A sewage treatment system exhaust gas concentration monitoring and processing method

Abstract

The present application belongs to the technical field of sewage waste gas treatment, and discloses a sewage treatment system waste gas concentration monitoring and treatment method. The present application collects wastewater images, analyzes multi-dimensional feature data of each gas bubble, and identifies each waste gas type and concentration, directly realizes rapid identification of waste gas type and dynamic evaluation of concentration based on real-time analysis of multi-dimensional features of gas bubbles, has higher efficiency and smaller error, can support real-time process regulation, is superior to the hysteresis and singleness of traditional secondary treatment, and through waste gas concentration evaluation coefficient sorting, the priority of the waste gas type to be treated is clear, the treatment process can be dynamically adjusted, the monitoring, evaluation and treatment closed loop is realized, the resource precise investment is ensured, the treatment efficiency is improved, the energy consumption and reagent consumption are reduced, and the defects of passive treatment of heavy monitoring and light planning in the prior art are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of sewage and waste gas treatment, and relates to a method for monitoring and treating waste gas concentration in a sewage treatment system. Background Art

[0002] Waste gas generated during sewage treatment primarily includes malodorous gases, toxic and hazardous gases, and volatile organic compounds (VOCs). Pollutant concentrations vary significantly across different process steps. Excessive waste gas concentrations can pose serious risks to human health, environmental safety, facility operations, and social life. Therefore, research on monitoring waste gas concentrations in sewage treatment systems is of great significance.

[0003] There are also technical solutions for sewage and waste gas treatment in the prior art. For example, the Chinese invention patent application with publication number CN108732113B is a system and method for measuring NO in water. The system consists of a water NO collection system and a NO gas detection system. The former includes a ventilation device, a water sample heating device, and a NO collection device, while the latter includes an oxygen supply device, a reaction device, and an exhaust gas collection device. By heating the water sample to release NO gas, which is collected and then reacted with oxygen to form a detectable product, the NO concentration in the water can be measured. This method is simple to operate, low in cost, and highly efficient. It is particularly suitable for monitoring NO in industrial wastewater, waste gas, and environmental water bodies, and provides a practical tool for analyzing nitric oxide concentrations in ecosystems.

[0004] Although the above scheme proposes some solutions for sewage and waste gas treatment, it still has certain limitations. For example: on the one hand, the existing technical solution monitors the waste gas concentration by performing secondary treatment on the water sample. This analysis method is complicated and time-consuming, and is prone to errors due to operational links, resulting in monitoring lags; at the same time, secondary treatment may change the original composition of the waste gas and cannot truly reflect the real-time characteristics of bubbles in the sewage treatment process.

[0005] On the other hand, existing technologies lack treatment planning based on waste gas concentration and can only achieve concentration monitoring but cannot link treatment strategies, resulting in delayed and lack of targeted waste gas treatment, which can easily lead to even distribution of treatment resources or blind addition of chemicals, increasing costs and reducing efficiency. Summary of the Invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a method for monitoring and treating waste gas concentration in a sewage treatment system is proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: A method for monitoring and treating waste gas concentration in a sewage treatment system, comprising: continuously collecting multiple wastewater images of a target wastewater sample using an image acquisition device, dividing the target wastewater sample into several depth layers, and focusing on the wastewater images of each depth layer.

[0008] The bubble position in each wastewater image is located and the depth layer is identified, thereby generating the movement trajectory of each bubble and constructing the position matrix of each bubble in different wastewater images.

[0009] The multidimensional feature data of each bubble, including sphericity, volume, chromaticity and movement speed, are analyzed based on the movement trajectory of each bubble and its position matrix in different wastewater images.

[0010] The multidimensional feature data of each bubble is matched with the pre-constructed exhaust gas type-multidimensional feature correspondence to identify the exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type.

[0011] Based on the exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type, it is determined whether exhaust gas treatment is required. If it is determined to be necessary, the treatment method is planned.

[0012] Compared with the existing technology, the beneficial effects of the present invention are as follows: (1) The present invention collects wastewater images, analyzes the multidimensional feature data of each bubble, and identifies the type and concentration of each waste gas. It directly realizes the rapid identification of waste gas type and dynamic evaluation of concentration based on the real-time analysis of the multidimensional characteristics of bubbles. It is more efficient, has smaller errors, and can support real-time control of the process, which is better than the lag and one-sidedness of traditional secondary treatment.

[0013] (2) The invention clarifies the priority of the types of waste gas to be treated by sorting the waste gas concentration evaluation coefficients, and can dynamically adjust the treatment process to achieve a closed loop of monitoring, evaluation, and treatment, ensuring accurate allocation of resources, improving treatment efficiency while reducing energy consumption and chemical consumption, and solving the problem of passive treatment that focuses on monitoring but neglects planning in existing technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0015] Figure 1 Schematic diagram of the steps of the method of the present invention.

[0016] Figure 2 A flowchart for determining the type of exhaust gas exceeding the standard corresponding to an embodiment provided by the present invention.

