An oil-containing sewage treatment method, device and system

Abstract

The present application relates to the technical field of sewage treatment, in particular to an oily sewage treatment method, device and system, which first evaluates the one-way accumulation degree of the gas group according to the time sequence change of the concentration, and accurately locks the stable time of the gas group in combination with the time sequence change stability trend, so as to truly capture the evolution law of the leakage gas group and exclude local transient disturbance; further, the pollution confidence is verified and determined from the time-space multidimensional cross verification by comprehensively considering the one-way accumulation degree of the gas group, the vertical gradient hierarchical distribution law and the overall fluctuation of the monitoring concentration before the stable time of the gas group, so as to effectively eliminate the misjudgment caused by the environmental factors; finally, the oily sewage treatment operation is adaptively executed according to the high-reliability pollution confidence, so as to avoid blind adjustment or unnecessary process interruption, and the accuracy of evaluating the gas leakage risk and feeding back the adjustment of the oily sewage treatment process is higher.

Description

Technical Field

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

[0002] In integrated oily wastewater treatment processes, because the treatment unit is typically located within a closed enclosure, hazardous gases such as dissolved methane and hydrogen sulfide in the wastewater are prone to precipitate and accumulate within the confined space. To ensure the safety of the continuous treatment process and to adaptively adjust the oil removal and slag discharge process, real-time monitoring of the pollutant gas status within the enclosure is necessary to mitigate safety risks. Existing technologies typically employ a single-point static concentration monitoring method, which involves deploying sensors at fixed locations within the enclosure. When the gas concentration detected at a single location exceeds a preset threshold, it is directly determined that a gas accumulation and leak has occurred, triggering corresponding wastewater regulation or ventilation actions.

[0003] However, this monitoring method based on fixed concentration values ​​at a single point does not take into account the significant vertical gradient stratification characteristics of hazardous gases of different densities escaping into a confined space. It also ignores the temporal evolution of unidirectional gas cloud accumulation during actual leaks, making it highly susceptible to interference from factors such as localized temperature changes or transient airflow disturbances within the enclosure. This limitation fails to accurately reflect the stable accumulation state and physical distribution characteristics of multi-component pollutants in a three-dimensional space, leading to misjudgments of actual leak risks and pollution confidence levels. This, in turn, causes unnecessary interruptions or improper adjustments to treatment processes, ultimately resulting in low accuracy of existing technologies in assessing gas leak risks and providing feedback for adjusting oily wastewater treatment processes based on fixed concentration values ​​at a single point. Summary of the Invention

[0004] To address the low accuracy of existing technologies that assess gas leakage risk and adjust oily wastewater treatment processes based on single-point fixed concentrations, the present invention aims to provide an oily wastewater treatment method, apparatus, and system. The specific technical solution adopted is as follows: The first aspect of this invention provides a method for treating oily wastewater, comprising: At each sampling time, the concentration of each monitored gas in the integrated oily wastewater treatment device is obtained at different vertical gradient levels at each monitoring point within the device's casing. For each type of gas monitored at each monitoring point, the unidirectional accumulation degree of the gas mass at each sampling time is determined based on the temporal changes in the monitored concentration at different vertical gradient levels; and the stable time of the gas mass is determined based on the temporal stability trend of the unidirectional accumulation degree. Based on the unidirectional accumulation degree of the air mass, the hierarchical distribution of the vertical gradient of the monitoring concentration of each monitoring gas at each monitoring point at the stable time of the air mass, and the overall fluctuation of the monitoring concentration before the stable time of the air mass, the pollution confidence level is determined. Oily wastewater is treated based on the pollution confidence level.

[0005] Furthermore, the process of obtaining the unidirectional accumulation degree of the air mass includes: Each sampling time is taken as the target time in sequence; all sampling times within the preset historical time window of the target time are taken as the corresponding accumulation analysis time. For each monitoring point of each monitored gas: Based on the absolute deviation between the monitored concentrations at adjacent accumulation analysis times for each vertical gradient level, the absolute concentration change coefficient at each accumulation analysis time is determined; based on the central tendency of the absolute concentration change coefficients at all accumulation analysis times, the degree of absolute concentration change is determined; based on the temporal increasing distribution of all monitored concentrations corresponding to each vertical gradient level, the number of concentration increasing times is determined. Based on the degree of absolute concentration change and the number of concentration increase moments, the hierarchical unidirectional accumulation degree of each monitoring point for each type of gas under each vertical gradient level is determined; based on the maximum value of the hierarchical unidirectional accumulation degree of each monitoring point for each type of gas under all vertical gradient levels, the gas mass unidirectional accumulation degree at the target time is determined.

[0006] Furthermore, the process of obtaining the stable moment of the air mass includes: For each monitoring point of each type of gas, the degree of gas mass accumulation difference is determined based on the deviation between the gas mass unidirectional accumulation degree at each sampling time and the gas mass unidirectional accumulation degree at the previous sampling time; the sampling time at which the first corresponding gas mass accumulation difference degree in time sequence is less than the preset stability threshold is taken as the gas mass stability time.

[0007] Furthermore, the process of obtaining the pollution confidence level includes: Based on the degree of convergence of the ideal distribution of the monitoring concentration of each monitored gas under different vertical gradient levels, the corresponding distribution regularity is determined; For each monitored gas at each monitoring point, the vertical gradient level with the highest monitored concentration at the stable moment of the gas mass is taken as the historical analysis level; the degree of concentration characteristic fluctuation is determined based on the range of all monitored concentrations corresponding to the historical analysis level at all sampling moments before the stable moment of the gas mass. Based on the unidirectional accumulation degree of the air mass at the stable moment, the degree of concentration characteristic fluctuation, and the distribution regularity, the pollution confidence level of each monitored gas at each monitoring point is determined; the unidirectional accumulation degree of the air mass, the degree of concentration characteristic fluctuation, and the distribution regularity are all positively correlated with the pollution confidence level.

[0008] Furthermore, after determining the pollution confidence level, the process also includes: After the air mass stabilizes, a square wave pulsed airflow is applied, and the pollution leakage weight is determined based on the pulse pattern of the monitored concentration after the application. The pollution confidence level is then corrected based on the pollution leakage weight to determine the corrected pollution confidence level.

