Environment-friendly sewage stirring and impurity screening intelligent monitoring system

Abstract

The invention discloses an environment-friendly sewage stirring and impurity screening intelligent monitoring system, and particularly relates to the technical field of intelligent monitoring. Sewage impurity characteristic information at different moments is acquired, a first screen adjustment demand index is calculated, and control response delay of a screen control system and driving voltage fluctuation of an electric motor are monitored; calculating a second screen adjustment demand index to accurately reflect the response performance of the screen control system; and comprehensively analyzing the first screen adjustment demand index and the second screen adjustment demand index, generating an adjustment demand evaluation index, evaluating the load capacity of the current screen control system, and when the evaluation result shows that the screen control system can meet the real-time adjustment demand, determining that the screen control system does not meet the real-time adjustment demand. The screen mesh adjusting and correcting module can adjust the mesh size and the vibration frequency of the screen mesh according to the real-time data and correct the adjusting time of the screen mesh at the same time, it is ensured that solid impurities in sewage are efficiently removed, the sewage treatment efficiency is improved, and the failure rate and the maintenance cost of equipment are reduced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and more specifically, to an intelligent monitoring system for environmentally friendly sewage mixing and impurity screening. Background Art

[0002] With the continuous advancement of the global industrialization process, sewage treatment has become one of the important issues of environmental protection. Especially in industrial sewage treatment, sewage often contains a large amount of solid impurities, suspended matter and harmful chemicals. The effective removal of these impurities is crucial to the subsequent treatment process; however, in the treatment of sewage with high concentrations of pollutants or complex components, there are still technical challenges such as poor screening efficiency, uneven stirring, and excessive equipment load. Especially when the sewage contains grease, chemicals or heavy metals, traditional screens may be easily blocked or damaged, further leading to a decrease in treatment efficiency, and may even affect the stability and safety of the entire sewage treatment system. Therefore, how to achieve efficient, stable and low-energy sewage treatment in a complex environment is still a technical problem that needs to be solved in this field. Summary of the invention

[0003] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent monitoring system for environmentally friendly sewage mixing and impurity screening to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] An environmentally friendly sewage mixing and impurity screening intelligent monitoring system, including an impurity monitoring module, a control response module, an adjustment demand assessment module, an early warning module, and a screen adjustment correction module;

[0006] An impurity monitoring module is used to obtain impurity characteristic information of sewage at different times, establish an impurity characteristic information time series according to the impurity characteristic information of sewage at different times, and calculate the first screen adjustment demand index according to the impurity characteristic information time series;

[0007] A control response module, used to obtain control response delay information of the screen control system and driving voltage fluctuation information of the electric motor, and calculate the second screen adjustment demand index according to the control response delay information and the driving voltage fluctuation information;

[0008] An adjustment demand evaluation module is used to construct an adjustment demand evaluation model according to the first screen adjustment demand index and the second screen adjustment demand index, generate an adjustment demand evaluation index, and evaluate whether the current screen control system can meet the real-time adjustment demand of the screen;

[0009] The early warning module is used to generate an early warning signal when the screen control system cannot meet the real-time adjustment requirements of the screen, and is used to automatically alarm and start the emergency treatment plan;

[0010] The screen adjustment correction module is used to adjust the mesh size and vibration frequency of the screen according to the first screen adjustment demand index when the screen control system meets the real-time adjustment demand of the screen, and to correct the adjustment time of the screen according to the second screen adjustment demand index.

[0011] In a preferred embodiment, the impurity characteristic information includes but is not limited to particle size, sewage flow rate, sewage flow rate, suspended matter concentration, oil content, and fluid viscosity;

[0012] Obtain impurity characteristic information at different times, and establish an impurity characteristic information time series based on the impurity characteristic information of sewage at different times, and mark the impurity characteristic information time series as XL = {X t}={X1,X2,...,X T}, where X t represents the impurity feature information obtained at time t, t∈{1,2,...,T}, X t is a multidimensional vector, namely X t =[Particle size t , sewage flow rate t , sewage flow t , suspended matter concentration t , oil content t , fluid viscosity t ]; preprocess the impurity feature information data in the impurity feature information time series, including data cleaning: removing missing values ​​and outliers in the data; feature standardization;

[0013] The logistic regression model is used to calculate the first screen adjustment demand index SH1 based on the impurity characteristic information time series. The mathematical expression of the logistic regression model is as follows Where P(Y=1|X) is the output probability of the logistic regression model, indicating the demand probability of screen adjustment, [X1,X2,…,X T ] is the input feature of the logistic regression model, [ω0,ω1,…,ω T is the weight parameter of the logistic regression model;

[0014] The output probability P(Y=1|X) of the logistic regression model is used as the first screen adjustment demand index SH1, that is, SH1=P(Y=1|X(.

