Method for monitoring and evaluating separation effect of oil-water residue separator

Abstract

The invention discloses a method for monitoring and evaluating the separation effect of an oil-water residue separator, particularly relates to the field of wastewater treatment, and aims to solve the problem of misjudgment of the separation efficiency caused by grease solidification and flow field disorder in a cold start stage. Thermodynamic state offset and flow field stability parameters are accurately calculated, an oil layer semi-solid distribution proportion and separation interface reconstruction delay time are dynamically predicted by combining a pre-training model and an interface recovery theory, an actual effective separation area is solved by utilizing a dynamic compensation algorithm, and an oil layer polymerization degree evolution curve is predicted; finally, the separation effect standard reaching opportunity is intelligently judged through the synchronization rate index of the two-parameter evaluation matrix, oil layer damage caused by too early oil discharge or water quality pollution caused by too late operation is avoided, meanwhile, the equipment operation strategy is optimized by accurately predicting the oil layer polymerization state, ineffective abrasion of mechanical parts is reduced, the service life of key parts is prolonged, and the product quality is improved. And the effluent quality is stable and reaches the standard.

Description

Technical Field

[0001] The invention relates to the field of wastewater treatment, and more specifically to a method for monitoring and evaluating the separation effect of an oil-water-slag separator. Background Art

[0002] In the oil-water-slag separation operation in the catering industry, the equipment is usually concentratedly operated during the daily meal peak hours and shut down for a long time during non-operating hours. During the shutdown period, the residual grease inside the separator solidifies due to the drop in temperature, and the slag is compacted again under the action of gravity to form a compacted layer, resulting in a turbulent flow field and uneven temperature distribution in the cavity at the initial restart. The traditional separation effect evaluation method is based on the modeling of the equipment's continuous operation data, and misjudges the transient operating conditions that have not reached thermal equilibrium during the cold start phase as a stable state, erroneously triggering the oil discharge or stirring command, resulting in falsely high separation efficiency, excessive water quality, and abnormal equipment wear.

[0003] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method for monitoring and evaluating the separation effect of an oil-water-slag separator, which collects the axial temperature distribution and fluid flow velocity fluctuation data of the separation cavity in real time, accurately calculates the thermodynamic state offset and the flow field stability parameters, and dynamically predicts the semi-solid distribution ratio of the oil layer and the delay time of the separation interface reconstruction by combining the pre-training model and the interface recovery theory. The dynamic compensation algorithm is used to solve the actual effective separation area and predict the evolution curve of the oil layer polymerization degree. Finally, the synchronization rate indicator of the dual-parameter evaluation matrix is ​​used to intelligently judge the time when the separation effect meets the standard, so as to avoid oil layer damage caused by premature oil discharge or water pollution caused by too late operation. At the same time, the equipment operation strategy is optimized by accurately predicting the polymerization state of the oil layer, the ineffective wear of mechanical parts is reduced, the service life of key parts is extended, and the water quality of the effluent is ensured to be stable and meet the standards, so as to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: S1. Real-time collection of the axial temperature distribution of the separation chamber and the fluid velocity fluctuation data, calculation of the temperature gradient integral to obtain the thermodynamic state offset, and extraction of the spectral energy concentration of the velocity fluctuation as a flow field stability parameter; S2. Input the thermodynamic state offset into the pre-trained model to output the semi-solid distribution ratio of the oil layer, and calculate the separation interface reconstruction delay time by combining the flow field stability parameters and the equipment downtime through the Kelvin-Helmholtz interface recovery theory; S3. Based on the semi-solid distribution ratio of the oil layer and the delay time of separation interface reconstruction, the dynamic compensation algorithm is used to solve the actual effective separation area. At the same time, combined with the current temperature recovery rate and the semi-solid distribution ratio of the oil layer, the Arrhenius equation is used to predict the evolution curve of the oil layer polymerization degree; S4. A dual-parameter evaluation matrix is ​​established based on the actual effective separation area and the degree of polymerization of the oil layer, the synchronization rate between the two is calculated and compared with the preset evaluation threshold, a separation effect reaching standard signal is generated and the oil discharge instruction execution timing judgment module is triggered.

[0006] In a preferred embodiment, the processing logic of step S1 is as follows: During the equipment restart phase, the axial temperature distribution data of the separation chamber and the fluid flow velocity fluctuation data are collected in real time. Multiple temperature sensors are evenly set along the axial direction of the separation chamber to record the temperature values ​​at different positions to form a temperature distribution sequence that changes with time and position. At the same time, the fluid flow velocity changes are monitored by a flow velocity sensor to obtain a flow velocity sequence that fluctuates with time.

[0007] In a preferred embodiment, step S1 further includes the following logic: Based on the temperature distribution data, the temperature change rate along the axial direction, that is, the temperature gradient, is calculated by dividing the difference between adjacent temperature values ​​by the axial distance, and the thermodynamic state offset is calculated based on this. The difference between the current temperature gradient and the reference temperature gradient during stable operation is accumulated in the entire axial range, and the accumulated result is the thermodynamic state offset; The velocity fluctuation data is analyzed in the frequency domain and converted into spectrum characteristics. The ratio of the spectrum energy within the preset frequency range to the total spectrum energy is calculated to obtain the flow field stability parameters.

