

[0017] A non-transitory computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method for controlling the material level of a single hopper in an electric separator.

[0018] Compared with the prior art, the advantages and positive effects of the present invention are as follows: (1) The present invention provides a single-machine silo material level control system and method for an electric separator. The solution effectively overcomes the system lag by dynamically monitoring the material level and adjusting it in real time, and can control the material level fluctuation range within a very narrow preset range, thereby significantly improving the accuracy and stability of the control. (2) The solution described in this invention achieves an advanced response to the trend of material level change, fundamentally overcoming the control lag. Specifically, the solution abandons the traditional direct control based on the deviation of "material level - set value" and innovatively adopts the material level change rate (i.e., derivative) as the core control quantity. With this setting, when the material level just begins to drop (even if the absolute material level is still higher than the target value), the negative change rate will immediately trigger the adjustment of frequency increase, and vice versa. This control strategy based on "speed" rather than "position" enables the system to predict the future trend of material level and make advanced adjustments, which can effectively suppress the large fluctuation of material level caused by the large inertia of the system, thereby quickly converging to a stable state. (3) The scheme of the present invention significantly improves the robustness and self-learning ability of the system to various working conditions by constructing a two-layer adaptive mechanism of dynamic proportional coefficient and sampling interval. Specifically, in the self-tuning process of dynamic proportional coefficient, the scheme system evaluates the control effect in real time through online performance indicators such as mean absolute deviation (static accuracy), mean absolute rate of change (dynamic intensity), and oscillation index (oscillation degree). According to the strategy of increasing the gain when the adjustment is insufficient and decreasing the gain when the adjustment is excessive, the dynamic proportional coefficient is adaptively adjusted. This enables the system of the present invention to automatically adjust its own gain to the state that best matches the working condition when dealing with materials with different fluidity and viscosity, completely eliminating the burden of repeated manual parameter adjustment. Secondly, in the adaptive adjustment of sampling interval, the sampling period is automatically extended in quasi-steady state to save resources, and the sampling period is automatically shortened in the event of large disturbance or response lag to improve the response speed. By dynamically changing the sensing capability, the system can achieve optimal resource allocation while ensuring control accuracy and further enhance the ability to deal with sudden working conditions. (4) The solution described in this invention forms a complete intelligent control closed loop, which improves the level of production automation and intelligence. Specifically, the solution organically integrates trend prediction (rate of change control), self-evaluation (performance index calculation) and strategy optimization (dynamic proportional coefficient and sampling interval adjustment) into a closed loop framework. Through this closed loop framework, the system described in this invention can continuously perceive the environment (i.e. different working conditions) and its own performance, and optimize the control behavior accordingly. The solution can automatically maintain high-precision and stable control of the material level without human intervention, ensuring the continuous optimal electro-separation process conditions and improving the sorting efficiency and product quality stability. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below: Figure 1 This is a single-unit hopper level control system for an electric separator as described in this embodiment of the invention; Figure 2 This is a schematic diagram of the control logic of a single-unit silo level control system for an electrostatic separator as described in an embodiment of the present invention; Figure 3 This is a flowchart of a single-machine hopper level control method for an electrostatic separator as described in an embodiment of the present invention; Figure 4 This is a schematic diagram of an electronic device structure according to an embodiment of the present invention. Detailed Implementation

[0020] To better understand the above-mentioned objectives, features and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0021] Numerous specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways than those described herein, and therefore the invention is not limited to the specific embodiments disclosed in the following specification.

[0022] Example 1 The following is a detailed description of the single-machine hopper level control system for the electrostatic separator in Embodiment 1, with reference to the accompanying drawings.