[0015] In a preferred embodiment, the control response delay information includes a control response delay coefficient, and the driving voltage fluctuation information includes a driving voltage fluctuation coefficient; the control response delay coefficient and the driving voltage fluctuation coefficient are marked as kyc and qdb respectively.

[0016] In a preferred embodiment, the control response delay information of the screen control system is obtained, the control response delay of the screen control system is analyzed, and the control response delay coefficient is obtained to measure the control response delay degree of the screen control system;

[0017] The logic for obtaining the control response delay coefficient is as follows:

[0018] When the screen control system performs screen control, the control signal receiving time T1, screen adjustment completion time T2, and expected response time T3 of each screen control are obtained, and the response time ΔT=T2-T1 is calculated; the response delay ratio YC is calculated, and the expression is as follows Calculate the average response delay ratio ypj, the expression is as follows Among them, YC i It represents the response delay ratio calculated by the screen control system when the screen is controlled for the i-th time, i∈{1,2,...,I}; the standard deviation of the response delay ratio ybc is calculated as follows: Calculate the control response delay coefficient kyc, the expression is as follows

[0019] In a preferred embodiment, the driving voltage fluctuation of the electric motor is analyzed through the driving voltage fluctuation information of the electric motor, and the driving voltage fluctuation coefficient is obtained to measure the driving voltage fluctuation degree of the electric motor;

[0020] The logic for obtaining the driving voltage fluctuation coefficient is as follows:

[0021] Get the driving voltage signal V(t) of the electric motor = {V(t1), V(t2), ..., V(t N )}; perform data preprocessing on the driving voltage signal, including data cleaning: removing missing values ​​and outliers in the data; feature standardization; calculating the driving voltage fluctuation coefficient qdb, the expression is as follows Where τ represents the time lag, which is an integer multiple of the time interval between voltage signals, V(t n ) represents the time t n The voltage value, Represents the mean value of the voltage signal:

[0022] In a preferred embodiment, the second screen adjustment demand index SH2 is calculated based on the control response delay coefficient and the driving voltage fluctuation coefficient, and the expression is as follows: SH2=a1*kyc+a2*qdb, wherein a1 and a2 are preset proportional coefficients of the control response delay coefficient and the driving voltage fluctuation coefficient, respectively, and a1 and a2 are both greater than 0.

[0023] In a preferred embodiment, an adjustment demand evaluation model is constructed based on the first screen adjustment demand index and the second screen adjustment demand index to generate an adjustment demand evaluation index Reval. The model is based on the following formula: Wherein b1 and b2 represent the preset proportional coefficients of the first screen adjustment demand index and the second screen adjustment demand index respectively, and b1 and b2 are both greater than 0.

[0024] In a preferred embodiment, the adjustment demand evaluation index is compared with a preset adjustment demand evaluation index threshold to evaluate whether the current screen control system can meet the real-time adjustment demand of the screen, as follows:

[0025] If the adjustment demand assessment index is greater than the adjustment demand assessment index threshold, a warning signal is generated through the warning module; if the adjustment demand assessment index is less than or equal to the adjustment demand assessment index threshold, a screen adjustment correction signal is generated.

[0026] In a preferred embodiment, when the screen adjustment correction signal is generated, the corresponding first screen adjustment demand index and second screen adjustment demand index are obtained;

[0027] The adjustment time of the screen is corrected according to the second screen adjustment demand index, as follows: tadjust = tadjust 1 +ρ*SH2, where tadjust is the screen adjustment time after correction, tadjust 1 is the initial screen adjustment moment of the screen control system, ρ is the correction factor of the adjustment moment, which is used to control the adjustment amplitude at the adjustment moment, and SH2 is the second screen adjustment demand index;

[0028] The mesh size and vibration frequency of the screen are adjusted according to the adjustment demand index of the first screen, as follows: Wherein, Dmesh(tadjust) is the mesh adjustment size required at the corrected screen adjustment moment, Dmesh(tadjust-1) is the mesh size at the moment before the corrected screen adjustment moment, α is the mesh size adjustment coefficient, which is used to control the adjustment amplitude of the mesh size, Fvibrate(tadjust) is the vibration adjustment frequency required at the corrected screen adjustment moment, Fvibrate(tadjust-1) is the vibration frequency at the moment before the corrected screen adjustment moment, β is the vibration frequency adjustment coefficient, which is used to control the adjustment amplitude of the vibration frequency, and SH1 is the first screen adjustment demand index.

