Integrated sewage separation device and intelligent control method thereof

Abstract

The invention relates to the technical field of sewage flow rate control, in particular to an integrated sewage separation device and an intelligent control method thereof. Setting a plurality of flow velocities and acquiring time sequence data of sewage oxygen content, biological membrane thickness and ion concentration at each flow velocity; the method comprises the following steps: constructing an element contrast ratio through dynamic synchronism of oxygen content and ion concentration on the basis of anaerobic and aerobic microorganism characteristics in a biological membrane, quantifying implicit association of water quality parameters, and preliminarily screening out a preliminary ideal flow velocity matched with the current water quality; further, considering biological membrane thickness change and oxygen content change caused by impact difference of different flow rates on a biological membrane attached water layer, analyzing the numerical value difference of the oxygen content and the biological membrane thickness at each initial ideal flow rate, and then fusing element contrast to quantify a biological membrane damage degree value; and finally, integrating the thickness of the biological membrane and the damage degree value of the biological membrane at each initial ideal flow rate, and determining an ideal sewage flow rate for controlling the sewage flow rate of the sewage separation device.

Description

Technical Field

[0001] This invention relates to the field of wastewater flow rate control technology, specifically to an integrated wastewater separation device and its intelligent control method. Background Technology

[0002] An integrated wastewater separation device refers to a device that integrates multiple units and steps in the wastewater treatment process (equalization tank, anaerobic tank, reaction tank, etc.) into one device. It is used to remove pollutants such as organic matter, nitrogen, and phosphorus from wastewater, thereby achieving a highly efficient and compact treatment method. Furthermore, when selecting technical means to treat wastewater, the biofilm method is widely used because it has the advantages of lower maintenance costs and convenient management compared to other technical means.

[0003] When performing integrated wastewater separation and treatment, it is often necessary to find a suitable wastewater flow rate to enable a more efficient reaction between the wastewater and the biofilm surface, thereby improving wastewater treatment efficiency. When wastewater flows over the biofilm surface, the oxygen content that aerobic and anaerobic microorganisms beneath the biofilm can effectively access differs. Current technologies typically determine the ideal wastewater flow rate by detecting the oxygen content in the wastewater. However, in actual reaction processes, the biofilm surface is at risk of damage under the impact of wastewater, affecting the activity of microorganisms beneath the biofilm. Therefore, determining the ideal wastewater flow rate solely based on the oxygen content of the wastewater will reduce the degree of wastewater purification and may even cause a precipitous drop in wastewater treatment efficiency. Summary of the Invention

[0004] To address the risk of biofilm surface damage during actual reaction processes due to the impact of wastewater, which could affect the activity of microorganisms beneath the biofilm, and the fact that determining the ideal wastewater flow rate solely based on the oxygen content of the wastewater would reduce the degree of wastewater purification and even cause a precipitous drop in wastewater treatment efficiency, this invention aims to provide an integrated wastewater separation device and its intelligent control method. The specific technical solution adopted is as follows: An intelligent control method for an integrated wastewater separation device includes: At each wastewater flow rate, time-series data on wastewater oxygen content, biofilm thickness, and ion concentration were acquired. At each wastewater flow rate, the elemental contrast was determined based on the synchronization of data changes between wastewater oxygen content and ion concentration; and the preliminary ideal flow rate was screened among all wastewater flow rates based on the elemental contrast. At each preliminary ideal flow rate, the numerical variation characteristics of wastewater oxygen content were analyzed and integrated with the numerical fluctuation characteristics of biofilm thickness to determine the initial biofilm damage degree. The initial biofilm damage degree was adjusted using elemental contrast to obtain the biofilm damage degree value at each preliminary ideal flow rate. At each preliminary ideal flow rate, the ideal wastewater flow rate is determined based on the numerical characteristics of the biofilm thickness and the degree of biofilm damage, thereby controlling the wastewater flow rate of the wastewater separation device.

[0005] Furthermore, the method for obtaining the element contrast includes: At each wastewater flow rate, the normalized Pearson correlation coefficient between the time series data of wastewater oxygen content and the time series data of ion concentration was used as the elemental change correlation value corresponding to each wastewater flow rate. At each wastewater flow rate, the similarity between the fluctuation characteristics of wastewater oxygen content and ion concentration was analyzed to determine the elemental change synchronization value corresponding to each wastewater flow rate. At each wastewater flow rate, the product of the element change correlation value and the element change synchronization value is negatively correlated and normalized, and this value is used as the element contrast at each wastewater flow rate.

[0006] Furthermore, the method for obtaining the element change synchronization value includes: At each wastewater flow rate, the normalized standard deviation of wastewater oxygen content at all times in the wastewater oxygen content time series data is used as the wastewater oxygen content change factor. Similarly, the normalized standard deviation of ion concentration at all times in the ion concentration time series data is used as the ion concentration change factor. The absolute value of the difference between the wastewater oxygen content change factor and the ion concentration change factor is negatively correlated and mapped to the element change synchronization value corresponding to each wastewater flow rate.

