A MBBR suspended filler biofilm thickness monitoring and control system

Abstract

The present invention relates to the field of water treatment and discloses an MBBR suspended filler biofilm thickness monitoring and control system, which mainly consists of three modules: suspended filler biofilm thickness monitoring, early warning and control. The monitoring module comprises a suspended filler biofilm image acquisition unit that acquires biofilm images in real time through an online monitoring device; an image processing unit that processes the images to obtain biofilm thickness as monitoring data; a thickness analysis unit that further analyzes the data; an early warning module that determines whether the biofilm thickness is abnormal and issues an early warning if so; and a control module that determines whether the biofilm growth or shedding rate is normal and issues an early warning if so; and a control module that combines the monitoring data of the monitoring module and the early warning signal of the early warning module to accurately control the opening of an automatic control valve of an aeration module in the MBBR water tank, so as to maintain the biofilm thickness within an optimal range and ensure efficient and stable operation of the water treatment system.

Description

Technical Field

[0001] The present invention relates to the field of water treatment, and in particular to an MBBR suspended filler biofilm thickness monitoring and control system. Background Art

[0002] The Moving Bed Biofilm Reactor (MBBR) is a highly efficient technology for the biological treatment of wastewater and low-pollution water (e.g., polluted river water, sewage treatment plant tailwater, rainwater runoff, agricultural runoff, and similar water bodies). It primarily relies on a biofilm attached to the surface of the suspended media to degrade pollutants. Pollutants in wastewater and low-pollution water are removed through the metabolic activity of microorganisms in the biofilm.

[0003] Biofilm thickness is crucial in the pollutant degradation process of an MBBR system, and dynamic regulation is key to optimizing the MBBR process. Different treatment targets require varying biofilm thicknesses on the surface of the MBBR suspended media. For example, when treating high-concentration wastewater, a thicker biofilm is necessary to ensure sufficient biomass to degrade pollutants. However, excessively thick biofilms can expand the inner anaerobic zone, compromising treatment effectiveness. When treating less polluted water, a thin biofilm is necessary to ensure efficient mass transfer and maintain high microbial activity. To ensure that effluent meets Category IV standards in the "Surface Water Environmental Quality Standard" (GB3838-2002), precise biofilm thickness control is essential to achieve a balanced ratio of nitrifying and denitrifying bacteria, effectively removing nitrogen pollutants. Therefore, precise control of biofilm thickness is crucial for the efficient and stable operation of the MBBR process.

[0004] However, current methods for controlling the biofilm thickness of MBBR suspended media are relatively outdated and largely rely on empirical experience. Typically, aeration intensity is adjusted based on experience or historical data to alter hydraulic shear forces, or the media dosage is adjusted to change the biofilm growth space. However, these methods present numerous challenges, including delayed response, an inability to adapt promptly to water quality changes, and limited control precision, making it difficult to maintain optimal biofilm thickness. For example, excessive aeration not only prevents precise control of biofilm thickness but also significantly increases system energy consumption, resulting in energy waste. Statistics show that in MBBR systems using traditional empirical control methods, increased energy consumption due to improper aeration control accounts for approximately 20%-30% of total energy consumption. Therefore, developing a system for controlling the biofilm thickness of MBBR suspended media that integrates real-time monitoring, intelligent analysis, and precise control is crucial. This is crucial for overcoming the technical bottlenecks of traditional methods, characterized by delayed response, extensive control, and low energy efficiency, and for achieving optimized operation and energy conservation in water treatment processes. Summary of the Invention

[0005] The purpose of the present invention is to provide an MBBR suspended filler biofilm thickness monitoring and control system to solve the above technical problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A MBBR suspended filler biofilm thickness monitoring and control system, the system is configured in an MBBR tank, the system comprising:

[0008] Suspended media biofilm thickness monitoring module, including:

[0009] An image acquisition unit, which acquires a biofilm image of the suspended filler in real time based on an online monitoring device for the biofilm thickness of the suspended filler;

[0010] An image processing unit is used to process the suspended filler biofilm image acquired by the image acquisition unit to obtain the suspended filler biofilm thickness as monitoring data;

[0011] The thickness analysis unit performs further analysis based on the suspended filler biofilm thickness data obtained by the image processing unit;

[0012] The suspended filler biofilm thickness warning module is used to issue a warning signal when it is determined that the suspended filler biofilm thickness is abnormal; it also issues a warning signal based on the judgment result of whether the growth or shedding rate of the suspended filler biofilm is normal;

[0013] The suspended filler biofilm thickness control module controls the opening of the automatic control valve of the aeration module in the MBBR tank according to the monitoring data of the suspended filler biofilm thickness monitoring module and the early warning signal of the early warning module.

