Liftable aeration device and sewage treatment system

Abstract

The invention relates to the technical field of sewage treatment, in particular to a liftable aeration device and a sewage treatment system.The system comprises a data acquisition module for acquiring dissolved oxygen concentration, gas flow and air pressure at multiple moments before each moment in the sewage treatment process and recording the dissolved oxygen concentration, the gas flow and the air pressure as historical data sets of each moment; the feature analysis module is used for determining the gas supply stability at each moment; determining a first trend degree, a second trend degree, a first collaborative factor and a second collaborative factor of each fluctuation moment in the historical data set of each moment; determining a relative collaboration degree and a forward feedback index at each moment; the aeration control module is used for determining a proportionality coefficient and an integral parameter of a PID controller at each moment; and in combination with a PID (Proportion Integration Differentiation) controller, obtaining a gas flow control value at each moment, and controlling the concentration of the dissolved oxygen in the sewage. The gas flow can be more accurately adjusted, the control accuracy of the concentration of dissolved oxygen in sewage is improved, and the sewage treatment efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of sewage treatment, and in particular to a liftable aeration device and a sewage treatment system. Background Art

[0002] The liftable aeration device is a key technology in the sewage treatment system. It injects air into the sewage to increase the dissolved oxygen content in the water, promote the growth of microorganisms, and accelerate the decomposition of organic matter. With the acceleration of industrialization and urbanization, the amount of sewage discharge has increased sharply. Traditional sewage treatment methods can no longer meet environmental protection requirements. Early aeration devices were mostly fixed, which had problems such as inconvenient maintenance and low efficiency. The liftable aeration device can adjust the height adaptively according to needs to adapt to different water depths. The promotion and use of this device has improved sewage treatment efficiency and reduced energy consumption.

[0003] In aerated sewage treatment devices, uneven gas supply is a common problem in the sewage treatment process. Uneven gas supply will cause the dissolved oxygen concentration in some areas of the aeration tank to be too high, while the dissolved oxygen in other areas is insufficient, resulting in low efficiency of microbial decomposition of organic matter in sewage. In addition, uneven gas supply may also cause sludge swelling and floating. In areas where the gas supply is too large, the sludge may become loose due to excessive stirring, lose its sedimentation performance, and form sludge swelling; while in areas where the gas supply is insufficient, the sludge may produce gas due to anaerobic conditions, causing the sludge to float. This reduces the efficiency of the entire sewage treatment system and may even cause the system to collapse. Summary of the invention

[0004] In order to solve the above technical problems, a liftable aeration device and a sewage treatment system are provided to solve the existing problems.

[0005] The solution to the technical problem of the present application is to provide a liftable aeration device and a sewage treatment system, comprising the following steps: In a first aspect, an embodiment of the present application provides a liftable aerated sewage treatment system, the system comprising: The data acquisition module is used to obtain the dissolved oxygen concentration, gas flow rate, and air pressure at multiple moments before each moment in the sewage treatment process, and record them as historical data sets at each moment; The feature analysis module is used to obtain the positive feedback index at each moment, including: (1) Determine the gas supply stability at each moment based on the correlation between the gas flow rate and the gas pressure in the historical data set at each moment, and the trend degree of the change between the gas flow rate and the gas pressure; (2) Analyze the fluctuation of dissolved oxygen concentration at all times in the historical data set to obtain each fluctuation time; determine the first trend degree and the second trend degree of each fluctuation time in the historical data set at each time according to the change trend of air pressure and gas flow in the local time period of each fluctuation time; analyze the consistency of the change trend of air pressure and gas flow at each fluctuation time with the change of dissolved oxygen concentration, and determine the first synergy factor and the second synergy factor of each fluctuation time in the historical data set at each time in combination with the first trend degree and the second trend degree; determine the relative synergy degree at each time based on the first synergy factor and the second synergy factor; determine the positive feedback index at each time in combination with the gas supply stability; Aeration control module, used to control the dissolved oxygen concentration in sewage, including: Based on the gas supply stability and the positive feedback index, the proportional coefficient and integral parameter of the PID controller at each moment are determined respectively; in combination with the PID controller, the gas flow control value at each moment is obtained to control the dissolved oxygen concentration in the sewage.