[0017] Figure 3 A schematic diagram of associated bubble identification corresponding to an embodiment provided by the present invention.

[0018] Reference numerals: 11—wastewater image, 12—adjacent wastewater image, 20—bubble, 21—bubble one, 22—bubble two, 23—bubble three, 31—monitoring distance one, 32—monitoring distance two, 33—monitoring distance three. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0020] See also Figure 1 As shown, the present invention provides a method for monitoring and treating waste gas concentration in a sewage treatment system, including: continuously collecting multiple wastewater images of a target wastewater sample using an image acquisition device, dividing the target wastewater sample into several depth layers, and focusing on the wastewater images of each depth layer.

[0021] It should be noted that the image acquisition device may be an industrial-grade color image sensor, such as a CCD or CMOS sensor, integrated into an industrial camera.

[0022] Preferably, the specific manner of dividing the target wastewater sample into a plurality of depth layers is as follows: performing static depth layer division on the target wastewater sample based on preset equally spaced distances to obtain a plurality of static depth layers.

[0023] It should be noted that the static depth layering of the target wastewater sample based on preset equally spaced intervals means dividing the entire wastewater sample from the bottom to the surface into multiple parallel layers at predetermined fixed distances perpendicular to the wastewater surface. For example, if the total depth of the wastewater is 1 meter and the preset interval is 20 cm, it can be divided into 5 static depth layers.

[0024] The specific depth can be measured by an ultrasonic ranging sensor or a laser ranging sensor.

[0025] It should be further explained that the continuous wastewater space is discretized into several static layers with clear depth ranges through a standardized and equally spaced approach. This provides a unified quantitative reference dimension for subsequent bubble state analysis and spatial positioning, making bubble characteristics at different depths comparable and facilitating further delineation of functional zones such as generation zones, intermediate zones, and fragmentation zones through dynamic analysis.

[0026] Extract multiple wastewater images of the target wastewater sample, locate the position and volume of each bubble in each wastewater image, and determine whether each bubble is complete. The incomplete bubble is recorded as a broken-stage bubble.

[0027] In a preferred embodiment, the determination of whether each bubble is complete is specifically as follows: using image processing software to extract the outer contour of the bubble, extracting the surface area and convex hull area of ​​the bubble, comparing the difference between the surface area and the convex hull area of ​​the bubble with a preset threshold, if the difference between the surface area and the convex hull area of ​​the bubble is greater than the preset threshold, it is determined to be an incomplete bubble.

[0028] The bubble volume is compared with a preset identifiable bubble volume threshold, and bubbles with a volume smaller than the identifiable bubble volume threshold are recorded as generation stage bubbles.

[0029] It's important to explain that the recognizable bubble volume threshold is the critical volume value used to distinguish between bubbles that can be effectively identified and analyzed and those that are too small to be reliably detected in wastewater treatment system exhaust gas monitoring. This threshold is a preset volume value determined by the resolution of the image processing equipment, the sensitivity of the algorithm, and the characteristics of the wastewater treatment process.

[0030] It should be noted that if the bubble volume is greater than or equal to the recognizable bubble volume threshold, it is a recognizable bubble, and its shape, position, movement trajectory and other characteristics can be accurately captured by the image acquisition device and analysis software for subsequent depth layer division, feature analysis and exhaust gas concentration assessment.

[0031] The number of bubbles in the breaking stage, the number of bubbles in the generation stage and the total number of bubbles in each static depth layer are counted, and then the proportion of the number of bubbles in the breaking stage and the number of bubbles in the generation stage to the total number of bubbles are calculated to obtain the proportion of the number of bubbles in the breaking stage and the proportion of the number of bubbles in the generation stage in each static depth layer.

[0032] The bubble number ratio in the crushing stage and the bubble number ratio in the generation stage are respectively compared with the preset bubble number ratio threshold value, the static depth layer in which the bubble number ratio in the crushing stage is greater than the bubble number ratio threshold value is recorded as the crushing layer, the static depth layer in which the bubble number ratio in the generation stage is greater than the bubble number ratio threshold value is recorded as the generation layer, and other static depth layers are recorded as intermediate layers.

[0033] The static depth layers are sorted from the bottom to the liquid surface, and the static depth layers before the first appearance of the intermediate layer are recorded as the generation zone, the static depth layers after the first appearance of the crushing layer are recorded as the crushing zone, and the other static depth layers are recorded as the intermediate zone, thereby dividing the target wastewater sample into the generation zone, the intermediate zone and the crushing zone.

[0034] It should be noted that if all static layers are generation layers or fragmentation layers, then the generation zone is all generation layers, the fragmentation zone is all fragmentation layers, and the intermediate zone does not exist.

[0035] It should be noted that this module divides wastewater samples into areas with different functional characteristics through the generation, rise, and breakup states of bubbles at different depths.