[0014] As a further technical solution, the working process of the thickness analysis unit is as follows:

[0015] Compare the real-time monitored suspended filler biofilm thickness with the preset optimal suspended filler biofilm thickness corresponding to different water quality treatments, and calculate the suspended filler biofilm thickness deviation ;

[0016] The expression is: ;in, is the actual monitored suspended filler biofilm thickness, To determine the optimal suspended media biofilm thickness for different treatment water qualities;

[0017] The thickness deviation of the suspended filler biofilm Deviation threshold of suspended media biofilm thickness from the preset value For comparison: If , it is judged that the thickness of the biofilm of the suspended filler is abnormal, otherwise, it is judged that the thickness of the biofilm of the suspended filler is normal;

[0018] Then analyze the changing trend of the suspended filler biofilm thickness over time to determine whether the growth or shedding rate of the suspended filler biofilm is normal.

[0019] As a further technical solution, the process of analyzing the change trend of suspended filler biofilm thickness over time is as follows:

[0020] The thickness data of the suspended filler biofilm is obtained from the suspended filler biofilm image processing unit according to the preset time interval, and the suspended filler biofilm thickness data is constructed. Time series data sets , The number of times the suspended filler biofilm thickness was collected;

[0021] By formula:

[0022] ;

[0023] Calculate the cumulative change in the thickness of the suspended filler biofilm ;

[0024] in, For the The time period corresponding to the time series data, 、 are the starting time point and the ending time point of each time period respectively. is the weight coefficient for each time period, is the maximum value of the suspended filler biofilm thickness in each time period, is the minimum value of the suspended filler biofilm thickness in each time period, The preset proportional coefficient corresponding to each time period; The curve of the thickness of the suspended filler biofilm over time obtained by fitting the time series data set is: is the inlet water quality coefficient, and its expression is: , is the effluent water quality coefficient, and its expression is: ;in, is the mean value of any influent water quality parameter, is the number of water quality parameters, is the reference value of the corresponding influent water quality parameter, is the mean value of any effluent water quality parameter, is the standard value of the corresponding effluent water quality parameter, 、 is the influence coefficient, which is determined based on analysis of historical data and experimental data.

[0025] As a further technical solution, the process of determining whether the growth or shedding rate of the suspended filler biofilm is normal is as follows:

[0026] The calculated cumulative change in the thickness of the suspended filler biofilm is Substituting into the formula: The average change rate of the suspended filler biofilm thickness was calculated ;

[0027] like , it is judged that the suspended filler biofilm is in a growth state;

[0028] like , it is judged that the suspended filler biofilm is in a shedding state;

[0029] The average change rate of the suspended media biofilm thickness and the preset change rate threshold range Make a comparison;

[0030] like and , it is judged that the growth of the suspended filler biofilm is abnormal;

[0031] like and , it is judged that the shedding of the suspended filler biofilm is abnormal;

[0032] Otherwise, the growth or shedding of the suspended filler biofilm is judged to be normal.

[0033] As a further technical solution, the working process of the image processing unit is as follows:

[0034] Screening suspended filler biofilm images at a set angle, and performing a preprocessing operation on the screened suspended filler biofilm images, wherein the preprocessing operation includes image enhancement, denoising, and normalization;

[0035] Inputting the pre-treated suspended filler biofilm image into a pre-trained biofilm thickness prediction model based on a convolutional neural network, wherein the biofilm thickness prediction model based on the convolutional neural network includes multiple convolutional layers, pooling layers, and fully connected layers;

[0036] The biofilm thickness prediction model based on convolutional neural network extracts features from the input image, learns the texture, edge and color features of the biofilm through the convolution layer, and downsamples the feature map through the pooling layer to reduce the amount of calculation and the number of parameters;

[0037] The extracted features are mapped to the predicted value of biofilm thickness through the fully connected layer, and the thickness of the suspended filler biofilm is finally output. .