[0008] In a preferred embodiment, the processing logic of step S2 is as follows: The thermodynamic state offset is used as input data, and the pre-trained model is used to analyze the oil phase distribution characteristics, and the semi-solid distribution ratio of the oil layer is output, which indicates the volume ratio of the semi-solid state in the oil layer.

[0009] In a preferred embodiment, step S2 further includes the following logic: Combining the flow field stability parameters and the equipment downtime, the separation interface reconstruction delay time is calculated based on the interface recovery theoretical model, and the time scale required from equipment restart to separation interface recovery stability is generated.

[0010] In a preferred embodiment, the processing logic of step S3 is as follows: Based on the semi-solid distribution ratio of the oil layer and the delay time of the reconstruction of the separation interface, the dynamic compensation algorithm is applied to solve the actual effective separation area. The theoretical maximum separation area of ​​the separation cavity is first determined, and then the volume ratio of the flowable oil is calculated according to the semi-solid distribution ratio of the oil layer and multiplied by the theoretical maximum separation area to obtain the separation area contributed by the flowable oil. Then, a time-evolution function with the delay time of the reconstruction of the separation interface as the characteristic time scale is used to describe the dynamic recovery process of the separation area, and the recovery rate is controlled by adjusting the coefficient. Finally, the actual effective separation area is determined by the product of the separation area contributed by the flowable oil and the dynamic recovery function.

[0011] In a preferred embodiment, step S3 further includes the following logic: The evolution curve of the polymerization degree of the oil layer is predicted by combining the current temperature recovery rate and the semi-solid distribution ratio of the oil layer. Specifically, the initial polymerization degree is first determined, and then based on the principle of polymerization kinetics, a rate function that changes with temperature is used to describe the polymerization reaction rate and the invalid contribution of the semi-solid part of the oil layer is eliminated. Finally, the evolution curve of the polymerization degree of the oil layer with time is obtained by accumulating the polymerization rate with time.

[0012] In a preferred embodiment, the processing logic of step S4 is as follows: A dual-parameter evaluation matrix was constructed using the actual effective separation area and the evolution curve of oil layer polymerization degree. The synchronization rate index was calculated by analyzing the changing trends of the actual effective separation area and oil layer polymerization degree over time.

[0013] In a preferred embodiment, step S4 further includes the following logic: The synchronization rate index is compared with the preset evaluation threshold. When the synchronization rate index reaches or exceeds the evaluation threshold, a separation effect reaching standard signal is generated, and the oil discharge instruction execution timing judgment module is triggered to realize the comprehensive evaluation of the separation effect and the optimization judgment of the oil discharge operation timing.

[0014] In a preferred embodiment, the calculation logic of the synchronization rate indicator is as follows: First, the average values ​​of the actual effective separation area and the degree of polymerization of the oil layer within the specified time period are calculated, and then the deviations of the actual effective separation area and the degree of polymerization of the oil layer relative to their respective average values ​​at each time point are calculated. The relationship between the deviations and the ratio of their respective fluctuation amplitudes are calculated by integration to obtain a dimensionless synchronization rate index.

[0015] Technical effects and advantages of a method for monitoring and evaluating the separation effect of an oil-water-slag separator of the present invention: The present invention collects the axial temperature distribution and fluid flow rate fluctuation data of the separation cavity in real time, accurately calculates the thermodynamic state offset and flow field stability parameters, combines the pre-trained model with the interface recovery theory to dynamically predict the semi-solid distribution ratio of the oil layer and the delay time of the separation interface reconstruction, uses the dynamic compensation algorithm to solve the actual effective separation area and predict the polymerization degree evolution curve of the oil layer, and finally intelligently judges the time when the separation effect reaches the standard through the synchronization rate index of the dual-parameter evaluation matrix, effectively solving the problem of misjudgment of separation efficiency caused by oil solidification and flow field turbulence in the cold start stage of traditional methods, significantly improving the evaluation accuracy, avoiding oil layer damage caused by premature oil discharge or water pollution caused by late operation, and optimizing the equipment operation strategy by accurately predicting the polymerization state of the oil layer, reducing the ineffective wear of mechanical parts, extending the service life of key parts, ensuring that the effluent water quality is stable and meets the standards, meeting the requirements of environmental protection supervision, and providing an efficient and reliable full-condition monitoring solution for oil-water residue separators in catering, industry and other scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flow chart of a method for monitoring and evaluating the separation effect of an oil-water-slag separator.