[0023] The solution described in this embodiment is an optimization and upgrade based on the traditional control logic of "increasing frequency at high levels and decreasing frequency at low levels". Its core is that when the material level deviates from the preset value, the system collects continuous material level data according to the preset sampling interval, calculates the difference in material level between two adjacent samples as the rate of change, and multiplies it by the dynamic proportional coefficient K to dynamically determine the precise adjustment amount of the feed motor frequency. At the same time, the system has self-learning ability. If the material level change rate still does not improve significantly after multiple adjustments, the system will automatically adjust the dynamic proportional coefficient K to achieve adaptive matching for different material conditions. Secondly, to address the inherent lag in material level response, this system introduces an adaptive sampling strategy mechanism to optimize control performance. The core of this mechanism is to establish an intelligent correlation between the sampling interval T and the system operating state: if the material level change rate is still too low after multiple adaptive adjustments of the dynamic proportional coefficient K, the sampling interval T will be automatically extended; conversely, if the material level change rate is detected to be too high or the response is sluggish, the sampling interval T will be dynamically shortened to improve the control response speed. Through this mechanism, an autonomous trade-off between control real-time performance and operating efficiency is achieved, enabling the system to maintain optimal control performance under different operating conditions, significantly improving the system's control accuracy and adaptability.

[0024] The single-machine silo level control system for the electrostatic separator described in this embodiment is essentially an intelligent control system for automatically monitoring and adjusting the silo level. This system effectively ensures the continuity and stability of the electrostatic separation process by maintaining a dynamically constant silo level, while significantly reducing manual intervention and achieving precise and efficient management of the production process. The system consists of three core components: a level detection device, a PLC controller, and a feeding frequency converter, forming a complete closed-loop control architecture. Its processing flow is as follows: the level detection device collects level data in real time and transmits it to the PLC controller; the PLC controller performs calculations according to preset logic, outputs a motor speed command, and sends the command to the feeding frequency converter via RS-485 communication, thereby adjusting the feeding motor speed and achieving precise feeding control. Specifically, as shown... Figure 1 and Figure 2 As shown, the single-unit material level control system for the electrostatic separator includes: The material level detection device is used to collect material level data in real time and transmit it to the PLC controller; The PLC controller is used to determine the adjustment amount of the feeding motor frequency based on the received material level data and the material level difference between two adjacent samples as the rate of change; based on the rate of change and a dynamic proportional coefficient, the controller constructs a motor speed adjustment command based on the obtained adjustment amount and sends it to the feeding frequency converter; wherein, the interval between two adjacent samples is determined based on a sampling strategy adaptive mechanism, and the dynamic proportional coefficient is adaptively adjusted based on a parameter self-tuning strategy to adapt to different material conditions. A feeder frequency converter is used to adjust the speed of the feeder motor based on received motor speed adjustment commands, thereby achieving precise feed control.

[0025] In one or more embodiments, determining the adjustment amount of the feed motor frequency based on the rate of change combined with the dynamic proportional coefficient specifically involves: based on a preset material level threshold, increasing the feed motor frequency when it is higher than the preset material level threshold and decreasing the feed motor frequency when it is lower than the preset material level threshold as a basic control logic; calculating the material level difference between the latest two adjacent samples as the rate of change according to a predetermined sampling interval, and multiplying it by the dynamic proportional coefficient to determine the adjustment amount of the feed motor frequency; and determining the latest feed motor output frequency based on the adjustment amount of the feed motor frequency combined with the output frequency of the previous cycle.

[0026] In one or more embodiments, the output frequency of the feed motor is specifically represented as follows: in, This is the latest feed motor output frequency. This is the output frequency of the previous cycle. This refers to the adjustment amount of the feed motor frequency. The dynamic proportional coefficient determined in the previous cycle. for The rate of change is calculated based on the difference between the current sampled material level and the previous sampled material level. for The material level is sampled at all times. for The material level is sampled at all times.

[0027] In one or more embodiments, the sampling strategy adaptive mechanism specifically includes: Based on the material level data sequence sampled within the preset evaluation window, the mean absolute deviation and mean absolute rate of change are calculated respectively. Based on the obtained mean absolute deviation and mean absolute rate of change, combined with a preset threshold, the system operating state is determined; wherein, the system operating state includes quasi-steady state, large disturbance or response hysteresis, and dynamic steady state. Based on the obtained system operating status, the sampling interval between two adjacent samplings is dynamically adjusted.

