CN115082721A - Pressure control method for air-float decontamination of oil-containing sewage - Google Patents
Pressure control method for air-float decontamination of oil-containing sewage Download PDFInfo
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Abstract
The invention relates to the field of pressure control, in particular to a pressure control method for air floatation sewage treatment of oily sewage. The method comprises the following steps: according to the gray value of pixel points in the bubble image corresponding to each pressure supply pressure and the distance between the pixel points, carrying out initial clustering on the pixel points in the image to obtain each first clustering cluster corresponding to each image; dividing each image into a set number of areas; for any region of any image: calculating the clustering distance of any two clusters according to the average gray value of each cluster corresponding to the region and the distance between the pixel centers of any two clusters; performing hierarchical clustering according to the clustering distance to obtain each second clustering cluster; calculating a corresponding air flotation effect evaluation index according to the number of the second clustering clusters in the bubble image corresponding to each pressure supply pressure and the weighted average size of the second clustering clusters; and obtaining the optimal pressure according to the evaluation index of the sewage air flotation effect. The invention improves the sewage treatment efficiency and ensures the benefit of factories.
Description
Technical Field
The invention relates to the field of pressure control, in particular to a pressure control method for air floatation sewage treatment of oily sewage.
Background
While the material life is becoming abundant, environmental pollution has become one of the focus problems of global concern. Among them, the discharge of oily wastewater can seriously affect the environment, and the oily wastewater has adverse effects on human beings, animals, plants and even the whole ecological system, so the treatment and reinjection of oily wastewater become important issues for the environmental protection of oil and gas fields at present. The prior oily sewage treatment process comprises the following steps: sedimentation, air flotation, microorganism treatment, etc., wherein the air flotation is a high-efficiency and rapid separation technology. When the air floatation treatment technology is adopted to treat oily sewage, the supply of pressure is an important factor influencing the air floatation effect, people often set the supply of pressure according to experience, but due to the difference of water quality, the air floatation time is long or short, the supply of pressure is small, the treatment efficiency is reduced, and the supply of pressure is large, so that energy is wasted.
Disclosure of Invention
In order to solve the problems of low treatment efficiency or energy waste caused by unreasonable pressure setting in the oil-containing sewage decontamination process by the existing method, the invention aims to provide a pressure control method for oil-containing sewage air flotation decontamination, which adopts the following technical scheme:
the invention provides a pressure control method for air-float decontamination of oily sewage, which comprises the following steps:
acquiring bubble images of the air flotation tank under different pressure supply pressures; according to the gray value of the pixel points in the bubble image corresponding to each pressure supply pressure and the distance between the pixel points, performing initial clustering on the pixel points in the bubble image corresponding to each pressure supply pressure to obtain each first clustering cluster corresponding to the bubble image corresponding to each pressure supply pressure;
dividing the bubble image corresponding to each pressure supply pressure into a set number of areas; for any area of the bubble image corresponding to any given pressure: calculating the clustering distance between any two clustering clusters according to the average gray value of each clustering cluster corresponding to the region and the distance between the pixel centers of any two clustering clusters; according to the clustering distance, carrying out hierarchical clustering on the region to obtain each second clustering cluster corresponding to the region;
counting the number of second clustering clusters in the bubble image corresponding to each pressure supply pressure; calculating the weighted average size of the second cluster in the bubble image corresponding to each pressure supply pressure; calculating the evaluation index of the air flotation effect of the sewage corresponding to each pressure supply pressure according to the number of the second clustering clusters in the bubble image corresponding to each pressure supply pressure and the weighted average size of the second clustering clusters; and obtaining the optimal pressure supply pressure according to the sewage air flotation effect evaluation indexes corresponding to the pressure supply pressures.
Preferably, the following formula is adopted to calculate the clustering distance between any two clustering clusters:
wherein the content of the first and second substances,
is the clustering distance between any two clusters,
is the average gray value of one of the cluster clusters,
is the average gray value of another cluster of clusters,
is the distance between the pixel centers of the two clusters.
Preferably, the performing hierarchical clustering on the region according to the clustering distance to obtain each second clustering cluster corresponding to the region includes:
calculating the cluster evaluation index of the region by adopting the following formula:
wherein the content of the first and second substances,
is a cluster evaluation index of the region,
is the average size of the region cluster,
the variance of the mean gray value for the region cluster,
the number of clusters clustered for the region;
and performing hierarchical clustering on the region according to the clustering distance between any two clustering clusters in the region, judging whether the clustering evaluation index of the region is greater than a set threshold value, stopping clustering the region if the clustering evaluation index of the region is greater than the set threshold value, and marking the clustering cluster obtained by the last clustering as each second clustering cluster corresponding to the region.