[0036] It should be noted that the reasons for depth layer division are: 1. By dividing the depth layer, the bubble state can be matched with the time series and spatial position of exhaust gas generation, which facilitates the analysis of the complete life cycle of the exhaust gas. 2. The multi-dimensional characteristics of bubbles such as sphericity, volume, and movement speed may vary at different depth layers. For example, deep bubbles are affected by water pressure and have a smaller volume, while shallow bubbles have a larger volume when they are close to bursting. The depth layer division provides a spatial coordinate reference for subsequent bubble movement trajectory tracking and feature data correction, ensuring the accuracy of the monitoring data. 3. The depth layer division is the spatial basis of the entire monitoring and treatment method. By structurally decomposing the wastewater samples into areas with different functional attributes, it realizes the upgrade from overall monitoring to layered precision analysis, providing key support for subsequent bubble feature extraction, exhaust gas type identification and treatment planning.

[0037] The bubble position in each wastewater image is located and the depth layer is identified, thereby generating the movement trajectory of each bubble and constructing the position matrix of each bubble in different wastewater images.

[0038] It should be noted that this part realizes the tracking of the position of bubbles in continuous wastewater images through cross-frame image correlation analysis. The core purpose is to construct the movement path of bubbles in different depth layers to provide a data basis for subsequent multi-dimensional feature analysis.

[0039] Preferably, the specific analysis method of the movement trajectory of each bubble is as follows: locating the position of each bubble in each adjacent wastewater image, obtaining the monitoring distance between the position of each bubble in each wastewater image and the position of each bubble in each adjacent wastewater image, and then comparing it with a pre-set distance threshold, taking each bubble whose monitoring distance is less than the distance threshold as the suspected adjacent image associated bubble corresponding to the bubble, comparing each bubble corresponding to each suspected adjacent image associated bubble with the monitoring distance of the bubble, and selecting the suspected adjacent image associated bubble with the smallest monitoring distance as the associated bubble of the bubble.

[0040] In a preferred embodiment, please refer to Figure 3As shown, the corresponding monitoring distances of bubble 20 in the wastewater image 11 and bubble 1 21, bubble 22, and bubble 3 23 in the adjacent wastewater image 12 are monitoring distance 1 31, monitoring distance 2 32, and monitoring distance 3 33, respectively. The above three monitoring distances are all less than the distance threshold, and the three bubbles are all recorded as suspected adjacent image associated bubbles of bubble 20, among which monitoring distance 2 32 is the smallest, so bubble 2 22 is the associated bubble of bubble 20.

[0041] It should be noted that this step is the core link of bubble movement trajectory analysis. By matching the bubble positions of adjacent images and filtering the distance threshold, it ensures that the bubbles associated in consecutive frames are the same physical entity, avoiding mismatching caused by bubble overlap or noise.

[0042] It should be noted that by limiting the maximum allowable movement distance, interference from non-identical bubbles is eliminated. For example, if the maximum theoretical movement speed of bubbles in wastewater is 0.1m / s and the image acquisition interval is 0.5s, the threshold can be set to 0.05m, and bubbles exceeding this threshold are considered distinct. In dense bubble generation or fragmentation areas, multiple bubbles may appear within a range of less than the threshold in adjacent frames. In this case, minimum distance matching can minimize the misjudgment rate.

[0043] By performing associated bubble analysis on each bubble in all adjacent wastewater images, associated bubble groups of all adjacent wastewater images are obtained, and then associated bubble sets are constructed through association transfer, which indicate the position changes of different bubbles in different wastewater images.

[0044] The bubble positions of each wastewater image in each associated bubble set are connected front and back to generate the movement trajectory of each bubble.

[0045] It should be noted that, through the transitivity of association, all associated bubble groups are connected in series to form associated bubble sets. For example, if 1 is associated with 2, and 2 is associated with 3, then 1 is associated with 3. Each set corresponds to the position change record of an independent bubble in the full-time image sequence.

[0046] Preferably, the specific method of constructing the position matrix of each bubble in different wastewater images is as follows: based on the movement trajectory of each bubble, the bubble position corresponding to each bubble in each wastewater image is obtained, and then the position matrix of each bubble in different wastewater images is obtained by arranging them according to the wastewater image acquisition time sequence.

[0047] The multidimensional feature data of each bubble, including sphericity, volume, chromaticity and movement speed, are analyzed based on the movement trajectory of each bubble and its position matrix in different wastewater images.

[0048] It should be noted that the reasons for selecting sphericity, volume, chromaticity and movement speed as multidimensional feature data are: 1. Sphericity reflects the regularity of bubble shape. Bubbles are close to spherical in the generation stage and become irregular due to rupture in the breakup stage. It can be used to determine the stage of the bubble and the risk of exhaust gas release.

[0049] 2. The volume is positively correlated with the amount of exhaust gas carried. Combined with the depth correction coefficient to eliminate water pressure interference, the amount of exhaust gas generated at different depths can be accurately evaluated.

[0050] 3. Chromaticity corresponds to the characteristics of exhaust gas components. For example, sulfur-containing bubbles are yellowish, which is the optical basis for identifying the type of exhaust gas.

