Heavy oil sewage treatment system for coal chemical industry

Abstract

The invention relates to the technical field of coal chemical industry sewage treatment, and discloses a coal chemical industry heavy oil sewage treatment system which comprises a pretreatment module, an adjusting tank, a chemical precipitation module, a biological treatment module, a membrane separation module, a sludge treatment module, an environment-friendly chemical treatment module, a waste gas treatment module, a disinfection module and a recycling and discharging module. The pretreatment module is used for removing particulate matters and suspended matters in sewage; the adjusting tank is used for balancing sewage flow and water quality fluctuation; the chemical precipitation module is used for removing suspended matters and colloidal substances in the sewage through chemical agent precipitation; the biological treatment module is used for degrading organic pollutants in the sewage through microorganisms. Through the automatic screen mesh system and the rotational flow grit chamber, particulate matters and grit in sewage are effectively removed, the load on a subsequent treatment module is reduced, and the removal efficiency of suspended matters and colloidal matters is remarkably improved through precise medicament addition and the design of the efficient inclined plate sedimentation tank.

Description

Technical Field

[0001] The invention relates to the technical field of coal chemical wastewater treatment, and in particular to a coal chemical heavy oil wastewater treatment system. Background Art

[0002] In the coal gasification wastewater treatment industry, there are multiple metal ions and heavy oil in the wastewater after deacidification and deammoniation. Therefore, it is necessary to precipitate the heavy metal ions, separate the heavy oil in the wastewater, and remove the phenols in the wastewater. However, in the coal chemical industry, the treatment of heavy oil wastewater has the following deficiencies in actual application:

[0003] In traditional sewage treatment systems, simple screens and grit chambers are usually used in the pretreatment stage to remove particulate matter and grit. However, conventional screen systems have problems such as incomplete cleaning and frequent clogging, which results in the failure to effectively remove particulate matter and grit, and increases the burden on subsequent treatment modules.

[0004] Traditional chemical precipitation modules usually rely on manual dosing and a relatively simple sedimentation tank design, which results in low accuracy of dosing and low precipitation efficiency. The membrane materials used in traditional membrane separation systems are easily contaminated and need to be cleaned frequently, which affects the service life of the membrane.

[0005] Traditional sludge treatment technology mainly relies on physical or chemical methods, which cannot effectively reduce the amount of sludge, resulting in high treatment and disposal costs, further increasing operating costs. Photocatalytic oxidation and plasma technologies are rarely used in traditional waste gas treatment systems, resulting in low waste gas treatment efficiency and short equipment life. Traditional sewage treatment systems lack real-time monitoring and data analysis capabilities, and the adjustment of operating parameters relies on manual experience, which cannot achieve accurate dynamic adjustment.

[0006] Therefore, those skilled in the art provide a coal chemical heavy oil wastewater treatment system to solve the problems raised in the above background technology. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention provides a coal chemical heavy oil wastewater treatment system to solve the problems raised in the above background technology.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a coal chemical heavy oil wastewater treatment system, including a pretreatment module, a regulating tank, a chemical precipitation module, a biological treatment module, a membrane separation module, a sludge treatment module, an environmental chemical treatment module, an exhaust gas treatment module, a disinfection module, and a reuse and discharge module;

[0009] The pretreatment module is used to remove particulate matter and suspended matter in sewage;

[0010] The regulating tank is used to balance the sewage flow and water quality fluctuations;

[0011] The chemical precipitation module removes suspended matter and colloidal substances in sewage through chemical precipitation;

[0012] The biological treatment module degrades organic pollutants in sewage through microorganisms;

[0013] The membrane separation module uses membrane filtration technology to further remove particles and dissolved substances in the water;

[0014] The sludge treatment module treats and disposes of the sludge generated during the sewage treatment process;

[0015] The environmentally friendly chemical treatment module removes refractory organic matter and toxic substances;

[0016] The waste gas treatment module treats harmful gases generated during sewage treatment;

[0017] The disinfection module disinfects the treated water;

[0018] The reuse and discharge module reuses or safely discharges the treated water.

[0019] Preferably, the pretreatment module comprises a screen unit and a grit chamber unit; the screen unit regularly removes sediment on the screen; the grit chamber unit uses cyclonic force to help settle sand particles to collect the settled sand particles;

[0020] The regulating pool includes a monitoring unit, a data analysis unit, and an odor control unit; the monitoring unit is used to monitor water quality and flow in real time; the data analysis unit analyzes data and automatically adjusts the processing flow; the odor control unit uses microorganisms to decompose organic matter in the gas, absorb odor molecules, and purify the gas;

[0021] The chemical precipitation module comprises a reagent dosing unit and a sedimentation tank; the reagent dosing unit controls the amount of the dosing by real-time monitoring of the pollutant concentration; and the sedimentation tank collects the precipitated sludge and sediment.

[0022] Preferably, the biological treatment module includes an intelligent adjustment unit and a sludge return unit; the intelligent adjustment unit is used to optimize operating parameters; the sludge return unit uses membrane technology to separate and return activated sludge to reduce sludge bulking;

[0023] The sludge treatment module includes a reduction unit and a dehydration unit; the reduction unit reduces the volume of sludge through anaerobic digestion and produces biogas to convert the sludge into gas and solid products; the dehydration unit dries the sludge through thermal treatment equipment;

[0024] The exhaust gas treatment module includes a photocatalytic oxidation unit and a plasma unit; the photocatalytic oxidation unit uses a photocatalyst to decompose harmful substances in the exhaust gas under ultraviolet light; the plasma unit uses a plasma reactor to remove harmful gases in the exhaust gas;

[0025] The reuse and discharge module includes a water quality monitoring unit and a reuse unit; the water quality monitoring unit detects various water quality parameters of the reused water; the reuse unit uses big data and AI to optimize the allocation of the reused water.