[0028] In one or more embodiments, the dynamic adjustment of the interval between two adjacent samplings is specifically expressed as follows: When the system is in a quasi-steady state, the following adjustments are performed: If and only if the mean absolute deviation is less than the lower limit of deviation and the mean absolute rate of change is less than the lower limit of rate of change and the stable duration is greater than the stable duration threshold. When the system is experiencing a large disturbance or slow response, the following adjustments should be made: If and only if the absolute rate of change at the current moment is greater than the preset disturbance threshold, or if the absolute deviation at the current moment is greater than the upper limit of the deviation and the absolute rate of change at the current moment is less than the lower limit of the rate of change and the stable duration is greater than the hysteresis judgment time threshold. When the system is in a dynamically stable state, that is, when it does not meet the requirements of quasi-steady state and response hysteresis state, the current sampling interval remains unchanged; in, The latest sampling interval after adjustment. This is the upper limit of the sampling interval. This is the lower limit of the sampling interval. For the current sampling interval, To extend the sampling period, To shorten the sampling period, The value can be greater than 1 (for example, 1.5 can be selected). The value is less than 1 (for example, 0.7 can be selected). This means taking the minimum of the two values. This indicates taking the maximum of the two values.

[0029] In one or more embodiments, the dynamic scaling factor is adaptively adjusted for gain based on a parameter self-tuning strategy, specifically as follows: Based on the material level data sequence sampled within the preset evaluation window, the mean absolute deviation, mean absolute rate of change, and oscillation index are calculated respectively. Based on the obtained mean absolute deviation, mean absolute rate of change, and oscillation index, combined with a preset threshold, the control performance status is determined; wherein, the control performance status includes under-regulation, over-regulation, and acceptable performance. Based on the obtained control performance status, the dynamic proportional coefficient is adaptively adjusted for gain.

[0030] In one or more embodiments, the dynamic scaling factor is specifically represented as follows: When the control performance status is under-adjusted, the following adjustments are performed: If and only if the mean absolute deviation is greater than the upper limit of deviation and the mean absolute rate of change is less than the lower limit of rate of change; When the control performance status is over-adjusted, the following adjustments are performed: If and only if the mean absolute deviation is less than the lower limit of deviation and the mean absolute rate of change is greater than the upper limit of rate of change, or the oscillation index is greater than the oscillation index threshold; When the control performance is in an acceptable state, i.e., when it does not meet the conditions of under-regulation or over-regulation, the current dynamic proportional coefficient remains unchanged. Finally, regarding the states of under-regulation and over-regulation, As the latest dynamic proportional coefficient; the purpose here is to keep the sign of the dynamic proportional coefficient negative to ensure the correct control direction; in, This is the upper limit of the dynamic scaling factor. This is the lower limit of the dynamic proportional coefficient. To increase the amplitude of the dynamic scaling factor, To reduce the amplitude of the dynamic scaling factor, among which, The value must be greater than 1 (for example, 1.2 can be selected). The value is less than 1 (for example, 0.8 can be selected).

[0031] It should be noted here that the calculations for the mean absolute deviation, mean absolute rate of change, and oscillation index mentioned above are specifically expressed as follows: Mean Absolute Deviation (MAE): in, Let be the average absolute deviation of all sampling points within the evaluation window corresponding to time t, and N be the number of sampling points within the evaluation window. To evaluate the deviation of the i-th sampling point within the window.

[0032] Mean absolute rate of change (MALR): in, Let be the average absolute rate of change of several material level changes within the evaluation window corresponding to time t. To assess the number of sampling points within the window, This represents the rate of change in material level.

[0033] Oscillator (OI): in, Rate of change The number of times the sign changes. A value close to 1 indicates frequent oscillations, while a value close to 0 indicates unidirectional changes.