[0051] 4. The moving speed reflects the bubble trajectory and wastewater flow state. The bubble speed in the generation area is slow and the speed in the breakup area is fast, which can be used to analyze the waste gas transmission efficiency.

[0052] By comprehensively analyzing the dynamic changes of the four, the life cycle of bubbles from generation to burst can be fully portrayed, and then the waste gas type-multidimensional feature correspondence can be combined to realize waste gas component identification and concentration assessment, providing data support for the optimization of sewage treatment process.

[0053] Preferably, the specific analysis method of the multidimensional characteristic data of each bubble is as follows: use image processing software to obtain the sphericity and volume of each bubble in different wastewater images, and obtain the depth layer of each bubble in each wastewater image, and calculate the mean of the sphericity and volume of the same depth layer to obtain the sphericity and volume of each bubble in different depth layers.

[0054] The sphericity of each bubble at different depth layers is averaged to obtain the monitored sphericity of each bubble.

[0055] The reference depth correction coefficient of each depth layer is obtained by calculating the ratio of the distance from the center of each depth layer to the liquid surface and the liquid surface height of the target wastewater sample.

[0056] The volume of each bubble at different depth layers is multiplied by the reference depth correction coefficient and then summed with the volume to obtain the corrected volume of each bubble at different depth layers, and then the average is calculated to obtain the monitoring volume of each bubble.

[0057] It should be noted that according to the ideal gas law, bubbles in deep water experience increased water pressure and decreased volume. The volume captured in the image is the apparent volume after compression, which can lead to errors when directly used for cross-layer comparisons. Using a depth correction factor, volume data from different depth layers is unified to a single, standardized dimension, resolving the issue of incomparable cross-layer data. The monitored volume is used to calculate the exhaust gas concentration evaluation coefficient. This corrected data more closely reflects actual exhaust gas carryover, preventing biased treatment decisions due to water pressure errors.

[0058] The chromaticity analysis software is used to obtain the chromaticity of each bubble in different wastewater images, and then the mean value is calculated to obtain the monitored chromaticity of each bubble.

[0059] Based on the position matrix of each bubble in different wastewater images, the movement distance of each bubble in the adjacent wastewater image is obtained, and based on the acquisition time of each wastewater image, the movement time of each bubble in the adjacent wastewater image is obtained. The ratio of the movement distance and the movement time is calculated to obtain the movement speed of each bubble in the adjacent wastewater image, and then the average calculation is performed to obtain the monitored movement speed of each bubble.

[0060] The multidimensional feature data of each bubble is matched with the pre-constructed exhaust gas type-multidimensional feature correspondence to identify the exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type.

[0061] Preferably, the exhaust gas type-multidimensional feature correspondence is constructed in the following way: by monitoring and identifying the bubble generation, rising and breaking stages of different exhaust gas types, multiple sets of experimental data corresponding to the monitoring sphericity, monitoring volume, monitoring chromaticity and monitoring movement speed of different exhaust gas types are obtained, and then the mean is calculated to obtain the reference sphericity, reference volume, reference chromaticity and reference movement speed of different exhaust gas types.

[0062] It should be noted that this part establishes a mapping relationship between different exhaust gas types and multi-dimensional characteristics of bubbles in a way driven by experimental data. The core purpose is to provide a feature library for exhaust gas type identification.

[0063] An exhaust gas type-multidimensional feature correspondence is constructed based on the reference sphericity, reference volume, reference chromaticity and reference moving speed of the different exhaust gas types.

[0064] It's important to note that the exhaust gas type-multidimensional feature mapping essentially transforms abstract exhaust gas components into measurable and comparable quantitative features through data-driven modeling. The accuracy of this relationship directly determines the reliability of exhaust gas identification, which in turn influences the targeted treatment strategy.

[0065] Preferably, the specific process of matching the multidimensional feature data of each bubble with the pre-constructed exhaust gas type-multidimensional feature correspondence is as follows: the monitored sphericity, monitored volume, monitored chromaticity and monitored moving speed of each bubble are respectively subjected to relative deviation analysis with the reference sphericity, reference volume, reference chromaticity and reference moving speed of each exhaust gas type in the exhaust gas type-multidimensional feature correspondence to obtain the sphericity deviation, volume deviation, chromaticity deviation and moving speed deviation of each bubble and each exhaust gas type.

[0066] The sphericity deviation, volume deviation, chromaticity deviation and movement speed deviation are weightedly fused and calculated according to preset weights to obtain a multi-dimensional characteristic deviation between each bubble and each exhaust gas type.

[0067] It should be noted that the multi-dimensional feature deviation is calculated by fusing the sphericity, volume, chromaticity, and moving speed deviations according to preset weights in order to quantify the overall difference between the bubble characteristics and the exhaust type reference values ​​and to solve the misjudgment problem that may be caused by single-dimensional deviation.