[0007] Furthermore, the method for obtaining the initial biofilm damage level includes: Under each preliminary ideal flow rate, the numerical variation characteristics of oxygen content in wastewater were analyzed, and the oxygen content gradation factor corresponding to each preliminary ideal flow rate was determined. The value of the wastewater oxygen content change factor corresponding to each preliminary ideal flow velocity after negative correlation mapping is multiplied by the oxygen content gradual change factor to obtain the wastewater oxygen content anomaly degree under each preliminary ideal flow velocity. At each initial ideal flow rate, the normalized standard deviation of the biofilm thickness at all times in the biofilm thickness time series data is used as the biofilm thickness change value. The normalized value of the product of the wastewater oxygen anomaly and the biofilm thickness change corresponding to each preliminary ideal flow rate is used as the initial biofilm damage degree under each preliminary ideal flow rate.

[0008] Furthermore, the method for obtaining the oxygen content gradation factor includes: At each initial ideal flow rate, the time series data of wastewater oxygen content are curve-fitted based on the least squares method to obtain the wastewater oxygen content curve. The curvature value at each data point on the wastewater oxygen content curve is obtained. The mean value of the curvature values ​​at all data points on the wastewater oxygen content curve is negatively correlated and normalized, and used as the oxygen content gradient factor corresponding to each initial ideal flow rate.

[0009] Furthermore, the method for obtaining the degree of biofilm damage includes: At each initial ideal flow rate, the normalized value of the product of elemental contrast and initial biofilm damage degree is used as the biofilm damage degree value at each initial ideal flow rate.

[0010] Furthermore, the method for obtaining the ideal sewage flow velocity includes: At each initial ideal flow rate, in the biofilm thickness time series data, the absolute value of the difference between the biofilm thickness at each time point and the preset standard thickness is used as the thickness deviation factor, and the normalized value of the mean of the thickness deviation factor at all times is used as the activity interference degree value. At each preliminary ideal flow rate, the product of the degree of activity disturbance and the degree of biofilm damage is negatively correlated and normalized, and the result is used as the biofilm water purification intensity at each preliminary ideal flow rate. Under all preliminary ideal flow rates, the preliminary ideal flow rate corresponding to the maximum biofilm water purification intensity is taken as the ideal wastewater flow rate.

[0011] Furthermore, controlling the wastewater flow rate of the wastewater separation device includes: The ideal sewage flow rate is taken as the target flow rate of the sewage separation device, and the difference between the target flow rate and the current flow rate of the sewage separation device is taken as the flow rate error value. The wastewater flow rate of the wastewater separation device is controlled by PID based on preset PID control parameters and the flow rate error value.

[0012] Furthermore, the method for obtaining the preliminary ideal flow velocity includes: At all wastewater flow rates, the wastewater flow rate with an element contrast less than a preset contrast threshold is taken as the initial ideal flow rate.

[0013] An integrated wastewater separation device includes a wastewater separation device body and a control module. The control module includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. When the processor loads and executes the at least one instruction, at least one program, code set, or instruction set, it implements the steps of an intelligent control method for the integrated wastewater separation device.

[0014] The present invention has the following beneficial effects: To screen for the ideal wastewater flow rate, multiple wastewater flow rates can be set, and time-series data on wastewater oxygen content, biofilm thickness, and ion concentration can be acquired for each flow rate. This overcomes the limitations of traditional single-parameter monitoring and enables real-time, multi-dimensional sensing of water quality changes and biofilm status. Anaerobic microorganisms in the biofilm mainly absorb nitrogen and phosphorus ions from the wastewater, while aerobic microorganisms mainly absorb oxygen and organic matter. Therefore, elemental contrast can be constructed based on the dynamic synchronicity of oxygen content and ion concentration at each flow rate to quantify the implicit correlation between water quality parameters and initially screen for the ideal flow rate that matches the current water quality. Furthermore, different wastewater flow velocities exert varying impacts on the attached water layer on the biofilm surface, leading to differences in microbial detachment and biofilm thickness variations. This, in turn, alters the oxygen content within the wastewater. Therefore, at each preliminary ideal flow velocity, the differences between the oxygen content variation and biofilm thickness are analyzed to establish an initial biofilm damage model. Next, at each preliminary ideal flow velocity, the initial biofilm damage level is adjusted using the hidden correlations (elemental contrast) of corresponding water quality parameters in the wastewater, obtaining biofilm damage values ​​at each preliminary ideal flow velocity, thus achieving a quantitative assessment of biofilm health. Finally, at each preliminary ideal flow velocity, the ideal wastewater flow velocity is determined by combining the numerical characteristics of biofilm thickness and the biofilm damage value. This ideal wastewater flow velocity not only analyzes the variation characteristics of wastewater oxygen content but also considers the changes in the biofilm during treatment. Therefore, when subsequently controlling the wastewater flow velocity of the wastewater separation device based on the ideal wastewater flow velocity, a better balance between wastewater treatment efficiency and biofilm health can be achieved, ensuring the degree of wastewater purification. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages 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.

