Process and system for treating oil and grease-containing wastewater

Abstract

The application belongs to the technical field of wastewater treatment, and particularly relates to an oil-containing wastewater treatment process and system, which comprises a three-phase separator, a cold slag removal tank, a heating tank, a data acquisition module and a central control module; the data acquisition module is used for collecting the true density of pure oil phase, the water phase conductivity, the centrifugal slag compactness, the cold slag removal tank body temperature, the sedimentation interface height, the upper oil sample turbidity, the heating tank micro-positive pressure pulsation frequency, the condenser pipeline absorbance, the emulsion layer dielectric constant, the solid slag moisture content and the light phase outlet water turbidity; the central control module is in communication connection with the data acquisition module and the three-phase separator, breaks the traditional hysteresis which depends on a single sensor and artificial qualitative observation, enables the system to accurately predict the separation potential and the layering difficulty of the material, and thereby upgrades the system control logic from passive response to active prediction, and provides solid data support for the subsequent dynamic processing strategy.

Description

Technical Field

[0001] This invention belongs to the field of wastewater treatment technology, specifically a process and system for treating oily wastewater. Background Technology

[0002] Existing oily wastewater treatment systems mostly adopt open-loop control strategies or experience-based fixed-frequency slag discharge modes in their operation and control. During the treatment process, the system usually relies on a single temperature sensor or level gauge for basic operating condition monitoring. The slag discharge frequency of the three-phase separator is often preset manually. Operators need to periodically observe the oil transmittance at the light phase outlet or the wetness of the mud cake at the slag discharge port with the naked eye to manually fine-tune the separator's operating cycle and slag discharge action in a passive and lagging manner.

[0003] The aforementioned technologies lack deep fusion of multi-source heterogeneous sensor data, failing to perform feedforward quantitative assessment of the inherent recyclability of raw materials and their tendency for natural cold stratification, resulting in an inability to predict the separation difficulty of materials. Secondly, due to the lack of dynamic monitoring of pressure pulsation, condensed volatiles, and the dielectric constant of the emulsion layer, the system cannot sense the severe disturbances caused by thermal-wet phase transitions. At the same time, the rigid fixed slag discharge frequency cannot match the dynamic fit of actual fluidized separation. When system disturbances intensify or incoming materials deteriorate, it is very easy to cause excessive water content in light phase oils and excessive accumulation of solid slag to block the flow channels, thereby severely reducing the continuous operation stability of the equipment and the final recovery quality of the oil.

[0004] Therefore, the present invention provides a process and system for treating oily wastewater. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0006] The technical solution adopted by the present invention to solve its technical problem is: the oily wastewater treatment process and system of the present invention includes a three-phase separator, a cold slag removal tank, a heating tank, a data acquisition module and a central control module; The data acquisition module is used to collect the true density of pure oil phase, conductivity of aqueous phase, density of centrifuged residue, temperature of cold deslagging tank, height of settling interface, turbidity of upper oil sample, frequency of micro-positive pressure pulsation in heating tank, absorbance of condensing pipeline, dielectric constant of emulsion layer, water content of solid residue and water content and turbidity of light phase outlet. The central control module is communicatively connected to the data acquisition module and the three-phase separator, and the central control module is configured as follows: A raw material recyclability quality model was constructed based on the true density of pure oil phase, the electrical conductivity of aqueous phase, and the density of centrifuged residue, and the raw material recyclability quality coefficient was obtained. A natural cold stratification tendency model is constructed based on the demulsification point temperature, sedimentation interface migration velocity and cloud point temperature corresponding to temperature abrupt changes, and the natural cold stratification tendency coefficient is obtained. A thermal-wet phase transition perturbation model was constructed based on the micro-positive pressure pulsation frequency, the COD equivalent of condensate corresponding to absorbance, and the dielectric constant, and the thermal-wet phase transition perturbation coefficient was obtained. Based on the quality coefficient, stratification tendency coefficient, dry matter content corresponding to solid slag moisture content, and light phase outlet turbidity, a fluidized bed separation fit model is constructed to obtain the fluidized bed separation fit coefficient. Based on the fit coefficient and the disturbance coefficient, a slag discharge frequency optimization model is constructed, the slag discharge frequency of the target three-phase separator is output, and the three-phase separator is controlled to perform slag discharge at this frequency.

[0007] The beneficial effects of this invention are as follows: 1. The oil-containing wastewater treatment process and system described in this invention integrates multiple physicochemical parameters such as the true density of the pure oil phase, the abrupt change value of the conductivity of the aqueous phase, and the migration velocity of the settling interface. This enables a quantitative assessment of the inherent characteristics of the raw materials and their spontaneous phase separation capabilities. This feedforward quantitative assessment mechanism breaks through the lag of traditional reliance on single sensors and manual qualitative observation, allowing the system to accurately predict the separation potential and the ease of stratification of materials. This upgrades the system control logic from passive response to active prediction, providing solid data support for the formulation of subsequent dynamic treatment strategies.

[0008] 2. The oily wastewater treatment process and system described in this invention deeply extracts the gas pressure pulsation characteristics, volatile organic compound migration, and dielectric property changes of the emulsion layer inside the heating tank, and uniformly maps the multi-source heterogeneous microscopic disturbance signals into intuitive disturbance coefficients. This enables the control center to perceive complex disturbances caused by gas-liquid two-phase flow or boiling and condensation in real time and accurately predict the deterioration trend of the internal operating environment. This provides a key sensing foundation for predictive adjustment and efficient operation of the system under complex and variable operating conditions.

[0009] 3. The oil-containing wastewater treatment process and system described in this invention completely abandons the traditional rigid fixed-frequency slag discharge mode by using thermodynamic disturbance sensing as feedforward compensation and actual separation matching degree as feedback adjustment. The central control module can calculate and issue the target slag discharge frequency after exponential-scale dynamic gain correction in real time, and finely and dynamically adjust the slag discharge duty cycle. This not only effectively balances the solid slag discharge efficiency and the purity of light phase oil, avoiding the occurrence of flow channel blockage due to solid slag accumulation or excessive light phase water content, but also significantly improves the continuous operation stability of the equipment and the final oil recovery quality. Attached Figure Description

[0010] The invention will now be further described with reference to the accompanying drawings.

[0011] Figure 1 This is the control logic diagram for oily wastewater in this invention; Figure 2 This is a flowchart of the multi-source heterogeneous sensor data acquisition and feature parameter extraction process in this invention; Figure 3 This is a flowchart illustrating the logic for evaluating the recyclability quality coefficient of raw materials in this invention. Figure 4 This is a flowchart of the logic for evaluating the natural cold stratification tendency coefficient in this invention; Figure 5 This is a flowchart of the logic for evaluating the thermal and humid phase transition disturbance coefficient in this invention; Figure 6 This is a flowchart of the fluidized bed separation compatibility assessment and dynamic optimization of slag discharge frequency in this invention. Detailed Implementation

[0012] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0013] An oily wastewater treatment system according to an embodiment of the present invention includes a three-phase separator, a cold slag removal tank, a heating tank, a data acquisition module, and a central control module; The data acquisition module is used to collect the true density of the pure oil phase, the conductivity of the aqueous phase, the density of the centrifuged residue, the temperature of the cold slag removal tank, the height of the settling interface, the turbidity of the upper oil sample, the frequency of the micro-positive pressure pulsation in the heating tank, the absorbance of the condenser pipeline, the dielectric constant of the emulsion layer, the water content of the solid residue, and the water content and turbidity of the light phase outlet. The central control module is communicatively connected to the data acquisition module and the three-phase separator. The central control module is configured as follows: A raw material recyclability quality model was constructed based on the true density of pure oil phase, the electrical conductivity of aqueous phase, and the density of centrifuged residue, and the raw material recyclability quality coefficient was obtained. A natural cold stratification tendency model is constructed based on the demulsification point temperature, sedimentation interface migration velocity and cloud point temperature corresponding to temperature abrupt changes, and the natural cold stratification tendency coefficient is obtained. A thermal-wet phase transition perturbation model was constructed based on the micro-positive pressure pulsation frequency, the COD equivalent of condensate corresponding to absorbance, and the dielectric constant, and the thermal-wet phase transition perturbation coefficient was obtained. A fluidized bed separation fit model was constructed based on the quality coefficient, stratification tendency coefficient, dry matter content corresponding to solid slag moisture content, and light phase outlet turbidity to obtain the fluidized bed separation fit coefficient. Based on the fit coefficient and disturbance coefficient, a slag discharge frequency optimization model is constructed to output the slag discharge frequency of the target three-phase separator, and the three-phase separator is controlled to perform slag discharge at this frequency.

