PLC-based control method and system for bottom discharge centrifuge

Abstract

This invention relates to the field of centrifuge control technology, specifically to a PLC-based control method and system for a bottom-discharge centrifuge. The method includes: acquiring the flow rate time series, concentration time series, and power time series of the material at the feed valve during the feeding stage; obtaining first and second characteristic values ​​for each control moment by combining the correlation and average trend of the flow rate and concentration time series within the time range corresponding to any control moment and the previous control moment, as well as the periodic fluctuation characteristics of the power time series; and obtaining a proportional parameter value by combining the first and second characteristic values, thereby controlling the speed of the main motor of the bottom-discharge centrifuge at the corresponding control moment. This invention improves the control effect of the main motor of the bottom-discharge centrifuge, thereby improving the filtration effect of the material.

Description

Technical Field

[0001] This invention relates to the field of centrifuge control technology, specifically to a PLC-based control method and system for a bottom-discharge centrifuge. Background Technology

[0002] Bottom discharge centrifuges are centrifuges that use centrifugal force to separate solids from liquids and discharge solid materials from the bottom of the equipment. They are mainly used for solid-liquid separation of suspensions containing solid particles. PLCs are programmable logic controllers and are widely used in the fully automatic or semi-automatic control of centrifuges.

[0003] During the operation of a bottom-discharge centrifuge, the PLC control system is mainly used to control the centrifuge's start-up, shutdown, speed, and running time. The control accuracy of the PLC control system is crucial for ensuring the centrifuge's efficient and stable operation, especially the control of the centrifuge drum speed. However, due to the inherent time lag in the PLC control system, and the uneven drum load caused by material changes at the feed valve and unstable drum motor power during the feeding phase of the bottom-discharge centrifuge, the centrifuge drum speed experiences significant lag changes. This exacerbates the actual error caused by this time lag, making it difficult for the PLC control system to respond promptly to changes in drum speed during the feeding phase. This reduces the control accuracy of the PLC control system during the feeding phase, easily leading to frequent and drastic fluctuations in the centrifuge drum speed. This not only exacerbates the uneven material distribution on the centrifuge filter screen, affecting the subsequent centrifuge filtration effect, but also makes it difficult for the centrifuge to operate stably during the feeding phase, accelerating equipment wear and reducing its service life. Summary of the Invention

[0004] This invention provides a PLC-based control method and system for a bottom-discharge centrifuge to solve existing problems.

[0005] The PLC-based bottom-discharge centrifuge control method and system of the present invention adopts the following technical solution:

[0006] One embodiment of the present invention provides a PLC-based control method for a bottom-discharge centrifuge, the method comprising the following steps:

[0007] The flow rate and concentration time series of the material at the feed valve of the lower discharge centrifuge during the feeding stage are obtained, as well as the power time series of the centrifuge's main motor. Each data point in the series corresponds to a control moment.

[0008] The first characteristic value of the control time is obtained by combining the correlation and average trend of the flow time series and concentration time series within the time range corresponding to any control time and the previous control time.

[0009] By utilizing the periodic fluctuation characteristics of the power time series within the time range corresponding to any control time and the previous control time, a second characteristic value for the control time is obtained; by combining the first characteristic value and the second characteristic value, the proportional parameter value at the control time is obtained.

[0010] The speed of the main motor of the lower unloading centrifuge is controlled by the proportional parameter value at the corresponding control time.

[0011] Furthermore, the method for obtaining the first characteristic value of the control time by combining the correlation and average trend of the flow rate time series and concentration time series within the time range corresponding to any control time and the previous control time includes the following specific methods:

[0012] The trend components of the flow rate time series and concentration time series within the time range corresponding to any control time and the previous control time are obtained by using the time series decomposition algorithm. Based on the correlation between the trend components, the trend change characteristic values ​​between the flow rate time series and the concentration time series are obtained.

[0013] Linear fitting is performed on the trend components of the flow and concentration time series respectively. The first characteristic value of the control time is obtained by combining the mean slope of the linear fitting results and the trend change characteristic value. The mean slope and the trend change characteristic value are both positively correlated with the first characteristic value.