[0068] In a preferred embodiment, the calculation formula of the multi-dimensional feature deviation is: ,in Represents the multidimensional feature deviation, They represent the deviations corresponding to sphericity, volume, chromaticity, and moving speed respectively. They represent the influence weights of sphericity deviation, volume deviation, chromaticity deviation, and moving speed deviation respectively.

[0069] It should be noted that the weights are set based on: 1. Incorporating knowledge from the wastewater treatment field, weights are set based on the importance of each feature to identifying the type of waste gas. For example, the color characteristic of sulfur-containing waste gas is the most recognizable, so it is given a higher weight; while the volume and velocity characteristics of methane waste gas better reflect its physical properties, so the volume and velocity characteristics are relatively higher weighted.

[0070] 2. Calculate the information entropy or contribution rate of each feature through historical experimental data, use machine learning and other methods to automatically analyze the importance of features, achieve objective weight distribution, reduce human experience bias, and improve the model's adaptability to complex working conditions.

[0071] Preferably, the specific method of identifying the exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type is as follows: arrange the multidimensional feature deviations of each bubble and each exhaust gas type in order from small to large, and take the exhaust gas type corresponding to the minimum multidimensional feature deviation as the exhaust gas type to which the bubble belongs.

[0072] It should be noted that the core of selecting the exhaust gas type corresponding to the minimum multidimensional feature deviation as the exhaust gas type to which the bubble belongs lies in the principle of feature similarity: the multidimensional features are directly related to the physical properties of the exhaust gas components. The smaller the deviation, the closer the bubble characteristics are to the typical performance of a certain type of exhaust gas. Minimum means that in the preset feature template, the overall difference between the bubble and a certain type of exhaust gas is the smallest, which is most consistent with the scientific logic that similar substances have similar characteristics. At the same time, weighted fusion of multidimensional data can reduce the interference of a single feature, and the minimum rule ensures that the best match can still be selected in noisy or fluctuating scenarios, achieving fast and reliable exhaust gas type identification, and meeting the accuracy and timeliness requirements of industrial real-time monitoring.

[0073] It should be further explained that the reasons for classifying the exhaust gas type based on the multi-dimensional feature data are: 1. Sphericity reflects the stability and rupture stage of the bubble. Bubbles of different exhaust gas types are affected differently by surface tension and viscosity during their generation and rising processes, resulting in significant differences in morphology.

[0074] 2. Volume is related to gas generation and solubility. The volume is affected by gas solubility and generation rate: gases with low solubility tend to aggregate into larger bubbles, while gases with high solubility have smaller bubbles.

[0075] 3. Chromaticity directly relates optical properties to chemical composition. Gas components or entrained suspended matter will give bubbles a specific color. Chromaticity is the most direct optical identification indicator.

[0076] 4. The movement speed reveals the gas buoyancy and wastewater flow state. The bubble density determined by the gas molecular weight and the wastewater resistance jointly affect the movement speed.

[0077] The monitored volumes of the bubbles corresponding to the same exhaust gas type are summed up to obtain the total exhaust gas volume of each exhaust gas type.

[0078] The exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type is calculated by calculating the ratio of the total exhaust gas volume of each exhaust gas type to the volume of the target wastewater sample.

[0079] It should be noted that directly measuring the absolute volume of exhaust gas cannot reflect the wastewater treatment efficiency or pollution level, while ratio calculation can convert the concentration into a relative indicator, which facilitates horizontal comparison between different working conditions, equipment or processes.

[0080] It should be noted that the present invention collects wastewater images, analyzes the multidimensional feature data of each bubble, and identifies the type and concentration of each waste gas. It directly realizes the rapid identification of waste gas types and dynamic evaluation of concentration based on the real-time analysis of the multidimensional characteristics of bubbles. It has higher efficiency, smaller errors, and can support real-time control of the process, which is better than the lag and one-sidedness of traditional secondary treatment.

[0081] Based on the exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type, it is determined whether exhaust gas treatment is required. If it is determined to be necessary, the treatment method is planned.

[0082] Preferably, see Figure 2 As shown, the specific process of determining whether exhaust gas treatment is required is as follows: the exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type is compared with the preset exhaust gas concentration evaluation coefficient threshold, and the exhaust gas type whose exhaust gas concentration evaluation coefficient is greater than the exhaust gas concentration evaluation coefficient threshold is regarded as an excessive exhaust gas type.

[0083] It should be noted that the threshold value of the exhaust gas concentration evaluation coefficient is set based on: first, referring to the emission limits for various types of exhaust gas pollutants in national and local environmental protection laws and regulations to ensure that the sewage treatment system meets emission standards; second, combining safety parameters, such as the explosion limits and occupational health exposure thresholds of flammable and explosive gases, to prevent the risk of poisoning and explosion; at the same time, considering the characteristics of the sewage treatment process, such as the equipment's tolerance range to corrosive gases and the critical concentration at which microbial activity is affected by exhaust gas; finally, based on statistical analysis of historical monitoring data and process experiments, determine a reasonable threshold value that can both ensure safety and meet economic operation requirements, and balance environmental protection, safety and treatment efficiency.