[0017] Figure 2 It is a schematic diagram of the synchronization rate acquisition steps of a method for monitoring and evaluating the separation effect of an oil-water-slag separator of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Embodiment 1: Figure 1 The present invention provides a method for monitoring and evaluating the separation effect of an oil-water-slag separator, comprising: S1. Collect the axial temperature distribution and fluid velocity fluctuation data of the separation cavity in real time, calculate the temperature gradient integral to obtain the thermodynamic state offset, and extract the spectral energy concentration of the velocity fluctuation as the flow field stability parameter.

[0020] S2. Input the thermodynamic state offset into the pre-trained model to output the semi-solid distribution ratio of the oil layer. At the same time, combine the flow field stability parameters and the equipment downtime to calculate the separation interface reconstruction delay time through the Kelvin-Helmholtz interface recovery theory.

[0021] S3. Based on the semi-solid distribution ratio of the oil layer and the delay time of separation interface reconstruction, the dynamic compensation algorithm is used to solve the actual effective separation area. At the same time, combined with the current temperature recovery rate and the semi-solid distribution ratio of the oil layer, the Arrhenius equation is used to predict the evolution curve of the polymerization degree of the oil layer.

[0022] S4. A dual-parameter evaluation matrix is ​​established based on the actual effective separation area and the degree of polymerization of the oil layer, the synchronization rate between the two is calculated and compared with the preset evaluation threshold, a separation effect reaching standard signal is generated and the oil discharge instruction execution timing judgment module is triggered.

[0023] In the oil-water-slag separation operation in the catering industry, the equipment is often intensively operated during peak meal times and shut down for a long time during non-operating periods. During the shutdown period, the residual grease inside the separator solidifies due to the drop in temperature, and the slag is compacted again under the action of gravity to form a compacted layer, resulting in a disordered flow field and uneven temperature distribution in the separation chamber at the initial stage of equipment restart. Traditional evaluation methods are based on continuous operation data modeling, which fails to accurately handle transient operating conditions in the cold start phase, and often misjudges the state that has not reached thermal equilibrium as a stable state, causing erroneous oil discharge or stirring instructions, resulting in falsely high separation efficiency, excessive water quality and equipment wear. In view of the special operating conditions in the equipment restart phase, the present invention proposes to collect temperature and flow rate data in the separation chamber in real time, analyze the thermodynamic and fluid mechanics states, and provide a quantitative basis for subsequent separation effect evaluation.

[0024] The processing logic of step S1 is as follows: S1-1, Data collection:

[0025] During the equipment restart phase, in order to accurately evaluate the thermodynamic state and fluid mechanics characteristics of the separation chamber, it is necessary to collect the axial temperature distribution data and fluid flow rate fluctuation data in the separation chamber in real time.

[0026] The method for collecting axial temperature distribution data is as follows: multiple temperature sensors are evenly arranged along the axial direction of the separation cavity, and the temperature values ​​at different positions are recorded in real time by these sensors to form a temperature distribution sequence that changes with time and position.

[0027] The method for collecting fluid flow velocity fluctuation data is: using a flow velocity sensor to monitor the flow velocity changes of the fluid in the separation chamber in real time, and obtaining sequence data of flow velocity fluctuations over time.

[0028] In this step, a dynamic data sequence is formed through multi-point real-time acquisition. Since the measurement of a single position cannot reflect the overall state of the separation cavity, the dynamic sequence can capture transient changes.

[0029] S1-2, calculation of thermodynamic state shift: The thermodynamic state deviation is calculated based on the axial temperature distribution data to quantify the degree of thermodynamic state deviation of the separation cavity.

[0030] The rate of change of temperature along the axial position, that is, the degree of temperature change within a unit distance, is called the temperature gradient. The specific method is: take the difference between the temperature values ​​recorded by two adjacent temperature sensors, divide it by the axial distance between the two sensors, and get the temperature gradient of the section. Then calculate the temperature gradient between all adjacent sensors.

[0031] The thermodynamic state offset is calculated based on the temperature gradient. The method is: subtract the current temperature gradient from the reference temperature gradient when the equipment is in stable operation to obtain the temperature gradient difference of each section. The temperature gradient differences of all sections are accumulated from the axial starting point to the end point of the separation chamber. The accumulated result is the thermodynamic state offset, which indicates the cumulative degree of deviation of the temperature distribution from the stable operating state.

[0032] The thermodynamic deviation of the entire separation chamber is comprehensively evaluated by accumulating temperature gradients. Local temperature measurement cannot reflect the overall state, while the accumulation method can reflect the total amount of deviation; thus providing a quantitative indicator for judging whether the equipment has recovered from the abnormal state of cold start to a near-stable operating state.

[0033] S1-3, flow field stability parameter calculation: The flow field stability parameters are calculated based on the fluid velocity fluctuation data to quantify the stability of the fluid in the separation chamber.

[0034] The velocity fluctuation data is subjected to frequency domain analysis. The specific method is as follows: the time-varying velocity sequence data is converted into frequency domain signals through fast Fourier transform to obtain the frequency spectrum characteristics of the velocity fluctuation, which reflects the distribution of the velocity fluctuation at different frequencies.