[0014] Furthermore, the specific method for obtaining the trend change characteristic value is as follows:

[0015] The STL time series decomposition algorithm is used to extract the trend components of the flow rate time series and concentration time series within the time range corresponding to any control time and the previous control time, respectively, which are denoted as the first trend component and the second trend component. The Pearson correlation coefficient between the first trend component and the second trend component is denoted as the trend change characteristic value. If the result of the Pearson correlation coefficient is less than 0, the trend change characteristic value is assigned to 0.

[0016] Furthermore, the specific method for obtaining the first feature value is as follows:

[0017] The first and second trend components are fitted with straight lines using the least squares method, resulting in a first fitted line and a second fitted line. The mean slope of the first and second fitted lines is used as the input to the sigmoid function, and the range of the mean value is mapped to... Within the range, the product between the output of the sigmoid function and the trend change characteristic value is recorded as the first characteristic value at the control time.

[0018] Furthermore, the method for obtaining a second feature value for a control moment by utilizing the periodic fluctuation characteristics of the power time series within the time range corresponding to any control moment and the previous control moment, and combining the first and second feature values ​​to obtain the proportional parameter value at the control moment, includes the following specific methods:

[0019] The seasonal component of the power time series within the time range corresponding to any control time and the previous control time is obtained by using the time series decomposition algorithm. The second feature value of the control time is obtained based on the mean of the absolute values ​​of all data points in the seasonal component.

[0020] The upper and lower limits of the preset proportional parameters are used to calculate the proportional parameter value at the control time by combining the first and second eigenvalues ​​with the upper and lower limits of the proportional parameters.

[0021] Furthermore, the specific method for obtaining the second feature value at the control moment is as follows:

[0022] The seasonal component of the power time series is extracted using the STL time series decomposition algorithm. The mean of the absolute values ​​of all data points in the seasonal component is calculated, and this mean is used as the input to the sigmoid function, mapping the range of the mean to... Within the range, the output of the sigmoid function is recorded as the second characteristic value of the control time.

[0023] Furthermore, the specific method for obtaining the proportional parameter value at the control moment is as follows:

[0024] Obtain the numerical range formed by the upper and lower limits of the preset proportional parameter, and denot it as the proportional parameter range value; obtain the average of the first characteristic value and the second characteristic value, and denot it as the adjustment coefficient; round down the product of the adjustment coefficient and the proportional parameter range value to obtain the compensation value; add the lower limit of the proportional parameter to the compensation value to obtain the proportional parameter value at the control time.

[0025] Furthermore, the specific method for controlling the speed of the main motor of the lower unloading centrifuge at the corresponding control time using proportional parameter values ​​includes:

[0026] The centrifuge drum speed signal during the feeding stage of the lower discharge centrifuge and the set value of the drum speed are used as inputs to the PID control algorithm in the PLC control system, and the control time is... The corresponding proportional parameter value is used as the control time of the PID control algorithm. The value of the proportional parameter within the time period of the next control moment is used as the output signal of the PID control algorithm to control the speed of the drum by the PLC control system. The control signal is converted into a current signal by a D / A converter, and the inverter maps the current signal into a corresponding frequency to control the speed of the main motor of the centrifuge.

[0027] Furthermore, the specific method for obtaining the flow rate time series and concentration time series of the material at the feed valve during the feeding stage of the lower discharge centrifuge, as well as the power time series of the centrifuge's main motor, includes:

[0028] During the feeding stage of the lower discharge centrifuge, flow rate data and concentration data of the material at the feed valve of the centrifuge are collected using a flow meter and a concentration meter, respectively. The motor that controls the rotation speed of the drum is called the main motor. The power data of the main motor is collected using a power meter. The flow rate data, concentration data and power data are normalized using linear normalization to obtain the flow rate time series, concentration time series and power time series.

[0029] The PLC-based bottom discharge centrifuge control system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of any of the PLC-based bottom discharge centrifuge control methods described above.