[0014] The three-phase separator is configured to perform the three-phase separation function of oil, water and solid. The cold slag removal tank is configured to promote the precipitation and separation of solid substances in a low-temperature environment. The heating tank is configured to heat the oily wastewater to break up the emulsion or promote phase change. The data acquisition module is configured to collect various physical and chemical parameters during the system operation. The central control module is configured as the decision center of the system, receiving data, performing calculations and issuing control commands.

[0015] The data acquisition module collects parameters such as the true density of the pure oil phase, the conductivity of the aqueous phase, and the density of the centrifuged residue. These parameters can be obtained through manual sampling and measurement using laboratory equipment. For example, the true density of the pure oil phase can be measured using a densitometer, the conductivity of the aqueous phase can be measured using a conductivity meter, and the density of the centrifuged residue can be calculated by measuring the volume and mass of the solid residue after a centrifugal sedimentation test.

[0016] Parameters such as the temperature of the cold slag removal tank, the height of the settling interface, and the turbidity of the upper oil sample can be monitored in real time using general-purpose temperature sensors, level gauges, and optical turbidity sensors installed outside or inside the tank. Parameters such as the micro-positive pressure pulsation frequency of the heating tank, the absorbance of the condensation pipeline, and the dielectric constant of the emulsion layer can be continuously collected using pressure sensors, photoelectric sensors, and capacitive sensors installed at appropriate locations. Parameters such as the water content of the solid slag and the water content and turbidity of the light phase outlet can be obtained by periodically sampling from the slag discharge port and the light phase outlet and analyzing them using the drying and weighing method and a turbidity meter.

[0017] The central control module communicates with the data acquisition module and the three-phase separator via an industrial fieldbus (such as...). , Data transmission can be performed using either Ethernet or Ethernet-based communication protocols. The central control module is configured to receive various parameters transmitted by the data acquisition module and send control commands to the three-phase separator.

[0018] The central control module is configured to build multiple models based on the collected data. First, a raw material recyclability quality model is built based on the true density of the pure oil phase, the conductivity of the aqueous phase, and the density of the centrifuged residue to obtain the raw material recyclability quality coefficient. This model adopts a preset nonlinear empirical analytical formula that includes exponential decay and inverse proportional decay. By inputting the abrupt change values ​​of the true density of the pure oil phase, the conductivity of the aqueous phase, and the density of the centrifuged residue, the quantified raw material recyclability quality coefficient is directly calculated.

[0019] Secondly, a natural cooling stratification tendency model was constructed based on the demulsification point temperature, settling interface migration velocity, and cloud point temperature corresponding to temperature abrupt changes, to obtain the natural cooling stratification tendency coefficient. This model uses a normalized mathematical formula based on the arctangent function, taking the ratio of demulsification point temperature to cloud point temperature and the ratio of settling velocity as input variables, and smoothly mapping the output natural cooling stratification tendency coefficient between 0 and 1. Thirdly, a thermo-wet phase transition perturbation model was constructed based on the micro-positive pressure pulsation frequency, the COD equivalent of condensate corresponding to absorbance, and the dielectric constant, to obtain the thermo-wet phase transition perturbation coefficient. This model uses an improved... The activation function takes the normalized parameters such as the micro-positive pressure pulsation frequency, the COD equivalent of condensate, and the dielectric constant as the weighted sum and uses them as the exponential input. The output is a continuous nonlinear thermo-wet phase transition disturbance coefficient, which can reflect the degree of phase transition disturbance with high sensitivity.

[0020] Furthermore, based on the aforementioned quality coefficient, the aforementioned stratification tendency coefficient, the dry matter content corresponding to the solid slag moisture content, and the light phase outlet turbidity, a fluidized bed separation fit model is constructed to obtain the fluidized bed separation fit coefficient. This model can be a simple weighted average model, which comprehensively evaluates the degree of matching between the current separation state and the ideal fluidized bed separation by assigning different weights to each coefficient.

[0021] The central control module is configured to construct a slag discharge frequency optimization model based on the aforementioned fit coefficient and disturbance coefficient, and output the slag discharge frequency of the target three-phase separator. The optimization model adopts an exponential gain mathematical analytical expression with feedback and feedforward, uses the previously calculated thermo-wet phase change disturbance coefficient as feedforward compensation, and uses the fluidized separation fit coefficient as feedback adjustment to dynamically multiply the reference slag discharge frequency and directly and continuously output the target slag discharge frequency. Thus, the central control module controls the three-phase separator to perform slag discharge at this frequency. The three-phase separator can be equipped with a programmable timer to receive the frequency command sent by the central control module and periodically trigger the slag discharge mechanism to perform the action.

[0022] The system acquires multi-source heterogeneous data such as the true density of the pure oil phase, the conductivity of the aqueous phase, and the density of the centrifuged residue through the data acquisition module. The central control module then constructs a recyclable quality model for the raw materials, enabling a quantitative assessment of the inherent characteristics of the raw materials. This contrasts with existing technologies that lack feedforward quantitative assessment of raw material quality, allowing the system to predict the separation difficulty of materials.

[0023] Furthermore, by constructing a natural cold stratification tendency model and a thermal-wet phase change disturbance model, the system can assess the difficulty of stratification of materials during the cold slag removal stage in real time and capture dynamic disturbances during heating and phase change processes. For example, the system can determine the potential for cold separation based on parameters such as demulsification point temperature and settling interface movement speed, and sense the stability of the heating process based on parameters such as micro-positive pressure pulsation frequency and condensate COD contribution equivalent. This overcomes the limitations of existing technologies that lack dynamic monitoring of natural cold stratification tendency and thermal-wet phase change disturbances.

[0024] Furthermore, by constructing a fluidized bed separation fit model, the characteristics of the raw materials are correlated with the actual performance of the separation process, quantifying the degree of matching between the current separation state and the ideal fluidized bed separation. Finally, based on the aforementioned fit coefficient and disturbance coefficient, the slag discharge frequency optimization model can dynamically calculate and output the slag discharge frequency of the target three-phase separator, and control the three-phase separator to perform slag discharge at this frequency. This closed-loop control strategy changes the lag of traditional fixed-frequency slag discharge, enabling the three-phase separator to perform real-time and precise slag discharge actions according to actual working conditions. This can effectively avoid problems such as excessive water content in light phase oil and solid slag blockage, thereby improving the quality of oil recovery and enhancing the continuous operation stability of the system.

[0025] The feedstock recyclability quality model is constructed by integrating the deviation term of the true density of the pure oil phase, the attenuation term of the abrupt change in the conductivity of the aqueous phase, and the gain term of the density of the centrifuged residue. Among them, the feedstock recyclability quality coefficient has an exponential decay relationship with the degree of deviation of the true density from the standard industrial oil density, an inverse decay relationship with the dimensionless ratio of the abrupt change in the conductivity of the aqueous phase to the benchmark threshold, and a power function positive correlation with the density index of the centrifuged residue. The feedstock recyclability quality coefficient is obtained by multiplying the above three relational expressions and is used to characterize the upper limit of the potential for the effective oil in the feedstock to be recovered.

[0026] The formula for the raw material recyclability quality model is:

[0027] In the formula, The recyclability coefficient of raw materials (dimensionless); True density of pure oil phase (unit: ); Standard industrial oil density (unit: ); The abrupt change in the conductivity of the aqueous phase (unit: ); The threshold for sudden change in the conductivity of the reference aqueous phase (unit: ); The density index of the centrifuged residue (dimensionless). , , All are dimensionless sensitivity weight coefficients (dimensionless). It is the base of the natural logarithm (dimensionless).

[0028] This raw material recyclability quality model formula aims to comprehensively evaluate the quality and potential of recyclable oils in oily wastewater by quantifying multiple key physicochemical parameters. It transforms complex raw material characteristics into a single, operable quality coefficient, providing data support for the formulation of subsequent treatment strategies. The quality coefficient of recyclable raw materials is a dimensionless indicator, typically ranging from 0 to 1. It is used to visually represent the purity, ease of separation, and potential economic value of recyclable oils in the current raw materials. A higher quality coefficient indicates that the raw materials are easier to process and have higher recycling efficiency.