[0035] The spectral energy concentration is calculated as a flow field stability parameter. The specific method is as follows: a specific frequency range is determined in advance according to the equipment operation characteristics, and the range corresponds to the dominant fluctuation frequency of the flow field; then, the sum of the spectral energy within the frequency range is calculated, and then the sum of the spectral energy within the entire frequency range is calculated, and the former is divided by the latter to obtain a ratio, namely the spectral energy concentration. This parameter is a dimensionless value ranging from 0 to 1. The larger the value, the more concentrated the flow velocity fluctuation is at a specific frequency, and the more stable the flow field is.

[0036] The flow field stability is quantified by spectral energy concentration. The reason is that the mean value of flow velocity or simple change amplitude cannot reveal the dynamic characteristics of the flow field, while spectral analysis can capture the essence of fluctuations. It can accurately reflect the flow field instability caused by oil solidification and slag compaction during the cold start stage, and provide a basis for analyzing the reconstruction delay time of the separation interface.

[0037] Step S1 calculates the thermodynamic state offset and flow field stability parameters by collecting the axial temperature distribution data and fluid velocity fluctuation data of the separation chamber in real time. However, these parameters alone cannot fully quantify the dynamic reconstruction process of the semi-solid distribution of the oil layer and the separation interface during the cold start phase, both of which have a key impact on the separation effect. Therefore, step S2 needs to use the output of step S1 to further infer the semi-solid distribution ratio of the oil layer and calculate the delay time of the separation interface reconstruction.

[0038] The semi-solid distribution ratio of the oil layer reflects the proportion of the oil layer that cannot flow due to low-temperature solidification. This parameter directly determines the effectiveness of the amount of separable oil, because during the cold start phase, the phase state of oil and grease is significantly affected by temperature, and some oil and grease may condense into a semi-solid state, reducing fluidity. By quantifying this ratio, the actual amount of oil that can be separated can be accurately evaluated, thereby avoiding the error caused by the traditional method of ignoring the change of oil and grease phase under transient conditions.

[0039] Secondly, the separation interface reconstruction delay time characterizes the time required for the flow field to recover from a turbulent state to a stable stratified state. This parameter determines the time point when the equipment reaches a stable separation efficiency. During the cold start process, the flow field is initially in an unstable state, and the interface of oil, water, and slag requires a certain amount of time to reconstruct and stratify. By measuring this delay time, the response characteristics of the dynamic performance of the equipment can be understood, providing a basis for optimizing the separation process.

[0040] In summary, the acquisition of these two parameters makes up for the shortcomings of traditional evaluation methods in terms of the dynamic effects of oil phase state and flow field under transient conditions. By introducing the measurement of these two parameters in step S2, reliable data support can be provided for the subsequent dynamic compensation strategy and polymerization degree prediction model, thereby improving the accuracy and real-time performance of the separation effect evaluation and ensuring the performance optimization of the equipment during the cold start phase.

[0041] The processing logic of step S2 is as follows: S2-1, obtain the semi-solid distribution ratio of the oil layer: In order to quantify the distribution ratio of semi-solid oil in the oil layer, the thermodynamic state offset is used as input data. The phase recognition model is a mathematical model pre-trained based on historical experimental data, which can infer the phase distribution characteristics of oil based on the thermodynamic state offset. Specifically: the thermodynamic state offset is input into the phase recognition model, and the model analyzes the correspondence between the offset and the oil phase through an internal algorithm, and outputs the volume ratio of the current oil layer in a semi-solid state, which is called the semi-solid distribution ratio of the oil layer, and the numerical range is limited to between 0 and 1. The phase recognition model uses machine learning methods to convert thermodynamic data into oil phase parameters. Since the semi-solid structure formed by the solidification of oil at low temperature will significantly affect the separation efficiency, it is difficult for traditional technologies to quantify the distribution ratio of semi-solid oil in real time.

[0042] S2-2, calculation of separation interface reconstruction delay time: In order to evaluate the time required for the separation interface to recover to a stable state after the equipment is restarted, the interface recovery theory in fluid mechanics is used, combined with the flow field stability parameters and equipment downtime calculated in step S1 for analysis. The equipment downtime refers to the length of time from the equipment stopping to restarting. The calculation of the separation interface reconstruction delay time is based on the classic Kelvin-Helmholtz interface recovery theory model. The specific method is as follows: first determine the physical parameters of the fluid, such as dynamic viscosity, fluid density and characteristic flow velocity, where the dynamic viscosity reflects the viscous resistance characteristics of the fluid, the fluid density characterizes the mass distribution of the mixture, and the characteristic flow velocity is the average flow velocity of the fluid in the separation chamber, reflecting the inertia of the fluid; then, the equipment downtime and flow field stability parameters are combined to calculate a time scale, which represents the length of time required from the restart of the equipment to the recovery of the separation interface to stability, called the separation interface reconstruction delay time. During the calculation process, the longer the equipment is shut down, the more significant the initial disturbance of the flow field, and the lower the flow field stability parameter, all of which indicate that the fluid stability is poor, thereby prolonging the interface recovery time; at the same time, parameters such as dynamic viscosity, fluid density, and characteristic flow velocity jointly regulate the dynamic equilibrium state of the fluid and affect the interface recovery speed. The technical feature of the calculation of the delay time for separation interface reconstruction is that it quantifies the time required for interface recovery through a theoretical model, providing accurate time parameters for the dynamic compensation algorithm, and ensuring the timeliness and reliability of the separation effect evaluation.