[0034] In specific implementation, the threshold parameters involved in the scheme described in this embodiment mainly include: upper and lower limits of deviation, upper and lower limits of rate of change, disturbance threshold, stabilization time threshold, and hysteresis time threshold. These thresholds can be set by expert evaluation or by combining historical data with expert evaluation.

[0035] Example 2 In one or more embodiments, such as Figure 3 As shown, this embodiment provides a method for controlling the material level of a single hopper in an electric separator based on the above system.

[0036] A method for controlling the material level in a single hopper of an electrostatic precipitator, based on the aforementioned control system for the material level in a single hopper of an electrostatic precipitator, includes: Real-time material level data collection; Based on the obtained material level data sequence, the material level difference between the latest two adjacent samples is used as the rate of change; the adjustment amount of the feeding motor frequency is determined based on the rate of change and the dynamic proportional coefficient; the motor speed adjustment command is constructed based on the obtained adjustment amount; wherein, the interval between the two adjacent samples is determined based on the sampling strategy adaptive mechanism, and the dynamic proportional coefficient is adaptively adjusted based on the parameter self-tuning strategy to adapt to different material working conditions. Based on the obtained motor speed adjustment command, the speed of the feeding motor is adjusted to achieve precise feeding control.

[0037] Example 3 like Figure 4 As shown, this embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on it. When the processor executes the program, it implements the above-described method for controlling the material level of a single hopper in an electric separator.

[0038] Example 4 A non-transitory computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method for controlling the material level of a single hopper in an electric separator.

[0039] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications or equivalent changes made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A single-unit hopper level control system for an electrostatic separator, characterized in that, include: The material level detection device is used to collect material level data in real time and transmit it to the PLC controller; The PLC controller is used to determine the adjustment amount of the feeding motor frequency based on the received material level data and the material level difference between two adjacent samples as the rate of change; based on the rate of change and a dynamic proportional coefficient, the controller constructs a motor speed adjustment command based on the obtained adjustment amount and sends it to the feeding frequency converter; wherein, the interval between two adjacent samples is determined based on a sampling strategy adaptive mechanism, and the dynamic proportional coefficient is adaptively adjusted based on a parameter self-tuning strategy to adapt to different material conditions. A feeder frequency converter is used to adjust the speed of the feeder motor based on received motor speed adjustment commands, thereby achieving precise feed control.

2. The single-unit hopper level control system for the electrostatic separator as described in claim 1, characterized in that, The method of determining the adjustment amount of the feed motor frequency based on the rate of change combined with the dynamic proportional coefficient is as follows: based on a preset material level threshold, the feed motor frequency is increased when it is higher than the preset material level threshold and decreased when it is lower than the preset material level threshold. According to a predetermined sampling interval, the material level difference between the latest two adjacent samples is calculated as the rate of change and multiplied by the dynamic proportional coefficient to determine the adjustment amount of the feed motor frequency. Based on the adjustment amount of the feed motor frequency, combined with the output frequency of the previous cycle, the latest feed motor output frequency is determined.

3. The single-unit hopper level control system for the electrostatic separator as described in claim 2, characterized in that, The output frequency of the feed motor is specifically expressed as follows: in, This is the latest feed motor output frequency. This is the output frequency of the previous cycle. This refers to the adjustment amount of the feed motor frequency. The dynamic proportional coefficient determined in the previous cycle. for The rate of change is calculated based on the difference between the current sampled material level and the previous sampled material level. for The material level is sampled at all times. for The material level is sampled at all times.

4. The single-unit hopper level control system for the electrostatic separator as described in claim 1, characterized in that, The adaptive mechanism of the sampling strategy is as follows: Based on the material level data sequence sampled within the preset evaluation window, the mean absolute deviation and mean absolute rate of change are calculated respectively. Based on the obtained mean absolute deviation and mean absolute rate of change, combined with a preset threshold, the system operating state is determined; wherein, the system operating state includes quasi-steady state, large disturbance or response hysteresis, and dynamic steady state. Based on the obtained system operating status, the sampling interval between two adjacent samplings is dynamically adjusted.