[0006] Preferably, the determining of the gas supply stability at each moment includes: Calculate the correlation between gas flow and gas pressure at all times in the historical data set; The gas flow and the gas pressure at each moment in the historical data set at each moment are combined into a two-dimensional array; a linear fit is performed on the two-dimensional array at all moments in the historical data set at each moment, the slope of the fitting line is obtained, and the mean square error of the fitting line is calculated; The ratio of the slope to the mean square error is calculated, and the product of the correlation degree and the ratio is used as the gas supply stability at each moment.

[0007] Preferably, obtaining each fluctuation moment includes: The maximum and minimum values ​​of dissolved oxygen concentration at all times in the historical data set at each time are obtained; and the time corresponding to the maximum and the minimum is recorded as the fluctuation time.

[0008] Preferably, the determining of the first trend degree and the second trend degree of each fluctuation moment in the historical data set at each moment includes: The gas flow and pressure at each fluctuation moment in the historical data set and multiple moments in its neighborhood are respectively formed into a local flow vector and a local pressure vector; The slopes of the fitted lines obtained by linearly fitting the local flow vector and the local air pressure vector are respectively used as the first trend degree and the second trend degree of each fluctuation moment in the historical data set at each moment.

[0009] Preferably, the determining of the first synergy factor and the second synergy factor of each fluctuation moment in the historical data set at each moment includes: If each fluctuation moment corresponds to a maximum value, the label value of each fluctuation moment is assigned to -1; if each fluctuation moment corresponds to a minimum value, the label value of each fluctuation moment is assigned to 1; The product of the first trend degree and the second trend degree at each fluctuation moment and the label value at the corresponding fluctuation moment are respectively used as the first discrimination value and the second discrimination value at each fluctuation moment; If the first discriminant value is less than 0, the first synergy factor corresponding to the fluctuation moment is assigned a value of 0; otherwise, the first synergy factor corresponding to the fluctuation moment is the first discriminant value; For the second discriminant value, the same method as the first synergy factor is adopted to determine the second synergy factor of each fluctuation moment in the historical data set at each moment.

[0010] Preferably, the relative synergy degree at each moment is the sum of the mean of the first synergy factor at all fluctuation moments in the historical data set and the mean of the second synergy factor at all fluctuation moments.

[0011] Preferably, the positive feedback index at each moment is the product of the gas supply stability and the relative coordination degree.

[0012] Preferably, the proportional coefficient of the PID controller at each moment is determined by the calculation formula: ,in, For the The proportional coefficient of the PID controller at time t, For the Gas supply stability at all times, To preset the initial scale factor, is an exponential function with a natural constant as its base.

[0013] Preferably, the calculation formula of the integral parameter is: ,in, For the The integral coefficient of the PID controller at time , For the The positive feedback index of the moment, To preset the initial integral coefficient, is an exponential function with a natural constant as its base.

[0014] In a second aspect, an embodiment of the present application further provides a liftable aeration device, wherein sewage treatment of the device is implemented by using any of the liftable aeration sewage treatment systems described above.