[0009] Furthermore, the process of obtaining the pollution leakage weight includes: Two pulse phase segments of the square wave pulsed airflow are obtained in each pulse cycle; for each monitored gas at each monitoring point, the corresponding concentration characteristic value is determined based on the average monitoring concentration at the historical analysis level at all sampling times in each pulse phase segment. The concentration characteristic values ​​of all pulse phase segments are sequentially arranged to determine the pulse characteristic value sequence; a preset pulse reference sequence with the same length as the pulse characteristic value sequence is obtained; and the corresponding pollution leakage weight is determined based on the absolute value of the Pearson correlation coefficient between the pulse characteristic value sequence and the preset pulse reference sequence.

[0010] Furthermore, the process of treating oily wastewater based on the pollution confidence level includes: The corresponding decision confidence level is determined based on the maximum pollution confidence level of all monitored gases at all monitoring points; If the determination confidence level is less than or equal to a preset first determination threshold, the wastewater treatment adjustment coefficient is set to a preset first reference coefficient; if the determination confidence level is greater than or equal to a preset second determination threshold, the wastewater treatment adjustment coefficient is set to a preset second reference coefficient; the preset first determination threshold is less than the preset second determination threshold; the preset first reference coefficient is greater than the preset second reference coefficient. If the determination confidence level is greater than a preset first determination threshold and less than a preset second determination threshold, then the negative correlation mapping value of the determination confidence level is used as the corresponding wastewater treatment adjustment coefficient. Oily wastewater is treated according to the aforementioned wastewater treatment adjustment coefficient.

[0011] Furthermore, the process of treating oily wastewater according to the wastewater treatment adjustment coefficient includes: The wastewater influent volume is weighted by the wastewater treatment adjustment coefficient to determine the final treated wastewater influent volume; oily wastewater is then treated based on the final treated wastewater influent volume.

[0012] In a second aspect, the present invention provides an oily wastewater treatment system, the system comprising: The data acquisition module is used to acquire the monitoring concentration of each monitored gas in the integrated oily wastewater treatment device at different vertical gradient levels at each monitoring point at each sampling time. The first determining module is used to determine the unidirectional accumulation degree of the gas mass at each sampling time for each type of gas at each monitoring point, based on the temporal changes in the monitoring concentration under different vertical gradient levels; and to determine the stable time of the gas mass based on the temporal stability trend of the unidirectional accumulation degree of the gas mass. The second determining module is used to determine the pollution confidence level based on the unidirectional accumulation degree of the air mass, the hierarchical distribution law of the vertical gradient of the monitoring concentration of each monitoring gas at each monitoring point at the stable time of the air mass, and the overall fluctuation of the monitoring concentration before the stable time of the air mass. An oily wastewater treatment module is used to treat oily wastewater based on the pollution confidence level.

[0013] Thirdly, the present invention provides an oily wastewater treatment apparatus, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the steps of an oily wastewater treatment method.

[0014] This application has the following beneficial effects: This application first assesses the unidirectional accumulation degree of the gas mass based on the temporal changes in concentration, and accurately pinpoints the stable moment of the gas mass by combining its temporal stability trend, thereby truly capturing the evolution law of the leaked gas mass and eliminating local transient disturbances. Furthermore, it integrates the unidirectional accumulation degree of the gas mass, the hierarchical distribution law of the vertical gradient, and the overall fluctuation of the monitored concentration before the stable moment of the gas mass, cross-validating and determining the pollution confidence level from multiple spatiotemporal dimensions, effectively eliminating misjudgments caused by environmental factors. Finally, based on this highly reliable pollution confidence level, it adaptively executes oily wastewater treatment operations, avoiding blind adjustments or unnecessary process interruptions, thus making the assessment of gas leakage risk and feedback adjustment of the oily wastewater treatment process more accurate. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of an oily wastewater treatment method according to an embodiment of the present invention; Figure 2 This is a structural diagram of an oily wastewater treatment system provided in one embodiment of the present invention; Figure 3 This is a schematic diagram of an oily wastewater treatment device according to an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an oily wastewater treatment method, apparatus, and system proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment, and specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details a specific scheme for an oily wastewater treatment method, apparatus, and system provided by the present invention.

[0020] This invention provides a method for treating oily wastewater. Please refer to [link / reference]. Figure 1 The diagram illustrates a flow chart of an oily wastewater treatment method according to an embodiment of the present invention, the method comprising: Step S101: At each sampling time, obtain the monitoring concentration of each monitored gas in the integrated oily wastewater treatment device at different vertical gradient levels at each monitoring point.

[0021] To accurately capture the gas distribution characteristics within the integrated oily wastewater treatment unit, this embodiment of the invention first acquires the monitoring concentration of each monitored gas at different vertical gradient levels at each monitoring point at each sampling time. Specifically, the integrated oily wastewater treatment unit is typically integrated and enclosed within a box-shaped space. Since oily wastewater easily releases hazardous gases of varying densities during treatment (e.g., methane with a density much lower than air and hydrogen sulfide with a density greater than air), this embodiment of the invention uniformly plans multiple circumferential positions along the inner wall of the box as monitoring points. The number of monitoring points in this embodiment is set to 12, which can be adjusted according to the monitoring accuracy requirements of the specific implementation environment. For each inner wall monitoring point, three vertical gradient levels at different heights are set along the vertical direction of the inner wall of the box. In this embodiment of the invention, gas sensor modules are fixedly installed against the wall at the upper level (0.5 meters from the top of the box), the lower level (0.5 meters from the bottom), and the middle level (at the center of the inner wall height) to simultaneously monitor the required concentrations of various gases.

[0022] In this embodiment of the invention, methane and hydrogen sulfide are the monitored gases. Therefore, the gas sensor combination module includes an infrared absorption sensor for measuring methane concentration and an electrochemical sensor for measuring hydrogen sulfide concentration. To ensure that the concentration change characteristics under transient airflow disturbances can be effectively captured, the sampling frequency of all sensors in each level of the gas sensor combination module is set to 10Hz, and the concentration data is collected synchronously. Based on this three-dimensional monitoring hardware layout with circumferential points on the inner wall and vertical layers attached to the wall, multi-dimensional dynamic gas concentration data with clear spatial coordinate labels and timestamps can be continuously obtained through high-frequency real-time sampling without interfering with the operation of the sewage treatment machinery inside the tank.