[0016] Figure 1 A flowchart illustrating an intelligent control method for an integrated wastewater separation device according to an embodiment of the present invention; Figure 2 A flowchart illustrating a method for obtaining element contrast according to an embodiment of the present invention; Figure 3 A flowchart illustrating a method for obtaining the initial biofilm damage level according to an embodiment of the present invention; Figure 4This is a schematic diagram of the structure of a control module provided in one embodiment of the present invention. Detailed Implementation

[0017] 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 an integrated wastewater separation device and its intelligent control method 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.

[0018] 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.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the integrated wastewater separation device and its intelligent control method provided by the present invention.

[0020] Please see Figure 1 The diagram illustrates a method flowchart of an intelligent control method for an integrated wastewater separation device according to an embodiment of the present invention. The method includes the following steps: Step S1: At each wastewater flow rate, acquire time-series data on wastewater oxygen content, biofilm thickness, and ion concentration.

[0021] An integrated wastewater separation device refers to a device that integrates multiple units and steps in the wastewater treatment process (equalization tank, anaerobic tank, reaction tank, etc.) into one device to remove pollutants such as organic matter, nitrogen, and phosphorus from wastewater, thereby achieving a highly efficient and compact treatment method.

[0022] Integrated wastewater separation systems typically include: a screen to trap large suspended solids such as fibers, slag, and waste paper, preventing blockages in downstream pipes; an equalization tank for initial sedimentation and separation, regulating wastewater quality and quantity, and may be equipped with valves to control flow rate; an anaerobic tank to decompose high-molecular-weight organic matter into easily decomposable smaller organic molecules, increasing the B / C ratio (B / C ratio is the ratio of biochemical oxygen demand (BOD) to chemical oxygen demand (COD); a higher B / C ratio indicates better biological treatability of the wastewater); and an MBR (membrane bioreactor) reactor to decompose small-molecular-weight organic matter into harmless components through a biofilm formed by aerobic and anaerobic microorganisms and an attached water layer. The system removes pollutants such as nitrogen and phosphorus. Dissolved oxygen membrane electrode sensors and electrochemical ion sensors are installed 0.5 meters downstream of the inlet, avoiding stagnant water areas to ensure uniform water flow over the sensor membranes. The sensor probes are submerged 20-30 cm below the liquid surface to avoid surface foam interference. These sensors are used to capture time-series data on wastewater oxygen content and ion concentration (nitrogen ions are selected in this embodiment). A laser displacement sensor is horizontally installed on the surface of the biofilm carrier, with multiple monitoring points set up. The average value is used as the biofilm thickness to obtain time-series data on biofilm thickness. The sludge tank stores sludge produced in the MBR (membrane bioreactor). The clear water tank stores purified water after disinfection.

[0023] In this embodiment of the invention, multiple sewage flow rates are set. Specifically, the sewage flow rate can start from 50 ml / s, with a step size of 10, and gradually increase until it reaches 100 ml / s. This can be adjusted according to the implementation scenario and is not limited here. Furthermore, at each sewage flow rate, time-series data of sewage oxygen content, biofilm thickness, and ion concentration are acquired based on the aforementioned multiple sensors.

[0024] It should be noted that in this embodiment of the invention, multiple time-series data at each sewage flow rate need to be collected synchronously to ensure time synchronization. The collection frequency is set to once per second, and the length of the time-series data is set to 5 minutes. The collection frequency and the length of the time-series data can be adjusted according to the implementation scenario and are not limited here.

[0025] Step S2: At each wastewater flow rate, determine the elemental contrast based on the synchronization of data changes between wastewater oxygen content and ion concentration; and screen the preliminary ideal flow rate among all wastewater flow rates based on the elemental contrast.

[0026] Anaerobic microorganisms in biofilms mainly absorb nitrogen and phosphorus ions from wastewater. Nitrogen ions are relatively easy to detect, so this invention focuses on nitrogen ions and analyzes the impact of anaerobic microorganisms on ion concentration during wastewater treatment by examining changes in nitrogen ion concentration. Meanwhile, aerobic microorganisms in biofilms mainly absorb oxygen and organic matter from wastewater. Oxygen content is relatively easy to detect, so this invention analyzes the impact of aerobic microorganisms on ion concentration during wastewater treatment by examining changes in oxygen concentration. By analyzing the synchronization of data changes between the two, elemental contrast is determined to reflect the coupling state between microbial metabolism and pollutant degradation, indirectly indicating the efficiency of wastewater treatment. Based on this characteristic, a preliminary ideal flow rate can be selected from all wastewater flow rates.