[0029] Technical effects and advantages of the present invention:

[0030] 1. The present invention obtains sewage impurity characteristic information at different times through the impurity monitoring module, establishes the impurity characteristic information time series and calculates the first screen adjustment demand index, automatically adjusts the working state of the screen according to the changes in the specific composition, particle size, flow rate, suspended matter concentration and other changes of the sewage, and avoids the efficiency caused by environmental changes in the traditional screen treatment method. The control response module monitors the control response delay of the screen control system and the driving voltage fluctuation of the electric motor, and calculates the second screen adjustment demand index to accurately reflect the response performance of the screen control system, ensuring that the screen adjustment operation can be executed in a timely and accurate manner during the dynamically changing sewage treatment process; the adjustment demand evaluation module comprehensively analyzes the first screen adjustment demand index and the second screen adjustment demand index, generates an adjustment demand evaluation index, evaluates the load capacity of the current screen control system, and determines whether it can meet the real-time adjustment demand. Once it is detected that the screen control system cannot respond to the adjustment needs in time, the early warning module will promptly issue a warning signal and initiate an emergency treatment plan to avoid the adverse effects of system failures on the entire sewage treatment process; when the evaluation results show that the screen control system can meet the real-time adjustment needs, the screen adjustment correction module will adjust the mesh size and vibration frequency of the screen according to real-time data, and correct the adjustment time of the screen to ensure that solid impurities in the sewage are efficiently removed. The precise adjustment mechanism not only improves the efficiency of sewage treatment, but also greatly reduces the failure rate and maintenance cost of the equipment. It effectively improves the working efficiency and stability of the screen in a complex industrial sewage treatment environment, avoids system stagnation caused by screen blockage, equipment failure and other problems, and ensures the smooth progress of the sewage treatment process. At the same time, through intelligent early warning and automatic adjustment mechanisms, low-energy consumption, high-efficiency, long-term and stable sewage treatment can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0032] Figure 1 Flowchart of a system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0034] Embodiment: The present invention provides as Figure 1 An environmentally friendly sewage mixing and impurity screening intelligent monitoring system shown includes an impurity monitoring module, a control response module, an adjustment demand assessment module, an early warning module, and a screen adjustment correction module;

[0035] An impurity monitoring module is used to obtain impurity characteristic information of sewage at different times, establish an impurity characteristic information time series according to the impurity characteristic information of sewage at different times, and calculate the first screen adjustment demand index according to the impurity characteristic information time series;

[0036] A control response module, used to obtain control response delay information of the screen control system and driving voltage fluctuation information of the electric motor, and calculate the second screen adjustment demand index according to the control response delay information and the driving voltage fluctuation information;

[0037] An adjustment demand evaluation module is used to construct an adjustment demand evaluation model according to the first screen adjustment demand index and the second screen adjustment demand index, generate an adjustment demand evaluation index, and evaluate whether the current screen control system can meet the real-time adjustment demand of the screen;

[0038] The early warning module is used to generate an early warning signal when the screen control system cannot meet the real-time adjustment requirements of the screen, and is used to automatically alarm and start the emergency treatment plan;

[0039] A screen adjustment correction module, used to adjust the mesh size and vibration frequency of the screen according to a first screen adjustment demand index when the screen control system meets the real-time adjustment demand of the screen, and to correct the adjustment time of the screen according to a second screen adjustment demand index;

[0040] An impurity monitoring module is used to obtain impurity characteristic information of sewage at different times, establish an impurity characteristic information time series according to the impurity characteristic information of sewage at different times, and calculate the first screen adjustment demand index according to the impurity characteristic information time series;

[0041] The impurity characteristic information includes, but is not limited to, particle size, sewage flow rate, sewage flow rate, suspended solids concentration, oil content, and fluid viscosity;