Preferably, for any first cluster: the gray values of the pixels in the cluster are equal.
Preferably, the calculating a weighted average size of the second cluster in the bubble image corresponding to each pressure-applying pressure includes:
for any given pressure corresponding bubble image:
counting the number of pixel points in each second cluster in the bubble image, and marking the second cluster with the number of the pixel points being more than a first threshold value and less than a second threshold value as a target cluster; the first threshold is less than a second threshold;
calculating the sum of the number of pixel points in the target cluster, and counting the total number of the target cluster; and calculating the ratio of the sum of the number of the pixel points in the target cluster to the total number of the target cluster, and recording the ratio as the weighted average size of the second cluster in the bubble image.
Preferably, the calculating the evaluation index of the air flotation effect of the sewage corresponding to each pressure supply pressure according to the number of the second clustering clusters in the bubble image corresponding to each pressure supply pressure and the weighted average size of the second clustering clusters includes:
respectively calculating the difference value between the average gray value of the bubble image of the air floatation tank corresponding to each pressure supply pressure and the average gray value of untreated sewage;
and calculating the sewage air floatation effect evaluation index corresponding to each pressure supply pressure according to the number of the second clustering clusters in the bubble image corresponding to each pressure supply pressure, the weighted average size of the second clustering clusters and the difference value between the average gray value of the bubble image of the air floatation tank and the average gray value of untreated sewage.
Preferably, the calculating of the evaluation index of the air flotation effect of the sewage corresponding to each pressure supply pressure comprises:
for any given pressure corresponding bubble image: and calculating the product of the total number of the second clustering clusters in the bubble image corresponding to the pressure supply pressure, the weighted average size of the second clustering clusters and the difference value between the average gray value of the bubble image of the air floatation tank and the average gray value of untreated sewage, and taking the product as the evaluation index of the air floatation effect of the sewage corresponding to the pressure supply pressure.
Preferably, the obtaining of the optimal pressure supply pressure according to the evaluation index of the air flotation effect of the sewage corresponding to each pressure supply pressure comprises:
constructing a binary group corresponding to each pressure supply pressure according to each pressure supply pressure and the sewage air flotation effect evaluation index; the first element in the binary group is a pressure-supply value, and the second element is a corresponding sewage air flotation effect evaluation index;
screening binary groups of which the evaluation indexes of the air flotation effect of the sewage are smaller than an air flotation effect threshold value;
and taking the minimum pressure supply pressure in the residual binary group as the optimal pressure supply pressure.
The invention has the following beneficial effects: the invention carries out initial clustering according to pixel points in bubble images of an air flotation tank under different pressure-applying pressures to obtain each first clustering cluster corresponding to the bubble image corresponding to each pressure-applying pressure, and then carries out hierarchical clustering on the bubble images under different pressure-applying pressures by adopting a hierarchical clustering method; and if the pressure difference does not meet the preset threshold value, continuing clustering until a termination condition is met to obtain each second clustering cluster corresponding to each pressure supply pressure in the bubble image. Calculating the evaluation indexes of the air flotation effect of the sewage corresponding to different pressure supply pressures according to the number of the second clustering clusters in the bubble image and the weighted average size of the second clustering clusters; and obtaining the optimal pressure supply pressure according to the sewage air flotation effect evaluation indexes corresponding to the pressure supply pressures. When the oily sewage is treated subsequently, the oily sewage is directly subjected to decontamination treatment according to the optimal pressure supply pressure, so that the sewage treatment efficiency is improved, and the benefit of a factory is ensured.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a pressure control method for air-float decontamination of oily wastewater according to an embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention for achieving the predetermined objects, the following detailed description of the method for controlling pressure of air-float decontamination of oily wastewater according to the present invention will be made with reference to the accompanying drawings and preferred embodiments.
Unless defined otherwise, 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 belongs.
The following describes a specific scheme of the pressure control method for air-float decontamination of oily sewage provided by the invention in detail by combining with the accompanying drawing.