[0084] If there is any type of waste gas that exceeds the standard, it is determined that waste gas treatment is required, and the type of waste gas that exceeds the standard is used as the type of waste gas to be treated.

[0085] Preferably, the specific method of planning the treatment method is as follows: the exhaust gas concentration evaluation coefficients of each type of exhaust gas to be treated are arranged in order from large to small to obtain a ranking of the exhaust gas types to be treated, and then the exhaust gas is treated in the order of the ranking of the exhaust gas types to be treated.

[0086] It should be noted that the types of waste gas to be treated are sorted from large to small according to the concentration evaluation coefficient and then processed in sequence. The core logic is a differentiated management and control strategy based on risk priority. The higher the concentration evaluation coefficient, the higher the content of this type of waste gas in the unit wastewater, and the more significant the environmental risk or process impact. Sorting treatment ensures that enhanced treatment measures are taken first for high-risk waste gases to avoid the spread of risks; at the same time, it takes into account the rational allocation of treatment resources, gives priority to resolving major contradictions, and then gradually processes low-priority waste gases. This approach of prioritizing the heavy and then the light not only meets the bottom line requirements of environmental protection and safety, but also optimizes the efficiency of the treatment process and ensures the stable operation of the sewage treatment system.

[0087] It should be noted that the invention clarifies the priority of the types of waste gas to be treated by sorting the waste gas concentration evaluation coefficients, can dynamically adjust the treatment process, realize the closed loop of monitoring, evaluation and treatment, ensure the accurate allocation of resources, improve the treatment efficiency while reducing energy consumption and chemical consumption, and solve the defects of passive treatment of existing technologies that focus on monitoring and neglect planning.

[0088] In practice, 20 liters of wastewater from a regulating tank at a sewage treatment plant were selected as the target sample. An industrial camera, set to capture images at a 30-frame-per-second rate, was used to continuously capture wastewater images for 60 seconds. The sample was divided into six depth layers at predetermined intervals of 15 cm: 0-15 cm, 16-30 cm, 31-45 cm, 46-60 cm, 61-75 cm, and 76-90 cm from the tank bottom to the liquid surface.

[0089] Table 1. Statistics of bubble proportion in depth layer and determination area information

[0090]

[0091] By counting the proportion of bubbles in the generation phase and the proportion of bubbles in the breakup phase at different depths, the functional areas of the wastewater samples were divided into the generation zone, the intermediate zone, and the breakup zone. The area with a high proportion of bubbles in the generation phase was identified as the generation zone, such as the 0-15 cm layer, which accounted for 72%, and was the main source of bubbles. The area with a high proportion of bubbles in the breakup phase was identified as the breakup zone, such as the 61-75 cm layer, which accounted for 65%, and was the main source of bubbles. The rest was the intermediate zone, which was the transition zone for bubble rise.

[0092] By counting the bubble proportions in the depth layer and determining the area division, a spatial coordinate framework is provided for subsequent bubble feature analysis, and the behavior patterns of bubbles in different functional areas are clarified, which is the spatial basis of the entire monitoring method.

[0093] Twenty consecutive wastewater image frames were selected at intervals to track the trajectory of a typical bubble. In the first frame, the bubble was located in the 0-15 cm layer, 10 cm from the pool bottom. In the second frame, there were two suspected related bubbles, 2 mm and 3 mm away, respectively. The distance threshold was set to 5 mm. The bubble at 2 mm was the related bubble, located in the 0-15 cm layer, 12 cm from the pool bottom. Continuous tracking continued until the 20th frame, showing the bubble gradually rising from the generation zone to the fragmentation zone, and finally fragmenting in the 76-90 cm layer. A bubble position matrix was constructed based on the acquisition time sequence: [10, 12, 15, 18, 22, 25, 28, 32, 36, 40, 45, 49, 53, 58, 63, 68, 72, 75, 80, 85], in centimeters with the pool bottom as the origin.

[0094] Statistical analysis was performed on the characteristic data of the above bubbles and 200 bubbles in the area, and the results are shown in Table 2 below.

[0095] Table 2. Multidimensional characteristic data of bubbles in different regions

[0096]

[0097] In Table 2 above, the original and corrected mean volumes are both expressed in cubic millimeters, the mean movement speed is expressed in millimeters per second, and the chromaticity is the RGB mean. Sphericity reflects morphological regularity, with the generation zone being nearly spherical and the fragmentation zone being irregular. Volume includes both the original volume and depth-corrected volume, eliminating the influence of water pressure on volume. Chromaticity describes the optical properties of bubbles through RGB values ​​and is correlated with exhaust gas composition. Movement speed reflects the upward trend of bubbles, with the fragmentation zone having the highest speed. The multidimensional feature data in Table 2 above is used to identify exhaust gas types. By analyzing the characteristic differences between different regions, the changes in the bubble's life cycle from generation to fragmentation can be tracked, providing a quantitative basis for exhaust gas type matching.