[0029] True density of pure oil phase refers to the actual density of the pure oil phase separated from oily wastewater at a specific temperature and pressure. This parameter is an important indicator for measuring the purity and physical properties of oil products. Its value can reflect whether there are impurities or the mixing of different components in the oil product. True density of pure oil phase is obtained by a densitometer, a vibrating cylinder densitometer, or a laboratory method based on mass and volume measurement.

[0030] Standard industrial oil density refers to the standard density value of industrial recycled oil that is considered ideal or qualified under specific industrial application scenarios. This standard value is usually determined based on industry specifications, product requirements, or historical best operating data, and serves as a benchmark for assessing the deviation of the actual pure oil phase true density.

[0031] The abrupt change in aqueous phase conductivity refers to the significant change in aqueous phase conductivity over a short period of time during the treatment of oily wastewater. This abrupt change is usually related to rapid changes in ion concentration, dissolved salts, or emulsifier content in the aqueous phase. It is an important indicator reflecting the impurity content and emulsion stability of the aqueous phase. This value can be obtained by continuously monitoring the aqueous phase conductivity and calculating its time derivative. The reference aqueous phase conductivity mutation threshold refers to the maximum allowable value of the aqueous phase conductivity mutation under normal or acceptable process conditions. When the actual conductivity mutation value exceeds this threshold, it usually means that the aqueous phase environment has deteriorated, which may have an adverse effect on oil separation. This threshold can be set through experimental calibration, historical data analysis or according to process requirements.

[0032] The density index of centrifuged residue refers to an indirect indicator of the compactness or moisture content of the solid residue obtained through centrifugation. The density index can reflect the physical morphology, particle size distribution, and adsorption or entrainment capacity of the solid residue on the oil and water phases during the separation process. This index can be obtained indirectly by measuring the volume and mass of the centrifuged residue or by analyzing its structural characteristics through image analysis.

[0033] , , These are all dimensionless sensitivity weight coefficients. These coefficients are used to adjust the degree of influence of each parameter in the model on the final quality coefficient. They are dimensionless and are calibrated through experimental data fitting, expert experience, or optimization algorithms to ensure that the model can accurately reflect the relative importance of different parameters to the recyclability quality of raw materials. For example, It can adjust the rate of quality degradation when the density of the pure oil phase deviates from the standard value; It can adjust the intensity of the negative impact of sudden changes in the conductivity of the aqueous phase on quality; The contribution or limitation of centrifugal residue density to quality can be adjusted. is the base of the natural logarithm, a mathematical constant used in models to construct exponential functions to describe nonlinear relationships between certain physical quantities, such as the exponential decay effect of density deviation on mass.

[0034] Through the first term in the model By comparing the true density of the pure oil phase With standard industrial oil density The degree of deviation reflects the impact of oil purity on recovery quality in the form of exponential decay. The closer the true density of the pure oil phase is to the standard value, the larger this value is, indicating that the higher the oil purity, the greater its contribution to the quality coefficient.

[0035] Second item Then, through the abrupt change in the conductivity of the aqueous phase... Threshold for sudden change in conductivity of reference aqueous phase The ratio of the two values ​​quantifies the interference of aqueous phase impurities on the separation process in an inversely proportional decay manner. When the abrupt value of the aqueous phase conductivity increases, it indicates that the content of aqueous phase impurities is high. When this value decreases, the quality coefficient is reduced, reflecting the negative impact of the deterioration of the aqueous phase environment on the recyclable quality of the raw materials.

[0036] Third item Using the density index of centrifuged residue Its power function form reflects the constraint of the physical state of the solid slag on the recovery quality. A higher density index generally means that the solid slag is easier to separate and contains less entrained oil and water, which has a positive contribution to the quality coefficient. This is achieved through a dimensionless sensitivity weighting coefficient. , , By adjusting the parameters, this model can accurately characterize the nonlinear relationship between various parameters and the recyclability of raw materials, thereby transforming the complex physicochemical properties of raw materials into a single quality coefficient. As an important basis for the central control module to adjust subsequent processing strategies, for example in the slag discharge frequency optimization model, it works together with the fluidized bed separation fit model to provide the three-phase separator with a dynamic slag discharge frequency based on the actual quality of the raw materials. This overcomes the problem that traditional methods cannot accurately quantify the raw material recovery potential based solely on qualitative descriptions, enabling the system to dynamically adjust the processing strategy according to the actual quality of the raw materials, and significantly improving the efficiency and purity of oil recovery.

[0037] The natural cooling stratification tendency model is constructed based on the ratio of the demulsification point temperature to the cloud point temperature of the cooled waxy substance, and the ratio of the slag layer settling interface movement velocity to the reference settling velocity. The natural cooling stratification tendency model obtains the comprehensive driving force variable by linearly weighting and summing the above two ratios, and then nonlinearly compresses the comprehensive driving force variable into a bounded space through inverse trigonometric function mapping to output the natural cooling stratification tendency coefficient.

[0038] The formula for the natural cooling stratification tendency model is:

[0039] In the formula, is the natural cold stratification tendency coefficient (dimensionless). Demulsification point temperature (unit: ); The cloud point temperature at which waxy substances precipitate during cooling (unit: ); Velocity of slag layer settling interface (unit: ); For reference settlement velocity (unit: ); , All are dimensionless gain coefficients.

[0040] The core of this model lies in integrating multiple key physical parameters through nonlinear functions to provide a unified and operable index, among which the natural cooling stratification tendency coefficient is... It is a quantitative indicator output by the model. Its value directly reflects the potential of oil-water-solid three-phase separation of oily wastewater during the cooling process. A higher coefficient usually means that the material is more likely to achieve effective stratification through cooling, which is beneficial to subsequent separation operations.

[0041] Delay point temperature The demulsification point temperature refers to the critical temperature at which the emulsification state of oily wastewater begins to be disrupted and signs of oil-water separation appear during the cooling process. This temperature can be determined in various ways, and the temperature corresponding to the significant change in light transmittance is the demulsification point temperature.

[0042] Cloud point temperature at which waxy substances precipitate upon cooling The cloud point temperature refers to the temperature at which oily wastewater becomes turbid during the cooling process, as components such as waxes and high-melting-point fatty acids begin to precipitate. This temperature can be determined by visual observation, turbidimeter measurement, or infrared spectroscopy analysis. For example, in addition to direct measurement with a turbidimeter, differential scanning calorimetry (DSC) can be used to analyze the heat flow changes of the sample during the cooling process, and the starting temperature corresponding to the precipitation phase change can be used as the cloud point temperature.

[0043] Slag layer settling interface movement velocity This refers to the rate at which the solid-liquid interface or oil-water interface (especially the interface between the slag layer and the water phase) moves downward during the cooling and settling process. This rate reflects the kinetic characteristics of solid particles or heavy oil droplets separating from the liquid phase under the action of gravity. In addition to determining the settling interface height by measuring the rate of change of time using an ultrasonic interface meter installed in the cold slag removal tank, it can also be calculated by tracking the positional changes of the interface in the settling tube in real time using a visual recognition system combined with image processing technology.

[0044] Reference Settlement Velocity It is a benchmark value used to normalize the actual measured velocity of the slag layer settling interface. This reference velocity is usually set based on empirical values ​​for specific types of oily wastewater, laboratory standard test results, or equipment design parameters, and represents the settling performance of materials under ideal or standard conditions.

[0045] Dimensionless gain coefficient , The terms used to adjust the relative weights of the ratio of demulsification point temperature to cloud point temperature and the ratio of slag layer settling interface movement velocity to reference settling velocity in the model are dimensionless and can be calibrated through experimental data fitting, expert experience, or optimization algorithms to ensure that the natural cold stratification tendency coefficient output by the model can accurately reflect the actual working conditions.