[0026] Preferably, in the screen unit, a machine learning algorithm is used to predict the blockage of the screen based on sensor data;

[0027] Support vector machine algorithm formula:

[0028] f(x)=sign(w T x+b),

[0029] Among them, w is the weight vector, x is the input feature vector, and b is the bias term;

[0030] Optimization problem:

[0031]

[0032] Where C is the regularization parameter, ξ i is the slack variable, N is the number of samples;

[0033] The screen flux formula for calculating screen efficiency is:

[0034]

[0035] Where Q is the screen flux, A is the effective area of ​​the screen, and P in and P out is the pressure entering and leaving the screen, μ is the viscosity of the liquid, and Δx is the pore thickness of the screen.

[0036] Preferably, in the grit chamber unit, the flow rate and settling rate of the cyclone grit chamber can be estimated by the following equation:

[0037]

[0038] Among them, v s is the sedimentation velocity, g is the gravitational acceleration, d is the particle diameter, ρ p and ρ f is the density of the particle and the liquid, μ is the viscosity of the liquid;

[0039] Flow velocity distribution in the cyclone device:

[0040]

[0041] Among them, v avg is the average flow velocity, R is the radius of the cyclone, r is the particle settling radius, and ω is the angular velocity of the cyclone;

[0042] Calculation of sedimentation efficiency of grit chamber:

[0043]

[0044] Among them, η s is the sedimentation efficiency, V s is the volume of the grit chamber, and A is the effective area of ​​the grit chamber.

[0045] Preferably, in the odor control unit, the Langmu ir adsorption isotherm is used to describe the adsorption process of odor molecules. The Langmu ir adsorption isotherm formula is:

[0046]

[0047] Among them, q e is the amount of gas adsorbed per unit mass, q m is the maximum adsorption capacity, K L is the Langmuir constant, C e is the equilibrium concentration;

[0048] Gas removal efficiency calculation formula:

[0049]

[0050] Where η is the removal efficiency, C in is the gas concentration entering the odor control unit, C out is the gas concentration leaving the odor control unit.

[0051] Preferably, in the reagent dosing unit, the reagent dosing system based on feedback control uses a PID controller to dynamically adjust the dosage of the reagent to ensure the best precipitation effect;

[0052] PID controller formula:

[0053]

[0054] Among them, u(t) is the dosage of the agent, e(t) is the error, K p is the proportional gain, K i is the integral gain, K d is the differential gain;

[0055] Calculation formula for the dosage requirement of the reagent:

[0056]

[0057] Where D is the required dose, C target is the target concentration, C initial is the initial concentration, K is the dosage coefficient of the reagent, and V is the volume of treated water;

[0058] In the sedimentation tank, Stokes' law is used to estimate the settling velocity of particles in the sedimentation tank, and the calculation formula is:

[0059]

[0060] Among them, v s is the sedimentation velocity, ρ p and ρ f is the density of the particle and the liquid, g is the acceleration due to gravity, d is the particle diameter, and μ is the viscosity of the liquid;

[0061] According to the sedimentation velocity and water flow distribution, the continuous sedimentation tank model is used to calculate the effective sedimentation area of ​​the sedimentation tank. The calculation formula is:

[0062]

[0063] Where A is the effective sedimentation area of ​​the sedimentation tank, Q is the sewage flow, H is the height of the sedimentation tank, and v s is the settling velocity of the particle;

[0064] Particle removal rate calculation formula:

[0065]

[0066] Where η is the precipitation efficiency, C in is the influent concentration, C out is the outlet water concentration.

[0067] Preferably, in the sludge return unit, an activated sludge model is used to describe and optimize the sludge return process. The activated sludge model formula is:

[0068] Calculation of sludge concentration:

[0069] X=X0·exp(-k d t),

[0070] Among them, X is the sludge concentration, X0 is the initial sludge concentration, k d is the sludge degradation rate constant, t is the time;

[0071] The sludge return rate calculation uses the mass balance equation to calculate the amount of return sludge. The algorithm formula is:

[0072]

[0073] Among them, Qr is the return flow, X in and X out is the sludge concentration before and after the return, V is the reactor volume, X r is the concentration of return sludge;

[0074] The sludge bulking control model uses the sludge bulking prediction model to predict and control the sludge bulking phenomenon. The algorithm formula is:

[0075]

[0076] Where F is the expansion factor, X MLSS is the suspended solids concentration of the mixed solution, X MLVSS is the concentration of volatile suspended solids in the mixed liquor.

[0077] Preferably, in the reduction unit, an anaerobic digestion kinetic model is used to optimize the anaerobic digestion process of the sludge;

[0078] Anaerobic digestion kinetic equation:

[0079]

[0080] Where r is the sludge degradation rate, r max is the maximum degradation rate, S is the substrate concentration, K s is the half-saturation constant;

[0081] Gas generation model in anaerobic digestion reaction model:

[0082]

[0083] Where G is the amount of gas generated, V gas is the gas generation, C gas is the gas concentration, COD is the chemical oxygen demand;

[0084] Sludge gasification technology uses the sludge gasification reaction equation to calculate the sludge reduction during the gasification process. The algorithm formula is:

[0085]

[0086] Among them, Reduction is the reduction rate, M input and M output is the input and output sludge mass;

[0087] In the dehydration unit, the sludge dehydration rate model uses a filter press model to describe the efficiency of the dehydration process;

[0088] Filter press dehydration rate equation:

[0089]

[0090] in, is the dehydration rate, P is the pressure, A is the filter plate area, μ is the liquid viscosity, and ΔL is the filter cake thickness;

[0091] Moisture content model for calculating sludge moisture content:

[0092]

[0093] Among them, Moisture Content is the moisture content, W wet and W dry is the mass of wet sludge and dry sludge;

[0094] The centrifugal dehydration model uses the centrifugal dehydration rate equation to optimize dehydration efficiency:

[0095]

[0096] Among them, Centrifugal Force is the centrifugal force, m is the sludge mass, r is the centrifugal radius, ω is the angular velocity, and g is the gravitational acceleration.