Embodiment of pressure control method for air-float decontamination of oily sewage
The existing method has the problems of low treatment efficiency or energy waste caused by unreasonable pressure setting in the oil-containing sewage decontamination process. In order to solve the above problems, this embodiment proposes a pressure control method for air-float decontamination of oil-containing wastewater, and as shown in fig. 1, the pressure control method for air-float decontamination of oil-containing wastewater of this embodiment comprises the following steps:
step S1, acquiring bubble images of the air flotation tank under different pressure supply pressures; and performing initial clustering on the pixel points in the bubble images corresponding to the pressure supply pressures according to the gray values of the pixel points in the bubble images corresponding to the pressure supply pressures and the distances between the pixel points to obtain first cluster points corresponding to the bubble images corresponding to the pressure supply pressures.
The oily sewage contains a large amount of oil, suspended matters, heavy metals and other substances, and is discharged or reinjected randomly without being treated, so that the oily sewage has great harm to soil, aquatic organisms, human health and crop growth. The air float method adopted in the embodiment degreases. The principle of oil removal by air flotation is to introduce gas into oily wastewater, so that emulsified oil particles in the wastewater are adhered to generated fine bubbles and float to the water surface along with the bubbles to form scum, and then oil stains are removed. Under the same pressure supply pressure, the air floatation time of different water qualities is different, and when the air floatation method is adopted for decontamination, the low pressurization may cause the low decontamination efficiency; too much pressurization may result in waste of energy and reduced plant efficiency.
The method provided by the embodiment is used for treating oily sewage samples of one water quality as follows, and oily sewage of other water qualities can be treated by the method provided by the embodiment. In the embodiment, 20 relatively optimal pressure supply pressures are selected to respectively treat the sample sewage to obtain 20 images of the air flotation tank, the 20 images are respectively treated and analyzed to finally obtain the optimal pressure supply pressure of the type of sewage, and the optimal pressure supply pressure can be directly applied to the subsequent sewage containing oil when the sewage containing the type of sewage is subjected to decontamination treatment, so that the working efficiency is improved, and the benefit of a factory is ensured.
Specifically, a camera is used for collecting images of 20 air flotation tanks, a series of image preprocessing such as image graying, image filtering denoising and image enhancement is carried out on the collected images, and the accuracy of a subsequent detection result is improved by improving the image quality. The specific pretreatment process is well known and will not be described in detail herein. And then, acquiring a gray histogram of the image of the 20 preprocessed air flotation tanks, and dividing the image by using an Otsu threshold method according to the gray histogram to obtain bubble images of the 20 air flotation tanks.
Then, taking one of the bubble images corresponding to the pressure-feeding pressures as an example for analysis, and regarding the bubble image corresponding to the pressure-feeding pressure:
and (3) dividing all the adjacent pixel points into one class with consistent gray values to obtain basic hierarchical clustering clusters, namely growing the image by region growth and taking the gray level of each layer of pixels as a seed under the condition that the seeds are equal to obtain each first clustering cluster corresponding to the image. The region growing method is prior art and will not be described herein.
Step S2, dividing the bubble image corresponding to each supply pressure into a set number of areas; for any area of the bubble image corresponding to any given pressure: calculating the clustering distance between any two clustering clusters according to the average gray value of each clustering cluster corresponding to the region and the distance between the pixel centers of any two clustering clusters; and according to the clustering distance, performing hierarchical clustering on the region to obtain each second clustering cluster corresponding to the region.
In the embodiment, the bubbles in the bubble image are clustered by using a hierarchical clustering method, so that the subsequent calculation is facilitated. In view of the situation, the present embodiment provides a hierarchical clustering method with adaptive termination conditions. Judging the image clustering effect according to the clustering result, judging whether the clustering result meets a clustering termination condition, and if so, stopping clustering; and if not, continuing clustering until the termination condition is met.
In order to enable the efficiency of subsequent hierarchical clustering to be faster, the bubble image is divided into m regions with equal areas, and each first clustering cluster corresponding to each region is obtained. The embodiment divides the bubble image into 3 × 3 regions, i.e., 9 regions, and in a specific application, the bubble image is divided according to actual situations.