[0015] This application has at least the following beneficial effects: The present application determines the gas supply stability at each moment according to the correlation between the gas flow and the air pressure in the historical data set at each moment, and the trend degree of the change between the gas flow and the air pressure. The beneficial effect is that the changing relationship between the air pressure and the gas flow is taken into account to reflect the stability of the gas transport to the aeration tank and the uniformity of the gas supply, so as to facilitate the subsequent correction of the PID control parameters to reduce the error; the fluctuation of the dissolved oxygen concentration at all moments in the historical data set is analyzed to obtain each fluctuation moment; according to the changing trend of the air pressure and the gas flow in the local time period of each fluctuation moment, the first trend degree and the second trend degree of each fluctuation moment in the historical data set are respectively determined, and the beneficial effect is that the changing trend of the air pressure and the gas flow is taken into account when the dissolved oxygen concentration changes; the consistency of the changing trend of the air pressure and the gas flow at each fluctuation moment and the change of the dissolved oxygen concentration is analyzed, and the first trend degree and the second trend degree are combined to obtain the first trend degree and the second trend degree of each fluctuation moment in the historical data set. The first synergy factor and the first synergy factor of each fluctuation moment in the historical data set at each moment are determined respectively; based on the second synergy factor and the second synergy factor, the relative synergy degree at each moment is determined; in combination with the gas supply stability, the positive feedback index at each moment is determined, which has the beneficial effect of considering the synergy between the fluctuation of the dissolved oxygen concentration and the changes in the air pressure and the gas flow rate, reflecting the situation that the aeration device makes positive feedback when the dissolved oxygen concentration fluctuates, and determining the proportional coefficient and integral parameter of the PID controller at each moment based on the gas supply stability and the positive feedback index; in combination with the PID controller, the gas flow control value at each moment is obtained to control the dissolved oxygen concentration in the sewage, which has the beneficial effect of adjusting the parameters of the PID controller in real time, so that the gas flow rate can be adjusted more accurately, the control accuracy of the dissolved oxygen concentration in the sewage can be improved, and the sewage treatment efficiency can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The following is a further detailed description of a liftable aerated sewage treatment system of the present application in conjunction with the accompanying drawings.

[0017] Figure 1 A block diagram of a liftable aerated sewage treatment system provided in an embodiment of the present application; Figure 2 A schematic diagram of linear fitting of gas flow and pressure in a historical data set provided in an embodiment of the present application; Figure 3 A flowchart of the steps of a method for obtaining the gas supply stability at each moment provided in an embodiment of the present application; Figure 4 A schematic diagram of the extreme values ​​of dissolved oxygen concentration at all times in the historical data set provided in an embodiment of the present application; Figure 5A flowchart of the steps of a method for obtaining the relative degree of coordination at each moment provided in an embodiment of the present application; Figure 6 A flow chart of the steps of the process of controlling dissolved oxygen concentration in sewage provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the following is a further detailed description of a liftable aeration device and a sewage treatment system proposed in the present application in combination with the accompanying drawings and implementation examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0019] Unless defined otherwise, 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 application belongs.

[0020] See also Figure 1 , which shows a step flow chart of a liftable aerated sewage treatment system provided by an embodiment of the present application, the system includes: a data acquisition module, a feature analysis module, and an aeration control module.

[0021] The data acquisition module is used to obtain the dissolved oxygen concentration, gas flow rate, and air pressure at multiple moments before each moment in the sewage treatment process, and record them as historical data sets at each moment.

[0022] The aeration device is one of the core equipment in the aerobic tank section of sewage treatment. It controls the concentration of dissolved oxygen (DO) in the aeration tank, allowing aerobic microorganisms to efficiently decompose organic matter in sewage to achieve the purpose of water purification. In the aeration tank treatment stage, the activated sludge method is generally used for sewage treatment. The aerobic microorganisms in the activated sludge require a large amount of dissolved oxygen for aerobic respiration to maintain growth and reproduction activities. The microorganisms achieve the purpose of purifying the water body by decomposing organic matter in sewage. Therefore, it is necessary to accurately control the DO concentration in the aeration tank.

[0023] In the sewage treatment process of the sewage plant, the sewage enters the primary sedimentation tank and the aeration tank in turn after pretreatment. Among them, there is an aeration device at the bottom of the aeration tank. Through the aeration device, the air delivered by the blower is integrated into the sewage in the form of small bubbles, increasing the oxygen content in the sewage, and the dissolved oxygen concentration increases, so that organic pollutants and activated sludge are fully in contact with oxygen. After secondary sedimentation, the sewage becomes clear, and the initial purification is completed.