[0030] The beneficial effects of the technical solution of this invention are as follows: By combining the correlation between flow rate time series and concentration time series, as well as their average trends, the changing patterns of materials can be better understood. Simultaneously, the periodic fluctuation characteristics of the power time series are used to extract a second feature value, which helps to monitor the load of the main motor in real time. By dynamically adjusting the proportional parameter value in the PID control algorithm and adjusting the speed of the main motor according to this value, dynamic and real-time regulation can be achieved, enabling the centrifuge to maintain optimal operating conditions under different operating conditions. This improves the response speed of the PLC control system to changes in the main motor speed caused by uneven drum load due to changes in centrifuge material and unstable motor power, thereby improving the control accuracy of the PLC control system when controlling the centrifuge speed. It also avoids frequent and drastic fluctuations in the centrifuge speed during the feeding stage, further improving the stability and reliability of the system. This solution combines multi-dimensional data of flow rate, concentration, and power, and uses a calculation model to extract feature values ​​at the control moment, achieving automated intelligent control. This reduces human intervention, lowers operational risks, and also improves the level of intelligence in the production process. Furthermore, precise speed control ensures that the main motor provides the appropriate power as needed, thereby effectively reducing unnecessary energy waste, optimizing the efficiency of motor power utilization, and effectively improving the control effect of the main motor of the lower discharge centrifuge, thus improving the filtration effect of materials. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart illustrating the steps of the PLC-based bottom-discharge centrifuge control method of the present invention.

[0033] Figure 2 A flowchart illustrating a method for analyzing the first eigenvalue of a control moment according to an embodiment of the present invention;

[0034] Figure 3 This is a flowchart illustrating a method for analyzing proportional parameter values ​​at control moments according to an embodiment of the present invention. Detailed Implementation

[0035] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the PLC-based bottom-discharge centrifuge control method and system proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0036] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0037] The following description, in conjunction with the accompanying drawings, details the specific scheme of the PLC-based bottom-discharge centrifuge control method and system provided by this invention.

[0038] Please see Figure 1 The diagram illustrates a PLC-based control method for a bottom-discharge centrifuge according to an embodiment of the present invention. The method includes the following steps:

[0039] Step S001: Obtain the flow rate time series and concentration time series of the material at the feed valve during the feeding stage of the lower discharge centrifuge, as well as the power time series of the centrifuge's main motor, and set several control times according to preset time intervals.

[0040] It should be noted that this embodiment of the invention takes a scraper-discharged automatic centrifuge with PLC control system as an example. This embodiment of the invention adds a PID control module to the PLC control system during the feeding stage to control the drum speed of the centrifuge. This alleviates the time lag phenomenon in the PLC control system. By dynamically adjusting the proportional parameter in the PID control algorithm used in the PID control module, the response speed of the drum speed during the feeding stage is improved to the lag changes in drum speed caused by material changes at the feed valve, uneven drum load, and unstable motor power. This avoids frequent and drastic fluctuations in the drum speed during the feeding stage. The PID control module includes a data acquisition unit, a data processing unit, and a control unit. For ease of subsequent description, the scraper-discharged automatic centrifuge will be referred to as the lower discharge centrifuge.

[0041] Specifically, in order to implement the PLC-based bottom-discharge centrifuge control method proposed in this embodiment, it is first necessary to collect the flow rate time series, concentration time series, and power time series. The specific process is as follows:

[0042] First, in the data acquisition unit, during the feeding stage of the lower unloading centrifuge, the flow rate data and concentration data of the material at the feed valve of the centrifuge are collected by a flow meter and a concentration meter, respectively. The motor that controls the rotation speed of the drum is called the main motor, and the power data of the main motor is collected by a power meter.

[0043] It should be noted that in this embodiment of the invention, the sampling frequency of the flow meter, concentration meter and power meter are all set to 10Hz. They can be set according to the actual situation. All collected flow data, concentration data and power data are transmitted to the data processing unit.

[0044] Then, linear normalization is used to normalize the flow rate data, concentration data, and power data to obtain the flow rate time series, concentration time series, and power time series.

[0045] As an optional embodiment, the method for obtaining the flow rate time series, concentration time series, and power time series includes: in the data processing unit, this embodiment of the invention uses any control moment in the PID control module. Taking the first control moment as an example (excluding the first control moment), in the PID control module of this embodiment of the invention, the time interval between two adjacent control moments is preset, and the data at each control moment is obtained from the database of the data acquisition unit. and its previous control time ( All flow rate, concentration, and power data collected within the specified time period are normalized using the Min-Max normalization method to reduce the influence of data dimensions. All data points in each normalized data set are then sorted in ascending order according to their corresponding sampling times to obtain flow rate, concentration, and power time series. When normalizing the power data, the rated power value of the main motor of the lower unloading centrifuge is included in the power data normalization process.