In this embodiment, each first cluster corresponding to each region is used as an initial layer of hierarchical clustering to perform hierarchical clustering, specifically, for any region of a bubble image corresponding to any given pressure: and performing hierarchical clustering on the region until the region reaches the corresponding clustering termination condition, and stopping clustering. In this embodiment, the clustering distance between any two clustering clusters is calculated based on the average gray value of the pixel points in each clustering cluster and the distance between the pixel centers of any two clustering clusters, and hierarchical clustering is performed based on the clustering distance between any two clustering clusters. The clustering distance between any two clustering clusters in the region is as follows:
wherein the content of the first and second substances,
for the clustering distance between the two clusters,
is the average gray value of one of the cluster clusters,
is the average gray value of another cluster of clusters,
as the distance between the pixel centers of the two clusters,
which is the abscissa of the center of the pixel of one of the clusters,
is the ordinate of the pixel center of the cluster;
is the abscissa of the center of the pixel of another cluster,
is the ordinate of the pixel center of the cluster.
In this embodiment, based on the average size of the cluster in the region, the number of the cluster, and the average gray value of the cluster, the clustering termination condition of the region is obtained, that is, when the clustering result satisfies the clustering termination condition, it is determined that hierarchical clustering is completed. Specifically, after each clustering is completed, the average size of the regional clustering cluster is calculated; counting the total number of the regional clustering clusters; simultaneously calculating the average gray value of each cluster in the region, and calculating the variance of the average gray value of each cluster in the region according to the average gray value of each cluster in the region; then, calculating the cluster evaluation index of the secondary cluster of the area according to the average size of the cluster of the area, the total number of the cluster and the variance of the average gray value of the cluster, namely:
wherein the content of the first and second substances,
is the cluster evaluation index of the area,
is the average size of the region cluster,
the variance of the mean gray value for the region cluster,
cluster the number of clusters for the region.
And after each clustering is finished, calculating the current clustering evaluation index. When the clustering reaches a certain degree, the number of clustering clusters obtained by clustering is small, the variance of the clustering clusters is large, and the average size of the clustering clusters is large. In this embodiment, a cluster evaluation index threshold is set, whether the cluster evaluation index of the region is greater than the set threshold is judged, if so, clustering of the region is terminated, and a cluster obtained by clustering the region for the last time is marked as a second cluster corresponding to the region.
Based on the above method, a plurality of second cluster clusters corresponding to any one region in each bubble image can be obtained.
Step S3, counting the number of second cluster in the bubble image corresponding to each pressure supply pressure; calculating the weighted average size of the second cluster in the bubble image corresponding to each pressure supply pressure; calculating the evaluation index of the air flotation effect of the sewage corresponding to each pressure supply pressure according to the number of the second clustering clusters in the bubble image corresponding to each pressure supply pressure and the weighted average size of the second clustering clusters; and obtaining the optimal pressure supply pressure according to the sewage air flotation effect evaluation indexes corresponding to the pressure supply pressures.
In a certain period of time, the larger the amount of bubbles is, the more suspended particles in water can be taken away in the floating process, namely the better the sewage treatment effect is; the change of the gray level value of the sewage before and after treatment can reflect the sewage treatment effect of the air floatation method to a certain extent, and the larger the gray level difference obtained before and after the sewage treatment is, the better the decontamination effect under the pressure is. In the same time, the more the number of the floating bubbles is, the larger the bubbles are, and the larger the change of the gray value before and after the sewage treatment is, the better the sewage treatment effect is.
For any given pressure corresponding bubble image: the embodiment first counts the total number of the second cluster in the image
Total amount of
The sum of the number of second cluster clusters in all regions of the image. Then, the number of pixel points in each second cluster in the bubble image is counted, and a first threshold of the number of the pixel points is set in the embodiment
And a second threshold of the number of pixel points
Wherein, in the step (A),
is greater than the number of pixel points in the minimum second cluster,
less than the number of pixels in the largest second cluster,
much less than
(ii) a In this embodiment, the number of the pixel points is greater than
And is less than
The second cluster is recorded as a target cluster, and the ratio of the sum of the number of pixel points in the target cluster to the total number of the target cluster is calculated
The embodiment will use the ratio
Recording as the weighted average size of the second cluster in the bubble image; the existence of the pole data can weaken the representing effect of the average number on the data, the influence of the pole data on the average value is removed, namely, the influence of a larger cluster and a smaller cluster on the average size of a second cluster is eliminated, and the first threshold value of the number of pixels and the second threshold value of the number of pixels are set according to the actual situation. Then calculating the difference value between the average gray value in the image and the average gray value of the untreated sewage
(ii) a Further calculating the evaluation index of the air floatation effect of the sewage corresponding to the pressure supply pressureNamely:
wherein the content of the first and second substances,
and the evaluation index of the air flotation effect of the sewage corresponding to the pressure supply pressure is obtained.