[0027] Preferably, in one embodiment of the present invention, the method for obtaining element contrast includes: Please see Figure 2 The diagram illustrates a method flowchart for obtaining element contrast in one embodiment of the present invention, which includes the following steps: Step S201: At each wastewater flow rate, analyze the correlation between changes in wastewater oxygen content and ion concentration, and determine the elemental change correlation value corresponding to each wastewater flow rate.

[0028] At each wastewater flow rate, the Pearson correlation coefficient between the time-series data of wastewater oxygen content and ion concentration was calculated. A Pearson correlation coefficient closer to 1 indicates a stronger positive correlation between the two, meaning that at that flow rate, the aerobic and anaerobic microorganisms consume elements from the wastewater more similarly as it passes through the biofilm, indicating a more balanced metabolic reaction. Therefore, the normalized Pearson correlation coefficient was used as the elemental variation correlation value for each wastewater flow rate. Based on the aforementioned logic, a larger elemental variation correlation value indicates a more balanced elemental balance in the wastewater treatment process at that flow rate. Since the Pearson correlation coefficient can be positive or negative, the normalization here can be performed using... function.

[0029] Step S202: At each wastewater flow rate, analyze the similarity between the fluctuation characteristics of wastewater oxygen content and the fluctuation characteristics of ion concentration, thereby determining the elemental change synchronization value corresponding to each wastewater flow rate.

[0030] Furthermore, at each wastewater flow rate, the similarity between the overall change in wastewater oxygen content and the overall change in ion concentration can be compared to assess the degree of matching between the two in the dynamic process from a macroscopic perspective.

[0031] At each wastewater flow rate, the normalized standard deviation of wastewater oxygen content at all times in the time-series data is used as the wastewater oxygen content variation factor. Similarly, the normalized standard deviation of ion concentration at all times in the time-series data is used as the ion concentration variation factor. Normalization is a technique well-known to those skilled in the art, and the normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0032] The smaller the difference between the overall variation range of oxygen content and ion concentration in wastewater, the more consistent their macroscopic variation characteristics are, reflecting a good coupling between microbial metabolism and pollutant degradation. Therefore, the absolute value of the difference between the oxygen content variation factor and the ion concentration variation factor is calculated. The smaller the absolute value of the difference, the more consistent their macroscopic variation characteristics are. The negative correlation mapping of this absolute value is then used as the elemental variation synchronization value for each wastewater flow rate. Based on the previous analysis, a larger elemental variation synchronization value indicates a more balanced elemental composition and higher efficiency in the wastewater treatment process at that flow rate. This negative correlation mapping can be achieved using the formula... or ,in, Let x represent an exponential function with base e, where x represents the independent variable. This represents a preset constant, used to prevent the denominator from being 0, and can take a value of 0.001.

[0033] Step S203: At each sewage flow rate, the corresponding element change correlation value and element change synchronization value are fused to obtain the element contrast at each sewage flow rate.

[0034] Based on the analysis in steps S201 and S202, it is known that at each wastewater flow rate, both the correlation value and the synchronization value of elemental changes are positively correlated with the degree of balance of elemental contrast in the wastewater treatment process at that flow rate. Therefore, the product of the correlation value and the synchronization value of elemental changes was calculated. The larger the product, the more balanced the elemental contrast, indicating better normal operation of the biofilm and better wastewater treatment effect. Therefore, this product was negatively correlated and normalized to obtain the elemental contrast at each wastewater flow rate. The larger the elemental contrast, the worse the coupling between microbial metabolism and pollutant degradation at that flow rate, and the lower the likelihood that this flow rate will be selected as the preliminary ideal flow rate. The negative correlation mapping and normalization here can be performed using the formula... ,in, Let x represent an exponential function with the natural constant e as the base, and let x represent the independent variable.

[0035] Based on the aforementioned process, the elemental contrast corresponding to each wastewater flow rate can be calculated, and then the preliminary ideal flow rate can be screened based on this index.

[0036] Preferably, in one embodiment of the present invention, the method for obtaining the preliminary ideal flow rate includes: Given that a higher elemental contrast leads to a poorer coupling between microbial metabolism and pollutant degradation, resulting in a worse wastewater treatment effect, the wastewater flow rate with an elemental contrast less than a preset contrast threshold is used as the initial ideal flow rate for all wastewater flow rates.

[0037] It should be noted that in this embodiment of the present invention, the preset comparison threshold is set to 0.55. The specific value can be adjusted according to the implementation scenario and is not limited here.

[0038] Step S3: Under each preliminary ideal flow rate, analyze the numerical variation characteristics of oxygen content in wastewater and integrate them with the numerical fluctuation characteristics of biofilm thickness to determine the initial biofilm damage degree; adjust the initial biofilm damage degree using elemental contrast to obtain the biofilm damage degree value under each preliminary ideal flow rate.