[0097] Preferably, in the reuse unit, a genetic algorithm is used to optimize the water quality parameters and treatment process of the reused water, and the genetic algorithm optimization model is:

[0098] Fitness function:

[0099]

[0100] Among them, f(x) is the fitness value, and Objective Function is the objective function value;

[0101] Select an action:

[0102]

[0103] Among them, P i is the individual fitness, P i+1 is the probability of selection;

[0104] Crossover operation:

[0105]

[0106] Among them, C ij is the new individual after crossover, P i,j and P i+1,j is the parent individual;

[0107] Mutation operation:

[0108] P i,j =P i,j+δ·Rand,

[0109] Among them, δ is the variation amplitude, Rand is the random value;

[0110] Reclaimed water quality prediction uses artificial neural network for water quality prediction and reused water quality optimization. The feedforward neural network equation is:

[0111] y=σ(W·x+b),

[0112] Among them, y is the predicted output, σ is the activation function, W is the weight matrix, x is the input data, and b is the bias term.

[0113] The present invention provides a coal chemical heavy oil wastewater treatment system. It has the following beneficial effects:

[0114] 1. The present invention effectively removes particulate matter and sand in sewage through an automated screen system and a cyclone sand settling tank, reduces the load on subsequent treatment modules, and significantly improves the removal efficiency of suspended matter and colloidal matter through precise reagent addition and high-efficiency inclined plate sedimentation tank design. At the same time, the sludge return technology optimizes the degradation of organic matter and reduces sludge swelling.

[0115] 2. The present invention reduces membrane pollution and improves water quality through self-cleaning membrane materials and online cleaning systems. Anaerobic digestion and sludge gasification technologies significantly reduce the amount of sludge and reduce processing and disposal costs. The use of energy-saving dehydration equipment reduces energy consumption, reduces operating costs, optimizes water reuse and allocation, improves water resource utilization efficiency, and further reduces processing costs. At the same time, photocatalytic oxidation and plasma technology enhance the waste gas treatment effect and the life of the equipment.

[0116] 3. The present invention integrates real-time monitoring, data analysis, fuzzy logic control and other technologies to achieve precise dynamic adjustment of water quality and flow, and uses artificial intelligence and dynamic optimization algorithms to further improve the efficiency and stability of sludge treatment, ensure the stability of recycled water quality, optimize water reuse and discharge strategies, and improve the economy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0117] Figure 1 is a system diagram of the present invention;

[0118] Figure 2 It is a schematic diagram of a pre-processing module of the present invention;

[0119] Figure 3 It is a schematic diagram of a regulating tank of the present invention;

[0120] Figure 4 It is a schematic diagram of the chemical precipitation module of the present invention;

[0121] Figure 5 is a schematic diagram of a biological treatment module of the present invention;

[0122] Figure 6 It is a schematic diagram of a sludge treatment module of the present invention;

[0123] Figure 7 It is a schematic diagram of the exhaust gas treatment module of the present invention;

[0124] Figure 8 It is a schematic diagram of the reuse and discharge module of the present invention. DETAILED DESCRIPTION

[0125] In order to make the technical personnel in the technical field understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly and completely described below in combination with the drawings in the embodiment of the present invention. Obviously, the described embodiment is a partial embodiment of the present invention, not a complete embodiment. Based on the embodiment of the present invention, other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present invention.

[0126] The present invention is described in detail below in conjunction with the accompanying drawings:

[0127] Example:

[0128] Please refer to the attached Figure 1 - Attachment Figure 8 The embodiment of the present invention provides a coal chemical heavy oil wastewater treatment system, including a pretreatment module, a regulating tank, a chemical precipitation module, a biological treatment module, a membrane separation module, a sludge treatment module, an environmental protection chemical treatment module, a waste gas treatment module, a disinfection module, and a reuse and discharge module; the pretreatment module is used to remove particulate matter and suspended matter in the wastewater; the regulating tank is used to balance the wastewater flow and water quality fluctuations; the chemical precipitation module removes suspended matter and colloidal matter in the wastewater through chemical precipitation; the biological treatment module degrades organic pollutants in the wastewater through microorganisms; the membrane separation module uses membrane filtration technology to further remove particles and soluble substances in the water; the sludge treatment module treats and disposes of the sludge generated in the wastewater treatment process; the environmental protection chemical treatment module removes difficult-to-degrade organic matter and toxic substances; the waste gas treatment module treats harmful gases generated in the wastewater treatment process; the disinfection module disinfects the treated water; the reuse and discharge module reuses or safely discharges the treated water.