In this embodiment, the sewage air flotation effect evaluation indexes corresponding to the 20 bubble images are obtained according to the above method, and a binary set is constructed according to the pressure supply pressure and the sewage air flotation effect evaluation indexes, wherein the form is
Wherein, in the step (A),
in order to provide the pressure, the pressure-applying member,
is an index for evaluating the air floatation effect of the sewage. When sewage is discharged, the sewage has a certain discharge standard, in the embodiment, a sewage air flotation effect evaluation index threshold value is set, all binary groups with the sewage air flotation effect evaluation index smaller than the sewage air flotation effect evaluation index threshold value are screened out, and the minimum pressure supply pressure is selected from the remaining binary groups as the optimal pressure supply pressure. When the oily sewage with the water quality is subsequently decontaminated, the optimal pressure is directly given to decontaminate the oily sewage, so that the energy waste is prevented, and the decontamination efficiency is ensured.
In this embodiment, initial clustering is performed according to pixel points in bubble images of an air flotation tank under different pressure supply pressures to obtain first clustering clusters corresponding to the bubble images corresponding to the pressure supply pressures, and then hierarchical clustering is performed on the bubble images under the different pressure supply pressures by adopting a hierarchical clustering method, in this embodiment, a hierarchical clustering method of a self-adaptive termination condition is provided, whether a clustering result meets a clustering termination condition is judged, and if so, clustering is stopped; and if the pressure difference does not meet the preset threshold value, continuing clustering until a termination condition is met to obtain each second clustering cluster corresponding to each pressure supply pressure in the bubble image. Calculating the evaluation indexes of the air flotation effect of the sewage corresponding to different pressure supply pressures according to the number of the second clustering clusters in the bubble image and the weighted average size of the second clustering clusters; and obtaining the optimal pressure supply pressure according to the sewage air flotation effect evaluation indexes corresponding to the pressure supply pressures. When the oily sewage is treated subsequently, the oily sewage is directly subjected to decontamination treatment according to the optimal pressure, so that the sewage treatment efficiency is improved, and the benefit of a factory is ensured.
It should be noted that: the above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. A pressure control method for air-float decontamination of oily sewage is characterized by comprising the following steps:
acquiring bubble images of the air flotation tank under different pressure supply pressures; according to the gray value of the pixel points in the bubble image corresponding to each pressure supply pressure and the distance between the pixel points, performing initial clustering on the pixel points in the bubble image corresponding to each pressure supply pressure to obtain each first cluster corresponding to the bubble image corresponding to each pressure supply pressure;
dividing the bubble image corresponding to each pressure supply pressure into a set number of areas; for any area of the bubble image corresponding to any given pressure: calculating the clustering distance between any two clustering clusters according to the average gray value of each clustering cluster corresponding to the region and the distance between the pixel centers of any two clustering clusters; according to the clustering distance, carrying out hierarchical clustering on the region to obtain each second clustering cluster corresponding to the region;
counting the number of second clustering clusters in the bubble image corresponding to each pressure supply pressure; calculating the weighted average size of the second cluster in the bubble image corresponding to each pressure supply pressure; calculating the sewage air flotation effect evaluation index corresponding to each pressure supply pressure according to the number of the second clustering clusters in the bubble image corresponding to each pressure supply pressure and the weighted average size of the second clustering clusters; and obtaining the optimal pressure supply pressure according to the sewage air flotation effect evaluation indexes corresponding to the pressure supply pressures.
2. The pressure control method for air-float decontamination of oil-containing contaminated water according to claim 1, wherein the clustering distance between any two clustering clusters is calculated by using the following formula:
wherein the content of the first and second substances,
is the clustering distance between any two clusters,
is the average gray value of one of the cluster clusters,
is the average gray value of the other cluster,
is the distance between the pixel centers of the two clusters.
3. The method of claim 1, wherein the step of performing hierarchical clustering on the region according to the clustering distance to obtain each second cluster corresponding to the region comprises:
calculating the cluster evaluation index of the region by adopting the following formula:
wherein the content of the first and second substances,
is a cluster evaluation index of the region,
is the average size of the region cluster,
the variance of the mean gray value for the region cluster,
the number of clusters clustered for the region;
and performing hierarchical clustering on the region according to the clustering distance between any two clustering clusters in the region, judging whether the clustering evaluation index of the region is greater than a set threshold value, stopping clustering the region if the clustering evaluation index of the region is greater than the set threshold value, and marking the clustering cluster obtained by the last clustering as each second clustering cluster corresponding to the region.