[0046] By introducing the ratio of demulsification point temperature to cloud point temperature, the critical thermodynamic conditions for the material to transform from an emulsified state to a stratified state during cooling can be reflected. The higher the ratio, the easier it is for the material to demulsify within a specific temperature range, providing a thermodynamic basis for subsequent separation operations. By introducing the ratio of the settling interface movement velocity to the reference settling velocity, the actual settling kinetic characteristics of the slag layer under gravity can be dynamically captured. This ratio reflects the physical rate of solid-liquid separation and can effectively characterize the settling activity of the material. By weighting and integrating the above thermodynamic and kinetic parameters and normalizing them using the arctangent function, the central control module can comprehensively judge the natural stratification tendency of the material.

[0047] Based on this, the central control module uses the demulsification point temperature collected by the data acquisition module. , cloud point temperature at which waxy substances precipitate upon cooling , Slag layer settling interface movement velocity By substituting real-time or preset parameters into the formula for the natural stratification tendency model, the natural stratification tendency coefficient can be calculated. This coefficient, as a quantitative indicator, can accurately characterize the natural stratification potential of current oily wastewater. The central control module uses this coefficient as an important input to the subsequent fluidized bed separation fit model, thereby enabling the entire system to dynamically adjust the operating strategy of the three-phase separator, especially the slag discharge frequency, based on a forward-looking assessment of the material stratification characteristics. This solves the control lag problem caused by the lack of quantitative perception of material stratification characteristics in traditional control strategies, allowing the system to shift from passive response to active prediction and optimization, significantly improving the intelligence level and operating efficiency of the treatment system.

[0048] The thermo-wet phase transition perturbation model characterizes the system's instability by calculating the dimensionless ratios of multiple physical quantities relative to their respective reference values. The model weights and combines the ratios of the micro-positive pressure pulsation frequency, the equivalent contribution of condensate COD, and the dielectric constant of the emulsion layer, and obtains the comprehensive perturbation after subtracting the threshold bias term. The comprehensive perturbation is then input into an sigmoid nonlinear activation function for smooth mapping to output a range-limited thermo-wet phase transition perturbation coefficient.

[0049] The formula for the thermal-wet phase transition perturbation model is:

[0050] In the formula, is the thermal-wet phase transition disturbance coefficient (dimensionless). Micro-positive pressure pulsation frequency (unit: ); Reference pulsation frequency (unit: ); Equivalent contribution to COD of condensate (unit: ); Upper limit of baseline COD equivalent (unit: ); Dielectric constant of the emulsion layer (unit: ); Dielectric constant of pure water (unit: ); , , All are dimensionless weighting coefficients; This is a dimensionless threshold bias term.

[0051] Among them, the micro-positive pressure pulsation frequency This refers to the frequency characteristics exhibited by local periodic pressure fluctuations or instantaneous pressure changes caused by thermal-wet phase transitions (such as boiling, condensation, and gas-liquid two-phase flow) during the treatment of oily wastewater, especially in closed or semi-closed containers such as heating tanks. This frequency can directly reflect the instability of the fluid dynamics inside the system and is a key indicator for measuring the severity of thermal-wet phase transition disturbances. It can be obtained by installing high-precision pressure sensors on the top or side wall of the heating tank to collect pressure signals in real time and extracting its main frequency or characteristic frequency through digital signal processing methods such as Fourier transform.

[0052] Condensate COD contribution equivalent This refers to the condensate formed after the steam discharged from the heating tank is condensed during the treatment of oily wastewater, which contains volatile organic compounds (VOCs). The chemical oxygen demand (COD) value contributed by the liquid phase is indirectly reflected in how much organic matter volatilizes from the liquid phase and enters the gas phase during the thermal-wet phase transition process, thereby affecting the operating conditions of the condenser pipeline and even subsequent processing units. The implementation can include: installing an ultraviolet-visible spectrophotometer on the condenser pipeline to measure the absorbance at a specific wavelength (e.g., 254 nm) and establishing a linear or nonlinear relationship between absorbance and COD equivalent for conversion.

[0053] Dielectric constant of emulsion layer Dielectric constant refers to the dielectric properties exhibited by the emulsion layer formed, especially in the heating tank, during the treatment of oily wastewater. The dielectric constant is the ability of a substance to polarize under the action of an electric field. For emulsions, the dielectric constant is affected by various factors such as the oil-water ratio, the type of emulsifier, temperature, and dissolved salts. Therefore, the change in the dielectric constant of the emulsion layer can sensitively reflect the stability, composition changes, and phase interface state of the emulsion. It is an important parameter for evaluating the influence of thermal-wet phase transition on the structure of emulsions. The dielectric constant can be calculated by installing a capacitive sensor at the location of the emulsion layer in the heating tank, measuring the capacitance value of the emulsion, and calculating the dielectric constant based on the sensor's structural parameters.

[0054] The thermo-wet phase transition disturbance model proposed in this application aims to quantify the degree of internal disturbance caused by thermo-wet phase transition during the operation of an oily wastewater treatment system. This model integrates the micro-positive pressure pulsation frequency. Condensate COD contribution equivalent and the dielectric constant of the emulsion layer These three key parameters form a comprehensive evaluation system.

[0055] Micro-positive pressure pulsation frequency This reflects the instability of the system's internal fluid dynamics, relative to the reference pulsation frequency. The degree of deviation indicates the interference of pressure fluctuations on the separation process; the contribution equivalent of COD in condensate. This characterizes the amount of volatile organic compounds migrating during the thermal-wet phase transition process, relative to the upper limit of the baseline COD equivalent. The proportions reveal the impact of changes in material composition on the system environment; the dielectric constant of the emulsion layer... The change in dielectric constant directly reflects the stability of the emulsion and the phase interface state, and its relationship with the dielectric constant of pure water. The difference indicates a change in the degree of emulsification or the difficulty of phase separation.

[0056] The central control module will collect , and Data, respectively compared with the corresponding benchmark values , and Normalization was performed, and the result was obtained using dimensionless weighting coefficients. , , We perform a weighted summation and then introduce a dimensionless threshold bias term. Finally, this weighted sum is input into a... In the mathematical model in functional form, the thermal-wet phase transition perturbation coefficient is calculated. This nonlinear mapping method enables the model to quantize multi-source heterogeneous disturbance signals into a coefficient between 0 and 1, thereby effectively integrating monitoring data with different physical dimensions and highlighting the sensitivity of disturbances near the critical point. In this way, the central control module can perceive the thermal and wet phase change disturbances inside the system in real time and accurately, providing a quantitative basis for the dynamic optimization of the subsequent slag discharge frequency. This predictive adjustment based on disturbance perception enables the system to transform from a traditional passive response to an active adaptation, significantly enhancing the operational stability of the oily wastewater treatment system under complex operating conditions. It also effectively cooperates with the central control module's overall control strategy for the three-phase separator, jointly improving treatment efficiency and effectiveness.

[0057] By constructing a thermo-wet phase transition perturbation model and introducing a micro-positive pressure pulsation frequency... Condensate COD contribution equivalent and the dielectric constant of the emulsion layer These three key parameters enable the system to accurately quantify the degree of internal thermal and humid phase change disturbances. This quantification capability allows the central control module to perceive microscopic disturbances caused by pressure fluctuations, migration of volatile organic compounds, and changes in the stability of the emulsion layer in real time, thereby overcoming the limitations of relying solely on basic physical parameters for control.

[0058] when When the value increases, the central control module can adjust the operating parameters of the three-phase separator in advance, especially the slag discharge frequency, to adapt to the current complex working conditions and avoid problems such as excessive water content of light phase oil or excessive accumulation of solid slag. This significantly enhances the operational stability, adaptability and reliability of the oily wastewater treatment system under complex and variable working conditions, ensuring the quality of oil recovery and the continuous operating efficiency of the equipment.

[0059] The fluidized bed separation fit model is constructed using a rational fraction structure including a numerator and a denominator. The numerator of the rational fraction includes the product of the feed recyclability quality coefficient, the natural cooling stratification tendency coefficient, and the exponential saturation term constructed from the dry matter content of the solid slag, which is used to characterize the positive benefit of the system separation effect. The denominator of the rational fraction includes a penalty term constructed from the ratio of the light phase outlet water turbidity to the maximum allowable turbidity specification value, which is used to characterize the negative loss of the system separation effect. The fluidized bed separation fit coefficient is calculated by the quotient of the numerator and the denominator.