[0039] Different wastewater flow velocities have different impacts on the attached water layer on the biofilm surface. The higher the wastewater flow velocity, the more likely the attached water layer is to break down, allowing aerobic microorganisms to more effectively contact the flowing water surface and making it easier for microorganisms to detach, resulting in changes in biofilm thickness and reducing oxygen consumption in the wastewater. Therefore, the initial biofilm damage degree under each preliminary ideal flow velocity can be determined based on the numerical variation characteristics of wastewater oxygen content and the more obvious numerical differences in biofilm thickness.

[0040] Preferably, in one embodiment of the present invention, the method for obtaining the initial biofilm damage level includes: Please see Figure 3 The diagram illustrates a method flowchart for obtaining the initial biofilm damage level in one embodiment of the present invention, which includes the following steps: Step S301: Under each preliminary ideal flow rate, analyze the numerical variation characteristics of oxygen content in wastewater and determine the oxygen content gradient factor corresponding to each preliminary ideal flow rate.

[0041] When wastewater begins to flow into the integrated wastewater separation device, the flowing wastewater preferentially contacts aerobic microorganisms through the attached water layer, initiating metabolic treatment. Ideally, when wastewater first comes into contact with the biofilm, oxygen is absorbed by the aerobic microorganisms through the biofilm, consuming the dissolved oxygen in the wastewater. However, the metabolic reaction of microorganisms within the biofilm does not increase indefinitely and is subject to certain limitations. Therefore, the oxygen content in the wastewater will reach metabolic saturation within a certain time range. During this process, the oxygen content in the wastewater should exhibit a curve-like decrease, and the oxygen content should show relatively obvious differences within a certain period of time.

[0042] This sub-step focuses on analyzing the characteristics of the curve-like decrease in oxygen content: curvature can quantify the "degree of bending" of oxygen content changes. The greater the curvature, the more obvious the bending; conversely, the smaller the curvature, the less obvious the bending. Therefore, at each preliminary ideal flow rate, the time-series data of wastewater oxygen content are curve-fitted using the least squares method (the function model can be either polynomial or exponential, which is not limited here) to obtain the wastewater oxygen content curve. The curvature value at each data point on the wastewater oxygen content curve is then obtained. The mean of the curvature values ​​at all data points on the wastewater oxygen content curve is then calculated. The smaller this mean, the more gradual the overall average change in wastewater oxygen content over a period of time, which is less consistent with the ideal characteristics of wastewater oxygen content changes. In this case, the greater the possibility of biofilm damage. Therefore, this mean is negatively correlated and normalized here to correct the logical relationship and obtain the oxygen content gradient factor corresponding to each preliminary ideal flow rate. Based on the aforementioned analysis, it can be seen that the larger the oxygen content gradient factor, the greater the possibility of biofilm damage at that preliminary ideal flow rate. The negative correlation mapping and normalization here can be performed using the formula ,in, Let x represent an exponential function with the natural constant e as the base, and let x represent the independent variable.

[0043] It should be noted that the least squares method for curve fitting is a well-known technique, and the specific process will not be elaborated here.

[0044] Step S302: At each preliminary ideal flow rate, the wastewater oxygen content change factor and the oxygen content gradual change factor are combined to obtain the wastewater oxygen content anomaly at each preliminary ideal flow rate.

[0045] Based on the logic in step S301, when the biofilm is more ideal and the damage is lower, not only should the oxygen content in the wastewater exhibit a curve-like decrease, but there should also be significant differences in oxygen content over a period of time. The wastewater oxygen content change factor calculated in step S2 reflects the range of oxygen content change over a period of time; the larger the value, the greater the range of change and the more obvious the differences. Therefore, the wastewater oxygen content change factor is negatively correlated and, after logical relationship correction, multiplied by the oxygen content gradual change factor to obtain the wastewater oxygen anomaly degree at each preliminary ideal flow rate. Analysis shows that the larger the wastewater oxygen content anomaly degree, the greater the deviation between the oxygen content change and the ideal situation at that preliminary ideal flow rate, and the greater the possibility of biofilm damage. Since the wastewater oxygen content change factor ranges from 0 to 1, the negative correlation mapping here can be performed using the formula... , where x represents the independent variable.

[0046] Step S303: Under each preliminary ideal flow rate, analyze the numerical fluctuation characteristics of biofilm thickness and determine the change value of biofilm thickness.

[0047] The variation characteristics of biofilm thickness over time can more intuitively reflect the damage status of the biofilm. Therefore, at each initial ideal flow rate, the normalized value of the standard deviation of the biofilm thickness at all time points in the biofilm thickness time series data is used as the biofilm thickness variation value. The larger the biofilm thickness variation value, the more severe the damage. Normalization is a technique well-known to those skilled in the art, and the choice of normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0048] Step S304: At each preliminary ideal flow rate, combine the wastewater oxygen anomaly with the biofilm thickness change value to obtain the initial biofilm damage degree at each preliminary ideal flow rate.