[0038] As a further technical solution, the working process of the suspended filler biofilm thickness control module is as follows:

[0039] According to the deviation of the biofilm thickness of the suspended filler and the average rate of change Calculate and obtain the comprehensive deviation index E;

[0040] Compare the comprehensive deviation index E with the preset comprehensive deviation threshold ER;

[0041] If E≤ER, the thickness of the suspended filler biofilm is normal, and the opening of the automatic control valve of the aeration module in the MBBR tank remains unchanged at the current value K0, that is, K=K0; K is the adjusted opening value of the automatic control valve;

[0042] If E>ER, the opening value of the automatic control valve of the aeration module in the MBBR tank is adjusted according to the comprehensive deviation index E.

[0043] As a further technical solution, the process of adjusting the opening value K of the automatic control valve of the aeration module in the MBBR tank according to the comprehensive deviation index E is as follows:

[0044] By formula:

[0045] K = K0 + k (E - ER), k is the proportional coefficient;

[0046] When the thickness of the suspended filler biofilm deviates The average change rate of the suspended filler biofilm thickness When k takes a positive value, the aeration intensity increases; when and When , k takes a negative value, reducing the aeration intensity;

[0047] The calculated automatic control valve opening value K is compared with the preset lower limit value , upper limit value Perform comparison; if K < , then let K= ; If K> , then let K= .

[0048] As a further technical solution, the expression of the comprehensive deviation index E is: ;in, 、 is the weight coefficient, and .

[0049] Beneficial effects of the present invention:

[0050] The present invention realizes dynamic supervision of the thickness of the suspended filler biofilm through the mutual cooperation of the suspended filler biofilm thickness monitoring module, the suspended filler biofilm thickness early warning module and the suspended filler biofilm thickness control module. Once abnormal growth or shedding occurs, an early warning is immediately issued, and measures are taken in time to control the thickness of the suspended filler biofilm, thereby comprehensively improving the water treatment capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The present invention will be further described below with reference to the accompanying drawings.

[0052] Figure 1 This is a schematic diagram of the structure of the MBBR pool and suspended filler biofilm thickness detection and control system;

[0053] Figure 2 This is a system structure diagram of the present invention.

[0054] Reference numerals:

[0055] 10. Water inlet; 20. Water outlet; 30. Suspended filler interception grid; 40. Aeration pipe; 50. Automatic control valve; 60. Air diffuser; 70. Online monitoring device for floating filler biofilm thickness. DETAILED DESCRIPTION

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0057] See also Figure 1-Figure 2 As shown, the present invention is a MBBR suspended filler biofilm thickness monitoring and control system, which is configured in an MBBR tank and includes:

[0058] Suspended media biofilm thickness monitoring module, including:

[0059] An image acquisition unit, which acquires a biofilm image of the suspended filler in real time based on an online monitoring device for the biofilm thickness of the suspended filler;

[0060] An image processing unit is used to process the suspended filler biofilm image acquired by the image acquisition unit to obtain the suspended filler biofilm thickness as monitoring data;

[0061] The thickness analysis unit performs further analysis based on the suspended filler biofilm thickness data obtained by the image processing unit;

[0062] The suspended filler biofilm thickness warning module is used to issue a warning signal when it is determined that the suspended filler biofilm thickness is abnormal; it also issues a warning signal based on the judgment result of whether the growth or shedding rate of the suspended filler biofilm is normal;

[0063] The suspended filler biofilm thickness control module controls the opening of the automatic control valve of the aeration module in the MBBR tank according to the monitoring data of the suspended filler biofilm thickness monitoring module and the early warning signal of the early warning module.