[0043] For example, the calculation method for obtaining the calculation separation interface reconstruction delay time can be as follows: The interface reconstruction theory in fluid mechanics is used to calculate the separation interface reconstruction delay time by combining the downtime and flow field characteristics. The calculation formula is based on the classic Kelvin-Helmholtz interface recovery model, as follows: ; : The dynamic viscosity of the fluid is determined by the physical properties of the oil-water mixture and reflects the viscous resistance.

[0044] : Fluid density, characterizing the mass distribution of the mixture.

[0045] : Characteristic flow velocity, determined according to the average flow velocity in the separation chamber, reflecting the fluid inertia.

[0046] : Flow field stability parameters.

[0047] : Equipment downtime duration.

[0048] This formula is derived from Kelvin-Helmholtz instability analysis and describes the time scale for recovery from interface disturbances. The extension will lead to the intensification of the initial disturbance of the flow field. When the viscosity is low, the fluid stability is insufficient, which increases the time consumption of interface reconstruction. With density Ratio and flow rate This regulates the dynamic balance of the fluid.

[0049] The processing technology of step S2 is aimed at the special working conditions of the oil-water-slag separation equipment during the cold start phase. The phase recognition model is used to quantify the semi-solid distribution ratio of the oil layer, and the separation interface reconstruction delay time is calculated based on the interface recovery theory. The phase recognition model uses the thermodynamic state offset to infer the phase distribution characteristics of oil and fat, solving the quantification problem of the effect of oil and fat solidification on separation efficiency; the calculation of the separation interface reconstruction delay time combines the flow field stability parameters and the equipment downtime to provide the time scale of the dynamic recovery process of the separation interface, making up for the shortcomings of the traditional method in transient process evaluation.

[0050] Based on the output of step S1, step S2 uses the phase recognition model and coupling analysis to obtain the semi-solid distribution ratio of the oil layer and the delay time of the separation interface reconstruction. However, these parameters alone cannot directly reflect the actual separation efficiency and the dynamic evolution of the oil layer polymerization degree, which are the core indicators for judging whether the equipment has reached a stable operating state. Therefore, step S3 needs to further quantify the actual effective separation area based on the output of step S2 and predict the evolution curve of the oil layer polymerization degree.

[0051] The actual effective separation area is calculated by comprehensively considering the semi-solid distribution ratio of the oil layer and the delay time of the reconstruction of the separation interface, and dynamically correcting the theoretical separation area to reflect the limited separation capacity caused by oil solidification and flow field instability during the cold start stage, which makes up for the deficiency of the traditional method assuming a constant separation area, thereby improving the real-time and accuracy of the evaluation. The prediction of the evolution curve of the degree of polymerization of the oil layer is based on the current temperature recovery rate and the semi-solid distribution ratio of the oil layer, analyzing the polymerization reaction trend of the oil during the temperature recovery process, revealing the law of change of the oil layer state over time, solving the problem of traditional evaluation ignoring the dynamic change of oil quality, and providing data support for judging the separation efficiency and oil quality stability. The implementation of these two processes ensures that step S3 can accurately capture the separation characteristics under transient conditions.

[0052] The processing logic of step S3 is as follows: S3-1, dynamic compensation algorithm solves the actual effective separation area: In order to accurately evaluate the actual separation capacity of the separation chamber, the semi-solid distribution ratio of the oil layer and the delay time of separation interface reconstruction are first used as input data. The semi-solid distribution ratio of the oil layer indicates the volume ratio of the oil layer in a semi-solid state, reflecting the reduction effect of oil solidification on the separation effect; the delay time of separation interface reconstruction indicates the time scale required for the separation interface to restart and recover stability, reflecting the delay characteristics of the dynamic recovery of the flow field.

[0053] The processing process of the dynamic compensation algorithm is: Determine the theoretical maximum separation area of ​​the separation chamber, which is determined by the equipment design parameters and represents the separation capacity under ideal conditions; Based on the semi-solid distribution ratio of the oil layer, the contribution ratio of the flowable oil to the separation area is calculated, which is specifically the theoretical maximum separation area multiplied by the volume ratio of the flowable oil, that is, the result of multiplying the theoretical maximum separation area by 1 minus the semi-solid distribution ratio of the oil layer; Considering the dynamic process of the separation interface gradually recovering over time, a function that evolves over time is used to describe the recovery trend of the separation area. This function uses the delay time of separation interface reconstruction as the characteristic time scale and controls the recovery rate through an adjustment coefficient. The actual effective separation area is determined by the product of the contribution ratio of the flowable grease and the dynamic recovery function. The dynamic compensation algorithm comprehensively considers the influence of the grease phase and flow field dynamics on the separation ability. Traditional methods usually assume that the separation area is constant and ignore the transient characteristics of the cold start phase, resulting in evaluation results that deviate from reality.