[0129] The benefits of the pretreatment module are to reduce the maintenance frequency and improve the effects of subsequent chemical precipitation and biological treatment; the benefits of the regulating tank are to maintain the stability and consistency of the system and improve the overall treatment efficiency; the benefits of the chemical precipitation module are to effectively remove suspended matter and colloidal substances, reduce the burden on biological treatment and membrane separation, and improve the treatment effect; the biological treatment module reduces the organic load in the water and further improves the water quality; the benefits of the membrane separation module are to remove pollutants and improve the stability and reliability of the effluent water quality; the benefits of the sludge treatment module are to reduce the amount of sludge, reduce the cost of treatment and disposal, and reduce operating costs; the benefits of the environmental protection chemical treatment module are to use green chemicals and catalyst recovery technology to reduce secondary pollution and provide guarantees for reuse or discharge; the benefits of the exhaust gas treatment module are to improve the exhaust gas treatment effect, reduce the impact on the environment, and enhance the durability and life of the equipment; the benefits of the disinfection module are to effectively kill pathogenic microorganisms, ensure water quality safety, and reduce potential impacts on the environment; the benefits of the reuse and discharge module are to improve the stability of the reused water quality and the reuse efficiency, save water resources, and reduce negative impacts on the environment.

[0130] The pretreatment module includes a screen unit and a grit chamber unit; the screen unit regularly removes the sediment on the screen; the grit chamber unit uses cyclonic force to help settle the sand particles to collect the settled sand particles; the regulating tank includes a monitoring unit, a data analysis unit, and an odor control unit; the monitoring unit is used to monitor the water quality and flow in real time; the data analysis unit analyzes the data and automatically adjusts the treatment process; the odor control unit uses microorganisms to decompose organic matter in the gas, adsorb odor molecules, and purify the gas; the chemical precipitation module includes a reagent dosing unit and a sedimentation tank; the reagent dosing unit controls the amount of reagent added by real-time monitoring of the pollutant concentration; the sedimentation tank collects the precipitated sludge and sediment; the biological treatment module includes an intelligent regulation unit and a sludge return unit; the intelligent regulation unit is used to optimize the operating parameters number; the sludge return unit uses membrane technology to separate and return activated sludge to reduce sludge bulking; the sludge treatment module includes a reduction unit and a dehydration unit; the reduction unit reduces the sludge volume through anaerobic digestion and produces biogas, which can convert the sludge into gas and solid products; the dehydration unit dries the sludge through thermal treatment equipment; the waste gas treatment module includes a photocatalytic oxidation unit and a plasma unit; the photocatalytic oxidation unit uses a photocatalyst to decompose harmful substances in the waste gas under ultraviolet light; the plasma unit uses a plasma reactor to remove harmful gases in the waste gas; the reuse and discharge module includes a water quality monitoring unit and a reuse unit; the water quality monitoring unit detects various water quality parameters of the reused water; the reuse unit uses big data and AI to optimize the allocation of reused water.

[0131] The benefits of the screen unit are to regularly remove sediments to prevent screen clogging, reduce the burden on subsequent treatment modules, and improve overall treatment efficiency; the benefits of the grit chamber unit are to improve grit efficiency, ensure that the settled sand is effectively collected and processed, and reduce the wear and maintenance requirements of subsequent equipment caused by grit; the benefits of the monitoring unit are to quickly respond to water quality and flow fluctuations and optimize treatment effects; the benefits of the data analysis unit are to improve the system's adaptability, improve treatment efficiency and stability; the benefits of the odor control unit are to improve the comfort of the treatment environment; the benefits of the drug dosing unit are to accurately control the amount of drugs to improve the removal efficiency of suspended solids and colloids; the benefits of the sedimentation tank are to effectively collect sediments The benefits of the intelligent adjustment unit are to improve the biological treatment effect and reduce fluctuations and failures; the sludge return unit reduces sludge swelling; the benefits of the reduction unit are to reduce treatment and disposal costs and increase economic benefits; the benefits of the dehydration unit are to reduce moisture content and reduce transportation and disposal costs; the benefits of the photocatalytic oxidation unit are to improve the treatment effect; the benefits of the plasma unit are to improve the exhaust gas treatment effect and the durability of the exhaust gas treatment equipment; the benefits of the water quality monitoring unit are to ensure the stability and safety of water quality and optimize the quality of recycled water; the benefits of the reuse unit are to improve the efficiency of water resource utilization, reduce treatment costs and improve economic benefits.

[0132] In the screen unit, a machine learning algorithm is used to predict screen blockage based on sensor data;

[0133] Support vector machine algorithm formula:

[0134] f(x)=sign(w T x+b),

[0135] Among them, w is the weight vector, x is the input feature vector, and b is the bias term;

[0136] Optimization problem:

[0137]

[0138] Where C is the regularization parameter, ξ i is the slack variable, N is the number of samples;

[0139] The screen flux formula for calculating screen efficiency is:

[0140]

[0141] Where Q is the screen flux, A is the effective area of ​​the screen, and P in and P out is the pressure entering and leaving the screen, μ is the viscosity of the liquid, and Δx is the pore thickness of the screen.

[0142] Support vector machine algorithm formula function By finding the optimal hyperplane, the support vector machine can effectively separate different categories of data. In the screen unit, the support vector machine model predicts the blockage of the screen based on sensor data, helping to maintain and adjust the operating status of the screen in a timely manner;

[0143] The function of the screen flux calculation formula is to calculate the flux of the screen, that is, the volume of liquid passing through the screen per unit time, which helps to evaluate the filtration efficiency and processing capacity of the screen. By analyzing the screen flux, the degree of blockage and operating status of the screen can be determined, and the operating conditions can be adjusted or maintenance can be performed to keep the screen in the best working condition.