[0024] Based on the above analysis, in order to accurately control the DO concentration in the aeration tank, the dissolved oxygen in the aeration tank, the air volume and air pressure in the aeration pipeline are monitored in real time, so that the air supply to the aeration tank is in a uniform state, so that microorganisms can carry out decomposition activities, specifically: The dissolved oxygen concentration in the aeration tank is monitored in real time by extending an online dissolved oxygen analyzer into the aeration tank to reflect the metabolic state of the microorganisms in the aeration tank and the effectiveness of the oxygen supply; the flow meter and pressure sensor are installed in the aeration pipeline connected to the blower to collect the gas flow and pressure transported in the aeration pipeline to monitor the gas supply to the sewage; the collection frequency is f, and all the collected data are normalized to obtain the dissolved oxygen concentration, gas flow, and air pressure at each moment.

[0025] Preferably, in this embodiment, the acquisition frequency is 20 Hz. As other implementations, the implementer can set it according to the actual situation. Secondly, the maximum and minimum value normalization method is used for normalization. As other implementations, the implementer can adopt other methods of the prior art, such as Z-score normalization method, etc. This embodiment does not impose any special restrictions on this.

[0026] The dissolved oxygen concentration, gas flow rate, and air pressure at multiple moments before each moment are recorded as a historical data set at each moment; Preferably, in this embodiment, the dissolved oxygen concentration, gas flow rate, and air pressure at all times within 1 minute before each moment are recorded as a historical data set for each moment. As other implementation methods, the implementer can set them according to actual conditions.

[0027] At this point, the dissolved oxygen concentration, gas flow rate, and air pressure at multiple moments before each moment are obtained.

[0028] The feature analysis module is used to obtain the positive feedback index at each moment.

[0029] Step 1: Determine the gas supply stability at each moment according to the correlation between the gas flow and the gas pressure in the historical data set at each moment, and the trend degree of the change between the gas flow and the gas pressure.

[0030] During sewage treatment, if the air pressure in the aeration pipeline increases, based on the ideal gas state equation: , then the air pressure and volume are inversely proportional. The gas volume in the aeration pipe decreases, which means that the gas flow rate will also increase, which means that more air (or oxygen) is injected into the water, and more oxygen molecules are transferred to the water, which will cause an increase in the dissolved oxygen concentration. The increase in dissolved oxygen concentration can provide a better oxygen supply to microorganisms, thereby promoting their metabolism.

[0031] If the increase in dissolved oxygen concentration leads to an increase in the metabolic rate of microorganisms, the demand for oxygen will further increase, thus requiring a higher air pressure to increase the gas flow, thereby increasing the dissolved oxygen concentration, causing a positive feedback effect. On the contrary, if the dissolved oxygen concentration is too high, it will inhibit the metabolic rate of certain microorganisms, resulting in a decrease in oxygen demand. It is necessary to reduce the air pressure in the aeration pipeline and reduce the gas flow, thereby reducing the dissolved oxygen concentration and causing a negative feedback effect.

[0032] Based on the above analysis, the air pressure in the aeration pipeline reflects the flow resistance and distribution of the gas in the pipeline, and is a key factor affecting the gas flow. Therefore, the changes in the gas flow and air pressure are analyzed to reflect the stability and uniformity of the gas supply to the aeration tank and determine the gas supply stability, specifically: Calculating the correlation between the gas flow and the gas pressure at all times in the historical data set; Preferably, in this embodiment, the Pearson correlation coefficient between the gas flow rate and the air pressure at all times in the historical data set is calculated, wherein the calculation of the Pearson correlation coefficient is a well-known technology and will not be repeated here. As other implementation methods, the implementer can adopt other methods of the prior art, such as the Spearman correlation coefficient, cosine similarity, etc., and this embodiment does not impose any special restrictions on this.

[0033] The gas flow and pressure at each moment in the historical data set at each moment are combined into a two-dimensional array; Performing linear fitting on the two-dimensional arrays at all times in the historical data set at each time, obtaining the slope of the fitting line, and calculating the mean square error of the fitting line; Preferably, in this embodiment, the least square method is used for linear fitting, wherein the least square method and the calculation of the mean square error are well-known techniques and will not be described in detail herein.

[0034] Furthermore, the linear fitting diagram of gas flow and pressure in the historical data set provided in the embodiment of the present application is as follows: Figure 2 As shown, the horizontal axis is the normalized gas flow rate and the vertical axis is the normalized gas pressure.