[0023] Based on the obtained monitoring concentrations, to ensure the timeliness of feedback control for oily wastewater treatment, this embodiment of the invention artificially divides the continuous monitoring time stream into multiple continuous and non-overlapping treatment adjustment cycles. The duration of the treatment adjustment cycle in this embodiment is set to 10 minutes. Subsequent calculations in this embodiment are all performed within the same treatment adjustment cycle, and each treatment adjustment cycle outputs a pollution confidence level for oily wastewater treatment adjustment.

[0024] Step S102: For each type of gas at each monitoring point, determine the unidirectional accumulation degree of the gas mass at each sampling time based on the temporal changes of the monitoring concentration under different vertical gradient levels; determine the stable time of the gas mass based on the temporal stability trend of the unidirectional accumulation degree of the gas mass.

[0025] In a confined wastewater treatment tank environment, the leakage of hazardous gases typically manifests as a continuous process of gradual accumulation and diffusion at a specific height over time. Relying solely on the absolute concentration value at a single moment can easily lead to misinterpreting brief temperature fluctuations or transient airflow disturbances caused by equipment operation as genuine leakage events. Therefore, this invention further determines the unidirectional accumulation degree of the gas cloud at each sampling moment for each monitored gas at each monitoring point, based on the temporal changes in the monitored concentration at different vertical gradient levels. The core of this process lies in accurately capturing the continuous and unidirectional concentration accumulation characteristics of pollutants in vertical space. By quantifying and extracting the concentration trends at various levels over a continuous time series, it effectively filters out and removes disordered, bidirectional oscillating false-positive fluctuation data caused by environmental physical interference. This ensures that the system extracts only the gradual accumulation characteristics that conform to the true leakage and diffusion patterns, thus laying a data foundation for subsequently locking the stable moment of the leaking gas cloud and accurately assessing the pollution confidence level.

[0026] Considering that in the initial stage of hazardous gas leakage and diffusion, due to mixing with the existing air and interference from local thermal convection, the concentration distribution is often in a highly active and turbulent unsteady state. If data is extracted too early for risk assessment during this stage, it is easily misled by transient and drastic fluctuations. Therefore, this embodiment of the invention determines the stable moment of the gas mass based on the temporal stability trend of the unidirectional accumulation degree. By continuously tracking the evolution and convergence characteristics of the accumulation degree over time, the critical inflection point where the leaked gas mass transitions from the initial rapid diffusion phase to a relatively dynamic equilibrium state can be accurately identified. This process not only provides a physically representative time anchor for capturing the true three-dimensional spatial distribution characteristics of the pollutant gas but also effectively avoids data distortion caused by improper timing of risk assessment, thereby ensuring the accuracy of subsequent determinations of the confidence level of the leak pollution.

[0027] Step S103: Determine the pollution confidence level based on the unidirectional accumulation degree of the air mass, the vertical gradient distribution of the monitoring concentration of each type of gas at each monitoring point at the stable moment of the air mass, and the overall fluctuation of the monitoring concentration before the stable moment of the air mass.

[0028] After capturing the characteristic point at which the gas mass evolution reaches relative equilibrium, relying solely on a single isolated feature to determine the leakage risk is often insufficient to address the complex mixed gaseous environment inside the wastewater treatment tank, easily leading to false positives. Therefore, this invention comprehensively considers the spatiotemporal evolution, determining the pollution confidence level based on the unidirectional accumulation degree of the gas mass, the vertical gradient distribution of the monitoring concentration of each monitored gas at each monitoring point at the gas mass stabilization point, and the overall fluctuation of the monitoring concentration before the gas mass stabilization point.

[0029] Specifically, the three judgment dimensions mentioned above have an inherent physical correlation and complementarity: the unidirectional accumulation degree of the gas mass reflects the continuous unidirectional driving characteristic of the leak event on the time axis. The greater the unidirectional accumulation degree of the gas mass, the more it means that the gas concentration is not a short-term bidirectional oscillation caused by wind field disturbance, but a continuous accumulation of matter, thus directly and positively improving the certainty of a real leak. The vertical gradient hierarchical distribution pattern fits the natural spatial physical stratification properties of different component gases (such as methane with lower density and hydrogen sulfide with higher density) under the action of a confined gravity field. The closer the stratification structure of the monitored concentration data is to its inherent gravity distribution pattern, the more it indicates that the accumulation phenomenon is more consistent with the real fluid dynamic characteristics rather than a false positive response of the sensor caused by local temperature drift. This provides a solid space physical support for high-confidence risk judgment. The overall fluctuation of the monitored concentration before the gas mass stabilizes directly measures the evolution intensity and absolute concentration span of this accumulation event. The more significant the fluctuation span, the more intense and clear the evolution trajectory of the gas from background concentration to dangerous state, further improving the reliability of confirming a serious leak event. By deeply integrating and cross-validating the cumulative evolution over time, spatial physical distribution, and macroscopic intensity span, it is possible to effectively penetrate the fog of sporadic data in the complex industrial disturbances, accurately strip away the pseudo-anomalies caused by various environmental disturbances, and thus calculate a pollution confidence level that highly reflects the true dangerous state. This provides a highly robust quantitative decision-making benchmark for the final safety early warning and process adaptive adjustment.

[0030] Step S104: Treat oily wastewater based on pollution confidence level.

[0031] This invention addresses oily wastewater treatment based on pollution confidence levels. By directly incorporating highly reliable risk quantification indicators obtained from prior in-depth investigations into the control logic, it enables adaptive, tiered feedback adjustments to key wastewater treatment parameters (such as targeted reduction of wastewater influent flow to curb the continuous release of hazardous gases) based on the actual severity of gas leaks. This closed-loop treatment mechanism not only effectively avoids one-size-fits-all blind operations caused by environmental interference but also maximizes the continuity and treatment efficiency of oil removal, slag discharge, and filtration processes for oily wastewater while strictly adhering to the safety baseline of closed equipment operation, achieving a balance between risk prevention and industrial production efficiency.

[0032] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the unidirectional accumulation degree of the air mass includes: Each sampling time is sequentially used as the target time; all sampling times within a preset historical time window of the target time are used as the corresponding accumulation analysis times. To ensure the real-time nature of data analysis and avoid misleading current risk assessments with outdated historical data spanning multiple periods, the preset historical time window in this embodiment is set to 30 seconds.