[0049] Based on the analysis in step S302, it is known that at each preliminary ideal flow rate, the greater the anomaly in wastewater oxygen content, the greater the likelihood of biofilm damage. Based on the analysis in step S303, it is known that the greater the change in biofilm thickness, the more severe the biofilm damage. Therefore, both the anomaly in wastewater oxygen content and the change in biofilm thickness are positively correlated with the initial biofilm damage degree. Thus, the normalized product of the anomaly in wastewater oxygen content and the change in biofilm thickness corresponding to each preliminary ideal flow rate is used as the initial biofilm damage degree at each preliminary ideal flow rate. The greater the initial biofilm damage degree, the greater the likelihood of biofilm detachment at that preliminary ideal flow rate, and the less compatible that preliminary ideal flow rate is with the current wastewater treatment status. Normalization is a technique well-known to those skilled in the art. The normalization function can be linear normalization or standard normalization, etc., and the specific normalization method is not limited here.

[0050] In the wastewater treatment process, if the biofilm is intact, the content of various elements in the wastewater should be in a dynamic equilibrium under normal circumstances. Conversely, if the biofilm is damaged, the content of various elements in the wastewater will be unbalanced. The element contrast calculated in step S2 can be used to characterize the degree of balance of element contrast in the wastewater treatment process. Therefore, at each initial ideal flow rate, the initial biofilm damage degree can be adjusted using the element contrast to obtain the biofilm damage degree value at each initial ideal flow rate.

[0051] Preferably, in one embodiment of the present invention, the method for obtaining the degree of biofilm damage includes: Based on the logic in step S2, a higher elemental contrast indicates a weaker coupling between microbial metabolism and pollutant degradation at the initial ideal flow rate, resulting in a more unbalanced elemental contrast and a greater likelihood of biofilm damage. Therefore, at each initial ideal flow rate, the elemental contrast is multiplied by the initial biofilm damage level, and the normalized product is used as the biofilm damage level value at each initial ideal flow rate. A higher biofilm damage level value indicates more severe biofilm damage, and thus a significant decrease in the biofilm's water purification capacity at that initial ideal flow rate. Normalization is a well-known technique in the field, and the normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0052] Step S4: At each preliminary ideal flow rate, the ideal wastewater flow rate is determined based on the numerical characteristics of the biofilm thickness and the degree of biofilm damage, thereby controlling the wastewater flow rate of the wastewater separation device.

[0053] While biofilms treat wastewater, their thickness also affects the activity of aerobic and anaerobic microorganisms beneath their surface, thus influencing the overall activity of microorganisms within the biofilm. Therefore, at each preliminary ideal flow rate, the numerical characteristics of biofilm thickness and the degree of biofilm damage can be combined to screen out the ideal wastewater flow rate from all preliminary ideal flow rates.

[0054] Preferably, in one embodiment of the present invention, the method for obtaining the ideal sewage flow velocity includes: When wastewater flows through a biofilm at a certain initial ideal flow rate, the greater the biofilm thickness, the longer the channel for the exchange of substances between aerobic and anaerobic microorganisms and the external wastewater. Consequently, the metabolic reaction of the biofilm is slower, the activity of the corresponding microorganisms is lower, and the treatment capacity is worse. Conversely, the smaller the biofilm thickness, the less microorganisms are attached to the carrier. Insufficient quantity will lead to a decrease in the ability to degrade pollutants such as organic matter, nitrogen, and phosphorus in the wastewater, making it difficult for the effluent quality to meet the standards.

[0055] Therefore, at each preliminary ideal flow rate, the absolute value of the difference between the biofilm thickness and the preset standard thickness at each time point is calculated in the biofilm thickness time-series data, and this value is used as the thickness deviation factor. Based on the aforementioned analysis, it is known that the biofilm thickness deviation factor is negatively correlated with the metabolic reaction rate of the biofilm at the preliminary ideal flow rate. Therefore, the mean value of the thickness deviation factor at all time points is used as the normalized value, which is used as the activity interference value. The larger the activity interference value, the lower the activity of microorganisms and the worse the wastewater treatment capacity at the preliminary ideal flow rate. Normalization is a technique well known to those skilled in the art. The normalization function can be linear normalization or standard normalization, etc., and the specific normalization method is not limited here.

[0056] It should be noted that the preset standard thickness can be set by oneself based on experiments or experience, and can be adjusted according to the implementation scenario; no limitation is made here.

[0057] Then, at each preliminary ideal flow rate, the activity interference level value is multiplied by the biofilm damage level value. The larger the product, the higher the probability of biofilm damage and the lower the microbial activity at that preliminary ideal flow rate, resulting in poorer water purification capacity. Therefore, this product is negatively correlated and normalized to correct the logical relationship, and this value serves as the biofilm water purification intensity for each preliminary ideal flow rate. The biofilm water purification intensity characterizes the water purification capacity of the biofilm at that preliminary ideal flow rate; the larger the value, the stronger the water purification capacity. This negative correlation mapping and normalization can be performed using the formula... ,in, Let x represent an exponential function with the natural constant e as the base, and let x represent the independent variable.