[0064] It should be noted that:

[0065] The MBBR tank includes: a water inlet 10, a water outlet 20, an aeration module, an online monitoring device for the thickness of a suspended filler biofilm 70, a central processing unit, and a suspended filler interception grid 30; the water inlet 10 is located on the left side of the MBBR tank, the water outlet 20 is located on the right side of the MBBR tank, the suspended filler interception grid 30 is located on the side wall of the MBBR tank near the water outlet 20, the aeration module is located at the bottom of the MBBR tank, and multiple online monitoring devices 70 for the thickness of a suspended filler biofilm are provided and located inside the MBBR tank;

[0066] The aeration module includes an aeration pipe 40, an automatic control valve 50 and an air diffuser 60; the central processing unit includes a suspended filler biofilm thickness monitoring module, a suspended filler biofilm thickness early warning module and a suspended filler biofilm thickness control module.

[0067] In this embodiment, the system consists of three modules: suspended filler biofilm thickness monitoring, early warning, and control. The monitoring module includes three units: suspended filler biofilm image acquisition, processing, and thickness analysis. The suspended filler biofilm image acquisition unit acquires biofilm images in real time through an online monitoring device. The image processing unit processes the images to obtain biofilm thickness as monitoring data. The thickness analysis unit further analyzes the data. The early warning module has two warning criteria: one is to determine whether the biofilm thickness is abnormal, and if so, issue a warning; the other is to determine whether the biofilm growth or shedding rate is normal, and if so, issue a warning. Finally, the control module combines the monitoring data from the monitoring module and the early warning signal from the early warning module to accurately control the opening of the automatic control valve 50 of the aeration module in the MBBR tank to maintain the biofilm thickness within the appropriate range, ensuring the efficient and stable operation of the water treatment system and improving the sewage treatment effect. Through the cooperation between these multiple modules, dynamic monitoring and control of the suspended filler biofilm thickness are achieved. If growth or shedding abnormalities occur, an immediate warning is issued, and timely measures are taken to control the suspended filler biofilm thickness, thereby comprehensively improving water treatment capacity.

[0068] The working process of the suspended filler biofilm thickness analysis unit is as follows:

[0069] Compare the real-time monitored suspended filler biofilm thickness with the preset optimal suspended filler biofilm thickness corresponding to different water quality treatments, and calculate the suspended filler biofilm thickness deviation ;

[0070] The expression is: ;in, is the actual monitored suspended filler biofilm thickness, The optimal suspended media biofilm thickness for different treated water qualities is determined based on experimental data and actual operating experience;

[0071] The thickness deviation of the suspended filler biofilm Deviation threshold of suspended media biofilm thickness from the preset value For comparison: If , it is judged that the thickness of the biofilm of the suspended filler is abnormal, otherwise, it is judged that the thickness of the biofilm of the suspended filler is normal;

[0072] Then analyze the changing trend of the suspended filler biofilm thickness over time to determine whether the growth or shedding rate of the suspended filler biofilm is normal.

[0073] The process of analyzing the change trend of suspended media biofilm thickness over time is as follows:

[0074] The thickness data of the suspended filler biofilm is obtained from the suspended filler biofilm image processing unit according to the preset time interval, and the suspended filler biofilm thickness data is constructed. Time series data sets , The number of times the suspended filler biofilm thickness was collected;

[0075] By formula: Calculate the cumulative change in the thickness of the suspended filler biofilm ;

[0076] in, For the The time period corresponding to the time series data, 、 are the starting time point and the ending time point of each time period respectively. The weight coefficient for each time period is determined based on experimental data and actual operating experience. is the maximum value of the suspended filler biofilm thickness in each time period, is the minimum value of the suspended filler biofilm thickness in each time period, The preset proportional coefficient corresponding to each time period is determined based on experimental data and actual operating experience; The curve of the thickness of the suspended filler biofilm over time obtained by fitting the time series data set is: is the inlet water quality coefficient, and its expression is: , is the effluent water quality coefficient, and its expression is: ;in, is the mean value of any influent water quality parameter, is the number of water quality parameters, is the reference value of the corresponding influent water quality parameter, is the mean value of any effluent water quality parameter, is the standard value of the corresponding effluent water quality parameter, 、 is the influence coefficient, which is determined based on analysis of historical data and experimental data.