[0098] Matching the data in Table 2 with the preset exhaust gas type-multidimensional feature correspondence, the following results are obtained.

[0099] Table 3. Exhaust gas type-multidimensional characteristic information table

[0100]

[0101] In Table 3 above, the reference corrected volume unit is cubic millimeter, and the reference velocity unit is millimeter / second. It can be seen from Table 3 that the multi-dimensional characteristic deviation between bubbles and methane in this area is the smallest, and it is determined that the main exhaust gas type is methane.

[0102] The corrected total volume of all methane bubbles is 240 cubic millimeters. The target wastewater sample volume is 20,000 cubic millimeters, resulting in a calculated methane concentration evaluation coefficient of 0.012. The preset methane concentration evaluation coefficient threshold is 0.01, and the current methane concentration evaluation coefficient exceeds the preset threshold, indicating that treatment is required. Based on priority, a combination of negative pressure exhaust gas collection and catalytic combustion treatment can be used for treatment.

[0103] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the scope of protection of the present invention.

Claims

1. A method for monitoring and treating waste gas concentration in a sewage treatment system, characterized in that: include: Continuously collecting multiple wastewater images of a target wastewater sample using an image acquisition device, dividing the target wastewater sample into several depth layers, and focusing on the wastewater images of each depth layer; Locate the bubble position in each wastewater image and identify the depth layer in which it is located, thereby generating the movement trajectory of each bubble and constructing the position matrix of each bubble in different wastewater images; Analyze the multidimensional feature data of each bubble, including sphericity, volume, chromaticity, and movement speed, based on the movement trajectory of each bubble and its position matrix in different wastewater images; Match the multidimensional feature data of each bubble with the pre-established exhaust gas type-multidimensional feature correspondence to identify the exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type; Based on the exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type, it is determined whether exhaust gas treatment is required. If it is determined to be necessary, the treatment method is planned.

2. A method for monitoring and treating waste gas concentration in a sewage treatment system according to claim 1, characterized in that: The specific method of dividing the target wastewater sample into several depth layers is as follows: The target wastewater sample is divided into static depth layers based on a preset equal interval distance to obtain a number of static depth layers; Extracting multiple wastewater images of the target wastewater sample, locating the position and volume of each bubble in each wastewater image, and determining whether each bubble is complete, and recording the incomplete bubble as a broken-stage bubble; Comparing the bubble volume with a preset threshold value of identifiable bubble volume, and recording bubbles with a volume smaller than the threshold value as bubbles in the generation stage; The number of bubbles in the breaking stage, the number of bubbles in the generation stage, and the total number of bubbles in each static depth layer are counted, and then the proportion of the number of bubbles in the breaking stage and the number of bubbles in the generation stage to the total number of bubbles is calculated to obtain the proportion of the number of bubbles in the breaking stage and the proportion of the number of bubbles in the generation stage in each static depth layer; The bubble number ratio in the crushing stage and the bubble number ratio in the generation stage are respectively compared with the preset bubble number ratio threshold, and the static depth layer in which the bubble number ratio in the crushing stage is greater than the bubble number ratio threshold is recorded as the crushing layer, the static depth layer in which the bubble number ratio in the generation stage is greater than the bubble number ratio threshold is recorded as the generation layer, and the other static depth layers are recorded as the intermediate layers; The static depth layers are sorted from the bottom to the liquid surface, and the static depth layers before the first appearance of the intermediate layer are recorded as the generation zone, the static depth layers after the first appearance of the crushing layer are recorded as the crushing zone, and the other static depth layers are recorded as the intermediate zone, thereby dividing the target wastewater sample into the generation zone, the intermediate zone and the crushing zone.

3. The method for monitoring and treating waste gas concentration in a sewage treatment system according to claim 1, wherein: The specific analysis method of the movement trajectory of each bubble is as follows: Locating the position of each bubble in each adjacent wastewater image, obtaining a monitoring distance between the position of each bubble in each wastewater image and the position of each bubble in each adjacent wastewater image, and then comparing the distance with a pre-set distance threshold, taking each bubble whose monitoring distance is less than the distance threshold as a suspected adjacent image associated bubble corresponding to the bubble, comparing the corresponding suspected adjacent image associated bubble of each bubble with the monitoring distance of the bubble, and selecting the suspected adjacent image associated bubble with the smallest monitoring distance as the associated bubble of the bubble; By performing correlation bubble analysis on bubbles in all adjacent wastewater images, a correlation bubble group of all adjacent wastewater images is obtained, and then each correlation bubble set is constructed through correlation transfer, wherein the correlation bubble set indicates the position change of different bubbles in different wastewater images; The bubble positions of each wastewater image in each associated bubble set are connected front and back to generate the movement trajectory of each bubble.