[0035] The ratio of the slope to the mean square error is calculated, and the product of the correlation degree and the ratio is used as the gas supply stability at each moment.

[0036] Preferably, in this embodiment, the calculation formula for the gas supply stability at each moment is: ,in, For the Gas supply stability at all times, For the the degree of relevance of the moment, For the The slope at time, For the The mean square error at time.

[0037] It should be noted that the degree of correlation reflects the degree of linear change between air pressure and gas flow. The greater the degree of correlation, the more significant the correlation between the changes in air pressure and gas flow, and the more stable the gas supply to the aeration tank. The slope reflects the degree of influence of air pressure changes on gas flow. The greater the slope, the increase in pipe air pressure will lead to a significant increase in gas flow. The mean square error reflects the accuracy of the relationship between the change in air pressure and gas flow expressed by the slope. The greater the mean square error, the lower the accuracy of the slope in reflecting the change between air pressure and gas flow. The greater the obtained gas supply stability, the more it means that the change in air pressure can effectively and stably affect the gas flow, thereby ensuring the uniformity and efficiency of the aeration process.

[0038] Further, the step flow chart of the method for obtaining the gas supply stability at each moment provided in the embodiment of the present application is as follows: Figure 3 shown.

[0039] At this point, the gas supply stability at each moment is obtained.

[0040] Step 2, analyze the fluctuation of dissolved oxygen concentration at all times in the historical data set to obtain each fluctuation moment; determine the first trend degree and the second trend degree of each fluctuation moment in the historical data set at each moment according to the changing trends of air pressure and gas flow in the local time period of each fluctuation moment; analyze the consistency of the changing trends of air pressure and gas flow at each fluctuation moment with the change of dissolved oxygen concentration, and determine the first synergy factor and the second synergy factor of each fluctuation moment in the historical data set at each moment in combination with the first trend degree and the second trend degree; determine the relative synergy degree of each moment based on the first synergy factor and the second synergy factor; determine the positive feedback index at each moment in combination with the gas supply stability.

[0041] Furthermore, dissolved oxygen concentration can reflect the supply of oxygen in sewage. Even if the stability of gas supply is guaranteed, the dissolved oxygen concentration may still fluctuate due to imbalanced microbial metabolism, affecting the efficiency and stability of sewage treatment. Therefore, the fluctuation of dissolved oxygen concentration is analyzed and the fluctuation time is determined, specifically: Obtain the maximum and minimum values ​​of dissolved oxygen concentration at all times in the historical data set at each moment; Preferably, in this embodiment, the derivative method is used to obtain the maximum and minimum values, wherein the derivative method is a well-known technology and will not be described in detail here.

[0042] Further, the schematic diagram of the extreme values ​​of dissolved oxygen concentration at all times in the historical data set provided in the embodiment of the present application is as follows: Figure 4As shown, the horizontal axis is time, the vertical axis is the normalized dissolved oxygen concentration, and the small circles in the figure represent extreme values.

[0043] The time when the maximum value and the minimum value correspond to each other is recorded as the fluctuation time; If any fluctuation moment in the historical data set corresponds to a maximum value, the label value of any fluctuation moment is -1; if any fluctuation moment corresponds to a minimum value, the label value of any fluctuation moment is 1; The gas flow and pressure at each fluctuation moment in the historical data set and multiple moments in its neighborhood are arranged in the order of acquisition time to form a local flow vector and a local pressure vector at each fluctuation moment in the historical data set; Preferably, in this embodiment, the gas flow and pressure at each fluctuation moment and 13 moments in its neighborhood in the historical data set are selected as other implementation modes, and the implementer can set them according to the actual situation; it should be noted that if there is a local flow vector or a local pressure vector with a length less than 13, the mean filling method is used to fill it completely. As other implementation modes, the implementer can adopt other methods of the prior art, such as linear interpolation methods, etc., and this embodiment does not impose any special restrictions on this.