[0042] It should be noted that particle size is usually measured by a laser diffraction particle size analyzer or a particle counting sensor. These devices can measure the distribution of particles in sewage through the principle of laser scattering or dynamic light scattering technology, and calculate the size of particles based on the scattering characteristics of different particles. Flow rate sensors usually use ultrasonic flowmeters or electromagnetic flowmeters to measure the flow rate of sewage. Ultrasonic flowmeters measure the movement speed of particles in the fluid by sending and receiving ultrasonic signals, while electromagnetic flowmeters use the principle of electromagnetic induction to measure the flow rate based on the conductivity and flow velocity of the fluid. Flow sensors determine the flow rate by measuring the volume or mass of water flowing through a specific cross-section. Common devices include turbine flowmeters (which measure the flow rate by the speed of the rotating turbine), ultrasonic flowmeters (which measure the flow rate by using the change in the propagation speed of ultrasonic waves) and Orifice flowmeter (calculates flow rate based on the relationship between fluid pressure drop and flow rate); turbidity sensor uses the principle of light scattering to measure the degree of scattering or absorption of light by suspended particles in water samples. Higher turbidity values ​​usually indicate higher concentrations of suspended matter in sewage. Turbidity sensors are widely used in water treatment systems to monitor the concentration of suspended matter; based on the optical properties of grease, such as light absorption and reflection, grease sensors can measure the grease content in water in real time, and are particularly suitable for treating oil pollution in industrial wastewater; viscosity sensors evaluate viscosity by measuring the flow resistance of a fluid under specific conditions. Common viscosity sensors include rotational viscometers (measured by the resistance of a rotating rotor in a fluid) and rheometers (measure the flow characteristics of a fluid by applying shear stress);

[0043] Obtain impurity characteristic information at different times, and establish an impurity characteristic information time series based on the impurity characteristic information of sewage at different times, and mark the impurity characteristic information time series as XL = {X t}={X1,X2,...,X T}, where X t represents the impurity feature information obtained at time t, t∈{1,2,...,T}, X t is a multidimensional vector, namely X t =[Particle size t , sewage flow rate t , sewage flow t , suspended matter concentration t , oil content t , fluid viscosity t ]; preprocess the impurity feature information data in the impurity feature information time series, including data cleaning: removing missing values ​​and outliers in the data; feature standardization;

[0044] The logistic regression model is used to calculate the first screen adjustment demand index SH1 based on the impurity characteristic information time series. The mathematical expression of the logistic regression model is as follows Where P(Y=1|X) is the output probability of the logistic regression model, indicating the demand probability of screen adjustment, [X1,X2,…,X T ] is the input feature of the logistic regression model, [ω0,ω1,…,ω T is the weight parameter of the logistic regression model;

[0045] The output probability P(Y=1|X) of the logistic regression model is used as the first screen adjustment demand index SH1, that is, SH1=P(Y=1|X);

[0046] A control response module, used to obtain control response delay information of the screen control system and driving voltage fluctuation information of the electric motor, and calculate the second screen adjustment demand index according to the control response delay information and the driving voltage fluctuation information;

[0047] The control response delay information includes a control response delay coefficient, and the driving voltage fluctuation information includes a driving voltage fluctuation coefficient; the control response delay coefficient and the driving voltage fluctuation coefficient are marked as kyc and qdb respectively;

[0048] The control response delay coefficient is an indicator used to measure the response speed or delay degree of the screen control system in actually performing the screen adjustment operation after receiving the adjustment instruction. This coefficient reflects the time delay between the control system receiving the signal and the actual adjustment. A longer control response delay may lead to untimely adjustment of the screen, thus affecting the efficiency and quality of sewage treatment, especially when the impurity characteristics of sewage change drastically, the slow response speed may lead to untimely adjustment; if the control response delay coefficient is high, it means that the control system responds slowly to the adjustment instruction, which will cause the screen adjustment to lag in the sewage treatment process, and thus fail to quickly adapt to the changes in the impurity characteristics of sewage, affecting the sewage treatment effect; by analyzing the control response delay coefficient, the real-time processing capability and stability of the system can be evaluated, and a high delay coefficient indicates that the system may need to be optimized to improve real-time performance;

[0049] Therefore, by acquiring the control response delay information of the screen control system, analyzing the control response delay of the screen control system, and obtaining the control response delay coefficient, the control response delay degree of the screen control system is measured;

[0050] The logic for obtaining the control response delay coefficient is as follows:

[0051] When the screen control system performs screen control, the control signal receiving time T1, screen adjustment completion time T2, and expected response time T3 of each screen control are obtained, and the response time ΔT=T2-T1 is calculated; the response delay ratio YC is calculated, and the expression is as follows Calculate the average response delay ratio ypj, the expression is as follows Among them, YC i It represents the response delay ratio calculated by the screen control system when the screen is controlled for the i-th time, i∈{1,2,...,I}; the standard deviation of the response delay ratio ybc is calculated as follows: Calculate the control response delay coefficient kyc, the expression is as follows

[0052] The driving voltage fluctuation coefficient is an important parameter used to measure the degree of fluctuation of the driving voltage of the electric motor. It can reflect the voltage stability of the electric motor during operation and the impact of abnormal fluctuations on the motor performance. The driving voltage fluctuation of the electric motor may be caused by a variety of factors, such as unstable power supply, system load changes, equipment aging, etc. These factors may lead to reduced motor efficiency or even failure. Therefore, monitoring and evaluating driving voltage fluctuations are crucial for the stable operation of the system. If the driving voltage fluctuation coefficient is high, it means that the driving voltage fluctuation of the electric motor is large, which may cause the electric motor to be unstable or have performance degradation. At this time, the control system should take measures to adjust the voltage as soon as possible to avoid the impact of voltage fluctuations on the adjustment of the screen; if the driving voltage fluctuation coefficient is low, it means that the driving voltage is relatively stable, and the operation of the electric motor will be smoother, which can ensure that the screen adjustment operation is performed as expected; voltage fluctuations not only affect the efficiency of the motor, but also directly affect the adjustment accuracy of the screen. For example:

[0053] High voltage fluctuation: The electric motor may provide different speeds and torques under different fluctuation conditions, causing the mesh size and vibration frequency of the screen to shift, reducing the screening effect.

[0054] Low voltage fluctuation: The electric motor can maintain stable speed and torque, ensuring more precise screen adjustment, thereby improving screening effect and system efficiency.

[0055] Therefore, the driving voltage fluctuation of the electric motor is analyzed through the driving voltage fluctuation information of the electric motor, and the driving voltage fluctuation coefficient is obtained to measure the driving voltage fluctuation degree of the electric motor;

[0056] The logic for obtaining the driving voltage fluctuation coefficient is as follows:

[0057] Get the driving voltage signal V(t) of the electric motor = {V(t1), V(t2), ..., V(t N)}; perform data preprocessing on the driving voltage signal, including data cleaning: removing missing values ​​and outliers in the data; feature standardization; calculating the driving voltage fluctuation coefficient qdb, the expression is as follows Where τ represents the time lag, which is an integer multiple of the time interval between voltage signals, V(t n ) represents the time t n The voltage value, Represents the mean value of the voltage signal:

[0058] The second screen adjustment demand index SH2 is calculated according to the control response delay coefficient and the driving voltage fluctuation coefficient. The expression is as follows: SH2 = a1*kyc+a2*qdb, where a1 and a2 are preset proportional coefficients of the control response delay coefficient and the driving voltage fluctuation coefficient, respectively, and a1 and a2 are both greater than 0;

[0059] It should be noted that before calculating the second screen adjustment demand index, it is necessary to ensure that the control response delay coefficient and the driving voltage fluctuation coefficient are normalized. Common normalization methods include Min-Max normalization and Z-Score normalization. a1 and a2 are set according to actual conditions. For example, the expert empowerment method is adopted, that is, experts in related fields are invited to determine the preset proportional coefficients of various indicators through professional opinion surveys and comprehensive evaluations.

[0060] An adjustment demand evaluation module is used to construct an adjustment demand evaluation model according to the first screen adjustment demand index and the second screen adjustment demand index, generate an adjustment demand evaluation index, and evaluate whether the current screen control system can meet the real-time adjustment demand of the screen;

[0061] According to the adjustment demand index of the first screen and the adjustment demand index of the second screen, an adjustment demand evaluation model is constructed to generate the adjustment demand evaluation index Reval. The formula based on the model is as follows Wherein b1 and b2 represent the preset proportional coefficients of the first screen adjustment demand index and the second screen adjustment demand index, respectively, and b1 and b2 are both greater than 0;

[0062] It should be noted that before constructing the adjustment demand assessment model, it is necessary to ensure that the first screen adjustment demand index and the second screen adjustment demand index are normalized; b1 and b2 are set according to actual conditions, for example, the expert empowerment method is adopted, that is, experts in related fields are invited to determine the preset proportional coefficients of various indicators through professional opinion surveys and comprehensive evaluations;

[0063] It can be seen from the above calculation expression that the larger the first screen adjustment demand index and the second screen adjustment demand index are, the larger the adjustment demand evaluation index is, which means that the current screen control system has a greater pressure in meeting the real-time screen adjustment demand, which indicates that the system needs more adjustments or optimizations to cope with more complex sewage treatment environments or control requirements. On the contrary, the smaller the first screen adjustment demand index and the second screen adjustment demand index are, the smaller the adjustment demand evaluation index is, indicating that the current screen control system has a lighter load in meeting the real-time screen adjustment demand, and the system can adapt to changes in sewage relatively easily.