[0054] For example, the dynamic compensation algorithm can calculate the actual effective separation area as follows: The dynamic compensation algorithm is used to comprehensively consider the influence of the semi-solid distribution ratio of the oil layer and the delay time of the separation interface reconstruction to calculate the actual effective separation area. The calculation formula is as follows: ; Parameter explanation: : The theoretical maximum separation area of ​​the separation chamber is determined by the equipment design parameters and reflects the separation capacity under ideal conditions.

[0055] : The semi-solid distribution ratio of the oil layer (dimensionless), directly derived from the S2 output, reflects the reduction effect of oil solidification on the separation area.

[0056] : The running time after the device is restarted, starting from the restart time, indicating the time point of the current running status.

[0057] : Delay time of separation interface reconstruction, derived from S2 output, represents the time characteristics of dynamic recovery of the interface.

[0058] : Adjustment coefficient (dimensionless), calibrated by equipment characteristics, characterizes the rate at which the separation area recovers over time.

[0059] Formula function: Correct the contribution of the mobile portion of the oil layer to the separation area. It describes the dynamic process of the separation area gradually recovering over time, reflecting the delayed characteristics of interface reconstruction.

[0060] S3-2, prediction of evolution curve of oil layer polymerization degree: In order to further analyze the dynamic evolution of the oil layer state, the evolution trend of the oil layer polymerization degree over time is predicted by combining the current temperature recovery rate and the semi-solid distribution ratio of the oil layer. The current temperature recovery rate is obtained by time difference calculation of real-time temperature data, reflecting the dynamic trend of temperature recovery in the separation chamber; the semi-solid distribution ratio of the oil layer represents the volume proportion of the non-flowable part in the oil layer. The processing process of predicting the evolution curve of the oil layer polymerization degree is as follows: first determine the initial polymerization degree, which is obtained from historical data or calibration experiments, and characterizes the polymerization state of the oil layer at the initial stage of cold start; then, based on the principle of polymerization kinetics, considering the influence of temperature on the polymerization rate, a rate function that changes with temperature is used to describe the speed of the polymerization reaction. This function is adjusted by parameters such as activation energy and gas constant; at the same time, the invalid contribution of the semi-solid part in the oil layer to the polymerization reaction is eliminated, and only the participation of the flowable oil is considered; finally, the evolution curve of the oil layer polymerization degree over time is obtained by accumulating the polymerization rate over time. The technical feature of the prediction of the evolution curve of the oil layer polymerization degree is to predict the change of the oil layer state by combining temperature dynamics and oil phase state.

[0061] For example, the calculation method for predicting the evolution curve of oil layer polymerization degree can be as follows: Based on the Arrhenius equation and oil polymerization kinetics, the evolution curve of oil layer polymerization degree over time is predicted (dimensionless). The calculation formula is as follows: ; Parameter explanation: : Initial degree of polymerization (dimensionless), determined by historical data or calibration experiments, represents the polymerization state of the oil layer at the initial stage of cold start.

[0062] : The polymerization rate constant characterizes the inherent speed of oil polymerization reaction and is determined experimentally.

[0063] : Activation energy, reflecting the energy barrier of polymerization reaction, is determined by the characteristics of oil and fat.

[0064] : Gas constant (8.314 J / mol·K), a universal physical constant.

[0065] : Temperature changes over time, through real-time temperature data and Calculate, that is is the initial temperature).

[0066] : The semi-solid distribution ratio of the oil layer is derived from the S2 output and is used to correct the proportion of oil and fat that effectively participates in polymerization.

[0067] Formula function: Reflects the exponential effect of temperature on polymerization rate. Eliminate the ineffective contribution of semi-solid oil to the polymerization reaction. The integral form reflects the cumulative evolution characteristics of the degree of polymerization.

[0068] The processing technology of step S3 is aimed at the dynamic characteristics of the oil-water residue separation equipment during the cold start phase. The actual effective separation area is accurately calculated through the dynamic compensation algorithm, and the evolution curve of the polymerization degree of the oil layer is predicted based on the principle of polymerization kinetics. The dynamic compensation algorithm comprehensively considers the influence of the oil phase state and flow field dynamics on the separation ability, and solves the problem of insufficient transient characteristic evaluation of the traditional method; the prediction of the evolution curve of the polymerization degree of the oil layer combines the temperature dynamics and the oil phase state, providing a dynamic description of the oil layer state, making up for the defects of the traditional method in analyzing oil quality changes. The generation of these two parameters not only provides key input data for step S4, but also ensures the logical coherence of the entire technical process and the consistency of data transmission, thereby significantly improving the accuracy and reliability of the separation effect evaluation.