[0044] Performing linear fitting on the local flow vector, obtaining the slope of the fitted straight line, and recording it as the first trend degree of each fluctuation moment in the historical data set; Performing a linear fit on the local air pressure vector, and recording the slope of the fitted straight line as the second trend degree at each fluctuation moment in the historical data set; It should be noted that the maximum and minimum values ​​reflect the significant changes in microbial activity. By analyzing the local changes in gas flow and air pressure at the corresponding time when the microbial activity changes, that is, when the dissolved oxygen concentration fluctuates, the control feedback of the controller when the dissolved oxygen concentration changes can be reflected.

[0045] Further, based on the label value, the first trend degree and the second trend degree, the relative coordination degree of each fluctuation moment is determined, specifically: The product of the first trend degree at each fluctuation moment in the historical data set and the label value at the corresponding fluctuation moment is used as the first discrimination value at each fluctuation moment in the historical data set; If the first discriminant value is less than 0, the first synergy factor at the fluctuation moment is assigned a value of 0; if the first discriminant value is greater than or equal to 0, the first synergy factor at the fluctuation moment is the first discriminant value; Preferably, in this embodiment, the second synergy factor of each fluctuation moment in the historical data set at each moment is calculated as follows: ,in, For the The historical data set at time The second synergy factor of the fluctuation moment, For the The historical data set at time The label value of the fluctuation moment, For the The historical data set at time The second trend degree at each fluctuation moment.

[0046] The product of the second trend degree at each fluctuation moment in the historical data set and the label value at the corresponding fluctuation moment is used as the second discrimination value at each fluctuation moment in the historical data set; If the second discriminant value is less than 0, the second synergy factor corresponding to the fluctuation moment is assigned a value of 0; if the second discriminant value is greater than or equal to 0, the second synergy factor corresponding to the fluctuation moment is the second discriminant value; The sum of the mean of the first synergy factor at all fluctuation moments in the historical data set at each moment and the mean of the second synergy factor at all fluctuation moments is taken as the relative synergy degree at each moment; It should be noted that if the first discrimination value is greater than or equal to 0, it indicates that there are two situations, namely, when the dissolved oxygen concentration is at a minimum value, the gas flow rate shows an upward trend in the local time period near the fluctuation moment, or when the dissolved oxygen concentration is at a maximum value, the gas flow rate shows a downward trend in the local time period near the fluctuation moment. Correspondingly, if the second discrimination value is greater than or equal to 0, it also indicates that there are two situations, namely, when the dissolved oxygen concentration is at a minimum value, the air pressure shows an upward trend in the local time period near the fluctuation moment, or when the dissolved oxygen concentration is at a maximum value, the air pressure shows a downward trend in the local time period near the fluctuation moment, reflecting that the aeration device makes positive feedback when the dissolved oxygen concentration changes.

[0047] Furthermore, the step flow chart of the method for obtaining the relative coordination degree at each moment provided in the embodiment of the present application is as follows: Figure 5 shown.

[0048] Further, based on the air supply stability and the relative coordination degree, a positive feedback index is determined to reflect the accurate control of the aeration device by the control system, specifically: The product of the gas supply stability and the relative coordination degree is used as the positive feedback index at each moment; It should be noted that the greater the gas supply stability, the better the uniformity and stability of the gas supply process. The positive feedback index reflects the consistency between the fluctuation of gas supply and the change of dissolved oxygen concentration in the sewage treatment process. The larger the positive feedback index, the more consistent the change direction of gas flow and pipeline pressure with that of dissolved oxygen concentration at the moment when the dissolved oxygen concentration changes significantly, indicating that the stability of gas supply and the accuracy of feedback control of PID (proportional-integral-derivative control) controller are.

[0049] At this point, the positive feedback index at each moment is obtained.

[0050] The aeration control module is used to control the dissolved oxygen concentration in the sewage, including: based on the gas supply stability and the positive feedback index, respectively determining the proportional coefficient and integral parameter of the PID controller at each moment; combining with the PID controller, obtaining the gas flow control value at each moment to control the dissolved oxygen concentration in the sewage.