[0064] The adjustment demand assessment index is compared with the preset adjustment demand assessment index threshold to evaluate whether the current screen control system can meet the real-time adjustment demand of the screen, as follows:

[0065] If the adjustment demand assessment index is greater than the adjustment demand assessment index threshold, it means that the current screen control system cannot meet the real-time adjustment demand of the screen, and a warning signal is generated through the warning module; if the adjustment demand assessment index is less than or equal to the adjustment demand assessment index threshold, it means that the current screen control system has a light load in meeting the real-time screen adjustment demand, and the system can adapt to changes in sewage relatively easily, but the real-time adjustment of the screen may still be potentially affected by sewage impurities, control response delays, and driving voltage fluctuations, and a screen adjustment correction signal is generated;

[0066] The early warning module is used to generate an early warning signal when the screen control system cannot meet the real-time adjustment requirements of the screen, and is used to automatically alarm and start the emergency treatment plan;

[0067] When the screen control system cannot meet the real-time adjustment requirements, the early warning module not only sends an early warning signal, but also activates a set of emergency response plans. The specific plans include but are not limited to the following operations:

[0068] System redundancy enabled: Start the backup screen or backup control system to transfer the load from the current screen control system to the backup equipment to prevent the current equipment from overloading.

[0069] Add external auxiliary processing equipment: such as enabling external cleaning devices, increasing vibration frequency, etc., to help remove impurities or prevent screen clogging.

[0070] Limit sewage treatment flow: When the sewage flow is too large, the flow can be temporarily reduced to reduce the load on the screen and give the system more time to adjust.

[0071] A screen adjustment correction module, used to adjust the mesh size and vibration frequency of the screen according to a first screen adjustment demand index when the screen control system meets the real-time adjustment demand of the screen, and to correct the adjustment time of the screen according to a second screen adjustment demand index;

[0072] When a screen adjustment correction signal is generated, a corresponding first screen adjustment demand index and a second screen adjustment demand index are obtained;

[0073] The adjustment time of the screen is corrected according to the second screen adjustment demand index, as follows: tadjust = tadjust 1 +ρ*SH2, where tadjust is the screen adjustment time after correction, tadjust 1 is the initial screen adjustment moment of the screen control system, ρ is the correction factor of the adjustment moment, which is used to control the adjustment amplitude at the adjustment moment, and SH2 is the second screen adjustment demand index;

[0074] The mesh size and vibration frequency of the screen are adjusted according to the adjustment demand index of the first screen, as follows: Wherein Dmesh(tadjust) is the mesh adjustment size required at the corrected screen adjustment moment, Dmesh(tadjust-1) is the mesh size at the moment before the corrected screen adjustment moment, α is the mesh size adjustment coefficient, which is used to control the adjustment amplitude of the mesh size, Fvibrate(tadjust) is the vibration adjustment frequency required at the corrected screen adjustment moment, Fvibrate(tadjust-1) is the vibration frequency at the moment before the corrected screen adjustment moment, β is the vibration frequency adjustment coefficient, which is used to control the adjustment amplitude of the vibration frequency, and SH1 is the first screen adjustment demand index;