[0046] Additionally, it should be noted that the aforementioned control timing... and its previous control time ( The time period in question is the time range between any control moment and the previous control moment mentioned later in the embodiments of the present invention.

[0047] Finally, according to the preset time interval, samples are taken at equal intervals in the time series to obtain several moments as the control moments of the PLC control system.

[0048] It should be noted that, in this embodiment of the invention, the time interval between control moments is preset to 2 seconds based on experience. The time interval can be set by the implementer and is not specifically limited in this embodiment of the invention.

[0049] It should be noted that the Min-Max normalization method is a well-known technique, and the specific process will not be described in detail here.

[0050] Thus, the flow rate time series, concentration time series, and power time series were obtained through the above methods.

[0051] Step S002: By combining the correlation and average trend of the flow time series and concentration time series within the time range corresponding to any control time and the previous control time, the first characteristic value of the control time is obtained.

[0052] It should be noted that during the feeding process of the bottom-discharge centrifuge, when the flow rate and concentration at the centrifuge's feed valve exhibit the same trend of change, such as increasing simultaneously, the amount of material entering the drum in a short period will increase. This material, under the action of centrifugal force, is thrown towards the filter side, increasing the material accumulation on that side and consequently increasing the load on the drum on that side. Conversely, the opposite is also true. Changes in the drum load typically lead to changes in the drum motor torque, resulting in fluctuations in motor speed, which in turn cause subsequent fluctuations in drum speed. Furthermore, the greater the magnitude of the change in flow rate and concentration at the feed valve exhibiting the same trend, the greater the subsequent fluctuation in drum speed. Therefore, when the PLC control system of the bottom-discharge centrifuge controls the drum speed during its feeding phase, to improve the response speed of the drum speed to the lag changes in drum speed caused by the uneven drum load due to material changes at the centrifuge's feed valve, the following processing is performed: Figure 2 The flowchart shown is for the first eigenvalue analysis method at the control time.

[0053] Specifically, in this embodiment of the invention, the step of obtaining the first feature value at the control time includes:

[0054] Step S201: Use the time series decomposition algorithm to obtain the trend components of the flow time series and concentration time series within the time range corresponding to any control time and the previous control time. Based on the correlation between the trend components, obtain the trend change characteristic values ​​between the flow time series and the concentration time series.

[0055] It should be noted that the preset time interval is the time interval between adjacent control moments.

[0056] As an optional embodiment, the method for obtaining the trend change feature value is as follows: In the data processing unit, the trend components of the flow time series and concentration time series within the time range corresponding to any control time and the previous control time are extracted using the STL time series decomposition algorithm, and are denoted as the first trend component and the second trend component. The Pearson correlation coefficient between the first trend component and the second trend component is denoted as the trend change feature value. If the result of the Pearson correlation coefficient is less than 0, the trend change feature value is assigned to 0.

[0057] It should be noted that by extracting trend components, the influence of noise components introduced into the flow and concentration time series on subsequent evaluation of whether the flow and concentration time series have the same trend and on the evaluation of their respective magnitude of change is reduced. In addition, in this embodiment of the invention, the STL (Seasonal and Trend decomposition using Loess) time series decomposition algorithm is a well-known technology, and the specific process will not be described in detail.

[0058] It should be further noted that the trend change characteristic value is used to assess whether the flow rate and concentration at the feed valve of the lower discharge centrifuge have the same trend of change within the time period of control time t and the previous control time. The larger the trend change characteristic value, the more similar the flow rate and concentration are. In addition, if the result of the Pearson correlation coefficient is not greater than 0, the trend change characteristic value is assigned to 0, which is used to characterize that the flow rate and concentration do not have the same trend of change. The calculation of the Pearson correlation coefficient is a well-known technique, and the specific process will not be described in detail. The trend change characteristic value is between 0 and 1.

[0059] Step S202: Perform linear fitting on the trend components of the flow time series and concentration time series respectively. Combine the mean slope of the linear fitting results and the trend change characteristic value to obtain the first characteristic value of the control time. The mean slope and the trend change characteristic value are both positively correlated with the first characteristic value.