[0069] The processing logic of step S4 is as follows: S4-1, dual parameter evaluation matrix establishment: The actual effective separation area and the oil layer polymerization degree evolution curve outputted in step S3 are used as input data.

[0070] The construction process of the dual-parameter evaluation matrix is ​​as follows: the actual effective separation area and the degree of polymerization of the oil layer are taken as the two key parameters of the matrix, and the coordination between the two is quantified by analyzing their changing trends over time. Figure 2 , the specific method is: Firstly, the average values ​​of the actual effective separation area and the degree of polymerization of the oil layer over a period of time are calculated; Then, the deviations of the actual effective separation area and the polymerization degree of the oil layer from their respective average values ​​at each time point are analyzed, and the correlation between these deviations and their respective fluctuation ranges are calculated by integration; Finally, a dimensionless synchronization index is obtained by using the ratio of the deviation correlation to the fluctuation amplitude. The synchronization index reflects the consistency of the actual effective separation area and the change trend of the oil layer polymerization degree. The technical feature of the dual-parameter evaluation matrix is ​​to quantify the coordination of the separation ability and the oil layer state through the synchronization index. The reason is that the stability of the separation effect depends not only on the recovery of the actual effective separation area, but also requires the oil layer polymerization degree to be maintained at an appropriate level; its benefit is that it provides a scientific basis for the comprehensive evaluation of the equipment operation status, ensuring the comprehensiveness and accuracy of the evaluation.

[0071] For example, the synchronization rate can be calculated as follows: Constructing a two-parameter evaluation matrix , whose elements are separated by the actual effective area and the degree of polymerization of the oil layer Calculate the synchronization rate between the two over time , used to measure and The consistency of the changing trend. Synchronicity The calculation formula is: ; Parameter explanation: : At time The actual effective separation area at .

[0072] : From the initial time To current time The average value of the actual effective separation area.

[0073] : At time The degree of polymerization of the oil layer.

[0074] : From the initial time To current time The average value of the degree of polymerization of the oil layer.

[0075] : Synchronization rate (dimensionless), value range [-1,1], the closer the value is to 1, the better and The more consistent the changing trend is.

[0076] S4-2, separation effect reaching standard signal generation: In order to determine whether the equipment has reached a stable separation state, a preset evaluation threshold is set based on the synchronization rate index calculated in the dual-parameter evaluation matrix. The preset evaluation threshold is determined through equipment operation experience or experimental calibration, and represents the minimum requirement of the synchronization rate index. The generation process of the separation effect standard signal is: real-time comparison of the synchronization rate index at the current moment with the preset evaluation threshold; when the synchronization rate index reaches or exceeds the preset evaluation threshold, it indicates that the change trend of the actual effective separation area and the degree of polymerization of the oil layer has become coordinated and consistent, and the equipment has entered a stable separation state, and a separation effect standard signal is generated at this time.

[0077] S4-3, the oil discharge instruction execution timing judgment module is triggered: In order to ensure that the timing of the oil discharge operation is scientific and reasonable, the oil discharge instruction execution timing judgment module is triggered based on the separation effect reaching standard signal.

[0078] Once the separation effect reaches the standard signal, the oil discharge instruction execution timing judgment module is immediately activated; the oil discharge instruction execution timing judgment module further determines the specific execution time of the oil discharge operation according to the equipment operation strategy and current status. The oil discharge instruction execution timing judgment module uses the separation effect reaches the standard signal as a trigger condition and executes after the equipment is running stably to avoid premature oil discharge resulting in a decrease in separation efficiency or late oil discharge causing water pollution.

[0079] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0080] It should be noted that the system of the present invention can be deployed on the device itself to realize embedded applications, and can also be run on a PC or other terminal with a user interface, thereby meeting a variety of hardware environments and usage requirements.

[0081] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0082] It should be noted that, in this article, if there are relational terms such as first and second, etc., they are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including a..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0083] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for monitoring and evaluating the separation effect of an oil-water-slag separator, characterized in that: Includes steps: S1. Real-time collection of the axial temperature distribution of the separation chamber and the fluid velocity fluctuation data, calculation of the temperature gradient integral to obtain the thermodynamic state offset, and extraction of the spectral energy concentration of the velocity fluctuation as a flow field stability parameter; S2. Input the thermodynamic state offset into the pre-trained model to output the semi-solid distribution ratio of the oil layer, and calculate the separation interface reconstruction delay time by combining the flow field stability parameters and the equipment downtime through the Kelvin-Helmholtz interface recovery theory; S3. Based on the semi-solid distribution ratio of the oil layer and the delay time of separation interface reconstruction, the dynamic compensation algorithm is used to solve the actual effective separation area. At the same time, combined with the current temperature recovery rate and the semi-solid distribution ratio of the oil layer, the Arrhenius equation is used to predict the evolution curve of the oil layer polymerization degree; S4. A dual-parameter evaluation matrix is ​​established based on the actual effective separation area and the degree of polymerization of the oil layer, the synchronization rate between the two is calculated and compared with the preset evaluation threshold, a separation effect reaching standard signal is generated and the oil discharge instruction execution timing judgment module is triggered.