[0060] The formula for the fluidized bed separation fit model is:

[0061] In the formula, is the fluidization separation fit coefficient (dimensionless). The recyclability coefficient of the raw materials; This is the coefficient for natural cold stratification. The dry matter content of the solid slag is obtained by subtracting the moisture content of the solid slag from 1, and is a dimensionless decimal. Turbidity of light phase outlet water (unit: ); Maximum permissible turbidity specification value (unit: ); is a dimensionless dry matter saturation sensitivity coefficient; It is a dimensionless turbidity penalty factor.

[0062] This fluidized bed separation fit model formula is used to quantitatively evaluate the degree of matching between the fluidized bed separation process of oily wastewater in a three-phase separator and the current operating state. Its concept lies in integrating multiple key factors affecting separation efficiency into a comprehensive index to reflect the dynamic adaptability of the separation process. This model can be calculated by the processor in the central control module, for example, by executing a preset algorithm program on a microcontroller or industrial PC. The raw material recoverability coefficient is also considered. It characterizes the intrinsic quality and potential recovery value of recyclable oil in the raw material containing oily wastewater to be treated. It comprehensively considers factors such as the true density of the pure oil phase, the sudden change in the conductivity of the aqueous phase, and the density of the centrifuged residue. This coefficient can be obtained by the central control module based on the preset quality model after the relevant raw data is acquired by the data acquisition module.

[0063] Natural cooling stratification tendency coefficient It reflects the ease and trend of natural stratification (oil-water separation, solid-liquid separation) of oily wastewater under cooling conditions. It is mainly affected by factors such as demulsification temperature, cloud point temperature of waxy substances precipitated during cooling, and the movement speed of the slag layer settling interface. This coefficient is also calculated by the central control module based on real-time data provided by the data acquisition module and through a preset stratification tendency model.

[0064] Solid slag dry matter content The solid content of the solid slag in a three-phase separator is a key indicator for measuring the degree of solid slag accumulation and fluidity. It can be directly measured by online sensors (such as microwave moisture content sensors or gamma ray densitometers).

[0065] Light phase outlet water turbidity Used to measure the content of residual water and fine suspended solids in the light phase after three-phase separation, it is an important parameter for evaluating separation efficiency and the quality of recovered oil. It can be monitored in real time by an online turbidity sensor (such as a diffuse light turbidity meter or a transmitted light turbidity meter), and the measured value is transmitted to the central control module, allowing for a maximum turbidity specification value. It is a preset, acceptable upper limit standard for the turbidity of the light phase outlet water. It can be set according to industry standards, downstream process requirements, or historical operating experience, and stored in the parameter database of the central control module. Dry matter saturation sensitivity coefficient It is a dimensionless parameter used to adjust the influence of the solid slag dry matter content on the fluidized bed separation fit model. It can be set through experimental calibration, historical data fitting or expert experience and stored in the central control module.

[0066] Turbidity penalty factor It is a dimensionless parameter used to penalize the turbidity of the light phase outlet in the fluidized bed separation fit model. It can be set through system debugging, algorithm optimization or operational experience to balance separation efficiency and product quality.

[0067] By constructing a fluidized bed separation fit model, a quantitative characterization of the dynamic matching degree of the three-phase separation process in an oily wastewater treatment system was achieved, providing a core basis for the precise optimization of subsequent slag discharge frequency. This model incorporates the raw material recyclability coefficient... Natural cold stratification tendency coefficient Solid slag dry matter content and the turbidity of the light phase outlet Several key parameters are organically integrated.

[0068] Specifically, the recyclability coefficient of raw materials and natural cold stratification tendency coefficient As a fundamental component of the model, the product form reflects the synergistic influence of inherent material properties and environmental stratification conditions on separation efficiency, ensuring the comprehensiveness of the fit assessment. The model incorporates the dry matter content of the solid residue. index term Among them, the dry matter saturation sensitivity coefficient The nonlinear effect of solid slag accumulation on the separation flow regime was adjusted, enabling the model to accurately capture the fluctuations in separation resistance caused by changes in solid slag content. When this value is increased, the value of this item decreases, thereby reducing the overall fit coefficient. This reflects the adverse effects of solid slag accumulation on fluidized bed separation. Simultaneously, the model incorporates the turbidity of the light phase outlet water. With the maximum permissible turbidity specification value The ratio is used as a penalty item. And through turbidity penalty factor Real-time constraints are applied to the separation quality, specifically when the outlet turbidity... Deviation from standard value At that time, the penalty term will increase, leading to a decrease in the fit coefficient. The reduction triggers the central control module to correct the slag discharge frequency, effectively preventing the light phase oil from exceeding the water content standard. This fluidized bed separation fit model works closely with the data acquisition module and central control module in the aforementioned oily wastewater treatment system. The data acquisition module acquires key data in real time, such as the true density of the pure oil phase, the conductivity of the aqueous phase, the density of the centrifuged slag, the temperature of the cold slag removal tank, the settling interface height, the cloud point temperature of the cooled waxy precipitate, the water content of the solid slag, and the water content and turbidity of the light phase outlet. The central control module then uses this data to first calculate the raw material recoverability coefficient. and natural cold stratification tendency coefficient Then, combined with real-time monitoring of the solid slag dry matter content and light phase outlet water turbidity The fluidization separation fit coefficient is calculated using the above formula for the fluidization separation fit model. This compatibility coefficient It was then fed into the slag discharge frequency optimization model, along with the thermal-wet phase transformation perturbation coefficient. The slag discharge frequency of the target three-phase separator is jointly determined. This dynamic and quantitative evaluation mechanism enables the system to organically integrate multi-dimensional parameters such as material quality, stratification tendency, solid slag state and outlet quality. Through mathematical modeling, the complex fluidized separation process is transformed into a quantifiable fit coefficient, which solves the problems of slag discharge lag and poor separation effect caused by the lack of dynamic evaluation in traditional control strategies.

[0069] The slag discharge frequency optimization model uses the equipment's baseline slag discharge frequency as the base value, and combines it with an exponential scale dynamic gain term for correction to output the slag discharge frequency of the target three-phase separator. The exponential part of the exponential scale dynamic gain term is constructed by summing the positive proportional compensation amount of the thermal-wet phase change disturbance coefficient and the feedback error adjustment amount of the difference between the fluidized separation fit coefficients. The slag discharge frequency of the target three-phase separator is configured to increase exponentially and smoothly as the disturbance degree increases or the fit decreases.

[0070] The formula for the slag discharge frequency optimization model is:

[0071] In the formula, The slag discharge frequency of the target three-phase separator (unit: ); Reference slag discharge frequency (unit: ); The coefficient for thermal-wet phase transition disturbance; The fluidization separation fit coefficient; is the feedforward disturbance compensation proportional gain constant (dimensionless). The gain constant (dimensionless) is adjusted to accommodate the feedback adaptation error.

[0072] Among them, the slag discharge frequency of the target three-phase separator This refers to the number of times a three-phase separator performs a slag discharge operation per unit time. It directly determines the rate at which solid slag is discharged from the separator. Dynamic adjustment of this frequency is crucial for maintaining the stability of the solid-liquid interface inside the separator and preventing excessive accumulation or discharge of solid slag. The slag discharge frequency can be calculated and adjusted in real time according to actual working conditions to adapt to different material characteristics and operating conditions.

[0073] Reference slag discharge frequency This is the initial slag discharge frequency preset by the system under ideal or stable operating conditions. It is usually determined through historical operating data, empirical values, or design parameters. This reference frequency provides a stable starting point for the dynamic adjustment of the slag discharge frequency, and subsequent adjustments are made based on this. (Thermo-wet phase transition disturbance coefficient) It is an index that measures the degree of gas-liquid-solid phase change disturbance caused by changes in temperature and humidity within the system. The larger the value, the more severe the disturbance. This coefficient can be used as an input for feedforward control to predict and compensate for impending system instability.

[0074] Fluidization separation fit coefficient This is an index that assesses the degree of matching between the current separation state and the ideal fluidized bed separation state. A higher value indicates that the separation effect is closer to the ideal state. This coefficient can be used as an input for feedback control to correct separation efficiency deviations caused by changes in material quality or stratification tendency. It is also a proportional gain constant for feedforward disturbance compensation. Used to adjust the disturbance coefficient of hot and wet phase transition. Slag discharge frequency The strength of the influence, and its magnitude, determines the system's response sensitivity to disturbances. The feedback adaptation error adjustment gain constant... Used to adjust the fluidization separation fit coefficient Slag discharge frequency The strength of the influence, and the magnitude of its value, determines the degree to which the system corrects for deviations in the separation state.