[0077] By formula: Calculate the cumulative change in the thickness of the suspended filler biofilm Thus, the thickness change of the suspended filler biofilm in the time period corresponding to each time series data is calculated by integration, so as to achieve accurate calculation of the average cumulative change. At the same time, in order to improve the accuracy of the evaluation of the cumulative change, the extreme value difference in each time period is expressed in the form of an index. Incorporate the calculation formula to accurately evaluate the changes in suspended media biofilm thickness by combining the cumulative changes and extreme value differences;

[0078] The process of determining whether the growth or shedding rate of suspended media biofilm is normal is as follows:

[0079] The calculated cumulative change in the thickness of the suspended filler biofilm is Substituting into the formula: The average change rate of the suspended filler biofilm thickness was calculated ;

[0080] like , it is judged that the suspended filler biofilm is in a growth state;

[0081] like , it is judged that the suspended filler biofilm is in a shedding state;

[0082] The average change rate of the suspended media biofilm thickness and the preset change rate threshold range Make a comparison;

[0083] like and , it is judged that the growth of the suspended filler biofilm is abnormal;

[0084] like and , it is judged that the shedding of the suspended filler biofilm is abnormal;

[0085] Otherwise, the growth or shedding of the suspended filler biofilm is judged to be normal.

[0086] In this embodiment, a method for analyzing the thickness of the suspended filler biofilm is provided. Specifically, the thickness deviation of the suspended filler biofilm is first calculated. Deviation threshold of suspended media biofilm thickness from the preset value By comparison, it is possible to determine whether the current thickness of the suspended filler biofilm is normal. If it is abnormal, an early warning signal is issued. If it is normal, the trend of the suspended filler biofilm thickness change over time is analyzed to determine whether the growth or shedding rate of the suspended filler biofilm is normal, so as to realize the monitoring of the growth or shedding rate of the suspended filler biofilm in combination with the time series, improve the dynamic monitoring capability of the suspended filler biofilm thickness, and provide reliable support for timely early warning of subsequent abnormal changes in the suspended filler biofilm thickness.

[0087] The working process of the image processing unit is as follows:

[0088] Screening suspended filler biofilm images at a set angle, and performing a preprocessing operation on the screened suspended filler biofilm images, wherein the preprocessing operation includes image enhancement, denoising, and normalization;

[0089] Inputting the pre-treated suspended filler biofilm image into a pre-trained biofilm thickness prediction model based on a convolutional neural network, wherein the biofilm thickness prediction model based on the convolutional neural network includes multiple convolutional layers, pooling layers, and fully connected layers;

[0090] The biofilm thickness prediction model based on convolutional neural network extracts features from the input image, learns the texture, edge and color features of the biofilm through the convolution layer, and downsamples the feature map through the pooling layer to reduce the amount of calculation and the number of parameters;

[0091] The extracted features are mapped to the predicted value of biofilm thickness through the fully connected layer, and the thickness of the suspended filler biofilm is finally output. .

[0092] In this embodiment, the consistency and validity of the input data can be ensured by screening images at specific angles, and the preprocessing operation can improve the image quality, making it easier for the model to learn key features. CNN model: Convolutional neural networks are widely used in image recognition and processing, and can automatically learn discriminative features from images. The combination of multiple convolutional layers and pooling layers can gradually extract different levels of features of the biofilm, and the fully connected layer integrates these features and outputs the final thickness prediction value. Through the trained model, the input image is directly processed and the biofilm thickness is output, avoiding the complex edge detection and geometric calculation steps in traditional methods.

[0093] The working process of the suspended filler biofilm thickness control module is as follows:

[0094] According to the deviation of the biofilm thickness of the suspended filler and the average rate of change Calculate and obtain the comprehensive deviation index E; the expression of the comprehensive deviation index E is: ;in, 、 is the weight coefficient, and ;

[0095] Compare the comprehensive deviation index E with the preset comprehensive deviation threshold ER;

[0096] If E≤ER, the thickness of the suspended filler biofilm is normal, and the opening of the automatic control valve of the aeration module in the MBBR tank remains unchanged at the current value K0, that is, K=K0; K is the adjusted opening value of the automatic control valve;

[0097] If E>ER, the opening value of the automatic control valve of the aeration module in the MBBR tank is adjusted according to the comprehensive deviation index E.