[0033] To address the issue of amplified statistical bias due to extremely small data volumes at the beginning of the adjustment period, this invention introduces a minimum sample protection and adaptive window mechanism: If the time elapsed between the target time and the start time of the current adjustment period is less than the preset minimum effective analysis time (set to 5 seconds in this embodiment), the system determines that the number of collected concentration samples is insufficient to support reliable trend determination. To prevent false positive fluctuations caused by high-frequency environmental noise, the unidirectional accumulation degree corresponding to the target time is forcibly set to zero. If the time elapsed between the target time and the start time of the current adjustment period is greater than or equal to the preset minimum effective analysis time but less than 30 seconds, all sampling times between the start time of the current adjustment period and the target time are used as accumulation analysis times for calculation, and the analysis window adaptively grows over time. When the time elapsed between the target time and the start time of the current adjustment period exceeds 30 seconds, the system reverts to a fixed sliding analysis window of 30 seconds.

[0034] For each monitoring point of each monitored gas: Based on the absolute deviation between the monitored concentrations at adjacent accumulation analysis times in each vertical gradient level, the absolute concentration change coefficient at each accumulation analysis time is determined; based on the central tendency of the absolute concentration change coefficients at all accumulation analysis times, the degree of absolute concentration change is determined; based on the temporal increasing distribution of all monitored concentrations corresponding to each vertical gradient level, the number of concentration increasing times is determined; based on the degree of absolute concentration change and the number of concentration increasing times, the degree of unidirectional accumulation of each monitoring point for each monitored gas in each vertical gradient level is determined.

[0035] In this embodiment of the invention, for each accumulation analysis time, if the corresponding monitored concentration is greater than the monitored concentration of the previous accumulation analysis time, then the accumulation analysis time is taken as the concentration increase time; the number of increase times can be determined by counting the total number of concentration increase times in all accumulation analysis times.

[0036] In one specific implementation of this invention, the process of obtaining the corresponding hierarchical unidirectional accumulation degree for any monitoring point of any monitoring gas is expressed by the following formula: ;in, Vertical gradient level Next target time Hierarchical unidirectional aggregation degree; Vertical gradient level Next target time The number of concentration increase moments within the preset historical time window; Vertical gradient level Next target time The number of sampling moments within the preset historical time window, i.e. the number of accumulation analysis moments; Vertical gradient level Next target time The first in the preset historical time window The monitored concentration at each accumulation analysis time point; Vertical gradient level Next target time The first in the preset historical time window The monitored concentration at each accumulation analysis time point; It is the absolute value symbol; Vertical gradient level Next target time The first in the preset historical time window The absolute concentration change coefficient at each accumulation analysis time point; Vertical gradient level Next target time The degree of change in absolute concentration.

[0037] The normalization function uses a minimum-maximum normalization method. The process of obtaining the minimum and maximum values ​​in minimum-maximum normalization includes: retrieving all unnormalized hierarchical unidirectional clustering degrees generated in each completed processing and adjustment cycle from the system's historical operating data; extracting the historical minimum and maximum values ​​respectively; and using these as the minimum and maximum values ​​for the current minimum-maximum normalization calculation. It should be noted that if the currently calculated unnormalized hierarchical unidirectional clustering degree is less than the historical minimum, the result after normalization mapping is directly set to zero; if it is greater than the historical maximum, the result after normalization mapping is directly set to 1. Furthermore, for the first processing and adjustment cycle after startup, since sufficient historical reference benchmarks have not yet been accumulated, this embodiment of the invention does not perform subsequent pollution confidence calculation and analysis. Instead, it uses all unnormalized hierarchical unidirectional clustering degrees calculated from the data collected within this cycle as reference historical data for other subsequent processing and adjustment cycles. From the second processing and adjustment cycle onwards, the pollution confidence is officially output and feedback adjustment is performed.

[0038] By extracting the absolute concentration change per unit time and combining it with the frequency of positive concentration increases within the time window, random bidirectional fluctuations caused by equipment oscillations or temperature changes can be accurately isolated, while only the continuous unidirectional increase caused by the continuous enrichment of gas masses during actual leaks is retained and amplified. Simultaneously, dynamic extreme value normalization based on real historical operating data is introduced to eliminate the magnitude differences caused by the dimensions and physicochemical properties of different monitored gas types, thus improving the robustness of the analysis process.

[0039] This invention determines the unidirectional accumulation degree of the gas cloud at the target time based on the maximum value of the unidirectional accumulation degree of each monitoring point for each type of gas across all vertical gradient levels. Since the diffusion of the leaked gas cloud within the chamber is highly susceptible to the gas's own density (e.g., methane tends to move to higher levels, hydrogen sulfide to lower levels), by extracting the maximum accumulation response in real time across multiple vertical levels, the model can be ensured to remain anchored at the spatial level where the leakage physical characteristics are most significant and most sensitive to concentration evolution. This maximizes the prevention of potential missed detections caused by monitoring at a single altitude and improves the robustness of monitoring complex gaseous environments.

[0040] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the stable moment of the air mass includes: For each monitoring point of each monitored gas, the degree of difference in gas mass accumulation is determined based on the deviation between the unidirectional accumulation degree of the gas mass at each sampling time and the unidirectional accumulation degree of the gas mass at the previous sampling time. In this embodiment of the invention, the degree of difference in gas mass accumulation is determined by subtracting the unidirectional accumulation degree of the gas mass at the previous sampling time from the unidirectional accumulation degree of the gas mass at each sampling time.

[0041] For each monitoring point of each gas, the greater the difference in gas cloud accumulation, the more rapidly the gas accumulation rate increases per unit time. This indicates that the gas diffusion within the chamber is in a high-speed and extremely turbulent stage, meaning it has not yet reached a physical steady state that accurately reflects the pollution diffusion boundary. Therefore, the sampling moment when the first corresponding gas cloud accumulation difference in the time series is less than the preset stability threshold is taken as the gas cloud stabilization moment. This signifies that the unidirectional diffusion and accumulation rate of the leaking gas cloud within the confined space has initially converged and reached dynamic equilibrium. At this point, the gas distribution characteristics within the space are relatively clear and less affected by transient wind fields, improving the accuracy of subsequent calculations and analyses. It should be noted that if all monitored concentrations at each monitoring point for each gas are 0, it indicates that no leak has occurred, and the analysis should be stopped directly to make subsequent analysis meaningful.