[0051] Furthermore, in the sewage treatment process, the PID (proportion integration differentiation) controller adjusts the air supply of the aeration device to maintain the stability of the dissolved oxygen concentration through the combination of three links: proportional parameter, integral parameter and differential parameter. Able to respond immediately to dissolved oxygen concentration deviations and output a control signal proportional to the deviation to reduce the deviation, integral parameter The deviation is accumulated and a control signal proportional to the accumulated deviation is generated, which helps to eliminate the steady-state error. The differential parameter The rate of change of the deviation is predicted and a control signal proportional to the rate of change of the deviation is output, thereby reducing overshoot and oscillation.

[0052] Based on the above analysis, since the gas supply stability reflects the strength of the linear relationship between the gas pressure change and the gas flow change, when the stability and uniformity of the gas supply are poor, that is, when the gas supply stability is small, the proportional parameter should be increased to enhance the response speed and regulation ability of the system to reduce the deviation; secondly, since the fluctuation of dissolved oxygen concentration may affect the sewage treatment efficiency, the smaller the positive feedback index, the greater the integral parameter should be increased to eliminate steady-state errors.

[0053] Therefore, based on the gas supply stability and the positive feedback index, the parameters in the PID (proportion integration differentiation) controller are adjusted, specifically: The calculation formula of the proportional coefficient of the PID controller at each moment is: ,in, For the The proportional coefficient of the PID controller at time t, For the Gas supply stability at all times, is a preset initial proportionality coefficient. In this embodiment, the preset initial proportionality coefficient is The value is 2. As other implementation methods, implementers can set it according to actual conditions; is an exponential function with a natural constant as its base.

[0054] The calculation formula of the integral parameter of the PID controller at each moment is: ,in, For the The integral coefficient of the PID controller at time , For the The positive feedback index of the moment, To preset the initial integral coefficient, in this embodiment, the initial integral coefficient is preset The value is 1.5. As other implementation methods, implementers can set it according to actual conditions; is an exponential function with a natural constant as its base.

[0055] Based on the dissolved oxygen concentration at each moment, as well as the proportional coefficient, integral coefficient and preset initial differential coefficient of the PID controller at each moment, the PID controller is used to obtain the gas flow control value at each moment; Preferably, in this embodiment, the preset value of the initial differential coefficient is 1. As other implementation modes, the implementer can set it according to the actual situation. It should be noted that the control process of the PID controller is a well-known technology and will not be described in detail here.

[0056] The PID controller adjusts the opening of the electric regulating valve in the aeration pipeline connected to the blower according to the gas flow control value, adjusts it to the required gas flow control value, controls the aeration volume, and maintains the required dissolved oxygen concentration, thereby controlling the dissolved oxygen concentration in the sewage.

[0057] Further, the step flow chart of the process of controlling dissolved oxygen concentration in sewage provided in the embodiment of the present application is as follows: Figure 6 shown.

[0058] Based on the same inventive concept as the above method, an embodiment of the present application further provides a liftable aeration device, and sewage treatment of the device is achieved by using any of the liftable aeration sewage treatment systems described above.

[0059] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0060] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0061] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the present application. It should be pointed out that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application without departing from the content of the technical solution of the present application, shall fall within the protection scope of the technical solution of the present application.

Claims

1. A liftable aerated sewage treatment system, characterized in that: The system comprises: The data acquisition module is used to obtain the dissolved oxygen concentration, gas flow rate, and air pressure at multiple moments before each moment in the sewage treatment process, and record them as historical data sets at each moment; The feature analysis module is used to obtain the positive feedback index at each moment, including: (1) Determine the gas supply stability at each moment based on the correlation between the gas flow rate and the gas pressure in the historical data set at each moment, and the trend degree of the change between the gas flow rate and the gas pressure; (2) Analyze the fluctuation of dissolved oxygen concentration at all times in the historical data set to obtain each fluctuation time; determine the first trend degree and the second trend degree of each fluctuation time in the historical data set at each time according to the change trend of air pressure and gas flow in the local time period of each fluctuation time; analyze the consistency of the change trend of air pressure and gas flow at each fluctuation time with the change of dissolved oxygen concentration, and determine the first synergy factor and the second synergy factor of each fluctuation time in the historical data set at each time in combination with the first trend degree and the second trend degree; determine the relative synergy degree at each time based on the first synergy factor and the second synergy factor; determine the positive feedback index at each time in combination with the gas supply stability; Aeration control module, used to control the dissolved oxygen concentration in sewage, including: Based on the gas supply stability and the positive feedback index, the proportional coefficient and integral parameter of the PID controller at each moment are determined respectively; in combination with the PID controller, the gas flow control value at each moment is obtained to control the dissolved oxygen concentration in the sewage.