[0075] The present invention obtains sewage impurity characteristic information at different times through an impurity monitoring module, establishes a time series of impurity characteristic information and calculates a first screen adjustment demand index, automatically adjusts the working state of the screen according to changes in the specific composition, particle size, flow rate, suspended matter concentration and the like of the sewage, and avoids the efficiency caused by environmental changes in traditional screen treatment methods. The control response module monitors the control response delay of the screen control system and the driving voltage fluctuation of the electric motor, and calculates a second screen adjustment demand index to accurately reflect the response performance of the screen control system, ensuring that the screen adjustment operation can be executed in a timely and accurate manner during the dynamically changing sewage treatment process; the adjustment demand evaluation module comprehensively analyzes the first screen adjustment demand index and the second screen adjustment demand index, generates an adjustment demand evaluation index, evaluates the load capacity of the current screen control system, and determines whether it can meet the real-time adjustment demand. Once it is detected that the screen control system cannot respond to the adjustment needs in time, the early warning module will promptly issue a warning signal and initiate an emergency treatment plan to avoid the adverse effects of system failures on the entire sewage treatment process; when the evaluation results show that the screen control system can meet the real-time adjustment needs, the screen adjustment correction module will adjust the mesh size and vibration frequency of the screen according to real-time data, and correct the adjustment time of the screen to ensure that solid impurities in the sewage are efficiently removed. The precise adjustment mechanism not only improves the efficiency of sewage treatment, but also greatly reduces the failure rate and maintenance cost of the equipment. It effectively improves the working efficiency and stability of the screen in a complex industrial sewage treatment environment, avoids system stagnation caused by screen blockage, equipment failure and other problems, and ensures the smooth progress of the sewage treatment process. At the same time, through intelligent early warning and automatic adjustment mechanisms, low-energy consumption, high-efficiency, and long-term stable sewage treatment can be achieved.

[0076] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0077] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0078] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0079] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0080] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An intelligent monitoring system for environmentally friendly sewage mixing and impurity screening, characterized by: It includes impurity monitoring module, control response module, adjustment demand assessment module, early warning module, and screen adjustment correction module; An impurity monitoring module is used to obtain impurity characteristic information of sewage at different times, establish an impurity characteristic information time series according to the impurity characteristic information of sewage at different times, and calculate the first screen adjustment demand index according to the impurity characteristic information time series; A control response module, used to obtain control response delay information of the screen control system and driving voltage fluctuation information of the electric motor, and calculate the second screen adjustment demand index according to the control response delay information and the driving voltage fluctuation information; An adjustment demand evaluation module is used to construct an adjustment demand evaluation model according to the first screen adjustment demand index and the second screen adjustment demand index, generate an adjustment demand evaluation index, and evaluate whether the current screen control system can meet the real-time adjustment demand of the screen; The early warning module is used to generate an early warning signal when the screen control system cannot meet the real-time adjustment requirements of the screen, and is used to automatically alarm and start the emergency treatment plan; The screen adjustment correction module is used to adjust the mesh size and vibration frequency of the screen according to the first screen adjustment demand index when the screen control system meets the real-time adjustment demand of the screen, and to correct the adjustment time of the screen according to the second screen adjustment demand index.

2. According to claim 1, an environmentally friendly sewage mixing and impurity screening intelligent monitoring system is characterized by: The impurity characteristic information includes, but is not limited to, particle size, sewage flow rate, sewage flow rate, suspended solids concentration, oil content, and fluid viscosity; Obtain impurity characteristic information at different times, and establish an impurity characteristic information time series based on the impurity characteristic information of sewage at different times, and mark the impurity characteristic information time series as XL = {X t }={X1,X2,...,X T }, where X t represents the impurity feature information obtained at time t, t∈{1,2,...,T}, X t is a multidimensional vector, namely X t =[Particle size t , sewage flow rate t , sewage flow t , suspended matter concentration t , oil content t , fluid viscosity t ]; preprocess the impurity characteristic information data in the impurity characteristic information time series, including data cleaning: removing missing values ​​and outliers in the data; Feature standardization; The logistic regression model is used to calculate the first screen adjustment demand index SH1 based on the impurity characteristic information time series. The mathematical expression of the logistic regression model is as follows Where P(Y=1|X) is the output probability of the logistic regression model, indicating the demand probability of screen adjustment, [X1,X2,…,X T ] is the input feature of the logistic regression model, [ω0,ω1,…,ω T ] is the weight parameter of the logistic regression model; The output probability P(Y=1|X) of the logistic regression model is used as the first screen adjustment demand index SH1, that is, SH1=P(Y=1|X).

3. The intelligent monitoring system for environmentally friendly sewage mixing and impurity screening according to claim 1 is characterized by: The control response delay information includes a control response delay coefficient, and the driving voltage fluctuation information includes a driving voltage fluctuation coefficient; the control response delay coefficient and the driving voltage fluctuation coefficient are marked as kyc and qdb respectively.