[0042] Since the degree of gas mass accumulation difference depends on the comparison of adjacent sampling times, the calculation of the degree of gas mass accumulation difference is not performed at the first sampling time of each treatment adjustment cycle. Instead, the calculation process starts from the second sampling time of the cycle. If, during the current treatment adjustment cycle, no sampling time occurs where the degree of gas mass accumulation difference is less than the preset stability threshold, it indicates that the gas phase environment of the chamber is in a state of continuous extreme turbulence or has been subjected to severe and continuous transient interference, making it impossible to lock in a reliable physical assessment opportunity. In this case, the embodiment of the present invention will directly skip the pollution confidence analysis and subsequent calculation logic for the treatment adjustment cycle, directly restart the monitoring and assessment in the next cycle, and maintain the treatment state of the previous effective cycle, thereby effectively avoiding erroneous control actions caused by data distortion.

[0043] In one specific implementation of this invention, the preset stability threshold is preferably selected from a range of values. The preset reference threshold has a limited range of values. The specific selection of the threshold needs to be dynamically adjusted according to the actual airflow disturbance conditions inside the oily wastewater treatment tank. In this embodiment of the invention, the preset stability threshold is preferably set to 0.02, and the preset reference threshold is preferably set to 0.1. Specifically: when the oily wastewater treatment device is in a high-load operation stage (such as a large flotation bubble injection volume and frequent operation of the surface scraper), the background fluctuation of the gas phase inside the tank is large and the mechanical disturbance is strong, making it extremely difficult for the gas mass to reach a perfect static state. At this time, the preset stability threshold and the preset reference threshold should be selected with a larger value within this range to appropriately relax the stability judgment conditions and avoid the system failing to lock the stable moment due to overly stringent standards, thus frequently skipping the analysis. Conversely, when the wastewater treatment device is in a gentle settling stage or when the tank space is relatively closed and static, the gas has excellent natural diffusion and stratification conditions. At this time, the preset stability threshold and the preset reference threshold should be selected with a smaller value within this range to filter out weak noise with more stringent convergence standards, thereby capturing the steady-state data with the purest physical distribution characteristics and the highest fidelity.

[0044] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the pollution confidence level includes: Based on the degree of convergence of the ideal distribution of the monitoring concentration of each monitored gas at different vertical gradient levels, the corresponding distribution regularity is determined. Specifically: First, an ideal vertical spatial distribution model under a confined gravitational field is established based on the physical density characteristics of each monitored gas. For example, for methane and hydrogen sulfide analyzed in this embodiment, the ideal distribution characteristics of methane gas, whose density is much less than that of air, are that the monitoring concentration in the upper layers is greater than that in the middle layers, and the concentration in the middle layers is greater than that in the lower layers. The ideal distribution characteristics of hydrogen sulfide gas, whose density is greater than that of air, are completely opposite. Subsequently, the actual monitoring concentrations of each monitored gas at each vertical gradient level at the moment when the air mass is stable are compared one by one. For small-scale distribution relationships, if the actual distribution order completely matches the ideal vertical spatial distribution model (i.e., the distribution of monitored concentrations conforms to the corresponding ideal distribution characteristics), then the corresponding distribution regularity is set as the preset first distribution characteristic value; if the actual distribution order only partially matches the ideal distribution model (e.g., methane concentrations are higher in the upper layers than in the middle and lower layers, but lower in the middle layers than in the lower layers), then the corresponding distribution regularity is set as the preset second distribution characteristic value; if the actual distribution order completely contradicts the ideal distribution model, then the corresponding distribution regularity is set as the preset third distribution characteristic value; wherein, the preset first distribution characteristic value, the preset second distribution characteristic value, and the preset third distribution characteristic value decrease sequentially.

[0045] In this embodiment of the invention, the specific values ​​of the preset first distribution feature value, the preset second distribution feature value, and the preset third distribution feature value can be flexibly adjusted according to the tolerance of spatial hierarchical misalignment in the actual system. To ensure consistency in magnitude with other normalized dimensional indicators, this embodiment preferably sets the preset first distribution feature value to 1, the preset second distribution feature value to 0.5, and the preset third distribution feature value to 0. This setting aligns with… The dimensionless interval ensures that each dimension has equal mathematical weight when averaging and fusing; at the same time, it intuitively maps three distinct physical states: clear features, interference, and high probability of false alarms, realizing a smooth conversion from qualitative laws to quantitative weights.

[0046] For each monitored gas at each monitoring point, the vertical gradient level with the highest monitored concentration at the moment the gas mass stabilizes is used as the historical analysis level. The degree of concentration characteristic fluctuation is determined based on the range of all monitored concentrations corresponding to all sampling times before the gas mass stabilization at the historical analysis level. In this embodiment, the range of all monitored concentrations corresponding to all sampling times before the gas mass stabilization within the current processing adjustment cycle at the historical analysis level is normalized to determine the degree of concentration characteristic fluctuation. The normalization method uses maximum value normalization, where the maximum value is fixed by retrieving the upper limit of the sensor range corresponding to the monitored gas. Using the physical absolute upper limit as a benchmark allows for an objective and consistent measurement of the true burst intensity of this gas accumulation event across the macroscopic concentration range, preventing localized minor fluctuations from being abnormally amplified during normalization.

[0047] Furthermore, based on the unidirectional accumulation degree of the air mass, the degree of fluctuation of concentration characteristics, and the distribution regularity at the stable moment of the air mass, the pollution confidence level of each monitoring gas at each monitoring point was determined; the unidirectional accumulation degree of the air mass, the degree of fluctuation of concentration characteristics, and the distribution regularity were all positively correlated with the pollution confidence level.

[0048] This invention determines the pollution confidence level of each monitored gas at each monitoring point based on the average values ​​of the unidirectional accumulation degree, concentration characteristic fluctuation degree, and distribution regularity of the gas mass at the current stable moment. Compared with the product method for fusion, the average method can effectively avoid the extreme risk of false negatives caused by a parameter value of 0, and improve the fault tolerance and robustness of the assessment system in harsh industrial environments. Specifically, due to the complex operating conditions inside the wastewater treatment tank, the sensor may occasionally cause local distortion or even a brief score of zero in a certain assessment dimension (such as vertical distribution regularity) due to water mist condensation or short-term strong eddies. If the product fusion method is used, the zero value of this single dimension will directly lead to the final pollution confidence level being completely zero, thereby completely erasing the real high-risk signals emitted by other dimensions (such as the accumulation degree and fluctuation range that have shown drastic deterioration). The average method can smooth out the feature distortion caused by the above-mentioned local interference, and while allowing for physical observation flaws in a single dimension, it can still objectively and comprehensively reflect the overall risk level.