4. The method of claim 1, wherein for any one of the first cluster clusters: the gray values of the pixels in the cluster are equal.
5. The method of claim 1, wherein the calculating the weighted average size of the second cluster in the bubble image corresponding to each pressure-applying pressure comprises:
for any given pressure corresponding bubble image:
counting the number of pixel points in each second cluster in the bubble image, and marking the second cluster with the number of the pixel points being more than a first threshold value and less than a second threshold value as a target cluster; the first threshold is less than a second threshold;
calculating the sum of the number of pixel points in the target cluster, and counting the total number of the target cluster; and calculating the ratio of the sum of the number of the pixel points in the target cluster to the total number of the target cluster, and recording the ratio as the weighted average size of the second cluster in the bubble image.
6. The method of claim 1, wherein calculating the evaluation index of the flotation effect of the wastewater corresponding to each pressure supply pressure according to the number of the second cluster and the weighted average size of the second cluster in the bubble image corresponding to each pressure supply pressure comprises:
respectively calculating the difference value between the average gray value of the bubble image of the air floatation tank corresponding to each pressure supply pressure and the average gray value of untreated sewage;
and calculating the sewage air floatation effect evaluation index corresponding to each pressure supply pressure according to the number of the second clustering clusters in the bubble image corresponding to each pressure supply pressure, the weighted average size of the second clustering clusters and the difference value between the average gray value of the bubble image of the air floatation tank and the average gray value of untreated sewage.
7. The method of claim 6, wherein the calculating of the evaluation index of the flotation effect of the wastewater corresponding to each feeding pressure comprises:
for any given pressure corresponding bubble image: and calculating the product of the total number of the second clustering clusters in the bubble image corresponding to the pressure supply pressure, the weighted average size of the second clustering clusters and the difference value between the average gray value of the bubble image of the air floatation tank and the average gray value of untreated sewage, and taking the product as the evaluation index of the air floatation effect of the sewage corresponding to the pressure supply pressure.
8. The method as claimed in claim 1, wherein the obtaining of the optimal pressure supply pressure according to the evaluation index of the flotation effect of the sewage corresponding to each pressure supply pressure comprises:
constructing a binary group corresponding to each pressure supply pressure according to each pressure supply pressure and the sewage air flotation effect evaluation index; the first element in the binary group is a pressure-supply value, and the second element is a corresponding sewage air flotation effect evaluation index;
screening binary groups of which the evaluation indexes of the air flotation effect of the sewage are smaller than an air flotation effect threshold value;
and taking the minimum pressure supply pressure in the residual binary group as the optimal pressure supply pressure.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115877708A (en) * | 2022-10-12 | 2023-03-31 | 南通水山环保设备有限公司 | Self-adaptive control method of air floatation machine |
| CN116721391A (en) * | 2023-08-11 | 2023-09-08 | 山东恒信科技发展有限公司 | Method for detecting separation effect of raw oil based on computer vision |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106257498A (en) * | 2016-07-27 | 2016-12-28 | 中南大学 | Zinc flotation work condition state division methods based on isomery textural characteristics |
| CN114504867A (en) * | 2021-12-31 | 2022-05-17 | 江苏天河水务设备有限公司 | Farming-grazing wastewater multi-stage treatment system |
| CN114627287A (en) * | 2022-02-18 | 2022-06-14 | 南京三唯木科技有限公司 | Water turbidity detection method and system in air tightness detection based on artificial intelligence |
| CN114663405A (en) * | 2022-03-27 | 2022-06-24 | 扬州市苏灵农药化工有限公司 | Wastewater treatment control method for pesticide production enterprises |
-
2022
- 2022-07-22 CN CN202210865188.0A patent/CN115082721A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106257498A (en) * | 2016-07-27 | 2016-12-28 | 中南大学 | Zinc flotation work condition state division methods based on isomery textural characteristics |
| CN114504867A (en) * | 2021-12-31 | 2022-05-17 | 江苏天河水务设备有限公司 | Farming-grazing wastewater multi-stage treatment system |
| CN114627287A (en) * | 2022-02-18 | 2022-06-14 | 南京三唯木科技有限公司 | Water turbidity detection method and system in air tightness detection based on artificial intelligence |
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