[0058] Finally, under all preliminary ideal flow rates, the preliminary ideal flow rate corresponding to the maximum biofilm water purification intensity is taken as the ideal wastewater flow rate.

[0059] After the ideal wastewater flow rate is determined, the current wastewater flow rate of the wastewater separation device can be controlled and adjusted based on the ideal wastewater flow rate.

[0060] Preferably, in one embodiment of the present invention, controlling the wastewater flow rate of the wastewater separation device includes: The ideal sewage flow velocity is taken as the target flow velocity of the sewage separation device, that is, the desired sewage flow velocity. The difference between the target flow velocity and the current flow velocity of the sewage separation device is taken as the flow velocity error value. The flow velocity error value is used to reflect the deviation between the current state and the desired state.

[0061] Finally, based on the preset PID control parameters and the flow rate error value, the sewage flow rate of the sewage separation device is controlled by PID, thereby achieving rapid, stable and overshoot-free adjustment of the sewage flow rate.

[0062] It should be noted that the preset PID control parameters include the proportional gain coefficient, integral gain coefficient, and derivative gain coefficient, which can be calculated using the Ziegler-Nichols rule, a technique well-known to those skilled in the art, and will not be elaborated upon here. In other embodiments of the present invention, other PID data tuning methods, such as trial and error, critical oscillation, reference model, genetic algorithm, optimization algorithm, etc., can also be used to obtain the preset PID control parameters, and will not be elaborated upon here.

[0063] In summary, to screen for the ideal wastewater flow rate, multiple wastewater flow rates can be set, and time-series data on wastewater oxygen content, biofilm thickness, and ion concentration can be obtained for each flow rate. This overcomes the limitations of traditional single-parameter monitoring and enables real-time, multi-dimensional sensing of water quality changes and biofilm status. Anaerobic microorganisms in the biofilm mainly absorb nitrogen and phosphorus ions from the wastewater, while aerobic microorganisms mainly absorb oxygen and organic matter. Therefore, elemental contrast can be constructed based on the dynamic synchronicity of oxygen content and ion concentration at each flow rate to quantify the implicit correlation between water quality parameters and initially screen for the ideal flow rate that matches the current water quality. Furthermore, different wastewater flow velocities exert varying impacts on the attached water layer on the biofilm surface, leading to differences in microbial detachment and biofilm thickness variations. This, in turn, alters the oxygen content within the wastewater. Therefore, at each preliminary ideal flow velocity, the differences between the oxygen content variation and biofilm thickness are analyzed to establish an initial biofilm damage model. Next, at each preliminary ideal flow velocity, the initial biofilm damage level is adjusted using the hidden correlations (elemental contrast) of corresponding water quality parameters in the wastewater, obtaining biofilm damage values ​​at each preliminary ideal flow velocity, thus achieving a quantitative assessment of biofilm health. Finally, at each preliminary ideal flow velocity, the ideal wastewater flow velocity is determined by combining the numerical characteristics of biofilm thickness and the biofilm damage value. This ideal wastewater flow velocity not only analyzes the variation characteristics of wastewater oxygen content but also considers the changes in the biofilm during treatment. Therefore, when subsequently controlling the wastewater flow velocity of the wastewater separation device based on the ideal wastewater flow velocity, a better balance between wastewater treatment efficiency and biofilm health can be achieved, ensuring the degree of wastewater purification.

[0064] This invention also provides an integrated wastewater separation device, including a wastewater separation device body and a control module. Please refer to [link / reference]. Figure 4 The diagram illustrates a control module according to an embodiment of the present invention, including a processor 400, a memory 401, a bus 402, and a communication interface 403. The processor 400, the communication interface 403, and the memory 401 are connected via the bus 402. The memory 401 may include a high-speed random access memory, and the bus 402 may be an ISA bus, a PCI bus, or an EISA bus, etc. The processor 400 may be an integrated circuit chip with signal processing capabilities. The memory 401 stores at least one instruction, at least one program, a code set, or an instruction set. When the processor loads and executes the at least one instruction, at least one program, a code set, or an instruction set, it implements the steps in an intelligent control method for an integrated sewage separation device.

[0065] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0066] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. An intelligent control method for an integrated wastewater separation device, characterized in that, The method includes: At each wastewater flow rate, time-series data on wastewater oxygen content, biofilm thickness, and ion concentration were acquired. At each wastewater flow rate, the elemental contrast was determined based on the synchronization of data changes between wastewater oxygen content and ion concentration; and the preliminary ideal flow rate was screened among all wastewater flow rates based on the elemental contrast. At each preliminary ideal flow rate, the numerical variation characteristics of wastewater oxygen content were analyzed and integrated with the numerical fluctuation characteristics of biofilm thickness to determine the initial biofilm damage degree. The initial biofilm damage degree was adjusted using elemental contrast to obtain the biofilm damage degree value at each preliminary ideal flow rate. At each preliminary ideal flow rate, the ideal wastewater flow rate is determined based on the numerical characteristics of the biofilm thickness and the degree of biofilm damage, thereby controlling the wastewater flow rate of the wastewater separation device.