[0049] In another specific implementation of this invention, after determining the contamination confidence level, the method further includes: After the gas mass stabilizes, a square wave pulsed airflow is applied. The pollution leakage weight is determined based on the pulse pattern of the monitored concentration after application. Specifically, two pulse phase segments of the square wave pulsed airflow are obtained for each pulse cycle. For each monitored gas at each monitoring point, the corresponding concentration characteristic value is determined based on the average monitored concentration at the historical analysis level for all sampling times within each pulse phase segment. It should be noted that the specific application method of the square wave pulsed airflow is as follows: by activating the miniature explosion-proof fan channels installed on both sides of the circumferential monitoring points on the inner wall, intermittent low-speed, stable airflow is blown along the inner wall of the housing towards the surface of the corresponding vertical gradient sensor module. In this embodiment, the pulse cycle is preferably set to 4 seconds with a duty cycle of 50%, i.e., alternating between 2 seconds of blowing and 2 seconds of stopping, and continuing for several complete pulse cycles (e.g., 5 cycles, totaling 20 seconds). During this duration, each cycle is strictly divided into two pulse phase segments: blowing and stopping.

[0050] It should be noted that, since the application of the square wave pulsed airflow and data acquisition require a continuous 20 seconds, to prevent the verification process from crossing the boundary of the current processing adjustment cycle and interrupting the initial evaluation of the next cycle, this embodiment of the invention has reserved sufficient verification time redundancy at the end of the fixed duration (e.g., 10 minutes) of the processing adjustment cycle. Specifically, if the air mass stabilization moment is triggered less than 20 seconds before the end of the current processing adjustment cycle, the system will forcibly lock the timing boundary of the current cycle, automatically extend the duration of the current processing adjustment cycle until the pulse verification process is completely completed, and accordingly postpone the start time of the next processing adjustment cycle, thereby ensuring the integrity of the physical verification process and the independence of the cycle data.

[0051] The core purpose of introducing this square-wave pulsed airflow secondary verification mechanism is to thoroughly distinguish between genuine material leaks and non-material sensor false anomalies from a physical perspective. Specifically, the previously calculated pollution confidence level mainly relies on the natural diffusion and gravitational stratification of gases. However, high humidity or sudden local temperature changes inside the wastewater treatment tank can sometimes cause zero-point drift in the sensor, resulting in a false high-concentration output resembling gas accumulation. If the current high concentration is due to the accumulation of genuine leaked gas, the local purging airflow will physically dilute or shift it, causing the monitored concentration to decrease significantly during the purging phase and then rise and accumulate again during the stopping phase, thus exhibiting intermittent oscillations highly synchronized with the physical pulse in time. Conversely, if the high concentration is a false positive reading caused by sensor moisture or thermal effects, this non-material noise drift will not undergo instantaneous, regular abrupt changes due to weak local physical airflow; its concentration characteristic value will remain relatively stable or fluctuate irregularly. By quantifying the consistency of this fluctuation response, the accuracy of the corrected pollution confidence level can be improved.

[0052] The concentration characteristic values ​​of all pulse phase segments are sequentially arranged to determine the pulse characteristic value sequence; a preset pulse reference sequence with the same length as the pulse characteristic value sequence is obtained; the corresponding pollution leakage weight is determined based on the absolute value of the Pearson correlation coefficient between the pulse characteristic value sequence and the preset pulse reference sequence; finally, the corrected pollution confidence level is determined based on the product between the pollution leakage weight and the pollution confidence level before correction.

[0053] The preset pulse reference sequence in this embodiment of the invention is constructed based on the applied phase of a square wave pulsed airflow and the ideal gas concentration response state. Specifically, since the local purge airflow physically dilutes the accumulated hazardous gas, causing a decrease in concentration, and the gas re-accumulates when the airflow stops, causing a rebound in concentration, if the initial phase segment of the square wave pulsed airflow is set as the purge phase segment, followed by the stop phase segment, then when constructing the preset pulse reference sequence, since the purge phase segment represents the concentration trough and the stop phase segment represents the concentration peak, a preset pulse reference sequence with alternating values ​​of 0 and 1 is constructed. Conversely, if the initial phase segment of the square wave pulsed airflow is set as the stop phase segment, followed by the purge phase segment, the constructed preset pulse reference sequence is a sequence with alternating values ​​of 1 and 0.

[0054] The Pearson correlation coefficient is used to measure the degree of linear synchronization between two sequences. If a real leak occurs, the oscillation of the concentration characteristic value is highly synchronous with the preset pulse reference sequence, and the absolute value of the Pearson correlation coefficient will approach 1, thus mapping a pollution leak weight close to full, so that the real danger signal is preserved as is. Conversely, if it is a false positive signal caused by environmental interference, its characteristic sequence is not related to the pulse reference sequence, the absolute value of the correlation coefficient approaches 0, and the pollution leak weight is sharply reduced.

[0055] It should be noted that the Pearson correlation coefficient is a well-known technique in the art. Considering that the denominator of the Pearson correlation coefficient calculation contains the variance of the pulse feature value sequence, if the denominator is 0, it means that the values ​​in the pulse feature value sequence are completely consistent. In this case, the Pearson correlation coefficient is directly set to 0 to avoid the situation where it cannot be calculated.

[0056] Preferably, in some possible implementations of the embodiments of the present invention, the process of treating oily wastewater based on pollution confidence includes: The corresponding judgment confidence level is determined based on the maximum pollution confidence level of all monitored gases at all monitoring points. This embodiment of the invention adopts a fusion strategy that extracts the maximum value, primarily considering the high connectivity of the internal space of the integrated treatment device and the physical characteristics of the accumulation and diffusion of hazardous gases. Since a high-confidence leak in any local area indicates a safety threat to the entire confined space, using the maximum value as the global judgment benchmark effectively prevents severe local risk signals from being masked during spatial averaging, thereby ensuring the system has the highest level of response sensitivity to local extreme risks and guaranteeing the reliability of the risk defense logic.