[0098] The process of adjusting the opening value K of the automatic control valve of the aeration module in the MBBR tank according to the comprehensive deviation index E is as follows:

[0099] By the formula: K = K0 + k (E-ER), k is the proportional coefficient, which is determined based on experimental data and actual operation experience; when the thickness of the suspended filler biofilm deviates The average change rate of the suspended filler biofilm thickness When k takes a positive value, the aeration intensity increases; when and When , k takes a negative value, reducing the aeration intensity;

[0100] The calculated automatic control valve opening value K is compared with the preset lower limit value , upper limit value Perform comparison; if K < , then let K= ; If K> , then let K= .

[0101] In this embodiment, the opening of the automatic control valve of the aeration module is precisely controlled based on the monitoring data of the suspended filler biofilm thickness monitoring module and the warning signal of the warning module, so that the biofilm thickness can be maintained within the optimal biofilm thickness range determined for different treated water qualities. A biofilm of appropriate thickness can provide a good living environment for microorganisms, allowing them to fully exert their ability to decompose and transform pollutants in the water, thereby improving the removal rate of organic matter and effectively reducing indicators such as chemical oxygen demand (COD) and biochemical oxygen demand (BOD) in the wastewater.

[0102] When the biofilm thickness is detected to exceed the warning threshold, or when the biofilm growth or shedding rate is abnormal, the control module can respond quickly and adjust the aeration intensity in a timely manner. For example, when the biofilm is too thick, increasing the aeration intensity can promote the shedding of the biofilm, preventing problems such as internal anaerobic conditions and reduced mass transfer efficiency caused by the excessively thick biofilm; when the biofilm is too thin, reducing the aeration intensity is conducive to the growth and recovery of the biofilm, ensuring the normal operation of the system. This timely adjustment mechanism can effectively avoid system failures and fluctuations in treatment effects caused by abnormal biofilm thickness, and enhance the system's anti-interference ability and stability.

[0103] Aeration is one of the main energy-consuming links in the operation of the MBBR system. The control module in the present invention avoids unnecessary over-aeration or under-aeration by precisely controlling the opening of the automatic control valve of the aeration module, and provides an appropriate amount of oxygen according to the actual needs of the biofilm. It can minimize aeration energy consumption while ensuring the sewage treatment effect, thereby reducing the operating cost of the system.

[0104] It should be noted that the calculation formulas and various parameters involved in the calculations in the present invention have been dimensionally processed in advance, and the process of dimensionless processing is well known in the industry and will not be described here.

[0105] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A MBBR suspended filler biofilm thickness monitoring and control system, the system is configured in the MBBR tank, characterized in that: The system comprises: Suspended media biofilm thickness monitoring module, including: An image acquisition unit, which acquires a biofilm image of the suspended filler in real time based on an online monitoring device for the biofilm thickness of the suspended filler; An image processing unit is used to process the suspended filler biofilm image acquired by the image acquisition unit to obtain the suspended filler biofilm thickness as monitoring data; The thickness analysis unit performs further analysis based on the suspended filler biofilm thickness data obtained by the image processing unit; The working process of the thickness analysis unit is as follows: The difference between the real-time monitored suspended filler biofilm thickness and the preset optimal suspended filler biofilm thickness corresponding to different water quality treatments is taken as the suspended filler biofilm thickness deviation. ; According to the deviation of the biofilm thickness of the suspended filler Determine whether the thickness of the suspended filler biofilm is abnormal; then analyze the change trend of the suspended filler biofilm thickness over time to determine whether the growth or shedding rate of the suspended filler biofilm is normal; The process of analyzing the change trend of suspended media biofilm thickness over time is as follows: The thickness data of the suspended filler biofilm is obtained from the suspended filler biofilm image processing unit according to the preset time interval, and the suspended filler biofilm thickness data is constructed. Time series data sets , The number of times the suspended filler biofilm thickness was collected; By formula: ； Calculate the cumulative change in the thickness of the suspended filler biofilm ; in, For the The time period corresponding to the time series data, 、 are the starting time point and the ending time point of each time period respectively. The weight coefficient for each time period is determined based on experimental data and actual operating experience. is the maximum value of the suspended filler biofilm thickness in each time period, is the minimum value of the suspended filler biofilm thickness in each time period, The preset proportional coefficient corresponding to each time period is determined based on experimental data and actual operating experience; The curve of the thickness of the suspended filler biofilm over time obtained by fitting the time series data set is: is the inlet water quality coefficient, and its expression is: , is the effluent water quality coefficient, and its expression is: ;in, is the mean value of any influent water quality parameter, is the number of water quality parameters, is the reference value of the corresponding influent water quality parameter, is the mean value of any effluent water quality parameter, is the standard value of the corresponding effluent water quality parameter, 、 is the influence coefficient, which is determined based on the analysis of historical data and experimental data; The process of determining whether the growth or shedding rate of suspended media biofilm is normal is as follows: The calculated cumulative change in the thickness of the suspended filler biofilm is Substituting into the formula: The average change rate of the suspended filler biofilm thickness was calculated ; like , it is judged that the suspended filler biofilm is in a growth state; like , it is judged that the suspended filler biofilm is in a shedding state; The average change rate of the suspended media biofilm thickness and the preset change rate threshold range Make a comparison; like and , it is judged that the growth of the suspended filler biofilm is abnormal; like and , it is judged that the shedding of the suspended filler biofilm is abnormal; Otherwise, the growth or shedding of the suspended filler biofilm is judged to be normal; The suspended filler biofilm thickness warning module is used to issue a warning signal when it is determined that the suspended filler biofilm thickness is abnormal; it also issues a warning signal based on the judgment result of whether the growth or shedding rate of the suspended filler biofilm is normal; The suspended filler biofilm thickness control module controls the opening of the automatic control valve of the aeration module in the MBBR tank according to the monitoring data of the suspended filler biofilm thickness monitoring module and the early warning signal of the early warning module.