[0075] Through the thermo-wet phase transition perturbation coefficient in the model As a feedforward compensation term, the proportional gain constant is compensated by the feedforward disturbance. Acting on the slag discharge frequency, it can quickly respond to instantaneous disturbances caused by changes in gas pressure pulsation, condensate COD equivalent, and dielectric constant within the system. This allows for timely adjustment of the slag discharge frequency to maintain system stability when disturbances intensify. Simultaneously, the fluidization separation fit coefficient in the model... As a feedback adjustment term, the gain constant is adjusted through the feedback adaptation error. The model applies to the slag discharge frequency and uses the difference between the current separation state and the ideal fluidized separation by subtracting the fit coefficient. When the fit decreases, this factor can automatically increase the correction range of the slag discharge frequency to compensate for the loss of separation efficiency caused by fluctuations in material quality or changes in stratification tendency. By organically combining feedforward disturbance compensation and feedback adaptation error adjustment, the model realizes the transformation of the slag discharge frequency from a fixed mode to an adaptive mode, ensuring that the system can effectively balance solid slag discharge and light phase oil purity through precise slag discharge frequency control when facing variable operating conditions.

[0076] By introducing feedforward disturbance compensation and feedback adaptation error adjustment mechanisms, the slag discharge frequency can be dynamically adjusted according to the internal thermal and wet phase change disturbances and the actual fluidization separation fit. This avoids problems such as excessive water content of light phase oil and excessive accumulation of solid slag clogging the flow channel caused by a fixed slag discharge frequency. It significantly improves the continuous operation stability of the oily wastewater treatment system, optimizes the quality of oil recovery, and improves the overall treatment efficiency.

[0077] The data acquisition module includes:

[0078] The conductivity probe is inserted into the centrifuged aqueous phase. The maximum absolute value of the time derivative of the conductivity measured in real time is used as the abrupt change value of the conductivity of the aqueous phase.

[0079] A temperature sensor array is installed at different heights in the cold deslagging tank to plot the cooling curve. The absolute temperature at which the second derivative of the cooling curve is zero is taken as the demulsification point temperature.

[0080] An ultrasonic interface meter is installed inside a cold slag removal tank. The rate of change of the settling interface height over time is used as the settling interface movement speed.

[0081] A full-spectrum probe, installed on the exhaust condensate line of the heating tank, is used to measure absorbance at a wavelength of 254 nm, which is then linearly converted to the COD contribution equivalent of the condensate.

[0082] Among them, the conductivity probe is a sensor used to measure the conductivity of liquids. It reflects the conductivity by detecting the migration ability of ions in the solution. The probe can be a two-electrode conductivity probe, which determines the conductivity by measuring the resistance or conductivity between the electrodes. Its function is to monitor the changes in the conductivity of the aqueous phase in real time, especially its abrupt changes. This is crucial for assessing changes in the concentration of salt, acidity, alkalinity, or specific pollutants in wastewater, and provides key input for subsequent quality models. The temperature sensor array is composed of multiple temperature sensors arranged in a specific layout. It can simultaneously measure the temperature at different locations to obtain spatial temperature distribution information. The signals from multiple sensors are collected through a multiplexer or distributed bus system.

[0083] By arranging instruments at different heights, the temperature gradient and cooling curve inside the tank can be obtained, thereby accurately identifying the demulsification point temperature. This is of great significance for understanding and controlling the phase separation process of emulsions. An ultrasonic interface meter is a device that uses the reflection characteristics of ultrasonic waves at the interface of different media to detect and locate the interface. This interface meter can use the pulse-echo method, emitting ultrasonic pulses and receiving their reflected echoes at the interface to calculate the distance. Its function is to monitor the height change of settling interfaces (such as oil-water interfaces, solid-liquid interfaces) in real time, thereby calculating the settling interface movement speed, which directly reflects the settling of solid slag or heavy phase substances. Efficiency and separation dynamics provide direct data for assessing stratification tendencies. A full-spectrum probe is an optical sensor capable of measuring the intensity of light absorption or emission within a specific wavelength range. It is commonly used to analyze the composition and concentration of substances. This probe can be based on the principle of a UV-Vis spectrophotometer, detecting organic matter by measuring the absorption of ultraviolet light at a wavelength of 254 nm. By measuring the absorbance at a specific wavelength (such as 254 nm) in the condenser pipe, the content of volatile organic compounds in the condensate can be indirectly quantified, and then converted into COD contribution equivalents. This is of great significance for monitoring the volatilization of organic matter and pollution load during the thermal-wet phase transition process.

[0084] By integrating a conductivity probe, a temperature sensor array, an ultrasonic interface analyzer, and a full-spectrum probe, a multi-dimensional, high-precision process parameter sensing system was constructed. The conductivity probe monitors the conductivity changes of the centrifuged aqueous phase in real time, and its maximum absolute value of the time derivative can sensitively capture the instantaneous fluctuations of the aqueous phase components, providing key conductivity abrupt changes for the raw material recyclability quality model. Meanwhile, the temperature sensor array, arranged at different heights in the cold deslagging tank, enables the system to plot detailed cooling curves. By analyzing the zero second derivative of these curves, the demulsification point temperature is accurately identified, providing important thermodynamic parameters for the natural cooling stratification tendency model. The ultrasonic interface analyzer continuously tracks the dynamics of the settling interface within the cold deslagging tank, quantifying the settling efficiency of solid slag or heavy phase materials by calculating its movement speed, providing a kinetic basis for the stratification tendency model.

[0085] In addition, a full-spectrum probe was installed on the exhaust condensate pipe of the heating tank. By measuring the absorbance at a wavelength of 254 nm, the volatile organic compound content in the condensate was indirectly quantified and linearly converted into the COD contribution equivalent of the condensate. This provided important pollution load data for the thermal-wet phase transition perturbation model. The key parameters acquired by the data acquisition module are not isolated but serve as inputs to various models in the central control module. For example, the true density of the pure oil phase, the abrupt change in the conductivity of the aqueous phase, and the density of the centrifuged slag jointly construct the raw material recyclability quality model; the demulsification point temperature, the cloud point temperature of the cooled waxy precipitate, and the slag layer settling interface movement velocity jointly construct the natural cold stratification tendency model; and the micro-positive pressure pulsation frequency, the COD contribution equivalent of the condensate, and the dielectric constant of the emulsion layer jointly construct the thermal-wet phase transition perturbation model.

[0086] The quality coefficient, stratification tendency coefficient, and disturbance coefficient output by these models, combined with the dry matter content of solid slag and the water content and turbidity of the light phase outlet, are used to further construct a fluidized bed separation fit model. Finally, the fit coefficient and disturbance coefficient are input into the slag discharge frequency optimization model to output the slag discharge frequency of the target three-phase separator and control the three-phase separator to perform slag discharge at this frequency. In this way, the data acquisition module not only provides raw data, but also transforms complex physicochemical processes into quantifiable characteristic parameters with clear physical meaning through specific sensor selection and data processing logic. This precise data input enables the central control module to make decisions based on more comprehensive and accurate operating condition information, thereby overcoming the control lag and inefficiency problems caused by insufficient or inaccurate data acquisition in traditional systems. For example, by accurately identifying the demulsification point temperature and the settling interface movement speed, the system can predict the separation difficulty and trend of materials earlier and more accurately, rather than passively waiting for the results. By monitoring the COD contribution equivalent of condensate, the system can sense the potential disturbances brought about by the thermal-wet phase change, and thus adjust the slag discharge strategy in a timely manner when the disturbance intensifies. This avoids problems such as excessive water content of light phase oil or solid slag blockage caused by the inability of a fixed slag discharge frequency to adapt to dynamic operating conditions, significantly improving the adaptability and control accuracy of the entire oily wastewater treatment system to complex operating conditions.