[0144] In the grit chamber unit, the flow rate and settling rate of the cyclone grit chamber can be estimated by the following equation:

[0145]

[0146] Among them, v s is the sedimentation velocity, g is the gravitational acceleration, d is the particle diameter, ρ p and ρ f is the density of the particle and the liquid, μ is the viscosity of the liquid;

[0147] Flow velocity distribution in the cyclone device:

[0148]

[0149] Among them, v avg is the average flow velocity, R is the radius of the cyclone, r is the particle settling radius, and ω is the angular velocity of the cyclone;

[0150] Calculation of sedimentation efficiency of grit chamber:

[0151]

[0152] Among them, η s is the sedimentation efficiency, V s is the volume of the grit chamber, and A is the effective area of ​​the grit chamber.

[0153] The sedimentation velocity estimation formula is used to estimate the sedimentation velocity of particles in liquid, which helps determine the design and operating parameters of the grit chamber. By calculating the sedimentation velocity, the size and configuration of the grit chamber can be designed to ensure effective removal of settled particles and improve treatment efficiency.

[0154] The velocity distribution formula in the cyclone device helps to distribute the velocity inside the cyclone device, thereby optimizing the cyclone conditions and improving the grit settling efficiency. By analyzing the velocity distribution, the design and operating conditions of the cyclone device can be adjusted to make the distribution of settled particles more uniform, thereby improving the grit settling efficiency of the grit chamber.

[0155] The function of the sedimentation efficiency calculation formula of the grit chamber is to evaluate the actual sedimentation effect and treatment capacity of the grit chamber by calculating the sedimentation efficiency, which helps to adjust the operating conditions and design parameters of the grit chamber, improve the grit effect, and reduce the system maintenance requirements.

[0156] In the odor control unit, the Langmu ir adsorption isotherm is used to describe the adsorption process of odor molecules. The Langmu ir adsorption isotherm formula is:

[0157]

[0158] Among them, q e is the amount of gas adsorbed per unit mass, q m is the maximum adsorption capacity, K L is the Langmuir constant, C e is the equilibrium concentration;

[0159] Gas removal efficiency calculation formula:

[0160]

[0161] Where η is the removal efficiency, C in is the gas concentration entering the odor control unit, C out is the gas concentration leaving the odor control unit.

[0162] The Langmuir adsorption isotherm is used to describe the adsorption process of gas molecules on the adsorption medium. Assuming that each adsorption site can adsorb a single gas molecule, the formula can be used to predict the adsorption capacity of the adsorption medium under a specific gas concentration, help design and optimize the adsorption device of the odor control system, determine the maximum adsorption amount and adsorption constant of the adsorption material, and evaluate its performance in practical applications.

[0163] The gas removal efficiency calculation formula is used to calculate the removal efficiency of the odor control unit on odor molecules in the gas, providing a quantitative evaluation of the treatment effect. By analyzing the removal efficiency, the operating conditions can be adjusted to improve the treatment capacity and efficiency of the odor control unit and reduce the emission of odor molecules in the gas.

[0164] In the reagent dosing unit, the reagent dosing system based on feedback control uses a PID controller to dynamically adjust the dosage of the reagent to ensure the best precipitation effect;

[0165] PID controller formula:

[0166]

[0167] Among them, u(t) is the dosage of the agent, e(t) is the error, K p is the proportional gain, K iis the integral gain, K d is the differential gain;

[0168] Calculation formula for reagent dosage requirements:

[0169]

[0170] Where D is the required dose, C target is the target concentration, C initial is the initial concentration, K is the dosage coefficient of the reagent, and V is the volume of treated water;

[0171] In the sedimentation tank, Stokes' law is used to estimate the settling velocity of particles in the sedimentation tank. The calculation formula is:

[0172]

[0173] Among them, v s is the sedimentation velocity, ρ p and ρ f is the density of the particle and the liquid, g is the acceleration due to gravity, d is the particle diameter, and μ is the viscosity of the liquid;

[0174] According to the sedimentation velocity and water flow distribution, the continuous sedimentation tank model is used to calculate the effective sedimentation area of ​​the sedimentation tank. The calculation formula is:

[0175]

[0176] Where A is the effective sedimentation area of ​​the sedimentation tank, Q is the sewage flow, H is the height of the sedimentation tank, and v s is the settling velocity of the particle;

[0177] Particle removal rate calculation formula:

[0178]

[0179] Where η is the precipitation efficiency, C in is the influent concentration, C out is the outlet water concentration.

[0180] The PID controller formula dynamically adjusts the dosage of the reagent according to the error and the rate of change of the error to ensure that the precipitation effect is always maintained at the best level. By accurately controlling the dosage of the reagent, the PID controller optimizes the precipitation process, improves the treatment effect, reduces the waste of reagents, and adjusts the system parameters to ensure the stability of the reaction system and reduce system fluctuations and overreactions;

[0181] The formula for calculating the demand for chemical dosing is used to calculate the required dosage of chemical based on the target concentration, initial concentration and treated water volume, ensuring the dosage of chemical. By accurately calculating the dosage of chemical, excessive or insufficient dosage can be avoided, thus improving the treatment effect and reducing costs.

[0182] Stokes' law formula calculates the settling velocity of particles in liquid, which helps to design the size and operating parameters of the sedimentation tank. The operating conditions of the sedimentation tank can be adjusted to ensure effective particle removal;

[0183] The continuous sedimentation tank model formula helps determine the effective sedimentation area of ​​the sedimentation tank, ensuring that the design and operation can meet the treatment requirements. By calculating the effective sedimentation area, the design of the sedimentation tank can be optimized to improve the sedimentation efficiency and treatment capacity;

[0184] The particle removal rate calculation formula is used to evaluate the treatment effect of the sedimentation tank. By analyzing the removal rate, the operating parameters and design of the sedimentation tank can be optimized to ensure that the treatment goals are achieved.