[0057] If the confidence level is less than a preset first threshold, the wastewater treatment adjustment coefficient is set to a preset first reference coefficient; if the confidence level is greater than a preset second threshold, the wastewater treatment adjustment coefficient is set to a preset second reference coefficient; the preset first threshold is less than the preset second threshold; the preset first reference coefficient is greater than the preset second reference coefficient. In a specific implementation of this invention, the preset first threshold is set to 0.3, the preset second threshold is set to 0.7, the preset first reference coefficient is set to 1, and the preset second reference coefficient is set to 0. This parameter setting is to establish a tiered buffer control mechanism between ensuring production continuity and maintaining absolute safety. Specifically: When the confidence level is less than 0.3, it indicates that the concentration fluctuations currently detected are extremely weak or are likely residual background noise interference. At this time, the coefficient is set to 1 (i.e., no reduction in influent, maintaining 100% flux), which can prevent the system from frequently interrupting the treatment process due to oversensitivity. When the confidence level is greater than 0.7, it indicates that after spatiotemporal multidimensional investigation and physical airflow verification, the probability of a real serious leak is extremely high. At this time, the coefficient is directly set to 0, forcibly and completely cutting off the sewage influent, curbing the continued release and accumulation of dangerous gases from the source, and playing a last-ditch protection role.

[0058] If the confidence level is greater than a preset first threshold and less than a preset second threshold, the negative correlation mapping value of the confidence level is used as the corresponding wastewater treatment adjustment coefficient. In this embodiment of the invention, the corresponding wastewater treatment adjustment coefficient is determined by subtracting the confidence level from the real number 1. The higher the confidence level, the higher the actual risk of leakage and accumulation of hazardous gases inside the tank. Therefore, a smaller wastewater treatment adjustment coefficient needs to be output to proportionally reduce the amount of wastewater entering the final treatment tank, thereby suppressing the continued release of hazardous gases along with newly entering wastewater from the source and preventing further deterioration of the safety status.

[0059] Oily wastewater is treated according to a wastewater treatment adjustment coefficient. Specifically, the final treated wastewater influent volume is determined by multiplying the wastewater treatment adjustment coefficient by a preset standard wastewater influent volume; oily wastewater is then treated based on this final treated wastewater influent volume. In this embodiment, the preset standard wastewater influent volume is determined based on the average stable wastewater influent volume under historical data showing that oily wastewater purification meets standards. By applying the wastewater treatment adjustment coefficient, which reflects the gas-phase safety status, to the standard influent volume, which reflects the water purification process status, adaptive control of the oily wastewater treatment process under safety constraints is achieved, ensuring a balance between risk prevention effectiveness and water purification efficiency in the integrated treatment device.

[0060] In summary, an oily wastewater treatment method first assesses the unidirectional accumulation degree of the gas mass based on the temporal changes in concentration, and accurately pinpoints the stable moment of the gas mass by combining its temporal stability trend, thereby truly capturing the evolution law of the leaked gas mass and eliminating local transient disturbances. Furthermore, it integrates the unidirectional accumulation degree of the gas mass, the hierarchical distribution law of the vertical gradient, and the overall fluctuation of the monitored concentration before the stable moment of the gas mass, cross-validating and determining the pollution confidence level from multiple spatiotemporal dimensions, effectively eliminating misjudgments caused by environmental factors. Finally, based on this highly reliable pollution confidence level, it adaptively executes the oily wastewater treatment operation, avoiding blind adjustments or unnecessary process interruptions, thus improving the accuracy of assessing gas leakage risks and providing feedback to adjust the oily wastewater treatment process.

[0061] This invention also provides an oily wastewater treatment system; please refer to [link / reference]. Figure 2 The diagram shows a structural diagram of an oily wastewater treatment system according to an embodiment of the present invention. The system includes: a data acquisition module 201, a first determination module 202, a second determination module 203, and an oily wastewater treatment module 204.

[0062] Data acquisition module 201 is used to acquire the monitoring concentration of each monitored gas in the integrated oily wastewater treatment device at different vertical gradient levels at each monitoring point at each sampling time. The first determining module 202 is used to determine the unidirectional accumulation degree of the gas mass at each sampling time for each type of gas at each monitoring point, based on the temporal changes in the monitoring concentration under different vertical gradient levels; and to determine the stable time of the gas mass based on the temporal stability trend of the unidirectional accumulation degree of the gas mass. The second determining module 203 is used to determine the pollution confidence level based on the unidirectional accumulation degree of the air mass, the vertical gradient hierarchical distribution law of the monitoring concentration of each monitoring gas at each monitoring point at the stable moment of the air mass, and the overall fluctuation of the monitoring concentration before the stable moment of the air mass. Oily wastewater treatment module 204 is used for treating oily wastewater based on pollution confidence level.

[0063] It should be noted that the system provided in the above embodiments is only an example of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed to complete all or part of the functions described above. In addition, the oily wastewater treatment system and the oily wastewater treatment method embodiment provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiment, which will not be repeated here.

[0064] This invention also provides an oily wastewater treatment device; please refer to [link / reference]. Figure 3 The diagram illustrates a structural schematic of an oily wastewater treatment device according to an embodiment of the present invention, including a memory 301, a processor 302, and a computer program 303 stored in the memory 301 and running on the processor 302. When the processor 302 executes the computer program 303, the device can perform any of the oily wastewater treatment methods described above.

[0065] This invention also provides a computer program product that, when run on an oily wastewater treatment device, enables the oily wastewater treatment device to execute any of the aforementioned oily wastewater treatment methods.

[0066] This invention also provides a computer-readable storage medium storing computer program code. When the computer program code is run on an oily wastewater treatment device, the oily wastewater treatment device can perform any of the oily wastewater treatment methods described above.

[0067] In the embodiments provided by the present invention, it should be understood that the oily wastewater treatment device, computer program product and computer-readable storage medium provided are all used to execute the corresponding methods provided above, and therefore the beneficial effects they can achieve can be referred to the beneficial effects of the methods provided above, which will not be repeated here.