[0060] As a preferred embodiment, the specific method for obtaining the first feature value includes:

[0061] The first and second trend components are fitted with straight lines using the least squares method, resulting in a first fitted line and a second fitted line. The mean slope of the first and second fitted lines is used as the input to the sigmoid function, and the range of the mean value is mapped to... Within the range, the product between the output of the sigmoid function and the trend change characteristic value is recorded as the first characteristic value at the control time.

[0062] It should be noted that the first characteristic value is used to evaluate the magnitude of change when the flow rate and concentration at the feed valve of the lower discharge centrifuge show the same trend of change within the time period of control time t and the previous control time. The larger the first characteristic value, the larger the magnitude of change, and the larger the proportional parameter of the PID control algorithm used in the subsequent PID control module should be, so as to improve the response speed of the centrifuge drum to the lag change of the drum speed caused by the uneven drum load due to the material change at the centrifuge feed valve. In this embodiment of the invention, the linear fitting algorithm is a linear fitting algorithm based on the least squares method, which is a well-known technology and the specific process will not be described in detail. The trend characteristic value is between 0 and 1.

[0063] Thus, the first characteristic value of the control time is obtained through the above method.

[0064] Step S003: Utilize the periodic fluctuation characteristics of the power time series within the time range corresponding to any control time and the previous control time to obtain the second characteristic value of the control time; combine the first characteristic value and the second characteristic value to obtain the proportional parameter value at the control time.

[0065] It should be noted that during the feeding process of the bottom-discharge centrifuge, the power of the centrifuge's main motor (the motor controlling the drum speed) directly affects the drum speed. The higher the main motor power, the higher the drum speed, and vice versa. The main motor power varies due to changes in the motor load and power supply voltage and current. Therefore, fluctuations in motor power can easily cause fluctuations in the subsequent drum speed. Thus, when the PLC control system of the bottom-discharge centrifuge controls the drum speed during the feeding stage, to improve the response speed to the lag in drum speed changes caused by the instability of the centrifuge drum motor power, the following processing is performed: Figure 3 The diagram shows the flowchart of the proportional parameter value analysis method at the control time.

[0066] Specifically, the steps for obtaining the proportional parameter value at the control moment in this embodiment of the invention include:

[0067] Step S301: Use the time series decomposition algorithm to obtain the seasonal component of the power time series within the time range corresponding to any control time and the previous control time. Based on the mean absolute value of all data points in the seasonal component, obtain the second feature value of the control time.

[0068] As an optional embodiment, the method for obtaining the second feature value at the control moment is as follows:

[0069] The seasonal component of the power time series is extracted using the STL time series decomposition algorithm. The mean of the absolute values ​​of all data points in the seasonal component is calculated, and this mean is used as the input to the sigmoid function, mapping the range of the mean to... Within the range, the output of the sigmoid function is recorded as the second characteristic value of the control time.

[0070] It should be noted that the seasonal component of the power time series obtained in the embodiments of the present invention is used to characterize the local data fluctuation of each data point in the power time series, and to reduce the impact of the noise components introduced in the power time series and their own data change trends on the subsequent evaluation of the overall data fluctuation of the power time series; in addition, the mean of the absolute values ​​of all data points in the seasonal component is used to characterize the overall data fluctuation of the power time series.

[0071] It should be further explained that the second characteristic value is used to evaluate the overall data fluctuation of the power of the main motor of the lower unloading centrifuge during the time period between control time t and the previous control time. The larger the second characteristic value, the greater the fluctuation, and the larger the proportional parameter of the PID control algorithm used in the subsequent PID control module should be, so as to improve the response speed of the centrifuge drum to the lag change in drum speed caused by the instability of the centrifuge drum motor. The STL time series decomposition algorithm is a known technology, and the specific process will not be described in detail. The value of the second characteristic value is between 0 and 1.

[0072] Step S302: Preset the upper and lower limits of the proportional parameter, and calculate the proportional parameter value at the control time by combining the first and second characteristic values ​​with the upper and lower limits of the proportional parameter.

[0073] As a preferred embodiment, the method for obtaining the proportional parameter value is as follows: obtain the numerical range formed by the upper and lower limits of the preset proportional parameter, and record it as the proportional parameter range value; obtain the average of the first feature value and the second feature value, and record it as the adjustment coefficient; round down the product of the adjustment coefficient and the proportional parameter range value to obtain the compensation value; and add the lower limit of the proportional parameter to the compensation value as the proportional parameter value at the control time.