2. A liftable aerated sewage treatment system as claimed in claim 1, characterized in that: Determining the gas supply stability at each moment includes: Calculate the correlation between gas flow and gas pressure at all times in the historical data set; The gas flow and the gas pressure at each moment in the historical data set at each moment are combined into a two-dimensional array; a linear fit is performed on the two-dimensional array at all moments in the historical data set at each moment, the slope of the fitting line is obtained, and the mean square error of the fitting line is calculated; The ratio of the slope to the mean square error is calculated, and the product of the correlation degree and the ratio is used as the gas supply stability at each moment.

3. A liftable aerated sewage treatment system as claimed in claim 1, characterized in that: The obtaining of each fluctuation moment comprises: The maximum and minimum values ​​of dissolved oxygen concentration at all times in the historical data set at each time are obtained; and the time corresponding to the maximum and the minimum is recorded as the fluctuation time.

4. A liftable aerated sewage treatment system as claimed in claim 1, characterized in that: The step of determining the first trend degree and the second trend degree of each fluctuation moment in the historical data set at each moment includes: The gas flow and pressure at each fluctuation moment in the historical data set and multiple moments in its neighborhood are respectively formed into a local flow vector and a local pressure vector; The slopes of the fitted lines obtained by linearly fitting the local flow vector and the local air pressure vector are respectively used as the first trend degree and the second trend degree of each fluctuation moment in the historical data set at each moment.

5. A liftable aerated sewage treatment system as claimed in claim 3, characterized in that: The step of determining the first synergy factor and the second synergy factor of each fluctuation moment in the historical data set at each moment includes: If each fluctuation moment corresponds to a maximum value, the label value of each fluctuation moment is assigned to -1; if each fluctuation moment corresponds to a minimum value, the label value of each fluctuation moment is assigned to 1; The product of the first trend degree and the second trend degree at each fluctuation moment and the label value at the corresponding fluctuation moment are respectively used as the first discrimination value and the second discrimination value at each fluctuation moment; If the first discriminant value is less than 0, the first synergy factor corresponding to the fluctuation moment is assigned a value of 0; otherwise, the first synergy factor corresponding to the fluctuation moment is the first discriminant value; For the second discriminant value, the same method as the first synergy factor is adopted to determine the second synergy factor of each fluctuation moment in the historical data set at each moment.

6. A liftable aerated sewage treatment system as claimed in claim 1, characterized in that: The relative synergy degree at each moment is the sum of the mean value of the first synergy factor at all fluctuation moments in the historical data set and the mean value of the second synergy factor at all fluctuation moments.

7. The liftable aerated sewage treatment system according to claim 1, characterized in that: The positive feedback index at each moment is the product of the gas supply stability and the relative coordination degree.

8. The liftable aerated sewage treatment system according to claim 1, characterized in that: The proportional coefficient of the PID controller at each moment is determined by the following calculation formula: ,in, For the The proportional coefficient of the PID controller at time t, For the Gas supply stability at all times, To preset the initial scale factor, is an exponential function with a natural constant as its base.

9. The liftable aerated sewage treatment system according to claim 1, characterized in that: The calculation formula of the integral parameter is: ,in, For the The integral coefficient of the PID controller at time , For the The positive feedback index of the moment, To preset the initial integral coefficient, is an exponential function with a natural constant as its base.

10. A liftable aeration device, characterized in that: The sewage treatment process of the device is implemented by using a liftable aerated sewage treatment system as described in any one of claims 1-9.

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