[0068] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for treating oily wastewater, characterized in that, The method includes: At each sampling time, the concentration of each monitored gas in the integrated oily wastewater treatment device is obtained at different vertical gradient levels at each monitoring point within the device's casing. For each type of gas monitored at each monitoring point, the unidirectional accumulation degree of the gas mass at each sampling time is determined based on the temporal changes in the monitored concentration at different vertical gradient levels; and the stable time of the gas mass is determined based on the temporal stability trend of the unidirectional accumulation degree. Based on the unidirectional accumulation degree of the air mass, the hierarchical distribution of the vertical gradient of the monitoring concentration of each monitoring gas at each monitoring point at the stable time of the air mass, and the overall fluctuation of the monitoring concentration before the stable time of the air mass, the pollution confidence level is determined. Oily wastewater is treated based on the pollution confidence level.

2. The method for treating oily wastewater according to claim 1, characterized in that, The process of obtaining the unidirectional accumulation degree of the air mass includes: Each sampling time is taken as the target time in sequence; all sampling times within the preset historical time window of the target time are taken as the corresponding accumulation analysis time. For each monitoring point of each monitored gas: Based on the absolute deviation between the monitored concentrations at adjacent accumulation analysis times for each vertical gradient level, the absolute concentration change coefficient at each accumulation analysis time is determined; based on the central tendency of the absolute concentration change coefficients at all accumulation analysis times, the degree of absolute concentration change is determined; based on the temporal increasing distribution of all monitored concentrations corresponding to each vertical gradient level, the number of concentration increasing times is determined. Based on the degree of absolute concentration change and the number of concentration increase moments, the hierarchical unidirectional accumulation degree of each monitoring point for each type of gas under each vertical gradient level is determined; based on the maximum value of the hierarchical unidirectional accumulation degree of each monitoring point for each type of gas under all vertical gradient levels, the gas mass unidirectional accumulation degree at the target time is determined.

3. The method for treating oily wastewater according to claim 1, characterized in that, The process of obtaining the stable moment of the air mass includes: For each monitoring point of each type of gas, the degree of gas mass accumulation difference is determined based on the deviation between the gas mass unidirectional accumulation degree at each sampling time and the gas mass unidirectional accumulation degree at the previous sampling time; the sampling time at which the first corresponding gas mass accumulation difference degree in time sequence is less than the preset stability threshold is taken as the gas mass stability time.

4. The method for treating oily wastewater according to claim 1, characterized in that, The process of obtaining the pollution confidence level includes: Based on the degree of convergence of the ideal distribution of the monitoring concentration of each monitored gas under different vertical gradient levels, the corresponding distribution regularity is determined; For each monitored gas at each monitoring point, the vertical gradient level with the highest monitored concentration at the stable moment of the gas mass is taken as the historical analysis level; the degree of concentration characteristic fluctuation is determined based on the range of all monitored concentrations corresponding to the historical analysis level at all sampling moments before the stable moment of the gas mass. Based on the unidirectional accumulation degree of the air mass at the stable moment, the degree of concentration characteristic fluctuation, and the distribution regularity, the pollution confidence level of each monitored gas at each monitoring point is determined; the unidirectional accumulation degree of the air mass, the degree of concentration characteristic fluctuation, and the distribution regularity are all positively correlated with the pollution confidence level.

5. The method for treating oily wastewater according to claim 4, characterized in that, After determining the pollution confidence level, the process also includes: After the air mass stabilizes, a square wave pulsed airflow is applied, and the pollution leakage weight is determined based on the pulse pattern of the monitored concentration after the application. The pollution confidence level is then corrected based on the pollution leakage weight to determine the corrected pollution confidence level.

6. The method for treating oily wastewater according to claim 5, characterized in that, The process of obtaining the pollution leakage weight includes: Two pulse phase segments of the square wave pulsed airflow are obtained in each pulse cycle; for each monitored gas at each monitoring point, the corresponding concentration characteristic value is determined based on the average monitoring concentration at the historical analysis level at all sampling times in each pulse phase segment. The concentration characteristic values ​​of all pulse phase segments are sequentially arranged to determine the pulse characteristic value sequence; a preset pulse reference sequence with the same length as the pulse characteristic value sequence is obtained; and the corresponding pollution leakage weight is determined based on the absolute value of the Pearson correlation coefficient between the pulse characteristic value sequence and the preset pulse reference sequence.

7. The method for treating oily wastewater according to claim 1, characterized in that, The process of treating oily wastewater based on the pollution confidence level includes: The corresponding decision confidence level is determined based on the maximum pollution confidence level of all monitored gases at all monitoring points; If the determination confidence level is less than or equal to a preset first determination threshold, the wastewater treatment adjustment coefficient is set to a preset first reference coefficient; if the determination confidence level is greater than or equal to a preset second determination threshold, the wastewater treatment adjustment coefficient is set to a preset second reference coefficient; the preset first determination threshold is less than the preset second determination threshold; the preset first reference coefficient is greater than the preset second reference coefficient. If the determination confidence level is greater than a preset first determination threshold and less than a preset second determination threshold, then the negative correlation mapping value of the determination confidence level is used as the corresponding wastewater treatment adjustment coefficient. Oily wastewater is treated according to the aforementioned wastewater treatment adjustment coefficient.

8. The method for treating oily wastewater according to claim 7, characterized in that, The process of treating oily wastewater according to the wastewater treatment adjustment coefficient includes: The wastewater influent volume is weighted by the wastewater treatment adjustment coefficient to determine the final treated wastewater influent volume; oily wastewater is then treated based on the final treated wastewater influent volume.

9. An oily wastewater treatment system, characterized in that, The system includes: The data acquisition module is used to acquire the monitoring concentration of each monitored gas in the integrated oily wastewater treatment device at different vertical gradient levels at each monitoring point at each sampling time. The first determining module is used to determine the unidirectional accumulation degree of the gas mass at each sampling time for each type of gas at each monitoring point, based on the temporal changes in the monitoring concentration under different vertical gradient levels; and to determine the stable time of the gas mass based on the temporal stability trend of the unidirectional accumulation degree of the gas mass. The second determining module is used to determine the pollution confidence level based on the unidirectional accumulation degree of the air mass, the hierarchical distribution law of the vertical gradient of the monitoring concentration of each monitoring gas at each monitoring point at the stable time of the air mass, and the overall fluctuation of the monitoring concentration before the stable time of the air mass. An oily wastewater treatment module is used to treat oily wastewater based on the pollution confidence level.

10. An oily wastewater treatment device, the device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the oily wastewater treatment method as claimed in any one of claims 1 to 8.

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