5. The single-unit hopper level control system for the electrostatic separator as described in claim 4, characterized in that, The dynamic adjustment of the interval between two adjacent samplings is specifically expressed as follows: When the system is in a quasi-steady state, the following adjustments are performed: If and only if the mean absolute deviation is less than the lower limit of deviation and the mean absolute rate of change is less than the lower limit of rate of change and the stable duration is greater than the stable duration threshold. When the system is experiencing a large disturbance or slow response, the following adjustments should be made: If and only if the absolute rate of change at the current moment is greater than the preset disturbance threshold, or if the absolute deviation at the current moment is greater than the upper limit of the deviation and the absolute rate of change at the current moment is less than the lower limit of the rate of change and the stable duration is greater than the hysteresis judgment time threshold. When the system is in a dynamically stable state, that is, when it does not meet the requirements of quasi-steady state and response hysteresis state, the current sampling interval remains unchanged; in, The latest sampling interval after adjustment. This is the upper limit of the sampling interval. This is the lower limit of the sampling interval. For the current sampling interval, To extend the sampling period, To shorten the sampling period.

6. The single-unit hopper level control system for the electrostatic separator as described in claim 1, characterized in that, The dynamic scaling factor is based on a parameter self-tuning strategy for adaptive gain adjustment, specifically: Based on the material level data sequence sampled within the preset evaluation window, the mean absolute deviation, mean absolute rate of change, and oscillation index are calculated respectively. Based on the obtained mean absolute deviation, mean absolute rate of change, and oscillation index, combined with a preset threshold, the control performance status is determined; wherein, the control performance status includes under-regulation, over-regulation, and acceptable performance status. Based on the obtained control performance status, the dynamic proportional coefficient is adaptively adjusted for gain.

7. The single-unit hopper level control system for the electrostatic separator as described in claim 6, characterized in that, The dynamic scaling factor is specifically represented as follows: When the control performance status is under-adjusted, the following adjustments are performed: If and only if the mean absolute deviation is greater than the upper limit of deviation and the mean absolute rate of change is less than the lower limit of rate of change; When the control performance status is over-adjusted, the following adjustments are performed: If and only if the mean absolute deviation is less than the lower limit of deviation and the mean absolute rate of change is greater than the upper limit of rate of change, or the oscillation index is greater than the oscillation index threshold; When the control performance is in an acceptable state, i.e., when it does not meet the conditions of under-regulation or over-regulation, the current dynamic proportional coefficient remains unchanged. Finally, regarding the states of under-regulation and over-regulation, As the latest dynamic scaling factor; in, This is the upper limit of the dynamic scaling factor. This is the lower limit of the dynamic proportional coefficient. To increase the amplitude of the dynamic scaling factor, To reduce the amplitude of the dynamic scaling factor.

8. A method for controlling the material level in a single silo of an electrostatic separator, based on the material level control system for a single silo of an electrostatic separator as described in any one of claims 1-7, characterized in that, include: Real-time material level data collection; Based on the obtained material level data sequence, the change rate is taken as the material level difference between the two most recent adjacent samples; The adjustment amount of the feed motor frequency is determined based on the rate of change combined with the dynamic proportional coefficient; the motor speed adjustment command is constructed based on the obtained adjustment amount; wherein, the interval between two adjacent samplings is determined based on the sampling strategy adaptive mechanism, and the dynamic proportional coefficient is adaptively adjusted based on the parameter self-tuning strategy to adapt to different material working conditions. Based on the obtained motor speed adjustment command, the speed of the feeding motor is adjusted to achieve precise feeding control.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and running thereon, characterized in that, When the processor executes the program, it implements the single-machine hopper level control method for the electric separator as described in claim 8.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the single-machine hopper level control method for the electrostatic separator as described in claim 8.

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