4. A method for monitoring and treating waste gas concentration in a sewage treatment system according to claim 3, characterized in that: The specific method of constructing the position matrix of each bubble in different wastewater images is as follows: Based on the movement trajectory of each bubble, the bubble position corresponding to each bubble in each wastewater image is obtained, and then the position matrix of each bubble in different wastewater images is obtained by arranging them according to the wastewater image acquisition time sequence.

5. The method for monitoring and treating waste gas concentration in a sewage treatment system according to claim 1, wherein: The specific analysis method of the multi-dimensional characteristic data of each bubble is as follows: Image processing software is used to obtain the sphericity and volume of each bubble in different wastewater images, and the depth layer of each bubble in each wastewater image is obtained. The sphericity and volume of the same depth layer are averaged to obtain the sphericity and volume of each bubble at different depth layers. The sphericity of each bubble at different depth layers is averaged to obtain the monitored sphericity of each bubble; The reference depth correction coefficient of each depth layer is calculated by calculating the ratio of the distance from the center of each depth layer to the liquid surface and the liquid surface height of the target wastewater sample; The volume of each bubble at different depth layers is multiplied by the reference depth correction coefficient, and then the product is added to the volume to obtain the corrected volume of each bubble at different depth layers, and then the average is calculated to obtain the monitoring volume of each bubble; The chromaticity of each bubble in different wastewater images is obtained using chromaticity analysis software, and then the mean value is calculated to obtain the monitored chromaticity of each bubble; Based on the position matrix of each bubble in different wastewater images, the movement distance of each bubble in the adjacent wastewater image is obtained, and based on the acquisition time of each wastewater image, the movement time of each bubble in the adjacent wastewater image is obtained. The ratio of the movement distance and the movement time is calculated to obtain the movement speed of each bubble in the adjacent wastewater image, and then the average calculation is performed to obtain the monitored movement speed of each bubble.

6. A method for monitoring and treating waste gas concentration in a sewage treatment system according to claim 5, characterized in that: The method for constructing the exhaust gas type-multi-dimensional feature correspondence relationship is as follows: By monitoring and identifying the bubble generation, rise and breakup stages of different exhaust gas types, multiple sets of experimental data corresponding to the monitored sphericity, monitored volume, monitored chromaticity and monitored movement speed of different exhaust gas types are obtained, and then the mean values ​​are calculated to obtain the reference sphericity, reference volume, reference chromaticity and reference movement speed of different exhaust gas types; An exhaust gas type-multidimensional feature correspondence is constructed based on the reference sphericity, reference volume, reference chromaticity and reference moving speed of the different exhaust gas types.

7. A method for monitoring and treating waste gas concentration in a sewage treatment system according to claim 6, characterized in that: The specific process of matching the multi-dimensional feature data of each bubble with the pre-established exhaust gas type-multi-dimensional feature correspondence is as follows: The monitored sphericity, monitored volume, monitored chromaticity and monitored moving speed of each bubble are analyzed for relative deviation from the reference sphericity, reference volume, reference chromaticity and reference moving speed of each exhaust gas type in the exhaust gas type-multidimensional feature correspondence, and the sphericity deviation, volume deviation, chromaticity deviation and moving speed deviation of each bubble and each exhaust gas type are obtained; The sphericity deviation, volume deviation, chromaticity deviation and movement speed deviation are weightedly fused and calculated according to preset weights to obtain a multi-dimensional characteristic deviation between each bubble and each exhaust gas type.

8. The method for monitoring and treating waste gas concentration in a sewage treatment system according to claim 1, wherein: The specific method of identifying the exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type is as follows: Arrange the multidimensional feature deviations of each bubble and each exhaust gas type in ascending order, and take the exhaust gas type corresponding to the minimum multidimensional feature deviation as the exhaust gas type to which the bubble belongs; The monitored volumes of the bubbles corresponding to the same exhaust gas type are summed up to obtain the total exhaust gas volume of each exhaust gas type; The exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type is calculated by calculating the ratio of the total exhaust gas volume of each exhaust gas type to the volume of the target wastewater sample.

9. The method for monitoring and treating waste gas concentration in a sewage treatment system according to claim 1, wherein: The specific process of determining whether exhaust gas treatment is required is as follows: Compare the exhaust gas concentration evaluation coefficient corresponding to each exhaust gas type with the preset exhaust gas concentration evaluation coefficient threshold, and identify the exhaust gas type with an exhaust gas concentration evaluation coefficient greater than the exhaust gas concentration evaluation coefficient threshold as an excessive exhaust gas type; If there is any type of waste gas that exceeds the standard, it is determined that waste gas treatment is required, and the type of waste gas that exceeds the standard is used as the type of waste gas to be treated.

10. A method for monitoring and treating waste gas concentration in a sewage treatment system according to claim 9, characterized in that: The specific method of processing mode planning is as follows: The exhaust gas concentration evaluation coefficients of each type of exhaust gas to be treated are arranged in order from large to small to obtain a ranking of the types of exhaust gas to be treated, and then the exhaust gas is treated in the order of the ranking of the types of exhaust gas to be treated.

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