[0185] In the sludge return unit, the activated sludge model is used to describe and optimize the sludge return process. The activated sludge model formula is:

[0186] Calculation of sludge concentration:

[0187] X=X0·exp(-k d t),

[0188] Among them, X is the sludge concentration, X0 is the initial sludge concentration, k d is the sludge degradation rate constant, t is the time;

[0189] The sludge return rate calculation uses the mass balance equation to calculate the amount of return sludge. The algorithm formula is:

[0190]

[0191] Among them, Q r is the return flow, X in and X out is the sludge concentration before and after the return, V is the reactor volume, X r is the concentration of return sludge;

[0192] The sludge bulking control model uses the sludge bulking prediction model to predict and control the sludge bulking phenomenon. The algorithm formula is:

[0193]

[0194] Where F is the expansion factor, X MLSS is the suspended solids concentration of the mixed solution, X MLVSS is the concentration of volatile suspended solids in the mixed liquor.

[0195] The sludge concentration calculation formula predicts the concentration of sludge at a specific time. Based on the sludge degradation rate constant and the influence of time, by predicting the sludge concentration, the sewage treatment operation can be adjusted to maintain the best treatment effect and ensure the stability and efficiency of the system.

[0196] The sludge return rate calculation formula calculates the required sludge return flow rate to ensure that the amount of returned sludge can meet the treatment needs, which can optimize the sludge treatment process and improve the efficiency and stability of the sludge return system;

[0197] The sludge bulking control model calculates the expansion factor and predicts the degree of sludge bulking, which helps to identify and control sludge bulking problems. According to the changes in the expansion factor, the treatment operations and conditions are adjusted to control and reduce the sludge bulking phenomenon and improve the stability and efficiency of the sewage treatment system.

[0198] In the reduction unit, the anaerobic digestion kinetic model is used to optimize the anaerobic digestion process of sludge;

[0199] Anaerobic digestion kinetic equation:

[0200]

[0201] Where r is the sludge degradation rate, r max is the maximum degradation rate, S is the substrate concentration, K s is the half-saturation constant;

[0202] Gas generation model in anaerobic digestion reaction model:

[0203]

[0204] Where G is the amount of gas generated, V gas is the gas generation, C gas is the gas concentration, COD is the chemical oxygen demand;

[0205] Sludge gasification technology uses the sludge gasification reaction equation to calculate the sludge reduction during the gasification process. The algorithm formula is:

[0206]

[0207] Among them, Reduction is the reduction rate, M input and M output is the input and output sludge mass;

[0208] In the dewatering unit, the sludge dewatering rate model uses the filter press model to describe the efficiency of the dewatering process;

[0209] Filter press dehydration rate equation:

[0210]

[0211] in, is the dehydration rate, P is the pressure, A is the filter plate area, μ is the liquid viscosity, and ΔL is the filter cake thickness;

[0212] Moisture content model for calculating sludge moisture content:

[0213]

[0214] Among them, Moisture Content is the moisture content, W wet and W dry is the mass of wet sludge and dry sludge;

[0215] The centrifugal dehydration model uses the centrifugal dehydration rate equation to optimize dehydration efficiency:

[0216]

[0217] Among them, Centrifugal Force is the centrifugal force, m is the sludge mass, r is the centrifugal radius, ω is the angular velocity, and g is the gravitational acceleration.

[0218] The anaerobic digestion kinetic model describes the degradation of sludge over time during the anaerobic digestion process, which helps to optimize the rate and efficiency of the digestion process. By adjusting the digestion conditions and parameters, the degradation rate of sludge can be increased and the overall process of anaerobic digestion can be optimized.

[0219] The gas generation model calculates the amount of gas produced during anaerobic digestion, which helps to evaluate the efficiency of the digestion process. By controlling and optimizing digestion conditions, the gas generation can be increased and energy recovery can be enhanced.

[0220] The role of sludge gasification technology is to calculate the sludge reduction rate during the gasification process, which helps to evaluate the effect of gasification technology and adjust the operating conditions to improve the efficiency of the gasification process and reduce the amount of sludge after treatment;

[0221] The filter press dehydration rate model acts on the rate at which sludge is treated, which helps to optimize the efficiency of the filter press process. By adjusting parameters such as pressure and filter plate area, the dehydration rate can be increased and the sludge moisture content can be reduced.

[0222] Sludge moisture content calculation is used to calculate the moisture content of sludge, which helps to evaluate the effect of dehydration process. By monitoring and adjusting the moisture content, the dehydration operation can be optimized and the yield of dry sludge can be increased.

[0223] The centrifugal dehydration model helps calculate and optimize the rate of the centrifugal dehydration process. By adjusting the centrifugal force, radius and angular velocity, the dehydration efficiency can be improved. By optimizing the centrifugal dehydration conditions, the sludge moisture content can be reduced, and the treatment effect and resource utilization efficiency can be improved.