4. The environmentally friendly sewage mixing and impurity screening intelligent monitoring system according to claim 3 is characterized by: By acquiring the control response delay information of the screen control system, analyzing the control response delay of the screen control system, and acquiring the control response delay coefficient, the control response delay degree of the screen control system is measured; The logic for obtaining the control response delay coefficient is as follows: When the screen control system performs screen control, the control signal receiving time T1, the screen adjustment completion time T2, and the expected response time T3 of each screen control are obtained, and the response time ΔT=T2-T1 is calculated; Calculate the response delay ratio YC, the expression is as follows Calculate the average response delay ratio ypj, the expression is as follows Among them, YC i represents the response delay ratio calculated by the screen control system when the i-th screen control is performed, i∈{1,2,...,I}; Calculate the standard deviation of the response delay ratio ybc, the expression is as follows Calculate the control response delay coefficient kyc, the expression is as follows 5. The environmentally friendly sewage mixing and impurity screening intelligent monitoring system according to claim 3 is characterized by: By using the driving voltage fluctuation information of the electric motor, the driving voltage fluctuation of the electric motor is analyzed, and the driving voltage fluctuation coefficient is obtained to measure the driving voltage fluctuation degree of the electric motor; The logic for obtaining the driving voltage fluctuation coefficient is as follows: Get the driving voltage signal V(t) of the electric motor = {V(t1), V(t2), ..., V(t N )}; Perform data preprocessing on the driving voltage signal, including data cleaning: removing missing values ​​and abnormal values ​​in the data; Feature standardization; Calculate the driving voltage fluctuation coefficient qdb, the expression is as follows Where τ represents the time lag, which is an integer multiple of the time interval between voltage signals, V(t n ) represents the time t n The voltage value, Represents the mean value of the voltage signal: n∈{1,2,...,N}.

6. The environmentally friendly sewage mixing and impurity screening intelligent monitoring system according to claim 3 is characterized by: The second screen adjustment demand index SH2 is calculated according to the control response delay coefficient and the driving voltage fluctuation coefficient. The expression is as follows: SH2=a1*kyc+a2*qdb, wherein a1 and a2 are preset proportional coefficients of the control response delay coefficient and the driving voltage fluctuation coefficient, respectively, and a1 and a2 are both greater than 0.

7. The environmentally friendly sewage mixing and impurity screening intelligent monitoring system according to claim 1 is characterized by: According to the adjustment demand index of the first screen and the adjustment demand index of the second screen, an adjustment demand evaluation model is constructed to generate the adjustment demand evaluation index Reval. The formula based on the model is as follows Wherein b1 and b2 represent the preset proportional coefficients of the first screen adjustment demand index and the second screen adjustment demand index respectively, and b1 and b2 are both greater than 0.

8. The intelligent monitoring system for environmentally friendly sewage mixing and impurity screening according to claim 7 is characterized by: The adjustment demand assessment index is compared with the preset adjustment demand assessment index threshold to evaluate whether the current screen control system can meet the real-time adjustment demand of the screen, as follows: If the adjustment demand assessment index is greater than the adjustment demand assessment index threshold, a warning signal is generated through the warning module; if the adjustment demand assessment index is less than or equal to the adjustment demand assessment index threshold, a screen adjustment correction signal is generated.

9. The intelligent monitoring system for environmentally friendly sewage mixing and impurity screening according to claim 8 is characterized by: When a screen adjustment correction signal is generated, a corresponding first screen adjustment demand index and a second screen adjustment demand index are obtained; The adjustment time of the screen is corrected according to the second screen adjustment demand index, as follows: tadjust = tadjust 1 +ρ*SH2, where tadjust is the screen adjustment time after correction, tadjust 1 is the initial screen adjustment moment of the screen control system, ρ is the correction factor of the adjustment moment, which is used to control the adjustment amplitude at the adjustment moment, and SH2 is the second screen adjustment demand index; The mesh size and vibration frequency of the screen are adjusted according to the adjustment demand index of the first screen, as follows: Wherein, Dmesh(tadjust) is the mesh adjustment size required at the corrected screen adjustment moment, Dmesh(tadjust-1) is the mesh size at the moment before the corrected screen adjustment moment, α is the mesh size adjustment coefficient, which is used to control the adjustment amplitude of the mesh size, Fvibrate(tadjust) is the vibration adjustment frequency required at the corrected screen adjustment moment, Fvibrate(tadjust-1) is the vibration frequency at the moment before the corrected screen adjustment moment, β is the vibration frequency adjustment coefficient, which is used to control the adjustment amplitude of the vibration frequency, and SH1 is the first screen adjustment demand index.

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