[0074] As an optional embodiment, the specific calculation method for the proportional parameter value w(t) is as follows:

[0075]

[0076] In the formula, Indicates control time The following proportional parameter value; Indicates control time Adjustment factor below; , These represent the upper and lower limits of the preset proportional parameters, respectively. This is a rounding function.

[0077] It should be noted that, in this embodiment of the invention, the upper and lower limits of the preset proportional parameters are the upper and lower limits of the proportional parameters in the PID control algorithm used in the subsequent PID control module. Furthermore, the upper limit... and lower limit Based on empirical methods, the preset values ​​are 1 and 0.2.

[0078] Thus, the proportional parameter value at control time t is obtained using the above method.

[0079] Step S004: Control the speed of the main motor of the lower unloading centrifuge at the corresponding control time using the proportional parameter value.

[0080] Specifically, the centrifuge drum speed signal during the feeding stage of the lower discharge centrifuge and the set value of the drum speed are used as inputs to the PID control algorithm in the PLC control system, and the control time is... The corresponding proportional parameter value is used as the control time of the PID control algorithm. The value of the proportional parameter within the time period of the next control moment is used as the output signal of the PID control algorithm to control the speed of the drum in the PLC control system. The control signal is converted into a current signal by a D / A converter, and the inverter maps the current signal into a corresponding frequency to control the speed of the main motor of the centrifuge, thereby realizing the control of the drum speed of the centrifuge.

[0081] By following the above steps, the control of the lower discharge centrifuge can be completed.

[0082] In another embodiment of the present invention, a PLC-based bottom discharge centrifuge control system is also provided. The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements steps S001 to S004 of the PLC-based bottom discharge centrifuge control method.

[0083] By combining the correlation between flow rate time series and concentration time series, as well as their average trends, a better understanding of material variation patterns can be achieved. Simultaneously, utilizing the periodic fluctuation characteristics of the power time series to extract a second feature value helps in real-time monitoring of the main motor's load. By acquiring proportional parameter values ​​in real time and adjusting the main motor speed accordingly, dynamic and real-time regulation can be achieved, ensuring the centrifuge maintains optimal operating conditions under various operating conditions. This further improves system stability and reliability. This solution combines multi-dimensional data on flow rate, concentration, and power, using a computational model to extract feature values ​​at control moments, achieving automated intelligent control. This reduces human intervention, lowers operational risks, and enhances the intelligence level of the production process. Precise speed control ensures the main motor provides appropriate power as needed, effectively reducing unnecessary energy waste, optimizing motor power utilization efficiency, and significantly improving the control effect of the main motor in the lower-discharge centrifuge, thereby improving the filtration effect of the material.

[0084] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A PLC-based control method for a bottom-discharge centrifuge, characterized in that, The method includes the following steps: The flow rate time series and concentration time series of the material at the feed valve during the feeding stage of the lower discharge centrifuge, as well as the power time series of the centrifuge's main motor, are obtained, and several control times are set according to preset time intervals. The first characteristic value of the control time is obtained by combining the correlation and average trend of the flow time series and concentration time series within the time range corresponding to any control time and the previous control time. By utilizing the periodic fluctuation characteristics of the power time series within the time range corresponding to any control moment and the previous control moment, a second characteristic value for the control moment is obtained; by combining the first characteristic value and the second characteristic value, the proportional parameter value at the control moment is obtained. The speed of the main motor of the lower unloading centrifuge is controlled by the proportional parameter value at the corresponding control time. The method for obtaining the first characteristic value of the control time by combining the correlation and average trend of the flow time series and concentration time series within the time range corresponding to any control time and the previous control time includes the following specific methods: The trend components of the flow rate time series and concentration time series within the time range corresponding to any control time and the previous control time are obtained by using the time series decomposition algorithm. Based on the correlation between the trend components, the trend change characteristic values ​​between the flow rate time series and the concentration time series are obtained. Linear fitting is performed on the trend components of the flow time series and concentration time series respectively. The first characteristic value of the control time is obtained by combining the mean slope of the linear fitting results and the trend change characteristic value. The mean slope and the trend change characteristic value are both positively correlated with the first characteristic value. The method for obtaining a second characteristic value for a control moment by utilizing the periodic fluctuation characteristics of the power time series within the time range corresponding to any control moment and the previous control moment, and combining the first and second characteristic values ​​to obtain the proportional parameter value at the control moment, includes the following specific methods: The seasonal component of the power time series within the time range corresponding to any control time and the previous control time is obtained by using the time series decomposition algorithm. The second feature value of the control time is obtained based on the mean of the absolute values ​​of all data points in the seasonal component. The upper and lower limits of the preset proportional parameters are used to calculate the proportional parameter value at the control time by combining the first and second eigenvalues ​​with the upper and lower limits of the proportional parameters.