2. The method for monitoring and evaluating the separation effect of an oil-water-slag separator according to claim 1, characterized in that: The processing logic of step S1 is as follows: During the equipment restart phase, the axial temperature distribution data of the separation chamber and the fluid flow velocity fluctuation data are collected in real time. Multiple temperature sensors are evenly set along the axial direction of the separation chamber to record the temperature values ​​at different positions to form a temperature distribution sequence that changes with time and position. At the same time, the fluid flow velocity changes are monitored by a flow velocity sensor to obtain a flow velocity sequence that fluctuates with time.

3. The method for monitoring and evaluating the separation effect of an oil-water-slag separator according to claim 2, characterized in that: Step S1 also includes the following logic: Based on the temperature distribution data, the temperature change rate along the axial direction, that is, the temperature gradient, is calculated by dividing the difference between adjacent temperature values ​​by the axial distance, and the thermodynamic state offset is calculated based on this. The difference between the current temperature gradient and the reference temperature gradient during stable operation is accumulated in the entire axial range, and the accumulated result is the thermodynamic state offset; The velocity fluctuation data is analyzed in the frequency domain and converted into spectrum characteristics. The ratio of the spectrum energy within the preset frequency range to the total spectrum energy is calculated to obtain the flow field stability parameters.

4. The method for monitoring and evaluating the separation effect of an oil-water-slag separator according to claim 3, characterized in that: The processing logic of step S2 is as follows: The thermodynamic state offset is used as input data, and the pre-trained model is used to analyze the oil phase distribution characteristics, and the semi-solid distribution ratio of the oil layer is output, which indicates the volume ratio of the semi-solid state in the oil layer.

5. The method for monitoring and evaluating the separation effect of an oil-water-slag separator according to claim 4, characterized in that: Step S2 also includes the following logic: Combining the flow field stability parameters and the equipment downtime, the separation interface reconstruction delay time is calculated based on the interface recovery theoretical model, and the time scale required from equipment restart to separation interface recovery stability is generated.

6. The method for monitoring and evaluating the separation effect of an oil-water-slag separator according to claim 5, characterized in that: The processing logic of step S3 is as follows: Based on the semi-solid distribution ratio of the oil layer and the delay time of the reconstruction of the separation interface, the dynamic compensation algorithm is applied to solve the actual effective separation area. The theoretical maximum separation area of ​​the separation cavity is first determined, and then the volume ratio of the flowable oil is calculated according to the semi-solid distribution ratio of the oil layer and multiplied by the theoretical maximum separation area to obtain the separation area contributed by the flowable oil. Then, a time-evolution function with the delay time of the reconstruction of the separation interface as the characteristic time scale is used to describe the dynamic recovery process of the separation area, and the recovery rate is controlled by adjusting the coefficient. Finally, the actual effective separation area is determined by the product of the separation area contributed by the flowable oil and the dynamic recovery function.

7. The method for monitoring and evaluating the separation effect of an oil-water-slag separator according to claim 6, characterized in that: Step S3 also includes the following logic: The evolution curve of the polymerization degree of the oil layer is predicted by combining the current temperature recovery rate and the semi-solid distribution ratio of the oil layer. Specifically, the initial polymerization degree is first determined, and then based on the principle of polymerization kinetics, a rate function that changes with temperature is used to describe the polymerization reaction rate and the invalid contribution of the semi-solid part of the oil layer is eliminated. Finally, the evolution curve of the polymerization degree of the oil layer with time is obtained by accumulating the polymerization rate with time.

8. The method for monitoring and evaluating the separation effect of an oil-water-slag separator according to claim 7, characterized in that: The processing logic of step S4 is as follows: A dual-parameter evaluation matrix was constructed using the actual effective separation area and the evolution curve of oil layer polymerization degree. The synchronization rate index was calculated by analyzing the changing trends of the actual effective separation area and oil layer polymerization degree over time.

9. The method for monitoring and evaluating the separation effect of an oil-water-slag separator according to claim 8, characterized in that: Step S4 also includes the following logic: The synchronization rate index is compared with the preset evaluation threshold. When the synchronization rate index reaches or exceeds the evaluation threshold, a separation effect reaching standard signal is generated, and the oil discharge instruction execution timing judgment module is triggered to realize the comprehensive evaluation of the separation effect and the optimization judgment of the oil discharge operation timing.

10. The method for monitoring and evaluating the separation effect of an oil-water-slag separator according to claim 8, characterized in that: The calculation logic of the synchronization rate indicator is as follows: First, the average values ​​of the actual effective separation area and the degree of polymerization of the oil layer within the specified time period are calculated, and then the deviations of the actual effective separation area and the degree of polymerization of the oil layer relative to their respective average values ​​at each time point are calculated. The relationship between the deviations and the ratio of their respective fluctuation amplitudes are calculated by integration to obtain a dimensionless synchronization rate index.

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