[0087] The three-phase separator is equipped with an automatic slag discharge valve. The central control module integrates a programmable logic controller (PLC). The PLC is configured to receive the slag discharge frequency of the target three-phase separator and output a pulse control signal of the corresponding frequency to the automatic slag discharge valve to dynamically adjust the slag discharge duty cycle. The cold slag removal tank is equipped with a cooling jacket to provide natural cooling boundary conditions. An RF admittance sensor is installed at the outlet of the light phase in the heating tank to measure the dielectric constant of the emulsion layer in real time.

[0088] Among them, the automatic slag discharge valve is a valve that can automatically open and close according to a preset program or external control signal to discharge solid or high-density phase in the three-phase separator. The valve can be an electric ball valve or an electric butterfly valve, which is driven by a motor to open and close in response to an electrical signal.

[0089] A programmable logic controller (PLC) is a digital electronic system designed specifically for industrial environments and used for automated control. It can be based on industrial-grade PLC hardware platforms (such as Siemens S7 series, Rockwell Automation, etc.). The PLC can be implemented using a series of corresponding programming software for logic programming; or it can be based on an embedded system (such as an ARM Cortex-M series microcontroller) and implement the functions of a PLC through a real-time operating system and customized software. A cooling jacket is a structure that surrounds the outside of a container and usually circulates a cooling medium inside to control the temperature of the material inside the container. It can be designed as a double-layer tank structure with cooling water or cold air flowing through the jacket to remove the heat inside the tank through heat exchange.

[0090] A radio frequency admittance sensor is a sensor that uses radio frequency signals to measure changes in the admittance of a medium. Its probe can be designed as a rod or cable, directly inserted into the fluid, and the dielectric constant is calculated by measuring changes in capacitance and conductance between the probe and the fluid wall.

[0091] By installing an automatic slag discharge valve on the three-phase separator and using a programmable logic controller (PLC) integrated within the central control module for precise control, the slag discharge frequency of the target three-phase separator calculated by the central control module is transformed into specific, executable physical actions. Upon receiving the slag discharge frequency command, the PLC outputs a pulse control signal of the corresponding frequency to the automatic slag discharge valve, thereby dynamically adjusting the slag discharge duty cycle and ensuring a high degree of synchronization between theoretical optimization and actual execution. In addition, the cooling jacket surrounding the cold slag removal tank provides stable natural cooling boundary conditions for the natural cold stratification tendency model, making temperature changes during the cold slag removal process more controllable. This ensures the accuracy of measurements of key parameters such as demulsification point temperature and cloud point temperature. Simultaneously, the radio frequency admittance sensor installed at the light phase outlet in the heating tank can measure the dielectric constant of the emulsion layer in real time, enabling the system to accurately perceive changes in the state of the emulsion layer. Through these hardware-level optimizations and the deepening of control logic, the system's response speed and processing accuracy in the treatment of complex oily wastewater are significantly enhanced.

[0092] Through the above technical solution, this application can convert the target slag discharge frequency calculated by the central control module into precise physical actions. By dynamically adjusting the slag discharge duty cycle, the system can perform slag discharge operations with higher precision and faster response speed according to real-time operating conditions, overcoming the rigidity of the traditional fixed slag discharge mode.

[0093] Meanwhile, the cooling jacket provides stable natural cooling boundary conditions for the cold slag removal tank, ensuring that the material undergoes cold stratification in a controlled environment. This improves the accuracy of key parameter measurements in the natural cold stratification tendency model, making the model prediction more reliable. The radio frequency admittance sensor measures the dielectric constant of the emulsion layer in real time at the light phase outlet of the heating tank, providing key, real-time physical parameter input for the thermal-wet phase transition disturbance model. This enables the system to accurately perceive the state changes of the emulsion layer and thermal-wet phase transition disturbances, and to more effectively cope with complex working conditions and changes in incoming materials. It avoids problems such as excessive water content in the light phase oil and excessive accumulation of solid slag clogging the flow channel, significantly improving the continuous operation stability, separation efficiency, and oil recovery quality of the oil-containing wastewater treatment system.

[0094] A process for treating oily wastewater, which employs the aforementioned oily wastewater treatment system, includes the following steps:

[0095] S1: Real-time acquisition of the following parameters during the treatment of oily wastewater: true density of pure oil phase, electrical conductivity of aqueous phase, density of centrifuged residue, temperature of cold slag removal tank, height of settling interface, turbidity of upper oil sample, frequency of micro-positive pressure pulsation in heating tank, absorbance of condenser pipeline, dielectric constant of emulsion layer, water content of solid residue, and water content and turbidity of light phase outlet.

[0096] S2: Extract the maximum absolute value of the time derivative of conductivity as the abrupt change value of conductivity in aqueous phase, and combine it with true density and compactness to obtain the raw material recyclability quality coefficient that characterizes the raw material recovery potential;

[0097] The absolute temperature at which the second derivative of the cooling curve of the cold slag removal tank is zero is extracted as the demulsification point temperature. Combined with the settling interface movement velocity and the cloud point temperature, the natural cold stratification tendency coefficient, which characterizes the spontaneous ability of phase separation, is obtained.

[0098] The absorbance was linearly converted into the COD contribution equivalent of the condensate, and the thermal-wet phase transition disturbance coefficient, which characterizes the thermodynamic instability of the system, was obtained by combining the micro-positive pressure pulsation frequency and dielectric constant.

[0099] S3: Convert the solid slag moisture content into dry matter content, and obtain the fluidization separation fit coefficient between the current fluid state and the equipment operation based on the raw material recyclability quality coefficient, natural cold stratification tendency coefficient, dry matter content and light phase outlet water turbidity.

[0100] S4: Based on the fluidization separation fit coefficient and the thermal-wet phase change disturbance coefficient, the reference slag discharge frequency is dynamically corrected by exponential scale, the slag discharge frequency of the target three-phase separator is calculated and output, and the corresponding pulse control signal is generated and sent to the automatic slag discharge valve of the three-phase separator to control the three-phase separator to perform dynamic slag discharge at this frequency.

[0101] The operation of the overall solution of this invention can be summarized into four dynamic and coordinated steps: perception, evaluation, feedback, and execution.

[0102] Step 1: The data acquisition module relies on various sensor arrays to acquire various physical and chemical operating parameters of the three-phase separator, cold slag removal tank and heating tank in real time. The purpose of this step is to break through the lag and blind spots of traditional single-point monitoring and manual qualitative judgment, and provide a full-dimensional data foundation for the system. It digitally maps the material properties of the front-end raw materials (such as true density and conductivity) with the microscopic changes of the mid-end cold and heat treatment processes (such as temperature change and micro positive pressure pulsation), and accurately and in real time transmits them to the central control module.

[0103] The second step: After receiving the underlying data, the central control module calculates the raw material recyclability quality coefficient, the natural cold stratification tendency coefficient, and the thermal-wet phase change disturbance coefficient. The purpose of this step is to make advance predictions on the inherent separation potential of the material, the difficulty of cold separation, and the gas-liquid phase change disturbance in the heating system. It connects the spontaneous stratification driving force of the cold slag removal tank with the dynamic thermodynamic disturbance of the heating tank in the core algorithm layer, laying an accurate feedforward compensation foundation for subsequent dynamic slag discharge decisions.

[0104] The third step: The system further combines the actual performance at the discharge end (solid slag dry matter content and light phase outlet water content and turbidity) to calculate the fluidized bed separation fit coefficient. Its function is to construct the positive benefit and negative loss constraints of the actual system operation effect, quantify the degree of matching between the current separation state and the ideal model, and link the theoretical potential of the separation front end model with the actual output quality of the separation back end. A closed-loop error feedback link with the beginning and end is formed within the central control module.

[0105] Step 4: The central control module, combining the disturbance perception of the feedforward and the separation and matching degree of the feedback, performs exponential dynamic correction on the benchmark slag discharge frequency, outputs the target slag discharge frequency, and the PLC outputs pulse signals to directly control the automatic slag discharge valve of the three-phase separator. Its function is to directly convert the complex digital model calculation results into precise mechanical actions of the terminal hardware, completely abandoning the rigid fixed slag discharge mode. This enables seamless interconnection and linkage between the data acquisition and perception layer, the central control core model layer, and the terminal equipment execution layer. Ultimately, it achieves the overall effect of adaptively balancing the solid slag discharge efficiency and the purity of the light phase oil even under deteriorating incoming materials or complex and variable working conditions, greatly ensuring the continuous, efficient, and stable operation of the entire system.