2. The intelligent control method for an integrated wastewater separation device according to claim 1, characterized in that, The method for obtaining the element contrast includes: At each wastewater flow rate, the normalized Pearson correlation coefficient between the time series data of wastewater oxygen content and the time series data of ion concentration was used as the elemental change correlation value corresponding to each wastewater flow rate. At each wastewater flow rate, the similarity between the fluctuation characteristics of wastewater oxygen content and the fluctuation characteristics of ion concentration is analyzed to determine the synchronous value of elemental changes corresponding to each wastewater flow rate. At each wastewater flow rate, the product of the element change correlation value and the element change synchronization value is negatively correlated and normalized, and this value is used as the element contrast at each wastewater flow rate.

3. The intelligent control method for an integrated wastewater separation device according to claim 2, characterized in that, The method for obtaining the element change synchronization value includes: At each wastewater flow rate, the normalized standard deviation of wastewater oxygen content at all times in the wastewater oxygen content time series data is used as the wastewater oxygen content change factor. Similarly, the normalized standard deviation of ion concentration at all times in the ion concentration time series data is used as the ion concentration change factor. The absolute value of the difference between the wastewater oxygen content change factor and the ion concentration change factor is negatively correlated and mapped to the element change synchronization value corresponding to each wastewater flow rate.

4. The intelligent control method for an integrated wastewater separation device according to claim 2, characterized in that, The method for obtaining the initial biofilm damage level includes: Under each preliminary ideal flow rate, the numerical variation characteristics of oxygen content in wastewater were analyzed, and the oxygen content gradation factor corresponding to each preliminary ideal flow rate was determined. The value of the wastewater oxygen content change factor corresponding to each preliminary ideal flow velocity after negative correlation mapping is multiplied by the oxygen content gradual change factor to obtain the wastewater oxygen content anomaly degree under each preliminary ideal flow velocity. At each initial ideal flow rate, the normalized standard deviation of the biofilm thickness at all times in the biofilm thickness time series data is used as the biofilm thickness change value. The normalized value of the product of the wastewater oxygen anomaly and the biofilm thickness change corresponding to each preliminary ideal flow rate is used as the initial biofilm damage degree under each preliminary ideal flow rate.

5. The intelligent control method for an integrated wastewater separation device according to claim 4, characterized in that, The method for obtaining the oxygen content gradient factor includes: At each initial ideal flow rate, the time series data of wastewater oxygen content are curve-fitted based on the least squares method to obtain the wastewater oxygen content curve. The curvature value at each data point on the wastewater oxygen content curve is obtained. The mean value of the curvature values ​​at all data points on the wastewater oxygen content curve is negatively correlated and normalized, and used as the oxygen content gradient factor corresponding to each initial ideal flow rate.

6. The intelligent control method for an integrated wastewater separation device according to claim 1, characterized in that, The method for obtaining the degree of biofilm damage includes: At each initial ideal flow rate, the normalized value of the product of elemental contrast and initial biofilm damage degree is used as the biofilm damage degree value at each initial ideal flow rate.

7. The intelligent control method for an integrated wastewater separation device according to claim 1, characterized in that, The method for obtaining the ideal sewage flow velocity includes: At each initial ideal flow rate, in the biofilm thickness time series data, the absolute value of the difference between the biofilm thickness at each time point and the preset standard thickness is used as the thickness deviation factor, and the normalized value of the mean of the thickness deviation factor at all times is used as the activity interference degree value. At each preliminary ideal flow rate, the product of the degree of activity disturbance and the degree of biofilm damage is negatively correlated and normalized, and the result is used as the biofilm water purification intensity at each preliminary ideal flow rate. Under all preliminary ideal flow rates, the preliminary ideal flow rate corresponding to the maximum biofilm water purification intensity is taken as the ideal wastewater flow rate.

8. The intelligent control method for an integrated wastewater separation device according to claim 1, characterized in that, The control of the wastewater flow rate in the wastewater separation device includes: The ideal sewage flow rate is taken as the target flow rate of the sewage separation device, and the difference between the target flow rate and the current flow rate of the sewage separation device is taken as the flow rate error value. The wastewater flow rate of the wastewater separation device is controlled by PID based on preset PID control parameters and the flow rate error value.

9. The intelligent control method for an integrated wastewater separation device according to claim 1, characterized in that, The method for obtaining the preliminary ideal flow velocity includes: At all wastewater flow rates, the wastewater flow rate with an element contrast less than a preset contrast threshold is taken as the initial ideal flow rate.

10. An integrated wastewater separation device, comprising a wastewater separation device body and a control module, characterized in that, The control module includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. When the processor loads and executes the at least one instruction, at least one program, code set, or instruction set, it implements the steps of the intelligent control method for an integrated sewage separation device as described in any one of claims 1-9.

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