2. The PLC-based control method for a bottom-discharge centrifuge according to claim 1, characterized in that, The specific method for obtaining the trend change characteristic value is as follows: The STL time series decomposition algorithm is used to extract the trend components of the flow rate time series and concentration time series within the time range corresponding to any control time and the previous control time, respectively, which are denoted as the first trend component and the second trend component. The Pearson correlation coefficient between the first trend component and the second trend component is denoted as the trend change characteristic value. If the result of the Pearson correlation coefficient is less than 0, the trend change characteristic value is assigned to 0.

3. The PLC-based control method for a bottom-discharge centrifuge according to claim 2, characterized in that, The specific method for obtaining the first feature value is as follows: The first and second trend components are fitted with straight lines using the least squares method, resulting in a first fitted line and a second fitted line. The mean slope of the first and second fitted lines is used as the input to the sigmoid function, and the range of the mean value is mapped to... Within the range, the product between the output of the sigmoid function and the trend change characteristic value is recorded as the first characteristic value at the control time.

4. The PLC-based control method for a bottom-discharge centrifuge according to claim 1, characterized in that, The specific method for obtaining the second characteristic value at the control moment is as follows: The STL time series decomposition algorithm is used to extract the seasonal component of the power time series within the time range corresponding to any control time and the previous control time. The mean of the absolute values ​​of all data points in the seasonal component is calculated, and the mean is used as the input to the sigmoid function, so that the range of the mean is mapped to... Within the range, the output of the sigmoid function is recorded as the second characteristic value of the control time.

5. The PLC-based control method for a bottom-discharge centrifuge according to claim 1, characterized in that, The specific method for obtaining the proportional parameter value at the control moment is as follows: Obtain the numerical range formed by the upper and lower limits of the preset ratio parameter, and record it as the ratio parameter range value; obtain the mean of the first feature value and the second feature value, and record it as the adjustment coefficient; The product of the adjustment coefficient and the range value of the proportional parameter is rounded to obtain the compensation value. The lower limit of the proportional parameter is added to the compensation value to obtain the proportional parameter value at the control time.

6. The PLC-based control method for a bottom-discharge centrifuge according to claim 1, characterized in that, The method for controlling the speed of the main motor of the lower unloading centrifuge at the corresponding control time using a proportional parameter value includes the following specific methods: The centrifuge drum speed signal during the feeding stage of the lower discharge centrifuge and the set value of the drum speed are used as inputs to the PID control algorithm in the PLC control system, and the control time is... The corresponding proportional parameter value is used as the control time of the PID control algorithm. The value of the proportional parameter within the time period of the next control moment is used as the output signal of the PID control algorithm to control the speed of the drum by the PLC control system. The control signal is converted into a current signal by a D / A converter, and the inverter maps the current signal into a corresponding frequency to control the speed of the main motor of the centrifuge.

7. The PLC-based control method for a bottom-discharge centrifuge according to claim 1, characterized in that, The specific method for obtaining the flow rate time series and concentration time series of the material at the feed valve during the feeding stage of the lower discharge centrifuge, as well as the power time series of the centrifuge's main motor, includes: During the feeding stage of the lower discharge centrifuge, flow rate data and concentration data of the material at the feed valve of the centrifuge are collected using a flow meter and a concentration meter, respectively. The motor that controls the rotation speed of the drum is called the main motor. The power data of the main motor is collected using a power meter. The flow rate data, concentration data and power data are normalized using linear normalization to obtain the flow rate time series, concentration time series and power time series.

8. A PLC-based bottom-discharge centrifuge control system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the PLC-based bottom unloading centrifuge control method as described in any one of claims 1 to 7.

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