2. The MBBR suspended filler biofilm thickness monitoring and control system according to claim 1, characterized in that: The working process of the image processing unit is as follows: Screening suspended filler biofilm images at a set angle, and performing a preprocessing operation on the screened suspended filler biofilm images, wherein the preprocessing operation includes image enhancement, denoising, and normalization; Inputting the pre-treated suspended filler biofilm image into a pre-trained biofilm thickness prediction model based on a convolutional neural network, wherein the biofilm thickness prediction model based on the convolutional neural network includes multiple convolutional layers, pooling layers, and fully connected layers; The biofilm thickness prediction model based on convolutional neural network extracts features from the input image, learns the texture, edge and color features of the biofilm through the convolution layer, and downsamples the feature map through the pooling layer to reduce the amount of calculation and the number of parameters; The extracted features are mapped to the predicted value of biofilm thickness through the fully connected layer, and the thickness of the suspended filler biofilm is finally output. .

3. The MBBR suspended filler biofilm thickness monitoring and control system according to claim 1, characterized in that: The working process of the suspended filler biofilm thickness control module is as follows: According to the deviation of the biofilm thickness of the suspended filler and the average rate of change Calculate and obtain the comprehensive deviation index E; the expression of the comprehensive deviation index E is: ;in, 、 is the weight coefficient, and ; The suspended filler biofilm thickness deviation The expression is: ;in, is the actual monitored suspended filler biofilm thickness, To determine the optimal suspended media biofilm thickness for different treatment water qualities; Compare the comprehensive deviation index E with the preset comprehensive deviation threshold ER; If E≤ER, the thickness of the suspended filler biofilm is judged to be normal, and the opening of the automatic control valve of the aeration module in the MBBR tank remains unchanged at the current value K0; If E>ER, the opening value of the automatic control valve of the aeration module in the MBBR tank is adjusted according to the comprehensive deviation index E.

4. The MBBR suspended filler biofilm thickness monitoring and control system according to claim 3, characterized in that: The process of adjusting the opening value K of the automatic control valve of the aeration module in the MBBR tank according to the comprehensive deviation index E is as follows: By formula: K=K0+k(E-ER), where k is the proportionality coefficient; it is determined based on experimental data and actual operating experience; When the thickness of the suspended filler biofilm deviates The average change rate of the suspended filler biofilm thickness When k takes a positive value, the aeration intensity increases; when and When , k takes a negative value, reducing the aeration intensity; The calculated automatic control valve opening value K is compared with the preset lower limit value , upper limit value Perform comparison; if K < , then let K= ; If K> , then let K= .

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