[0224] In the reuse unit, genetic algorithms are used to optimize the water quality parameters and treatment process of the reused water. The genetic algorithm optimization model is as follows:

[0225] Fitness function:

[0226]

[0227] Among them, f(x) is the fitness value, and Objective Function is the objective function value;

[0228] Select an action:

[0229]

[0230] Among them, P i is the individual fitness, P i+1 is the probability of selection;

[0231] Crossover operation:

[0232]

[0233] Among them, C ij is the new individual after crossover, P i,j and P i+1,j is the parent individual;

[0234] Mutation operation:

[0235] P i,j =P i,j +δ·Rand,

[0236] Among them, δ is the variation amplitude, Rand is the random value;

[0237] Reclaimed water quality prediction uses artificial neural network for water quality prediction and reused water quality optimization. The feedforward neural network equation is:

[0238] y=σ(W·x+b),

[0239] Among them, y is the predicted output, σ is the activation function, W is the weight matrix, x is the input data, and b is the bias term.

[0240] The genetic algorithm optimization model evaluates the quality of individuals. By calculating the fitness value, the genetic algorithm can perform genetic operations on individuals with better performance, thereby optimizing the water quality parameters and treatment process of the reused water.

[0241] The selection operation formula is used to determine the probability of an individual being selected. Generally, individuals with higher fitness values ​​have a higher probability of being selected. By selecting individuals with higher fitness, the genetic algorithm can retain excellent genes and promote the evolution of the population towards a better solution.

[0242] The crossover operation generates a new individual by combining the genetic information of two parent individuals. The introduction of new gene combinations will produce a better solution, which helps to improve the diversity of the population and avoid falling into the local optimal solution.

[0243] The mutation operation introduces new genetic information by randomly modifying individual genes, which helps to explore undiscovered areas in the solution space. The mutation operation can prevent the population from converging to the local optimal solution too early and increase the possibility of finding the global optimal solution.

[0244] The feedforward neural network prediction function is used to predict the water quality of reused water based on the input water quality parameters. It can capture nonlinear relationships and make accurate predictions. Through the prediction output, the feedforward neural network helps optimize the treatment process, ensure that the reused water quality meets the expected standards, and improve the reuse efficiency.

[0245] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A coal chemical heavy oil wastewater treatment system, characterized in that: It includes pretreatment module, regulating tank, chemical precipitation module, biological treatment module, membrane separation module, sludge treatment module, environmental chemical treatment module, waste gas treatment module, disinfection module, reuse and discharge module; The pretreatment module is used to remove particulate matter and suspended matter in sewage; The regulating tank is used to balance the sewage flow and water quality fluctuations; The chemical precipitation module removes suspended matter and colloidal substances in sewage through chemical precipitation; The biological treatment module degrades organic pollutants in sewage through microorganisms; The membrane separation module uses membrane filtration technology to further remove particles and dissolved substances in the water; The sludge treatment module treats and disposes of the sludge generated during the sewage treatment process; The environmentally friendly chemical treatment module removes refractory organic matter and toxic substances; The waste gas treatment module treats harmful gases generated during sewage treatment; The disinfection module disinfects the treated water; The reuse and discharge module reuses or safely discharges the treated water.

2. A coal chemical heavy oil wastewater treatment system according to claim 1, characterized in that: The pretreatment module includes a screen unit and a grit chamber unit; the screen unit regularly removes sediments on the screen; the grit chamber unit uses cyclonic force to help settle sand particles to collect the settled sand particles; The regulating pool includes a monitoring unit, a data analysis unit, and an odor control unit; the monitoring unit is used to monitor water quality and flow in real time; the data analysis unit analyzes data and automatically adjusts the processing flow; the odor control unit uses microorganisms to decompose organic matter in the gas, absorb odor molecules, and purify the gas; The chemical precipitation module comprises a reagent dosing unit and a sedimentation tank; the reagent dosing unit controls the amount of the dosing by real-time monitoring of the pollutant concentration; and the sedimentation tank collects the precipitated sludge and sediment.

3. A coal chemical heavy oil wastewater treatment system according to claim 1, characterized in that: The biological treatment module includes an intelligent adjustment unit and a sludge return unit; the intelligent adjustment unit is used to optimize operating parameters; the sludge return unit uses membrane technology to separate and return activated sludge to reduce sludge bulking; The sludge treatment module includes a reduction unit and a dehydration unit; the reduction unit reduces the volume of sludge through anaerobic digestion and produces biogas to convert the sludge into gas and solid products; the dehydration unit dries the sludge through thermal treatment equipment; The exhaust gas treatment module includes a photocatalytic oxidation unit and a plasma unit; the photocatalytic oxidation unit uses a photocatalyst to decompose harmful substances in the exhaust gas under ultraviolet light; the plasma unit uses a plasma reactor to remove harmful gases in the exhaust gas; The reuse and discharge module includes a water quality monitoring unit and a reuse unit; the water quality monitoring unit detects various water quality parameters of the reused water; the reuse unit uses big data and AI to optimize the allocation of the reused water.

4. A coal chemical heavy oil wastewater treatment system according to claim 2, characterized in that: In the screen unit, a machine learning algorithm is used to predict the blockage of the screen based on sensor data; Support vector machine algorithm formula: f(x)=sign(w T x+b), Among them, w is the weight vector, x is the input feature vector, and b is the bias term; Optimization problem: Where C is the regularization parameter, ξ i is the slack variable, N is the number of samples; The screen flux formula for calculating screen efficiency is: Where Q is the screen flux, A is the effective area of ​​the screen, and P in and P out is the pressure entering and leaving the screen, μ is the viscosity of the liquid, and Δx is the pore thickness of the screen.