[0106] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A system for treating oily wastewater, characterized in that, Includes a three-phase separator, a cold slag removal tank, a heating tank, a data acquisition module, and a central control module; The data acquisition module is used to collect the true density of pure oil phase, conductivity of aqueous phase, density of centrifuged residue, temperature of cold deslagging tank, height of settling interface, turbidity of upper oil sample, frequency of micro-positive pressure pulsation in heating tank, absorbance of condensing pipeline, dielectric constant of emulsion layer, water content of solid residue and water content and turbidity of light phase outlet. The central control module is communicatively connected to the data acquisition module and the three-phase separator, and the central control module is configured as follows: A raw material recyclability quality model was constructed based on the true density of pure oil phase, the electrical conductivity of aqueous phase, and the density of centrifuged residue, and the raw material recyclability quality coefficient was obtained. A natural cold stratification tendency model is constructed based on the demulsification point temperature, sedimentation interface migration velocity and cloud point temperature corresponding to temperature abrupt changes, and the natural cold stratification tendency coefficient is obtained. A thermal-wet phase transition perturbation model was constructed based on the micro-positive pressure pulsation frequency, the COD equivalent of condensate corresponding to absorbance, and the dielectric constant, and the thermal-wet phase transition perturbation coefficient was obtained. Based on the quality coefficient, stratification tendency coefficient, dry matter content corresponding to solid slag moisture content, and light phase outlet turbidity, a fluidized bed separation fit model is constructed to obtain the fluidized bed separation fit coefficient. Based on the fit coefficient and the disturbance coefficient, a slag discharge frequency optimization model is constructed, the slag discharge frequency of the target three-phase separator is output, and the three-phase separator is controlled to perform slag discharge at this frequency.

2. The oily wastewater treatment system according to claim 1, characterized in that: The raw material recyclability quality model is constructed by integrating a deviation term for the true density of the pure oil phase, a decay term for the abrupt change in the conductivity of the aqueous phase, and a gain term for the density of the centrifuged residue. The raw material recyclability quality coefficient exhibits an exponential decay relationship with the degree to which the true density deviates from the standard industrial oil density, an inverse decay relationship with the dimensionless ratio of the abrupt change in the conductivity of the aqueous phase to a benchmark threshold, and a power-law positive correlation with the density index of the centrifuged residue. The raw material recyclability quality coefficient is obtained by multiplying the above three relational expressions and is used to characterize the upper limit of the potential for recovering effective oil from the raw material.

3. The oily wastewater treatment system according to claim 1, characterized in that: The natural cold stratification tendency model is constructed based on the ratio of the demulsification point temperature to the cloud point temperature of the cooled waxy substance, and the ratio of the slag layer settling interface movement velocity to the reference settling velocity. The natural cold stratification tendency model obtains the comprehensive driving force variable by linearly weighting and summing the above two ratios, and then nonlinearly compresses the comprehensive driving force variable into a bounded space through inverse trigonometric function mapping to output the natural cold stratification tendency coefficient.

4. The oily wastewater treatment system according to claim 1, characterized in that: The thermo-wet phase transition perturbation model characterizes the system's instability by calculating dimensionless ratios of multiple physical quantities relative to their respective reference values. The model weights and combines the ratios of micro-positive pressure pulsation frequencies, the ratios of condensate COD contribution equivalents, and the ratios of emulsion layer dielectric constants, and obtains the comprehensive perturbation after deducting a threshold bias term. The comprehensive perturbation is then input into an S-shaped nonlinear activation function for smooth mapping to output the thermo-wet phase transition perturbation coefficient, which has a limited range.

5. The oily wastewater treatment system according to claim 1, characterized in that: The fluidized bed separation fit model is constructed using a rational fraction structure including a numerator and a denominator. The numerator of the rational fraction includes the product of the feed recyclability quality coefficient, the natural cold stratification tendency coefficient, and an exponential saturation term constructed from the dry matter content of the solid slag, which is used to characterize the positive benefit of the system separation effect. The denominator of the rational fraction includes a penalty term constructed from the ratio of the light phase outlet turbidity to the maximum allowable turbidity specification value, which is used to characterize the negative loss of the system separation effect. The fluidized bed separation fit coefficient is calculated by the quotient of the numerator and the denominator.

6. The oily wastewater treatment system according to claim 1, characterized in that: The slag discharge frequency optimization model uses the equipment's benchmark slag discharge frequency as the base value and combines it with an exponential scale dynamic gain term for correction to output the slag discharge frequency of the target three-phase separator. The exponential part of the exponential-scale dynamic gain term is constructed by summing the positive proportional compensation of the thermal-wet phase change disturbance coefficient and the feedback error adjustment of the difference between the fluidized separation fit coefficients; the slag discharge frequency of the target three-phase separator is configured to increase exponentially and smoothly as the degree of disturbance increases or the fit decreases.

7. The oily wastewater treatment system according to claim 1, characterized in that: The data acquisition module includes: A conductivity probe is used to insert into the centrifuged aqueous phase. The maximum absolute value of the time derivative of the conductivity measured in real time is taken as the abrupt change value of the conductivity of the aqueous phase. A temperature sensor array is installed at different heights of the cold deslagging tank to plot a cooling curve. The absolute temperature at which the second derivative of the cooling curve is zero is taken as the demulsification point temperature. An ultrasonic interface meter is installed inside the cold slag removal tank, and the rate of change of the settling interface height over time is used as the settling interface movement speed. A full-spectrum probe, installed on the exhaust condensate pipe of the heating tank, is used to measure the absorbance at a wavelength of 254 nm, which is then linearly converted into the COD contribution equivalent of the condensate.

8. The oily wastewater treatment system according to claim 1, characterized in that: The three-phase separator is equipped with an automatic slag discharge valve. The central control module integrates a programmable logic controller (PLC). The PLC is configured to receive the slag discharge frequency of the target three-phase separator and output a pulse control signal of the corresponding frequency to the automatic slag discharge valve to dynamically adjust the slag discharge duty cycle. The cold slag removal tank is equipped with a cooling jacket to provide natural cooling boundary conditions. The light phase outlet in the heating tank is equipped with an RF admittance sensor to measure the dielectric constant of the emulsion layer in real time.

9. A process for treating oily wastewater, wherein the process employs the oily wastewater treatment system described in any one of claims 1-8, characterized in that, Includes the following steps: S1: Real-time acquisition of the following parameters during the treatment of oily wastewater: true density of pure oil phase, electrical conductivity of aqueous phase, density of centrifuged residue, temperature of cold slag removal tank, height of settling interface, turbidity of upper oil sample, frequency of micro-positive pressure pulsation in heating tank, absorbance of condenser pipeline, dielectric constant of emulsion layer, water content of solid residue, and water content and turbidity of light phase outlet. S2: Extract the maximum absolute value of the time derivative of the conductivity as the abrupt change value of the conductivity in the aqueous phase, and combine it with the true density and compactness to obtain the raw material recyclability quality coefficient that characterizes the raw material recycling potential; The absolute temperature at which the second derivative of the cooling curve of the cold slag removal tank is zero is extracted as the demulsification point temperature. Combined with the settling interface movement velocity and the cloud point temperature, the natural cold stratification tendency coefficient, which characterizes the spontaneous ability of phase separation, is obtained. The absorbance is linearly converted into the COD contribution equivalent of the condensate, and combined with the micro-positive pressure pulsation frequency and dielectric constant, the thermo-wet phase transition disturbance coefficient characterizing the thermodynamic instability of the system is obtained. S3: Convert the moisture content of the solid slag into dry matter content, and obtain the fluidization separation compatibility coefficient between the current fluid state and the equipment operation based on the recoverable quality coefficient of the raw material, the natural cold stratification tendency coefficient, the dry matter content, and the water content turbidity of the light phase outlet. S4: Based on the fluidized separation fit coefficient and the thermal-wet phase change disturbance coefficient, the reference slag discharge frequency is dynamically corrected by an exponential scale, the slag discharge frequency of the target three-phase separator is calculated and output, and the corresponding pulse control signal is generated and sent to the automatic slag discharge valve of the three-phase separator to control the three-phase separator to perform dynamic slag discharge according to this frequency.

Images