5. A coal chemical heavy oil wastewater treatment system according to claim 2, characterized in that: In the grit chamber unit, the flow rate and settling rate of the cyclone grit chamber can be estimated by the following equation: Among them, v s is the sedimentation velocity, g is the gravitational acceleration, d is the particle diameter, ρ p and ρ f is the density of the particle and the liquid, μ is the viscosity of the liquid; Flow velocity distribution in the cyclone device: Among them, v avg is the average flow velocity, R is the radius of the cyclone, r is the particle settling radius, and ω is the angular velocity of the cyclone; Calculation of sedimentation efficiency of grit chamber: Among them, η s is the sedimentation efficiency, V s is the volume of the grit chamber, and A is the effective area of ​​the grit chamber.

6. A coal chemical heavy oil wastewater treatment system according to claim 2, characterized in that: In the odor control unit, the Langmuir adsorption isotherm is used to describe the adsorption process of odor molecules. The Langmuir adsorption isotherm formula is: Among them, q e is the amount of gas adsorbed per unit mass, q m is the maximum adsorption capacity, K L is the Langmuir constant, C e is the equilibrium concentration; Gas removal efficiency calculation formula: Where η is the removal efficiency, C in is the gas concentration entering the odor control unit, C out is the gas concentration leaving the odor control unit.

7. A coal chemical heavy oil wastewater treatment system according to claim 2, characterized in that: In the reagent dosing unit, the reagent dosing system based on feedback control uses a PID controller to dynamically adjust the dosage of the reagent to ensure the best precipitation effect; PID controller formula: Among them, u(t) is the dosage of the agent, e(t) is the error, K p is the proportional gain, K i is the integral gain, K d is the differential gain; Calculation formula for reagent dosage requirements: Where D is the required dose, C target is the target concentration, C initial is the initial concentration, K is the dosage coefficient of the reagent, and V is the volume of treated water; In the sedimentation tank, Stokes' law is used to estimate the settling velocity of particles in the sedimentation tank, and the calculation formula is: Among them, v s is the sedimentation velocity, ρ p and ρ f is the density of the particle and the liquid, g is the acceleration due to gravity, d is the particle diameter, and μ is the viscosity of the liquid; According to the sedimentation velocity and water flow distribution, the continuous sedimentation tank model is used to calculate the effective sedimentation area of ​​the sedimentation tank. The calculation formula is: Where A is the effective sedimentation area of ​​the sedimentation tank, Q is the sewage flow, H is the height of the sedimentation tank, and v s is the settling velocity of the particle; Particle removal rate calculation formula: Where η is the precipitation efficiency, C in is the influent concentration, C out is the outlet water concentration.

8. A coal chemical heavy oil wastewater treatment system according to claim 3, characterized in that: In the sludge return unit, an activated sludge model is used to describe and optimize the sludge return process. The activated sludge model formula is: Calculation of sludge concentration: X=X0·exp(-k d ·t), Among them, X is the sludge concentration, X0 is the initial sludge concentration, k d is the sludge degradation rate constant, t is the time; The sludge return rate calculation uses the mass balance equation to calculate the amount of return sludge. The algorithm formula is: Among them, Q r is the return flow, X in and X out is the sludge concentration before and after the return, V is the reactor volume, X r is the concentration of return sludge; The sludge bulking control model uses the sludge bulking prediction model to predict and control the sludge bulking phenomenon. The algorithm formula is: Where F is the expansion factor, X MLSS is the suspended solids concentration of the mixed solution, X MLVSS is the concentration of volatile suspended solids in the mixed liquor.

9. A coal chemical heavy oil wastewater treatment system according to claim 3, characterized in that: In the reduction unit, an anaerobic digestion kinetic model is used to optimize the anaerobic digestion process of the sludge; Anaerobic digestion kinetic equation: Where r is the sludge degradation rate, r max is the maximum degradation rate, S is the substrate concentration, K s is the half-saturation constant; Gas generation model in anaerobic digestion reaction model: Where G is the amount of gas generated, V gas is the gas generation, C gas is the gas concentration, COD is the chemical oxygen demand; Sludge gasification technology uses the sludge gasification reaction equation to calculate the sludge reduction during the gasification process. The algorithm formula is: Among them, Reduction is the reduction rate, M input and M output is the input and output sludge mass; In the dehydration unit, the sludge dehydration rate model uses a filter press model to describe the efficiency of the dehydration process; Filter press dehydration rate equation: in, is the dehydration rate, P is the pressure, A is the filter plate area, μ is the liquid viscosity, and ΔL is the filter cake thickness; Moisture content model for calculating sludge moisture content: Among them, Moisture Content is the moisture content, W wet and W dry is the mass of wet sludge and dry sludge; The centrifugal dehydration model uses the centrifugal dehydration rate equation to optimize dehydration efficiency: Among them, Centrifugal Force is the centrifugal force, m is the sludge mass, r is the centrifugal radius, ω is the angular velocity, and g is the gravitational acceleration.

10. A coal chemical heavy oil wastewater treatment system according to claim 3, characterized in that: In the reuse unit, a genetic algorithm is used to optimize the water quality parameters and treatment process of the reused water. The genetic algorithm optimization model is: Fitness function: Among them, f(x) is the fitness value, and Objective Function is the objective function value; Select an action: Among them, P i is the individual fitness, P i+1 is the probability of selection; Crossover operation: Among them, C ij is the new individual after crossover, P i,j and P i+1,j is the parent individual; Mutation operation: P i,j =P i,j +δ·Rand, Among them, δ is the variation amplitude, Rand is the random value; Reclaimed water quality prediction uses artificial neural network for water quality prediction and reused water quality optimization. The feedforward neural network equation is: y=σ(W·x+b), Among them, y is the predicted output, σ is the activation function, W is the weight matrix, x is the input data, and b is the bias term.

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